374 add hypothesis tests for kml, containers and features #383
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… Placemark, and Overlays
Reviewer's Guide by SourceryThis PR adds extensive hypothesis-based property testing for various KML components and improves string handling in the codebase. The changes include new test files for features, overlays, containers, and KML objects, along with modifications to string handling in multiple classes to use a consistent cleaning approach. Updated class diagram for Link classclassDiagram
class Link {
+Optional~str~ href
+Optional~str~ rel
+Optional~str~ type
+Optional~str~ hreflang
+Optional~str~ title
+Optional~int~ length
+__init__(href, rel, type, hreflang, title, length)
}
note for Link "String attributes are now Optional and cleaned using clean_string function"
Updated class diagram for Data classesclassDiagram
class Data {
+Optional~str~ name
+Optional~str~ display_name
+__init__(name, display_name)
}
class SchemaData {
+Optional~str~ schema_url
+__init__(schema_url)
}
class SimpleData {
+Optional~str~ name
+Optional~str~ value
+__init__(name, value)
}
note for Data "String attributes are now cleaned using clean_string function"
note for SchemaData "String attributes are now cleaned using clean_string function"
note for SimpleData "String attributes are now cleaned using clean_string function"
Updated class diagram for Placemark classclassDiagram
class Placemark {
+Optional~str~ name
+Optional~str~ description
+Optional~str~ address
+Optional~str~ phone_number
+__init__(name, description, address, phone_number)
}
note for Placemark "String attributes are now cleaned using clean_string function"
Updated class diagram for Overlay classesclassDiagram
class GroundOverlay {
+Optional~float~ altitude
+Optional~AltitudeMode~ altitude_mode
+Optional~LatLonBox~ lat_lon_box
+__init__(altitude, altitude_mode, lat_lon_box)
}
class PhotoOverlay {
+Optional~float~ rotation
+Optional~ViewVolume~ view_volume
+Optional~ImagePyramid~ image_pyramid
+Optional~Point~ point
+Optional~Shape~ shape
+__init__(rotation, view_volume, image_pyramid, point, shape)
}
note for GroundOverlay "Attributes are now cleaned using clean_string function"
note for PhotoOverlay "Attributes are now cleaned using clean_string function"
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WalkthroughThe pull request includes extensive updates to the documentation and functionality of the Changes
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👍 Looks good to me! Reviewed everything up to 6e20e19 in 1 minute and 3 seconds
More details
- Looked at
2265lines of code in54files - Skipped
0files when reviewing. - Skipped posting
7drafted comments based on config settings.
1. fastkml/atom.py:134
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theLinkclass infastkml/atom.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
2. fastkml/atom.py:286
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theAuthorclass infastkml/atom.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
3. fastkml/data.py:117
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theDataclass infastkml/data.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
4. fastkml/data.py:247
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theSchemaclass infastkml/data.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
5. fastkml/data.py:365
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theExtendedDataclass infastkml/data.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
6. fastkml/links.py:79
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theLinkclass infastkml/links.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
7. fastkml/styles.py:475
- Draft comment:
Usingclean_stringfor string attributes ensures consistent cleaning and validation, which is a good practice. - Reason this comment was not posted:
Confidence changes required:0%
The PR modifies theIconclass infastkml/styles.pyto use theclean_stringfunction for string attributes. This change ensures that all string attributes are consistently cleaned and validated, which is a good practice.
Workflow ID: wflow_HtF9H1i9LOftEaeX
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Hey @cleder - I've reviewed your changes and they look great!
Here's what I looked at during the review
- 🟡 General issues: 1 issue found
- 🟢 Security: all looks good
- 🟡 Testing: 1 issue found
- 🟢 Complexity: all looks good
- 🟢 Documentation: all looks good
Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
| @@ -425,7 +425,7 @@ def __init__( | |||
| """ | |||
| if geometry is not None and kml_coordinates is not None: | |||
| raise GeometryError(MsgMutualExclusive) | |||
| if kml_coordinates is None: | |||
| if kml_coordinates is None and geometry: | |||
There was a problem hiding this comment.
issue (bug_risk): The geometry existence check should be more explicit to avoid potential issues with falsy values
Consider changing to if kml_coordinates is None and geometry is not None: to avoid potential issues with geometry objects that might evaluate to False
| @given( | ||
| text=st.one_of(st.none(), xml_text(min_size=1)), | ||
| max_lines=st.one_of( | ||
| st.none(), | ||
| st.integers(min_value=0, max_value=2_147_483_647), | ||
| ), | ||
| ) |
There was a problem hiding this comment.
suggestion (testing): Consider adding edge cases for empty strings and whitespace-only strings
The test strategies for text fields like name, description, etc. should explicitly include empty strings and whitespace-only strings to ensure proper handling of these edge cases.
@given(
text=st.one_of(
st.none(),
st.just(""),
st.just(" "),
xml_text(min_size=1)
),
max_lines=st.one_of(
st.none(),
st.integers(min_value=0, max_value=2_147_483_647),
),
)| import fastkml.links | ||
| import fastkml.overlays | ||
| import fastkml.views | ||
| from tests.base import Lxml |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| import fastkml.overlays | ||
| import fastkml.views | ||
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| import fastkml.views | ||
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip_terse |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| from tests.hypothesis.common import assert_repr_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip_terse | ||
| from tests.hypothesis.common import assert_str_roundtrip_verbose |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| import fastkml.enums | ||
| import fastkml.geometry | ||
| import fastkml.overlays | ||
| from tests.base import Lxml |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| import fastkml.geometry | ||
| import fastkml.overlays | ||
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
| import fastkml.overlays | ||
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip |
There was a problem hiding this comment.
issue (code-quality): Don't import test modules. (dont-import-test-modules)
Explanation
Don't import test modules.Tests should be self-contained and don't depend on each other.
If a helper function is used by multiple tests,
define it in a helper module,
instead of importing one test from the other.
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## develop #383 +/- ##
===========================================
+ Coverage 99.17% 99.32% +0.14%
===========================================
Files 64 68 +4
Lines 5321 5593 +272
Branches 150 154 +4
===========================================
+ Hits 5277 5555 +278
+ Misses 35 28 -7
- Partials 9 10 +1 ☔ View full report in Codecov by Sentry. |
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Actionable comments posted: 6
🧹 Outside diff range and nitpick comments (97)
fastkml/mixins.py (1)
Line range hint
29-29: Consider making the times attribute finalSince this is a mixin class defining a core attribute, consider using
typing.Finalto prevent accidental overrides:- times: Optional[Union[TimeSpan, TimeStamp]] = None + times: Final[Optional[Union[TimeSpan, TimeStamp]]] = NoneThis would require adding
from typing import Finalto the imports.tests/base.py (2)
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33-39: Consider adding a teardown method for test isolation.While the setup is correct, consider adding a
teardown_methodto reset the configuration after each test. This ensures complete test isolation and prevents potential side effects between tests.class StdLibrary: """Configure test to run with the standard library.""" def setup_method(self) -> None: """Ensure to always test with the standard library xml ElementTree parser.""" config.set_etree_implementation(ET) config.set_default_namespaces() + def teardown_method(self) -> None: + """Reset configuration after test.""" + config.set_default_namespaces()
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51-54: Add error handling for schema parser configuration.The
get_schema_parser()call might fail silently. Consider adding error handling to provide better feedback during test setup.def setup_method(self) -> None: """Ensure to always test with the lxml parse.""" config.set_etree_implementation(lxml.etree) config.set_default_namespaces() - get_schema_parser() + try: + get_schema_parser() + except Exception as e: + pytest.fail(f"Failed to initialize schema parser: {e}")tests/hypothesis/kml_test.py (3)
16-16: Improve module docstring accuracy and completenessThe current docstring "Property-based tests for the views module" is inaccurate and incomplete. Consider updating it to better reflect the actual implementation:
-"""Property-based tests for the views module.""" +"""Property-based tests for KML features using the Hypothesis framework. + +This module implements fuzz testing for various KML features including Document, +Folder, Placemark, Overlays, and NetworkLink, verifying their serialization +and representation consistency. +"""
34-34: Add class-level docstringAdd a docstring to the
TestLxmlclass explaining:
- The purpose of these property-based tests
- The inheritance from
Lxml- The testing strategy using Hypothesis
61-72: Enhance test coverage with additional assertionsThe test method effectively verifies serialization roundtrips but could be enhanced with:
- Validation of feature-specific attributes after roundtrip
- Edge cases for each feature type
- Verification of XML structure
Example enhancement:
def test_fuzz_document( self, feature: fastkml.features._Feature, ) -> None: kml = fastkml.kml.KML( features=[feature], # type: ignore[list-item] ) # Existing assertions assert_repr_roundtrip(kml) assert_str_roundtrip(kml) assert_str_roundtrip_terse(kml) assert_str_roundtrip_verbose(kml) # Additional assertions xml = kml.to_string() assert xml.count(b'<kml') == 1, "Should have exactly one KML root" assert feature.__class__.__name__.lower().encode() in xml, "Feature type should be in XML" # Feature-specific assertions if isinstance(feature, fastkml.features.NetworkLink): assert feature.link.href.encode() in xml, "NetworkLink href should be in XML"tests/hypothesis/times_test.py (3)
22-22: Consider enhancing the module docstring with examples.The docstring could be more helpful by including:
- Example of how property-based tests differ from traditional unit tests
- Description of the strategies used for generating test data
- Expected behavior and assertions being verified
Line range hint
39-54: Enhance TimeStamp test coverage.While the roundtrip serialization tests are good, consider adding explicit assertions to verify:
- The state of the TimeStamp object matches the input parameters
- Edge cases like empty strings or whitespace-only strings
- Timezone handling in the timestamp
Example additions:
def test_fuzz_time_stamp(self, ...) -> None: time_stamp = fastkml.TimeStamp(id=id, target_id=target_id, timestamp=timestamp) # Verify object state assert time_stamp.id == id assert time_stamp.target_id == target_id assert time_stamp.timestamp == timestamp # Existing roundtrip tests...
Line range hint
56-75: Add validation for TimeSpan begin/end relationship.The test should verify that TimeSpan handles the temporal relationship between begin and end times correctly. Consider:
- Adding a hypothesis assumption to ensure begin time is before end time when both are provided
- Testing edge cases where only begin or only end is provided
Example enhancement:
@given( id=st.one_of(st.none(), nc_name()), target_id=st.one_of(st.none(), nc_name()), begin=st.one_of(st.none(), kml_datetimes()), end=st.one_of(st.none(), kml_datetimes()), ) def test_fuzz_time_span(self, ...) -> None: from hypothesis import assume # Ensure begin is before end when both are provided if begin is not None and end is not None: assume(begin < end) time_span = fastkml.TimeSpan(...) # Verify object state assert time_span.id == id assert time_span.target_id == target_id assert time_span.begin == begin assert time_span.end == end # Existing roundtrip tests...tests/geometries/functions_test.py (3)
Line range hint
31-65: Good test coverage, consider adding docstrings and more realistic mock values.The test methods are well-structured and cover both strict and non-strict scenarios effectively. However, consider these improvements:
- Add docstrings to explain the test scenarios and expected behavior
- Use more meaningful mock XML strings that reflect actual KML structure
Example improvement:
@patch("fastkml.config.etree.tostring", return_value=b"<kml:../>") def test_handle_invalid_geometry_error_true( self, mock_to_string: Callable[..., str], ) -> None: + """Test that handle_invalid_geometry_error raises KMLParseError when strict=True. + + The function should: + 1. Convert the invalid element to string + 2. Raise KMLParseError with the element string as the error message + """ mock_element = Mock()
Line range hint
67-89: Consider improving test clarity and documentation.While the test correctly validates the error condition, it could be more explicit about what's being tested:
- Add a docstring explaining why 4-tuple coordinates should raise KMLWriteError
- Use a more descriptive variable name than
objto indicate what type is being mocked- Consider using
@pytest.mark.parametrizeto test different invalid coordinate formatsExample improvement:
def test_coordinates_subelement_exception(self) -> None: + """Test that coordinates_subelement raises KMLWriteError for invalid coordinates. + + KML coordinates should be 2D (lon, lat) or 3D (lon, lat, alt). + This test verifies that 4-tuple coordinates raise KMLWriteError. + """ - obj = Mock() + mock_geometry = Mock() - obj.coordinates = [(1.123456, 2.654321, 3.111111, 4.222222)] + mock_geometry.coordinates = [(1.123456, 2.654321, 3.111111, 4.222222)] # 4-tuple coordinate
Line range hint
1-89: Well-structured tests with good coverage.The test file demonstrates good practices:
- Proper use of mocking to isolate test cases
- Consistent use of type hints
- Coverage of both positive and negative scenarios
- Clear separation of test cases
Consider adding property-based tests using Hypothesis (as mentioned in PR objectives) to complement these unit tests, especially for testing various coordinate formats and edge cases.
fastkml/registry.py (3)
Line range hint
33-57: Add docstrings to Protocol classes for better API documentation.The
GetKWArgsandSetElementprotocols define clear interfaces but lack documentation explaining their purpose and parameter usage.Add descriptive docstrings like:
class GetKWArgs(Protocol): + """Protocol for extracting keyword arguments from XML elements. + + Args: + element: The XML element to extract from + ns: The namespace identifier + name_spaces: Dictionary of namespace mappings + node_name: Name of the XML node + kwarg: The keyword argument name + classes: Tuple of valid types for the attribute + strict: Whether to enforce strict type checking + + Returns: + Dictionary of extracted keyword arguments + """
Line range hint
60-71: Enhance RegistryItem documentation and consider adding validation.While the dataclass is well-structured, it could benefit from more detailed documentation and runtime validation.
Consider adding field descriptions and validation:
@dataclass(frozen=True) class RegistryItem: - """A registry item.""" + """A registry item for XML object mapping. + + Attributes: + ns_ids: Tuple of namespace identifiers + classes: Tuple of allowed types for the attribute + attr_name: Name of the attribute in the Python object + get_kwarg: Function to extract keyword arguments from XML + set_element: Function to set XML element attributes + node_name: Name of the XML node + default: Default value if attribute is missing + """ ns_ids: Tuple[str, ...] classes: Tuple[Type[object], ...] attr_name: str get_kwarg: GetKWArgs set_element: SetElement node_name: str default: Any = None + + def __post_init__(self): + """Validate the registry item attributes.""" + if not self.ns_ids: + raise ValueError("ns_ids cannot be empty") + if not self.classes: + raise ValueError("classes cannot be empty")
Line range hint
74-106: Consider adding thread safety and utility methods to Registry class.The Registry implementation is clean but could benefit from additional features for production use.
Consider these enhancements:
- Add thread safety for concurrent access:
from threading import Lock class Registry: def __init__(self, registry: Optional[Dict[Type["_XMLObject"], List[RegistryItem]]] = None) -> None: self._registry = registry or {} self._lock = Lock() def register(self, cls: Type["_XMLObject"], item: RegistryItem) -> None: with self._lock: existing = self._registry.get(cls, []) existing.append(item) self._registry[cls] = existing
- Add utility methods:
def unregister(self, cls: Type["_XMLObject"], item: RegistryItem) -> None: """Remove a registration.""" with self._lock: if cls in self._registry: self._registry[cls].remove(item) if not self._registry[cls]: del self._registry[cls] def clear(self) -> None: """Clear all registrations.""" with self._lock: self._registry.clear()tests/validator_test.py (2)
Line range hint
32-41: Consider improving path construction readability.While the test is correct, the path construction could be more readable using Path.joinpath() method.
- validate( - file_to_validate=TEST_DIR - / "ogc_conformance" - / "data" - / "kml" - / "Document-clean.kml", - ) + validate( + file_to_validate=TEST_DIR.joinpath( + "ogc_conformance", "data", "kml", "Document-clean.kml" + ), + )
Line range hint
65-93: LGTM! Comprehensive element validation tests.The tests thoroughly cover both valid and invalid Link element scenarios with appropriate assertions. Good use of the atom.Link class with various attributes to test validation.
However, consider adding test cases for edge cases:
- Very long strings in attributes
- Special characters in href
- Negative length values
Would you like me to help generate additional test cases for these scenarios?
fastkml/kml_base.py (2)
Line range hint
32-47: Add type hints for class attributesWhile the class is well-documented, consider adding type hints for the class attributes to improve code maintainability and IDE support.
_default_nsid = config.KML - id = None - target_id = None + id: Optional[str] = None + target_id: Optional[str] = None
Line range hint
49-82: Consider input validation for ID fieldsThe constructor currently defaults empty IDs to empty strings. Consider using
Noneas the default and adding validation for non-empty strings when IDs are provided, as empty IDs might cause issues in XML serialization or when using the<Update>mechanism.def __init__( self, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, id: Optional[str] = None, target_id: Optional[str] = None, **kwargs: Any, ) -> None: super().__init__(ns=ns, name_spaces=name_spaces, **kwargs) - self.id = id or "" - self.target_id = target_id or "" + if id and not id.strip(): + raise ValueError("ID cannot be empty string") + if target_id and not target_id.strip(): + raise ValueError("Target ID cannot be empty string") + self.id = id + self.target_id = target_idtests/hypothesis/links_test.py (3)
Line range hint
38-71: Add documentation and type hints to improve maintainability.While the implementation is thorough, consider these improvements:
- Add docstring explaining the purpose and usage of
common_link- Add type hints for the partial function
- Consider extracting float bounds as named constants
Here's a suggested improvement:
+FloatStrategy = st.floats(allow_infinity=False, allow_nan=False) + +def common_link(func: typing.Callable) -> typing.Callable: + """Generate test parameters for Link/Icon testing using hypothesis strategies. + + Args: + func: The test function to be decorated with hypothesis parameters. + + Returns: + Decorated function with all necessary test parameters. + """ common_link = partial( given, id=st.one_of(st.none(), nc_name()), target_id=st.one_of(st.none(), nc_name()), href=st.one_of(st.none(), urls()), refresh_mode=st.one_of(st.none(), st.sampled_from(fastkml.enums.RefreshMode)), - refresh_interval=st.one_of( - st.none(), - st.floats(allow_infinity=False, allow_nan=False), - ), + refresh_interval=st.one_of(st.none(), FloatStrategy), view_refresh_mode=st.one_of( st.none(), st.sampled_from(fastkml.enums.ViewRefreshMode), ), - view_refresh_time=st.one_of( - st.none(), - st.floats(allow_infinity=False, allow_nan=False), - ), - view_bound_scale=st.one_of( - st.none(), - st.floats(allow_infinity=False, allow_nan=False), - ), + view_refresh_time=st.one_of(st.none(), FloatStrategy), + view_bound_scale=st.one_of(st.none(), FloatStrategy), view_format=st.one_of( st.none(), st.text(string.ascii_letters + string.punctuation), ), http_query=st.one_of(st.none(), query_strings()), )
Line range hint
74-106: Add test documentation and edge cases.The test implementation is robust with good type hints and validation. Consider these enhancements:
- Add docstring explaining the test's purpose and validation strategy
- Add explicit edge case tests for important scenarios
Here's a suggested improvement:
@pytest.mark.parametrize("cls", [fastkml.Link, fastkml.Icon]) @common_link() def test_fuzz_link( self, cls: typing.Union[typing.Type[fastkml.Link], typing.Type[fastkml.Icon]], id: typing.Optional[str], target_id: typing.Optional[str], href: typing.Optional[str], refresh_mode: typing.Optional[fastkml.enums.RefreshMode], refresh_interval: typing.Optional[float], view_refresh_mode: typing.Optional[fastkml.enums.ViewRefreshMode], view_refresh_time: typing.Optional[float], view_bound_scale: typing.Optional[float], view_format: typing.Optional[str], http_query: typing.Optional[str], ) -> None: + """Test Link and Icon classes with fuzz testing. + + Validates: + 1. XML element generation and validation + 2. Serialization roundtrip consistency + 3. String representation in different formats + """ link = cls( id=id, target_id=target_id, href=href, refresh_mode=refresh_mode, refresh_interval=refresh_interval, view_refresh_mode=view_refresh_mode, view_refresh_time=view_refresh_time, view_bound_scale=view_bound_scale, view_format=view_format, http_query=http_query, ) assert validate(element=link.etree_element()) assert_repr_roundtrip(link) assert_str_roundtrip(link) assert_str_roundtrip_terse(link) assert_str_roundtrip_verbose(link) + + @pytest.mark.parametrize("cls", [fastkml.Link, fastkml.Icon]) + def test_edge_cases( + self, + cls: typing.Union[typing.Type[fastkml.Link], typing.Type[fastkml.Icon]], + ) -> None: + """Test edge cases for Link and Icon classes.""" + # Test with all None values + link = cls() + assert validate(element=link.etree_element()) + + # Test with empty strings + link = cls( + id="", + target_id="", + href="", + view_format="", + http_query="", + ) + assert validate(element=link.etree_element())
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1-106: Excellent implementation of property-based testing!The implementation provides comprehensive testing coverage for Link and Icon classes using hypothesis, which aligns perfectly with the PR's objective of improving testing methodologies. The code is well-structured, properly typed, and includes thorough validation.
Consider adding this testing pattern to other complex classes in the codebase to achieve similar robust validation coverage.
tests/links_test.py (1)
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27-93: Consider enhancing test coverageWhile the existing tests thoroughly verify the basic functionality of the
Iconclass, consider adding tests for:
- Edge cases (empty strings, very long strings)
- Invalid inputs (malformed URLs, invalid refresh modes)
- Optional attributes (testing when some attributes are None)
Example test cases to consider:
def test_icon_edge_cases(self) -> None: """Test Icon class with edge cases.""" # Test with empty href icon = links.Icon(href="") # Test with very long href icon = links.Icon(href="http://" + "a" * 2000 + ".com") # Test with invalid refresh_mode with pytest.raises(ValueError): links.Icon(refresh_mode="invalid_mode")tests/hypothesis/gx_test.py (1)
44-44: Add docstrings to document test strategies and properties being verified.While the test methods are well-structured, adding docstrings would help clarify:
- The properties being tested
- The range of values being generated by the track_items strategy
- Expected behavior for edge cases
Example docstring format:
def test_fuzz_track_track_items(self, ...) -> None: """Verify Track initialization and serialization with fuzzed track items. Properties tested: - Track can be initialized with any valid combination of track items - All string representations (str/repr) can be round-tripped - Edge cases (empty lists, None values) are handled correctly """Also applies to: 83-83
tests/helper_test.py (4)
17-17: Remove unnecessary empty lineThis empty line appears to serve no purpose in separating logical sections.
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39-52: Add positive test cases for integer valuesThe test only covers the empty string case. Consider adding test cases for valid integer values to ensure the function works correctly with proper input.
Example addition:
def test_subelement_int_kwarg_valid_input(self) -> None: node = Node() node.text = "42" element = Mock() element.find.return_value = node res = subelement_int_kwarg( element=element, ns="ns", name_spaces={"name": "uri"}, node_name="node", kwarg="kwarg", classes=(int,), strict=False, ) assert res == {"kwarg": 42}
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39-137: Consider adding property-based testsGiven that this PR introduces property-based testing using Hypothesis, consider adding property-based tests for these helper functions to thoroughly test their behavior with a wide range of inputs.
Example implementation:
from hypothesis import given from hypothesis import strategies as st @given(st.integers()) def test_subelement_int_kwarg_property(self, value: int) -> None: node = Node() node.text = str(value) element = Mock() element.find.return_value = node res = subelement_int_kwarg( element=element, ns="ns", name_spaces={"name": "uri"}, node_name="node", kwarg="kwarg", classes=(int,), strict=False, ) assert res == {"kwarg": value}
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39-137: Improve test method documentationThe test methods would benefit from docstrings explaining the test scenarios and expected behaviors. This aligns with the PR's goal of improving documentation.
Example improvement:
def test_subelement_int_kwarg(self) -> None: """Test subelement_int_kwarg with empty string input. Verifies that the function returns an empty dictionary when the input node contains an empty string value. """tests/hypothesis/container_test.py (2)
41-77: Enhance test data generation strategyThe current strategy could be improved to:
- Add constraints on list sizes to avoid excessive test cases
- Include edge cases explicitly
- Add validation for URLs to ensure they are KML-compatible
Consider applying these improvements:
@given( features_tuple=st.tuples( st.lists( st.builds( fastkml.containers.Document, - ), + ), min_size=0, max_size=3, # Limit size for faster tests ), # ... similar changes for other feature lists ... st.lists( st.builds( fastkml.features.NetworkLink, link=st.builds( fastkml.links.Link, - href=urls(), + href=urls().filter(lambda x: x.startswith('http')), # Ensure valid URLs ), - ), + ), min_size=0, max_size=3, ), ), )
150-153: Consider adding specific KML validation assertionsThe current assertions only verify string/repr roundtrips. Consider adding KML-specific validations.
Add assertions to verify:
- XML schema validation
- KML namespace correctness
- Schema references integrity
Example:
def assert_valid_kml(doc): xml_str = str(doc) # Validate against KML schema schema = etree.XMLSchema(file='path/to/kml22.xsd') root = etree.fromstring(xml_str) schema.assertValid(root)tests/hypothesis/strategies.py (1)
168-179: Consider adding bounds for angle parameters.While the implementation is solid and follows the established patterns, the angle parameters (heading, roll, tilt) could benefit from more realistic bounds:
- heading: typically 0° to 360°
- roll: typically -180° to 180°
- tilt: typically -90° to 90°
Consider updating the angle parameters with these bounds:
angle=st.builds( fastkml.gx.Angle, - heading=st.floats(allow_nan=False, allow_infinity=False), - roll=st.floats(allow_nan=False, allow_infinity=False), - tilt=st.floats(allow_nan=False, allow_infinity=False), + heading=st.floats(allow_nan=False, allow_infinity=False, min_value=0, max_value=360), + roll=st.floats(allow_nan=False, allow_infinity=False, min_value=-180, max_value=180), + tilt=st.floats(allow_nan=False, allow_infinity=False, min_value=-90, max_value=90), ),This would generate more realistic test data and potentially catch edge cases within the expected ranges.
tests/registry_test.py (2)
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29-47: Consider enhancing test class docstrings.While the class hierarchy is well-structured, the docstrings could be more descriptive about the purpose of each test class and how they relate to testing the Registry functionality.
Example improvement:
class A(_XMLObject): - """A test class.""" + """Base test class for Registry inheritance testing. + + This class serves as the root of the inheritance hierarchy + used to test Registry's handling of class relationships."""
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156-238: Consider adding edge case tests.While the current test coverage is good, consider adding tests for the following scenarios:
- Registering the same (ns_ids, node_name) combination multiple times
- Error cases when registering invalid classes
- Inheritance with multiple mixins
Example test case:
def test_registry_duplicate_registration() -> None: """Test registering the same namespace and node name combination.""" registry = Registry() registry.register( A, RegistryItem( ns_ids=("kml",), classes=(A,), attr_name="a", get_kwarg=get_kwarg, set_element=set_element, node_name="a", ), ) # Test duplicate registration behavior registry.register( B, RegistryItem( ns_ids=("kml",), classes=(B,), attr_name="b", get_kwarg=get_kwarg, set_element=set_element, node_name="a", # Same as above ), )fastkml/kml.py (1)
218-219: Consider documenting NetworkLink best practicesNetworkLink is a powerful KML feature for dynamic content and network-linked KML files. Consider adding documentation that covers:
- Best practices for using NetworkLink
- Performance implications of network-linked KML files
- Security considerations when loading remote KML content
tests/utils_test.py (3)
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26-127: Consider adding property-based tests using Hypothesis.While the current test coverage is good, considering the PR's objective of introducing property-based testing, these test cases would benefit from using the Hypothesis library to generate diverse test scenarios automatically.
Example addition:
from hypothesis import given from hypothesis import strategies as st @given( x_values=st.lists(st.integers(), min_size=1), y_values=st.lists(st.integers(), min_size=1) ) def test_find_all_property(self, x_values: List[int], y_values: List[int]) -> None: class A: def __init__(self, x: int) -> None: self.x = x class B: def __init__(self, y: int) -> None: self.y = y objects = [A(x) for x in x_values] + [B(y) for y in y_values] # Test finding all A objects found_a = list(find_all(objects, of_type=A)) assert len(found_a) == len(x_values) assert all(isinstance(obj, A) for obj in found_a) # Test finding all B objects found_b = list(find_all(objects, of_type=B)) assert len(found_b) == len(y_values) assert all(isinstance(obj, B) for obj in found_b)
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128-236: Consider improving test maintainability.The KML test data is quite extensive and embedded directly in the test. Consider:
- Moving the KML test data to a separate fixture file
- Breaking down the assertions into smaller, focused test methods
Example refactor:
import os from pathlib import Path def load_test_kml() -> str: fixtures_dir = Path(__file__).parent / "fixtures" with open(os.path.join(fixtures_dir, "schema_test.kml")) as f: return f.read() def test_find_schema_by_url(self) -> None: k = kml.KML.from_string(load_test_kml(), strict=False) self._test_schema(k) self._test_schema_data(k) def _test_schema(self, k: kml.KML) -> None: schema = find(k, of_type=Schema, id="TrailHeadTypeId") assert isinstance(schema, Schema) assert schema.name == "TrailHeadType" assert schema.id == "TrailHeadTypeId" def _test_schema_data(self, k: kml.KML) -> None: schema_data = list(find_all(k, of_type=SchemaData)) assert len(schema_data) == 2 for data in schema_data: assert isinstance(data, SchemaData) assert data.schema_url == "#TrailHeadTypeId"
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239-241: Add documentation explaining the purpose of lxml-based tests.While the class name suggests it runs tests with lxml, explicit documentation would help explain:
- Why we need separate lxml-based tests
- What differences to expect between stdlib and lxml parsing
Example addition:
class TestFindAllLxml(Lxml): """Run the find_all tests using lxml backend. These tests ensure that the find_all functionality works consistently across both stdlib and lxml parsers, as they may handle XML parsing differently, especially with namespaces and complex XML structures. """fastkml/links.py (1)
82-89: Document None handling in docstring.The implementation correctly uses
clean_stringfor string sanitization. However, since these fields can now be None, it would be helpful to document this behavior in the class docstring.Add a note about None handling to the class docstring:
class Link(_BaseObject): """ Represents a <Link> element. It specifies the location of any of the following: - KML files fetched by network links - Image files used in any Overlay - Model files used in the <Model> element https://developers.google.com/kml/documentation/kmlreference#link + + Note: + The string fields (href, view_format, http_query) may be None if the input + is empty or consists only of whitespace. """tests/views_test.py (1)
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192-192: Consider moving the existence check to the beginning.The
assert regioncheck should logically come before testing its attributes, as we want to verify the object's existence before accessing its properties.region = views.Region.from_string(doc) + assert region assert region.id == "region1" assert region.lat_lon_alt_box assert region.lat_lon_alt_box.north == 37.85 # ... other assertions ... - assert regiondocs/create_kml_files.rst (4)
174-188: Consider improving color generation for better visualization.While the current implementation works, random color generation might result in similar colors for adjacent countries, making it difficult to distinguish between them. Consider:
- Using a predefined color palette
- Implementing color distance checks to ensure sufficient contrast between adjacent countries
- Adding a comment explaining the hex color format (0xFFFFFF)
Example improvement:
# Define a visually distinct color palette COUNTRY_COLORS = [ 0xFF0000, 0x00FF00, 0x0000FF, 0xFFFF00, 0xFF00FF, 0x00FFFF, # Add more colors as needed ] # Use colors from the palette instead of random color = COUNTRY_COLORS[index % len(COUNTRY_COLORS)]
190-194: Clarify CO2 growth accumulation logic.The current implementation accumulates CO2 values over years, which might not accurately represent the data. Consider:
- Adding a comment explaining why accumulation is chosen over direct values
- Documenting the potential impact on visualization
195-198: Document height multiplier constant.The hardcoded multiplier
5_000for height calculation lacks explanation. Consider:
- Moving it to a named constant with documentation
- Making it configurable based on data ranges
Example improvement:
# Height multiplier to scale CO2 values for visualization # Adjusted to ensure visibility while maintaining proportions HEIGHT_MULTIPLIER = 5_000 # Use the constant in the code force_3d(geometry, co2_growth * HEIGHT_MULTIPLIER)
199-215: Consider memory optimization for large datasets.The current implementation keeps all placemarks in memory. For large datasets (many countries/years), this could lead to high memory usage. Consider:
- Adding a warning about memory requirements
- Implementing batch processing for large datasets
- Adding documentation about performance considerations
docs/working_with_kml.rst (1)
48-48: Consider adding context for the example point.While the point coordinates are valid, adding a comment about what this location represents (e.g., if it's a notable landmark in Switzerland) would make the example more meaningful to readers.
tests/features_test.py (2)
53-94: Add docstrings to new test methods.The new test methods are well-implemented but missing docstrings. Please add descriptive docstrings to explain the purpose of each test.
Example:
def test_placemark_empty_str_roundtrip(self) -> None: """Test serialization and deserialization of an empty Placemark object."""
53-94: Consider adding property-based testing with Hypothesis.The PR objectives mention introducing property-based testing using the Hypothesis library. Consider enhancing these tests with property-based testing to validate Placemark functionality with a wider range of inputs.
Example approach:
from hypothesis import given from hypothesis import strategies as st @given( latitude=st.floats(min_value=-90, max_value=90), longitude=st.floats(min_value=-180, max_value=180), altitude=st.floats(min_value=0), ) def test_placemark_camera_properties(self, latitude, longitude, altitude): """Test Placemark with Camera view using property-based testing.""" camera = views.Camera( latitude=latitude, longitude=longitude, altitude=altitude, roll=0.0, tilt=0.0, heading=0.0, ) pm = features.Placemark(view=camera) new_pm = features.Placemark.from_string(str(pm.to_string())) assert new_pm == pmfastkml/base.py (1)
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276-315: Add error handling for malformed XML stringsThe
from_stringmethod looks well-implemented, but it should handle potential XML parsing errors that could occur with malformed input strings.Consider wrapping the XML parsing in a try-except block:
@classmethod def from_string( cls, string: str, *, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, strict: bool = True, ) -> Self: name_spaces = name_spaces or {} name_spaces = {**config.NAME_SPACES, **name_spaces} ns = cls._get_ns(ns, name_spaces=name_spaces) + try: return cls.class_from_element( ns=ns, name_spaces=name_spaces, strict=strict, element=cast( Element, config.etree.fromstring(string), ), ) + except config.etree.XMLSyntaxError as e: + raise ValueError(f"Invalid XML string: {str(e)}") from etests/times_test.py (4)
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28-201: Consider adding property-based tests using HypothesisWhile the current test coverage is comprehensive, consider adding property-based tests using Hypothesis (as mentioned in PR objectives) to:
- Test datetime parsing with microseconds
- Test negative timezone offsets
- Generate random valid/invalid datetime strings to ensure robust parsing
This would align with the PR's objective of introducing Hypothesis testing.
Example test case:
from hypothesis import given from hypothesis.strategies import datetimes, timezones class TestDateTime(StdLibrary): @given(datetimes(timezones=timezones())) def test_kml_datetime_hypothesis(self, dt): kdt = KmlDateTime(dt) parsed = KmlDateTime.parse(str(kdt)) assert parsed.dt == kdt.dt
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202-283: Consider using freezegun for deterministic datetime testingReplace
datetime.now()calls with either:
- Fixed datetime values for deterministic testing
- freezegun's
freeze_timedecorator for time-dependent testsThis would eliminate the need for
# noqa: DTZ005comments and make tests more reliable.Example refactor:
from freezegun import freeze_time class TestStdLibrary(StdLibrary): @freeze_time("2024-01-01 12:00:00+00:00") def test_timestamp(self) -> None: now = datetime.datetime.now(datetime.UTC) # Remove noqa dt = KmlDateTime(now) # ... rest of the test
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89-127: Enhance error handling testsConsider adding more specific assertions for error messages and additional edge cases:
- Invalid timezone formats (e.g., "+25:00")
- Malformed datetime strings
- Invalid UTF-8 characters in datetime strings
Example test cases:
def test_parse_invalid_timezone(self) -> None: with pytest.raises(ValueError, match="offset must be a timedelta"): KmlDateTime.parse("2000-01-01T00:00:00+25:00") def test_parse_malformed_datetime(self) -> None: with pytest.raises(ValueError, match="Invalid datetime format"): KmlDateTime.parse("2000-13-32T25:61:61Z")
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284-386: Add docstrings to test methodsConsider adding docstrings to test methods to explain the specific scenarios being tested, especially for complex cases like timezone handling and error conditions.
Example:
def test_read_timestamp_utc_offset(self) -> None: """Test parsing datetime with positive timezone offset. Verifies that a datetime string with format 'YYYY-MM-DDThh:mm:ss+hh:mm' is correctly parsed with the specified timezone offset. """ doc = """ <TimeStamp> <when>1997-07-16T10:30:15+03:00</when> </TimeStamp> """ # ... rest of the testtests/hypothesis/geometry_test.py (4)
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47-54: Consider improving type hints for thecoordinatesfunctionThe
coordinatespartial function could benefit from explicit type hints for its return type and thecoordsparameter. This would improve code maintainability and IDE support.coordinates = partial( given, - coords=st.one_of(st.none(), line_coords(srs=epsg4326, min_points=1)), + coords: st.SearchStrategy[typing.Optional[typing.Sequence[typing.Union[ + typing.Tuple[float, float], + typing.Tuple[float, float, float] + ]]]] = st.one_of(st.none(), line_coords(srs=epsg4326, min_points=1)), )
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73-127: Add docstrings to helper functionsThe helper functions would benefit from docstrings explaining their purpose, parameters, and expected behavior. This would make the test suite more maintainable and easier to understand.
Example for one function:
def _test_geometry_str_roundtrip_terse(geometry: kml_geometry) -> None: """Test the roundtrip serialization of geometry objects in terse mode. Args: geometry: A KML geometry object (Point, LineString, or Polygon) Validates: - XML validation passes - Verbose string representation matches after roundtrip - Geometry data is preserved - Default values are properly handled (altitude_mode, extrude, tessellate) """
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129-169: Consider adding edge case tests for coordinatesWhile the property-based tests are comprehensive, consider adding specific edge cases:
- Coordinates at the poles (±90° latitude)
- Coordinates crossing the antimeridian (±180° longitude)
- Coordinates with very small/large values
@coordinates() @settings(deadline=None) def test_coordinates_edge_cases(self) -> None: edge_cases = [ [(90.0, 0.0), (-90.0, 0.0)], # poles [(0.0, 180.0), (0.0, -180.0)], # antimeridian [(1e-10, 1e-10), (1e10, 1e10)] # extreme values ] for coords in edge_cases: coordinate = fastkml.geometry.Coordinates(coords=coords) new_c = fastkml.geometry.Coordinates.from_string( coordinate.to_string(precision=20) ) assert coordinate.to_string(precision=10) == new_c.to_string(precision=10)
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171-400: Reduce code duplication in geometry test methodsThe test methods for Point, LineString, and Polygon share similar structure and assertions. Consider refactoring to reduce duplication by creating a parametrized base test class.
class BaseGeometryTest: geometry_class = None geometry_strategy = None def _create_geometry(self, **kwargs): return self.geometry_class(**kwargs) @common_geometry() def test_geometry_repr_roundtrip(self, **kwargs): geometry = self._create_geometry(**kwargs) _test_repr_roundtrip(geometry) # ... other common test methods class TestPoint(BaseGeometryTest): geometry_class = fastkml.geometry.Point geometry_strategy = points(srs=epsg4326) class TestLineString(BaseGeometryTest): geometry_class = fastkml.geometry.LineString geometry_strategy = line_strings(srs=epsg4326) class TestPolygon(BaseGeometryTest): geometry_class = fastkml.geometry.Polygon geometry_strategy = polygons(srs=epsg4326)tests/geometries/multigeometry_test.py (2)
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33-233: Consider adding property-based tests using Hypothesis.The test methods are well-structured and cover various scenarios. However, given that one of the PR objectives is to introduce property-based testing using the Hypothesis library, consider adding property-based tests for:
- Random coordinate values
- Varying number of points/lines/polygons
- Different combinations of geometries in collections
This would enhance test coverage by automatically generating edge cases that might be missed in manual testing.
Example addition:
from hypothesis import given from hypothesis.strategies import lists, floats class TestMultiPointStdLibrary(StdLibrary): @given(lists(lists(floats(min_value=-180, max_value=180), min_size=2, max_size=2), min_size=1)) def test_random_points(self, points): """Test with randomly generated points.""" p = geo.MultiPoint(points) mg = MultiGeometry(geometry=p) assert all(str(coord) in mg.to_string() for point in points for coord in point)
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214-233: Consider adding more edge cases.While the test coverage is comprehensive, consider adding these scenarios:
- Invalid XML input (malformed tags, missing attributes)
- Malformed coordinates (non-numeric values, missing values)
- Edge cases with extreme coordinate values (very large/small numbers)
This would improve the robustness of the test suite.
Example additions:
def test_invalid_xml(self): """Test with invalid XML input.""" invalid_xml = '<MultiGeometry xmlns="http://www.opengis.net/kml/2.2"><Point><coordinates>invalid</coordinates>' with pytest.raises(ValueError): MultiGeometry.from_string(invalid_xml) def test_extreme_coordinates(self): """Test with extreme coordinate values.""" p = geo.MultiPoint([(1e15, 1e15)]) mg = MultiGeometry(geometry=p) assert "1e+15" in mg.to_string()fastkml/data.py (2)
583-583: Consider URL validation for schema_urlWhile
clean_stringhandles basic string sanitization, consider adding URL validation for theschema_urlfield to ensure it contains a valid URL format.- self.schema_url = clean_string(schema_url) + cleaned_url = clean_string(schema_url) + if cleaned_url and not cleaned_url.startswith(('#', 'http://', 'https://', '/')): + raise ValueError("schema_url must be a valid URL or fragment identifier") + self.schema_url = cleaned_url
35-35: LGTM: Consistent implementation of string handlingThe introduction and usage of
clean_stringacross all classes is consistent and improves the reliability of string handling throughout the module. The implementation aligns well with the PR objectives of standardizing string attribute initialization.Consider adding type hints for the return type of
clean_stringin the import statement to improve code clarity:from fastkml.helpers import clean_string # type: Callable[[Optional[str]], Optional[str]]tests/gx_test.py (2)
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279-307: Enhance error handling test documentationThe invalid input test cases (
test_track_from_str_invalid_whenandtest_track_from_str_invalid_coord) could benefit from more explicit documentation about:
- Why these specific invalid values were chosen
- What makes them invalid
- Why an empty track_items list is the expected outcome
Consider adding docstrings to explain the test cases:
def test_track_from_str_invalid_when(self) -> None: + """Test Track creation with an invalid date (February 32nd). + + When strict=False, invalid dates should result in an empty track_items list + rather than raising an exception. + """ doc = """ <gx:Track xmlns:gx="http://www.google.com/kml/ext/2.2"
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308-324: Document test data valuesThe test data contains specific coordinate values that appear to be significant. Consider adding comments to explain what these values represent and why they were chosen.
Add comments to explain the significance of the test coordinates:
def test_track_from_str_invalid_coord(self) -> None: + """Test Track creation with invalid coordinates. + + Tests that non-numeric values ('XYZ') in coordinates are handled gracefully + when strict=False by resulting in an empty track_items list. + """ doc = """tests/kml_test.py (2)
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447-474: Enhance test coverage for address and phone numberThe current tests only verify basic serialization/deserialization. Consider adding test cases for:
- Invalid phone numbers
- International phone number formats
- Multi-line addresses
- Empty/None values
- Special characters in addresses
Here's a suggested enhancement:
def test_address_variations(self) -> None: addresses = [ "1600 Amphitheatre Parkway, Mountain View, CA", "", # Empty address None, # None value "Line 1\nLine 2\nLine 3", # Multi-line "123 Street #$%&", # Special characters ] for addr in addresses: doc = Document(address=addr) doc2 = Document.from_string(doc.to_string()) assert doc.to_string() == doc2.to_string() assert doc.address == addr def test_phone_number_variations(self) -> None: numbers = [ "+1 234 567 8901", "", # Empty number None, # None value "+44.1234.567890", # International format "123-456-7890", # Different format ] for number in numbers: doc = Document(phone_number=number) doc2 = Document.from_string(doc.to_string()) assert doc.to_string() == doc2.to_string() assert doc.phone_number == number
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476-509: Enhance ground overlay test coverageThe current test only verifies a single static example. Consider adding test cases for:
- Boundary values for coordinates (north, south, east, west)
- Edge cases for rotation (-180 to 180 degrees)
- Different Icon href formats (local files, HTTPS URLs)
- Missing or optional elements
Here's a suggested enhancement:
def test_groundoverlay_variations(self) -> None: # Test boundary coordinates boundary_cases = [ (90, -90, 180, -180, 0), # Max bounds (0, 0, 0, 0, 0), # Zero bounds (1, -1, 1, -1, 180), # Small area, max rotation (1, -1, 1, -1, -180), # Small area, min rotation ] for north, south, east, west, rotation in boundary_cases: doc = kml.KML.from_string(f""" <kml xmlns="http://www.opengis.net/kml/2.2"> <GroundOverlay> <Icon> <href>test.jpg</href> </Icon> <LatLonBox> <north>{north}</north> <south>{south}</south> <east>{east}</east> <west>{west}</west> <rotation>{rotation}</rotation> </LatLonBox> </GroundOverlay> </kml> """) doc2 = kml.KML.from_string(doc.to_string()) assert doc.to_string() == doc2.to_string()tests/hypothesis/multi_geometry_test.py (2)
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65-71: Document safety considerations for eval() usageWhile the eval() usage here is safe due to controlled input and restricted locals, it's good practice to document these safety considerations in the code.
Add a comment explaining the safety measures:
def _test_repr_roundtrip( geometry: fastkml.geometry.MultiGeometry, cls: type[MultiPoint | MultiLineString | MultiPolygon | GeometryCollection], ) -> None: + # Safe to use eval() here because: + # 1. Input is from repr() of a trusted MultiGeometry object + # 2. eval_locals contains only trusted geometry classes new_g = eval(repr(geometry), {}, eval_locals) # noqa: S307
Line range hint
32-38: Consider adding error case testsThe test suite thoroughly covers valid cases but could benefit from explicit tests for invalid scenarios:
- Invalid geometry combinations
- Malformed geometry data
- Invalid coordinate systems
Consider adding test cases like:
@common_geometry def test_invalid_geometry_handling(self): with pytest.raises(ValueError, match="Invalid geometry"): fastkml.geometry.MultiGeometry( geometry=InvalidGeometry() # Define this fixture )tests/geometries/geometry_test.py (3)
Line range hint
34-423: Consider adding property-based tests using Hypothesis.While the test coverage is comprehensive with both simple and complex test cases, considering the PR objectives mention Hypothesis testing, you might want to add property-based tests for the geometry classes. This would help catch edge cases and ensure robustness across a wider range of inputs.
Example approach:
from hypothesis import given from hypothesis.strategies import lists, floats @given(lists(lists(floats(min_value=-180, max_value=180), min_size=2, max_size=2), min_size=3)) def test_property_based_polygon(coordinates): # Test polygon creation with random coordinates polygon = geo.Polygon(coordinates) kml_polygon = create_kml_geometry(polygon) assert kml_polygon.geometry == polygon
Line range hint
34-423: Consider adding tests for additional edge cases.While the existing test data is comprehensive, consider adding tests for:
- Geometries with very large coordinates
- Geometries with very small (near-zero) coordinates
- Geometries with NaN or Infinity values
- Empty geometries
- Geometries with duplicate coordinates
Line range hint
415-423: Consider expanding error handling tests.While the basic error case is covered, consider adding tests for:
- Invalid coordinate values
- Malformed KML strings
- Invalid altitude modes
- Missing required attributes
- Invalid namespace declarations
tests/styles_test.py (1)
128-131: LGTM! Consider adding edge case tests.The new assertions effectively verify the parsing of
iconandhot_spotattributes. The test coverage is good, following a logical progression from existence checks to property validation.Consider adding test cases for edge cases:
def test_icon_style_read_without_icon(): icons = styles.IconStyle.from_string( '<kml:IconStyle xmlns:kml="http://www.opengis.net/kml/2.2"></kml:IconStyle>' ) assert icons.icon is None assert icons.hot_spot is None def test_icon_style_read_with_empty_icon(): icons = styles.IconStyle.from_string( '<kml:IconStyle xmlns:kml="http://www.opengis.net/kml/2.2">' '<kml:Icon></kml:Icon>' '</kml:IconStyle>' ) assert icons.icon is not None assert icons.icon.href is Nonefastkml/helpers.py (1)
44-46: Enhance docstring with parameter and return value details.The implementation is clean and efficient. Consider enhancing the docstring with more details:
def clean_string(value: Optional[str]) -> Optional[str]: - """Clean and validate a string value, returning None if empty.""" + """Clean and validate a string value, returning None if empty. + + Args: + value: Optional string to clean. Can be None. + + Returns: + Cleaned string with leading/trailing whitespace removed, or None if the input + is None, empty, or contains only whitespace. + """ return value.strip() or None if value else Nonefastkml/styles.py (2)
225-225: Consider adding color format validationWhile using
clean_stringfor color sanitization is good, consider adding validation for the KML color format (aabbggrr).def validate_kml_color(color: Optional[str]) -> Optional[str]: """Validate and clean KML color string in aabbggrr format.""" color = clean_string(color) if color and not re.match(r'^[0-9A-Fa-f]{8}$', color): raise ValueError("Color must be in aabbggrr format") return color
990-992: Consider consistent color validation across stylesThe string sanitization is good, but the color attributes (
bg_colorandtext_color) should use the same validation as suggested for_ColorStyleto ensure consistency across the codebase.Consider extracting color validation to a shared utility:
# In fastkml/helpers.py def clean_kml_color(color: Optional[str]) -> Optional[str]: """Clean and validate KML color string.""" color = clean_string(color) if color and not re.match(r'^[0-9A-Fa-f]{8}$', color): raise ValueError("KML color must be in aabbggrr format") return colorThen use it consistently:
-self.bg_color = clean_string(bg_color) -self.text_color = clean_string(text_color) +self.bg_color = clean_kml_color(bg_color) +self.text_color = clean_kml_color(text_color)fastkml/overlays.py (1)
472-473: Fix documentation formatting.There's an unnecessary blank line in the documentation that affects readability.
When you specify an image pyramid, you also need to modify the <href> in the <Icon> element to include specifications for which tiles to load. - https://developers.google.com/kml/documentation/kmlreference#imagepyramidfastkml/enums.py (3)
Line range hint
29-56: Replaceassertstatements with explicit type checks in_missing_methodUsing
assertstatements for type checking is not recommended in production code, as they can be disabled when Python is executed with optimizations (the-Oflag). It's better to use explicit type checks and raise appropriate exceptions to ensure that the code behaves correctly in all environments.Apply this diff to replace the
assertstatements with explicit type checks:@classmethod def _missing_(cls, value: object) -> "RelaxedEnum": - assert isinstance(value, str) # noqa: S101 + if not isinstance(value, str): + raise TypeError(f"Value must be a string, got {type(value).__name__}") value = value.lower() for member in cls: - assert isinstance(member.value, str) # noqa: S101 + if not isinstance(member.value, str): + raise TypeError( + f"Enum member values must be strings, got {type(member.value).__name__}" + ) if member.value.lower() == value.lower(): logger.warning( "%s: Found case-insensitive match for %s in %r", cls.__name__, value, member.value, ) return member msg = ( f"Unknown value '{value}' for {cls.__name__}'. " f"Known values are {', '.join(member.value for member in cls)}." ) raise ValueError(msg)
Line range hint
44-46: Reconsider logging level for case-insensitive matchesLogging a warning every time a case-insensitive match is found may result in excessive log output if this behavior is expected in normal usage. Consider changing the logging level to
INFOorDEBUG, or remove the log message if it's not critical.Apply this diff to adjust the logging level:
logger.warning( - "%s: Found case-insensitive match for %s in %r", + "%s: Found case-insensitive match for %s in %r", # Change to logger.info or remove cls.__name__, value, member.value, )
Line range hint
58-224: Potential conflict between@uniquedecorator andRelaxedEnumcase-insensitivityUsing the
@uniquedecorator withRelaxedEnummay not enforce uniqueness as intended when enum values differ only in case. SinceRelaxedEnumperforms case-insensitive matching, two members with values like"Value"and"value"would be considered the same, potentially leading to unexpected behavior despite the@uniqueconstraint.Consider verifying that all enum member values are unique regardless of case or remove the
@uniquedecorator if it's no longer applicable.fastkml/times.py (3)
Line range hint
49-63: Add exception handling toparsemethod to prevent unhandled exceptionsThe
parsemethod usesarrow.get(datestr).datetimewithout handling potential exceptions. Ifdatestris invalid or in an unsupported format, this could raise an exception and interrupt the program flow. To enhance robustness, consider adding atry-exceptblock to handle parsing errors gracefully.Apply this diff to add exception handling:
@classmethod def parse(cls, datestr: str) -> Optional["KmlDateTime"]: """Parse a KML DateTime string into a KmlDateTime object.""" resolution = None dt = None if year_month_day_match := year_month_day.match(datestr): # existing code... elif len(datestr) > 10: # noqa: PLR2004 - dt = arrow.get(datestr).datetime - resolution = DateTimeResolution.datetime + try: + dt = arrow.get(datestr).datetime + resolution = DateTimeResolution.datetime + except (arrow.parser.ParserError, ValueError): + return None return cls(dt, resolution) if dt else None
Line range hint
35-47: Simplify resolution assignment in__init__method for clarityThe current assignment of
self.resolutioninvolves a nested conditional that may reduce readability. Simplifying this assignment enhances understandability and maintains the intended functionality.Apply this diff to simplify the resolution assignment:
self.resolution = ( - DateTimeResolution.date - if not isinstance(self.dt, datetime) - and resolution == DateTimeResolution.datetime - else resolution + resolution )Given that adjustments to
dthave been made based onresolution, directly assigningself.resolution = resolutionis clearer and maintains consistency.
Line range hint
111-114: Correct the docstring inTimeStamp.__init__methodThe docstring currently states "Initialize a new instance of the Times class," which may confuse readers, as this is the
TimeStampclass.Apply this diff to correct the class name in the docstring:
""" -Initialize a new instance of the Times class. +Initialize a new instance of the TimeStamp class.fastkml/gx.py (5)
Line range hint
132-134: Correct the error message in the exception for clarityIn the
__init__method of theTrackclass, the error message incorrectly references'geometry', which is not an argument of the method. Since the condition checks for bothtrack_itemsandwhens/coordsbeing specified, please update the error message to accurately reflect the conflicting arguments.Apply this diff to fix the error message:
if (whens or coords) and track_items: - msg = "Cannot specify both geometry and track_items" + msg = "Cannot specify both track_items and whens/coords" raise ValueError(msg)
Line range hint
199-204: Ensure consistency between the docstring and the__init__methodIn the
__init__method of theMultiTrackclass, the docstring mentions that aValueErroris raised if bothgeometryandtracksare specified. However, there is nogeometryparameter in the method, and the code does not perform this check. Please update the docstring to reflect the actual parameters and behavior.Apply this diff to fix the docstring:
Raises: ------ - ValueError: If both geometry and tracks are specified. + # No ValueError is raised as 'geometry' is not a parameter.
Line range hint
136-145: Add validation to ensure matching lengths ofwhens,coords, andanglesIn the
__init__method of theTrackclass, when constructingtrack_items,zip_longestis used withfillvalue=(). This may lead to incompleteTrackIteminstances if the lengths ofwhens,coords, andanglesdo not match. Consider adding validation to ensure that these iterables have matching lengths to prevent potential errors.Apply this diff to add validation:
angles = list(angles) if angles else [] if not track_items and whens and coords: + if len(whens) != len(coords) or (angles and len(whens) != len(angles)): + raise ValueError("The lengths of 'whens', 'coords', and 'angles' must match") track_items = [
Line range hint
114-119: Clarify handling of potentiallyNonecoordinTrackItemIn the
TrackItemclass,coordis defined asgeo.Pointand is not optional. However, intrack_items_to_geometry, there's a conditionif item.coord is not None, implying thatcoordmight beNone. Please clarify whethercoordcan beNoneand update the type annotations accordingly. Ifcoordis always required, the condition may be unnecessary.
Line range hint
162-169: Simplify the__repr__method for clarityIn the
__repr__methods of bothTrackandMultiTrackclasses, there's an unnecessary trailing comma in the formatted string. Removing the comma will result in cleaner and more accurate string representations.Apply this diff to the
__repr__methods:f"**{self._get_splat()!r}," - ")" + ")"tests/hypothesis/feature_test.py (3)
96-129: Include zero values in test strategies forlongitude,latitude, andaltitudeZero is a valid coordinate value for longitude, latitude, and altitude. Including zero in your test cases ensures that your code correctly handles these values.
Apply this diff to include zero values:
longitude=st.floats( allow_nan=False, allow_infinity=False, min_value=-180, max_value=180, - ).filter(lambda x: x != 0), + ), latitude=st.floats( allow_nan=False, allow_infinity=False, min_value=-90, max_value=90, - ).filter(lambda x: x != 0), + ), altitude=st.floats( allow_nan=False, allow_infinity=False, - ).filter( - lambda x: x != 0, - ), + ),
169-176: Include empty and whitespace-only strings in test strategies foraddressandphone_numberIncluding empty and whitespace-only strings ensures that the code correctly handles these edge cases.
Apply this diff to enhance your test strategies:
address=st.one_of( st.none(), + st.just(""), + st.just(" "), - xml_text(min_size=1).filter(lambda x: x.strip() != ""), + xml_text(), ), phone_number=st.one_of( st.none(), + st.just(""), + st.just(" "), - xml_text(min_size=1).filter(lambda x: x.strip() != ""), + xml_text(), ),
304-328: IncludeNonein test strategy forextended_dataSince
extended_datais optional, includingNonein your test strategy ensures that cases where it's not provided are tested.Apply this diff to include
Nonein the test strategy:extended_data=st.one_of( + st.none(), st.builds( fastkml.ExtendedData, elements=st.tuples( st.builds( fastkml.data.Data, name=xml_text().filter(lambda x: x.strip() != ""), value=xml_text().filter(lambda x: x.strip() != ""), display_name=st.one_of(st.none(), xml_text()), ), st.builds( fastkml.SchemaData, schema_url=urls(), data=st.lists( st.builds( fastkml.data.SimpleData, name=xml_text().filter(lambda x: x.strip() != ""), value=xml_text().filter(lambda x: x.strip() != ""), ), min_size=1, max_size=3, ), ), ), ), ),fastkml/views.py (10)
Line range hint
77-135: Consider removing the 'Returns' section in__init__docstringsIn the
__init__method of the_AbstractViewclass (lines 77-135), the docstring includes aReturnssection statingNone. Since constructors in Python inherently returnNone, it's standard practice to omit this section to improve docstring clarity.
Line range hint
77-135: Ensure consistent docstring parameter headingsThe docstring in the
_AbstractViewclass uses the headingParametersfor the parameter list, while other classes likeCamerauseArgs. For consistency across the codebase, consider standardizing on one heading, such asParameters, in all docstrings.
Line range hint
141-167: Align default values between class attributes and registry entriesThe class attributes
longitude,latitude,altitude,heading, andtiltare initialized toNone, indicating they are optional. However, in the registry entries for_AbstractView(lines 141-167), these attributes have default values of0.0. This discrepancy could lead to inconsistencies, as the class might treat the absence of a value differently from a value of0.0.Proposed change to set consistent default values in the class constructor:
# In the __init__ method of _AbstractView - self.longitude = longitude - self.latitude = latitude - self.altitude = altitude - self.heading = heading - self.tilt = tilt + self.longitude = longitude if longitude is not None else 0.0 + self.latitude = latitude if latitude is not None else 0.0 + self.altitude = altitude if altitude is not None else 0.0 + self.heading = heading if heading is not None else 0.0 + self.tilt = tilt if tilt is not None else 0.0Alternatively, update the registry to have default values of
Noneif0.0is not the intended default.
Line range hint
179-235: Ensure consistent use of docstring headings inCameraclassIn the
Cameraclass__init__method (lines 179-235), the docstring uses the headingArgsinstead ofParametersas used in_AbstractView. For consistency, consider using the same heading across all docstrings.Proposed change:
- Args: + Parameters:
Line range hint
179-235: Align default values foraltitude_modebetween class and registryThe
altitude_modeattribute in theCameraclass is initialized toNone, but the registry entry (lines 232-239) sets a default ofAltitudeMode.clamp_to_ground. This inconsistency might cause unexpected behavior when the attribute is accessed through the registry. Consider setting a consistent default value.Proposed change to set default value in the class constructor:
- altitude_mode: Optional[AltitudeMode] = None, + altitude_mode: Optional[AltitudeMode] = AltitudeMode.clamp_to_ground,
Line range hint
241-275: Add missing registry entry foraltitude_modeinLookAtclassThe
LookAtclass defines thealtitude_modeattribute, but there is no corresponding registry entry for it. This omission could lead to issues when serializing or deserializing objects of this class.Proposed registry entry:
registry.register( LookAt, RegistryItem( ns_ids=("kml", "gx", ""), attr_name="altitude_mode", node_name="altitudeMode", classes=(AltitudeMode,), get_kwarg=subelement_enum_kwarg, set_element=enum_subelement, default=AltitudeMode.clamp_to_ground, ), )
Line range hint
276-354: Inconsistent types inLatLonAltBoxregistry entriesIn the
LatLonAltBoxclass (lines 276-354), attributes likenorth,south,east, andwestare declared asOptional[float], but in the registry entries (lines 335-360), they are registered withclasses=(float,)and no default values. If these attributes are optional, consider settingdefault=Nonein the registry entries to reflect their optional nature.Proposed change to registry entries:
RegistryItem( ns_ids=("kml",), attr_name="north", node_name="north", classes=(float,), get_kwarg=subelement_float_kwarg, set_element=float_subelement, + default=None, ),Repeat for
south,east, andwest.
Line range hint
358-417: Type mismatch inLodregistry entriesThe attributes
min_lod_pixels,max_lod_pixels,min_fade_extent, andmax_fade_extentin theLodclass (lines 358-417) are defined asOptional[int], but in the registry entries (lines 395-428), they are registered withclasses=(float,)and use integer default values. This type mismatch may lead to issues when parsing or writing these values.Proposed change to registry entries:
RegistryItem( ns_ids=("kml",), attr_name="min_lod_pixels", node_name="minLodPixels", - classes=(float,), + classes=(int,), get_kwarg=subelement_int_kwarg, set_element=int_subelement, default=256, ),Repeat for the other attributes.
Line range hint
358-417: Set default values forLodclass attributes in the constructorThe attributes in the
Lodclass are initialized toNone, but default values are provided in the registry. To maintain consistency, consider setting the default values directly in the constructor.Proposed change to the
__init__method:def __init__( self, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, - min_lod_pixels: Optional[int] = None, - max_lod_pixels: Optional[int] = None, - min_fade_extent: Optional[int] = None, - max_fade_extent: Optional[int] = None, + min_lod_pixels: Optional[int] = 256, + max_lod_pixels: Optional[int] = -1, + min_fade_extent: Optional[int] = 0, + max_fade_extent: Optional[int] = 0, **kwargs: Any, ) -> None:
Line range hint
421-468: Implement missing__eq__and__hash__methods forRegionclassThe
Regionclass (lines 421-468) may be used in contexts where object equality or hashing is important (e.g., in sets or as dictionary keys). Consider implementing__eq__and__hash__methods to define howRegionobjects are compared and hashed.
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
📒 Files selected for processing (54)
docs/create_kml_files.rst(1 hunks)docs/working_with_kml.rst(1 hunks)fastkml/__init__.py(1 hunks)fastkml/atom.py(4 hunks)fastkml/base.py(1 hunks)fastkml/config.py(2 hunks)fastkml/containers.py(6 hunks)fastkml/data.py(6 hunks)fastkml/enums.py(1 hunks)fastkml/features.py(5 hunks)fastkml/geometry.py(1 hunks)fastkml/gx.py(1 hunks)fastkml/helpers.py(1 hunks)fastkml/kml.py(3 hunks)fastkml/kml_base.py(1 hunks)fastkml/links.py(3 hunks)fastkml/mixins.py(1 hunks)fastkml/overlays.py(5 hunks)fastkml/registry.py(1 hunks)fastkml/styles.py(5 hunks)fastkml/times.py(1 hunks)fastkml/types.py(1 hunks)fastkml/views.py(1 hunks)tests/atom_test.py(1 hunks)tests/base.py(1 hunks)tests/base_test.py(0 hunks)tests/containers_test.py(0 hunks)tests/features_test.py(2 hunks)tests/geometries/coordinates_test.py(0 hunks)tests/geometries/functions_test.py(1 hunks)tests/geometries/geometry_test.py(1 hunks)tests/geometries/multigeometry_test.py(1 hunks)tests/gx_test.py(1 hunks)tests/helper_test.py(1 hunks)tests/hypothesis/atom_test.py(0 hunks)tests/hypothesis/common.py(2 hunks)tests/hypothesis/container_test.py(1 hunks)tests/hypothesis/feature_test.py(1 hunks)tests/hypothesis/geometry_test.py(1 hunks)tests/hypothesis/gx_test.py(3 hunks)tests/hypothesis/kml_test.py(1 hunks)tests/hypothesis/links_test.py(1 hunks)tests/hypothesis/multi_geometry_test.py(1 hunks)tests/hypothesis/overlay_test.py(1 hunks)tests/hypothesis/strategies.py(2 hunks)tests/hypothesis/times_test.py(1 hunks)tests/kml_test.py(1 hunks)tests/links_test.py(1 hunks)tests/registry_test.py(1 hunks)tests/styles_test.py(1 hunks)tests/times_test.py(1 hunks)tests/utils_test.py(1 hunks)tests/validator_test.py(1 hunks)tests/views_test.py(2 hunks)
💤 Files with no reviewable changes (4)
- tests/base_test.py
- tests/containers_test.py
- tests/geometries/coordinates_test.py
- tests/hypothesis/atom_test.py
✅ Files skipped from review due to trivial changes (4)
- fastkml/init.py
- fastkml/config.py
- fastkml/types.py
- tests/hypothesis/common.py
🔇 Additional comments (75)
fastkml/mixins.py (2)
Line range hint 17-24: LGTM! Well-structured imports with proper type hints
The imports are clean, well-organized, and include all necessary components for type safety and logging.
Line range hint 25-44: LGTM! Well-implemented mixin with proper type safety
The TimeMixin class is well-structured with:
- Clear and focused responsibility
- Proper type hints
- Comprehensive docstrings
- Null-safe property implementations
tests/base.py (2)
18-18: LGTM: Import statement is correctly placed and necessary.
The import of xml.etree.ElementTree is essential for providing standard library XML parsing capabilities.
Line range hint 42-42: LGTM: Skip condition is well implemented.
The skipif decorator correctly handles cases where lxml is not available, preventing test failures on systems without lxml installed.
tests/hypothesis/kml_test.py (2)
28-31: Refactor test utilities into a helper module
The current implementation imports assertion functions directly from test modules, which violates test isolation principles. Consider moving these utility functions to a dedicated helper module:
- Create a new module (e.g.,
tests/helpers/assertions.py) - Move the assertion functions there
- Update imports across all test files
This addresses the existing sourcery-ai comments about importing test modules.
66-66: Investigate and fix the type ignore comment
The # type: ignore[list-item] comment suggests a typing issue. Consider:
- Investigating why the type checker flags this
- Adding proper type hints or constraints to resolve the issue
- If the ignore is necessary, add a comment explaining why
Let's check the type definitions:
fastkml/registry.py (2)
Line range hint 109-111: LGTM! Clean and focused public API.
The exports are appropriately limited to just the essential components (registry and RegistryItem), maintaining a clean public API.
Line range hint 74-106: Consider adding validation for circular dependencies and maximum depth.
While the registry implementation handles inheritance well, it could benefit from additional safeguards.
Let's check for potential circular dependencies in the codebase:
tests/validator_test.py (2)
Line range hint 1-24: LGTM! Well-structured file header and imports.
The file is well-organized with proper copyright headers, docstrings, and imports. Good use of type hints with Final for constants.
Line range hint 27-30: LGTM! Good test isolation practice.
Clearing the schema parser cache before each test ensures proper test isolation.
fastkml/kml_base.py (3)
Line range hint 19-29: LGTM: Well-organized imports and module setup
The imports are properly organized, type-hinted, and follow best practices. The __all__ list correctly exports the new _BaseObject class.
Line range hint 84-103: LGTM: Well-implemented repr method
The __repr__ implementation is thorough and follows best practices:
- Includes all relevant attributes
- Properly handles the namespace and name spaces
- Includes additional kwargs via
_get_splat()
Line range hint 106-134: Verify registry usage across the codebase
The registry configuration looks correct. Let's verify that these registry entries are properly utilized across the codebase and that no conflicting registrations exist.
✅ Verification successful
Let me gather more specific information about the registry usage and implementation.
Let me check one more specific aspect about the actual usage of these registry entries.
Based on the comprehensive results from the shell scripts, I can now generate the final response:
Registry configuration for id and targetId attributes is properly implemented and utilized
The registry entries for id and target_id attributes are correctly configured and consistently used across the codebase:
- Base implementation in
kml_base.pyprovides the foundation for all KML objects - Proper XML serialization/deserialization with correct namespace handling
- Extensive test coverage verifying the behavior
- Consistent usage pattern across different KML element types (Styles, Geometries, Features, etc.)
- No conflicting registrations found
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for registry usage and potential conflicts
# Search for other registry configurations for id and targetId
echo "Checking for potential registry conflicts..."
rg -l "registry\.register.*id.*targetId" --type py
# Search for usage of these attributes in XML serialization
echo "Checking XML serialization usage..."
rg -l "(?i)(id|targetId).*(?:to_string|from_string|serialize|deserialize)" --type py
# Look for existing tests
echo "Checking for related tests..."
rg -l "(?i)test.*(?:id|targetId)" --type py tests/
Length of output: 850
Script:
#!/bin/bash
# Check the actual implementation and usage of these registry entries
# Look for the registry implementation details
echo "Registry implementation:"
rg -A 5 "class.*Registry" --type py
# Check for id and targetId attribute usage in base classes
echo "\nBase class attribute usage:"
rg -B 2 -A 2 "@property.*(?:id|target_id)" --type py
# Examine specific test cases for these attributes
echo "\nRelevant test cases:"
rg -B 2 -A 2 "def test.*(?:id|target_id)" tests/ --type py
# Check for actual XML serialization examples
echo "\nXML serialization examples:"
rg -B 2 -A 2 "to_string.*(?:id|targetId)" --type py
Length of output: 9256
Script:
#!/bin/bash
# Check for actual usage of id and target_id in the codebase
# Look for id attribute usage
echo "ID attribute usage:"
rg -B 2 -A 2 "\.id\s*=|id\s*=" --type py
# Look for target_id attribute usage
echo "\nTarget ID attribute usage:"
rg -B 2 -A 2 "\.target_id\s*=|target_id\s*=" --type py
# Check for any XML examples with these attributes
echo "\nXML examples with id/targetId:"
rg -B 2 -A 2 '<.*(?:id=|targetId=).*>' --type py
Length of output: 235982
tests/hypothesis/links_test.py (1)
Line range hint 17-36: LGTM! Well-organized imports.
The imports are properly organized and comprehensive, showing good separation between standard library, third-party, and local imports. All imports are relevant for property-based testing implementation.
tests/links_test.py (2)
18-18: LGTM!
The added empty line improves code readability by separating imports from class definitions.
Line range hint 94-95: Implementation appears incomplete
The TestLxml class is currently empty but inherits from both Lxml and TestStdLibrary. According to the PR summary, this class should include property-based testing using the Hypothesis library, particularly a test_fuzz_link method for testing fastkml.Link and fastkml.Icon.
Let's verify if the test implementation exists in other commits or files:
Would you like me to help generate the property-based test implementation using Hypothesis? This would include:
- Testing various combinations of Link/Icon parameters
- Testing edge cases and boundary conditions
- Ensuring proper handling of invalid inputs
tests/hypothesis/gx_test.py (1)
33-33: LGTM! Import of test strategies is appropriate here.
The import of track_items from the strategies module is a standard pattern for Hypothesis property-based testing, providing reusable test data generators.
tests/hypothesis/strategies.py (1)
31-31: LGTM!
The import is correctly placed and necessary for the new track items strategy.
tests/atom_test.py (1)
92-92: LGTM! Test updated to match new behavior.
The assertion change from "" to None correctly aligns with the refactoring that uses the new clean_string helper function for handling optional string attributes. This ensures consistent behavior across the codebase where missing or empty values are represented as None.
tests/registry_test.py (3)
17-17: LGTM! Well-organized imports with proper spacing.
The imports are properly organized and the added spacing improves readability.
Line range hint 241-245: LGTM! Simple and focused test.
The test case effectively verifies the string representation of an empty Registry.
Line range hint 63-77: Verify the intention of empty get_kwarg function.
The function has an empty body with # type: ignore[empty-body]. While this might be intentional for testing purposes, we should verify that this doesn't affect test coverage or functionality.
✅ Verification successful
Based on the search results, I can now generate the final response since I have enough context to verify the intention of the empty get_kwarg function in the test file.
Empty get_kwarg function is intentional for testing registry functionality.
The empty get_kwarg function in tests/registry_test.py is intentionally left empty as it's used as a mock function for testing the registry functionality. This is evident from:
- The function is used in multiple test registrations within the same test file
- It's consistently paired with
set_elementin test registry entries - The type ignore comment
# type: ignore[empty-body]is intentionally added to suppress the empty function warning - The function signature matches the pattern used throughout the codebase for actual get_kwarg implementations (like
subelement_text_kwarg,xml_subelement_kwarg, etc.)
🏁 Scripts executed
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#!/bin/bash
# Search for actual implementations or uses of get_kwarg
rg "get_kwarg" --type py -B 2 -A 2
Length of output: 44269
fastkml/kml.py (2)
48-48: LGTM: Import added correctly
The NetworkLink import is properly placed and aligns with the feature addition.
218-219: Verify NetworkLink integration with existing KML features
The addition of NetworkLink to the registry is correct and follows the KML specification. However, let's verify the integration:
✅ Verification successful
Let me gather more information about the NetworkLink implementation and its test coverage.
NetworkLink integration is properly implemented and tested
The verification shows that NetworkLink is well-integrated into the codebase:
- Comprehensive test coverage in multiple test files with both basic and advanced usage scenarios
- Proper implementation in
features.pywith complete documentation and KML spec compliance - Consistent registration across containers and KML parsers
- No circular dependencies found in the import structure
- Correctly integrated with other top-level features (Document, Folder, Placemark, etc.)
🏁 Scripts executed
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Script:
#!/bin/bash
# Description: Verify NetworkLink integration and usage
# Check if NetworkLink is used consistently in tests
echo "Checking for NetworkLink tests..."
rg -l "NetworkLink" --type py --glob "*test*.py"
# Verify if there are any existing KML files using NetworkLink
echo "Checking for NetworkLink examples..."
rg -l "NetworkLink" --type xml --type kml
# Check for any potential circular imports
echo "Checking for circular imports..."
rg -p "from.*import.*NetworkLink" --type py
Length of output: 645
Script:
#!/bin/bash
# Check NetworkLink test implementations
echo "NetworkLink test implementations:"
rg -A 5 "NetworkLink" tests/hypothesis/kml_test.py tests/hypothesis/container_test.py tests/features_test.py tests/hypothesis/feature_test.py
# Check NetworkLink feature implementation
echo -e "\nNetworkLink feature implementation:"
ast-grep --pattern 'class NetworkLink'
# Check if NetworkLink is properly registered in other places
echo -e "\nChecking other NetworkLink registrations:"
rg "NetworkLink" fastkml/ --type py -C 2
Length of output: 11807
tests/utils_test.py (1)
Line range hint 1-24: LGTM! Well-structured test file with proper imports.
The file follows good practices with:
- Up-to-date copyright header
- Organized imports
- Proper type hints
fastkml/links.py (2)
24-24: LGTM!
The clean_string helper import is correctly placed and necessary for the implementation.
49-56: Verify registry type consistency with Optional fields.
While the type annotations correctly specify Optional[str] for href, view_format, and http_query, the corresponding registry entries still specify classes=(str,). This might need to be updated to handle None values consistently.
tests/views_test.py (2)
146-156: LGTM! Well-structured assertions for Region object validation.
The added assertions provide comprehensive validation of the Region object, following a logical progression from object existence to specific attribute values. The test coverage is thorough and follows good testing practices.
179-187: LGTM! Comprehensive deserialization validation.
The added assertions thoroughly verify that all Region attributes are correctly preserved during XML deserialization.
docs/create_kml_files.rst (2)
169-170: LGTM!
Clear and appropriate initialization of the container lists for styles and folders.
171-173: LGTM!
The loop structure and feature extraction are well-implemented, maintaining consistency with the previous example.
docs/working_with_kml.rst (2)
Line range hint 1-48: Documentation structure and quality look great!
The documentation is well-organized, with clear examples and explanations. The code blocks are consistently formatted, and the examples effectively demonstrate the library's functionality.
Also applies to: 49-300
Line range hint 1-300: Verify doctest coverage for all examples.
The documentation contains numerous code examples with doctest directives. Let's verify that all examples are included in the test suite.
✅ Verification successful
Based on the gathered information, I can now provide the final response:
Documentation examples are properly tested through automated CI
The code examples in the documentation are verified through:
- A dedicated GitHub Actions job
doctest-lxmlthat runspython -m doctest docs/*.rst - Example files referenced in the documentation (e.g.,
gx_cascading_style.kml) exist in the examples directory - Sphinx configuration includes
sphinx.ext.doctestextension - All example scripts are executed in CI to ensure they work
🏁 Scripts executed
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Script:
#!/bin/bash
# Description: Check if all code examples in the documentation are tested
# Find all Python code blocks in the documentation
echo "Python code blocks found in documentation:"
rg -U "^\.\. code-block:: pycon\n\n( >>> .*\n)+" docs/working_with_kml.rst
# Look for corresponding test files
echo -e "\nSearching for test files that might contain these examples:"
fd -e py "test_.*\.py|.*_test\.py" | grep -i "doc\|example"
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Script:
#!/bin/bash
# Let's check if the documentation examples are tested through doctest
# First, check if there's a doctest configuration in setup.cfg or pytest.ini
echo "Checking for doctest configuration:"
fd "setup.cfg|pytest.ini|pyproject.toml" | xargs cat
# Then, look for test files that might run doctests
echo -e "\nLooking for test files that might run doctests:"
rg -l "doctest" tests/
# Finally, check if the documentation file itself is included in any test discovery
echo -e "\nChecking if documentation is referenced in test files:"
rg -l "working_with_kml.rst" tests/
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#!/bin/bash
# Let's check for doctest configuration in pytest configuration and actual test execution
# Check if there's a tox.ini file that might configure doctests
echo "Checking tox.ini for doctest configuration:"
fd "tox.ini" | xargs cat
# Look for any pytest configuration in conftest.py
echo -e "\nChecking conftest.py for doctest configuration:"
fd "conftest.py" | xargs cat
# Check the Makefile or other build scripts for test commands
echo -e "\nChecking Makefile for test commands:"
fd "Makefile" | xargs cat
# Look for any GitHub Actions workflow that runs tests
echo -e "\nChecking GitHub Actions workflows for test commands:"
fd -t f "\.github/workflows/.*\.(yml|yaml)" | xargs cat
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Script:
#!/bin/bash
# Let's check the docs directory for sphinx configuration and the CI directory for test configurations
# Check sphinx configuration for doctest settings
echo "Checking Sphinx configuration for doctest settings:"
fd "conf.py" docs/ | xargs cat
# Look for CI configuration files in the root directory
echo -e "\nChecking CI configuration files:"
rg -l "pytest|doctest" .circleci/ .github/ .gitlab-ci.yml .travis.yml 2>/dev/null || true
# Check if there are any test requirements files
echo -e "\nChecking test requirements:"
fd "requirements.*test.*\.(txt|in)" | xargs cat
# Look for pytest.ini or setup.cfg in the root
echo -e "\nChecking for pytest configuration in root:"
fd "pytest.ini|setup.cfg" --max-depth 1 | xargs cat
Length of output: 9660
Script:
#!/bin/bash
# Let's check the GitHub Actions workflow file and try to find how doctests are executed
echo "Checking GitHub Actions workflow for test execution:"
cat .github/workflows/run-all-tests.yml
# Also check if there are any example files referenced in the documentation
echo -e "\nChecking for example files referenced in docs:"
rg -l "examples/.*\.kml" docs/
# Check if the example files exist
echo -e "\nChecking for example KML files:"
fd -e kml . examples/
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tests/features_test.py (2)
19-30: LGTM: Imports are properly organized and necessary.
The new imports support the time-related functionality testing, aligning with the PR objectives.
53-94: LGTM: Well-structured test methods.
The new test methods are well-implemented:
- Each test focuses on a specific aspect (empty Placemark, Camera view, TimeSpan)
- Good coverage of edge cases and complex scenarios
- Proper use of assertions
- Consistent pattern for testing serialization/deserialization
tests/hypothesis/overlay_test.py (2)
36-244: Excellent property-based test coverage!
The test suite demonstrates comprehensive coverage of overlay classes using hypothesis strategies:
- Appropriate value ranges for angles, coordinates, and integers
- Good mix of optional (None) and required values
- Complex object composition testing
- Thorough roundtrip testing of string representations
This aligns well with the PR objective of introducing property-based testing using the Hypothesis library.
29-31: 🛠️ Refactor suggestion
Refactor test module imports into a helper module
As previously noted by sourcery-ai, importing from test modules is not recommended as tests should be self-contained. Consider moving the common test utilities (assert_repr_roundtrip, assert_str_roundtrip, etc.) into a dedicated helper module.
Create a new helper module (e.g., tests/helpers/assertions.py) and move the common test utilities there:
# tests/helpers/assertions.py
def assert_repr_roundtrip(obj):
# Implementation
pass
def assert_str_roundtrip(obj):
# Implementation
pass
# ... other assertion helpersThen update the imports:
-from tests.base import Lxml
-from tests.hypothesis.common import assert_repr_roundtrip
-from tests.hypothesis.common import assert_str_roundtrip
-from tests.hypothesis.common import assert_str_roundtrip_terse
-from tests.hypothesis.common import assert_str_roundtrip_verbose
+from tests.base import Lxml
+from tests.helpers.assertions import (
+ assert_repr_roundtrip,
+ assert_str_roundtrip,
+ assert_str_roundtrip_terse,
+ assert_str_roundtrip_verbose,
+)fastkml/base.py (2)
18-18: LGTM: Clean imports and proper type hints
The addition of Self type hint and proper module docstring spacing follows Python best practices.
Also applies to: 24-24
Line range hint 233-275: Verify the impact of strict parameter on existing code
The addition of the strict parameter to class_from_element looks good, but we should verify its usage in dependent code.
Let's check how this parameter is used across the codebase:
✅ Verification successful
Let me gather more information to verify the impact of the strict parameter.
The strict parameter is properly propagated and used consistently across the codebase
The verification shows that:
- All calls to
class_from_elementcorrectly pass thestrictparameter - The parameter is consistently propagated through helper functions in
fastkml/helpers.py - Test files demonstrate both strict and non-strict usage scenarios
- The implementation maintains backward compatibility while adding stricter validation
🏁 Scripts executed
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Script:
#!/bin/bash
# Description: Check usage of class_from_element and verify strict parameter handling
# Find all calls to class_from_element
echo "Checking calls to class_from_element:"
rg "class_from_element\(" -A 2
# Find all classes that inherit from _XMLObject
echo -e "\nChecking classes that might override class_from_element:"
ast-grep --pattern 'class $NAME($_XMLObject) { $$$ }'
Length of output: 1120
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#!/bin/bash
# Let's check the implementation details of class_from_element calls
# Check the content of files where class_from_element is called
echo "Content of fastkml/helpers.py around class_from_element calls:"
rg -B 5 -A 10 "class_from_element\(" fastkml/helpers.py
echo -e "\nContent of fastkml/kml.py around class_from_element calls:"
rg -B 5 -A 10 "class_from_element\(" fastkml/kml.py
# Check if there are any existing usages of 'strict' parameter
echo -e "\nChecking existing usages of 'strict' parameter:"
rg "\bstrict\s*=" -A 2
Length of output: 8214
fastkml/atom.py (3)
45-45: LGTM: Import of clean_string helper function
The import is correctly placed and aligns with the PR's objective of standardizing string attribute handling.
86-90: LGTM: Type hints and initialization updates
The changes correctly:
- Update type hints to
Optional[str]to reflect that attributes can be None - Use
clean_stringconsistently for all string attributes - Maintain compatibility with the XML registry configuration
These changes align with the PR's goal of standardizing string attribute handling.
Also applies to: 137-141
289-291: LGTM: Consistent string handling in _Person class
The initialization changes correctly use clean_string for all string attributes, maintaining consistency with the rest of the codebase.
fastkml/containers.py (4)
31-31: LGTM: New imports align with registry updates
The addition of NetworkLink, GroundOverlay, and PhotoOverlay imports supports the expanded container functionality.
Also applies to: 42-43
172-173: LGTM: Enhanced documentation with official reference
The addition of the KML documentation link improves the class documentation by providing a reference to the official specification.
208-208: LGTM: Enhanced parameter flexibility
The change from List to Iterable for the features parameter is a good improvement as it:
- Provides more flexibility in input types
- Maintains backward compatibility
- Follows Python's collections abstraction principles
331-332: Verify implementation and test coverage for newly registered classes
The registry updates appropriately expand container functionality to include overlay and network link features.
Let's verify the implementation and test coverage:
✅ Verification successful
Implementation and test coverage verified for newly registered classes
The classes are properly implemented and tested:
- All three classes (
GroundOverlay,PhotoOverlay,NetworkLink) have complete implementations with proper documentation infastkml/overlays.pyandfastkml/features.py - Comprehensive test coverage exists:
- Unit tests in
tests/overlays_test.pyandtests/features_test.py - Property-based tests in
tests/hypothesis/overlay_test.pyandtests/hypothesis/feature_test.py - Integration tests covering creation and reading scenarios
- Unit tests in
- Sample usage demonstrated in
examples/KML_Samples.kml
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check implementation and test coverage for newly registered classes
# Check for test files
echo "Checking for test files..."
fd -e py test
# Check test coverage for new features
echo "Checking test coverage for new features..."
rg -l "class.*(?:GroundOverlay|PhotoOverlay|NetworkLink).*Test" -t py
# Check for usage examples
echo "Checking for usage examples..."
rg -l "(?:GroundOverlay|PhotoOverlay|NetworkLink)" -g "*.rst" -g "*.md"
Length of output: 1539
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#!/bin/bash
# Let's check the implementation of these classes and their test coverage
# Check class implementations
echo "Checking class implementations..."
ast-grep --pattern 'class (GroundOverlay|PhotoOverlay|NetworkLink)'
# Check test content for these features
echo "Checking test content..."
rg -A 5 'class.*(GroundOverlay|PhotoOverlay|NetworkLink).*Test' tests/
# Check actual test cases
echo "Checking test cases..."
rg 'def test.*(ground|photo|network)' tests/ -i
# Check if these classes are imported and used in tests
echo "Checking imports in tests..."
rg '^from.*import.*(GroundOverlay|PhotoOverlay|NetworkLink)' tests/
Length of output: 1761
Script:
#!/bin/bash
# Let's check the actual implementation details of these classes
# Check for class implementations in the source code
echo "Checking source implementations..."
rg -A 10 '^class (GroundOverlay|PhotoOverlay|NetworkLink)' fastkml/
# Check for their property definitions
echo "Checking class properties..."
rg 'class.*(GroundOverlay|PhotoOverlay|NetworkLink).*:[\s\S].*property' fastkml/
# Check for any usage in example files
echo "Checking examples..."
fd -e py examples/
rg -l '(GroundOverlay|PhotoOverlay|NetworkLink)' examples/ || true
Length of output: 2984
tests/times_test.py (1)
Line range hint 1-18: Well-structured test organization!
The test file follows good practices with clear separation of concerns between different test categories and proper inheritance hierarchy.
tests/hypothesis/geometry_test.py (1)
Line range hint 1-400: Overall implementation looks solid
The property-based testing implementation is comprehensive and well-structured. The suggested improvements are mainly for maintainability and don't affect the functionality.
tests/geometries/multigeometry_test.py (2)
Line range hint 1-28: LGTM! Well-organized file structure.
The file follows good practices with:
- Clear license header
- Proper module docstring
- Well-organized imports (stdlib → third-party → local)
Line range hint 31-32: LGTM! Excellent test class organization.
The test classes follow best practices:
- Clear separation of concerns by geometry type
- DRY principle through inheritance (lxml classes reuse stdlib test cases)
- Consistent naming convention
Also applies to: 234-250
fastkml/data.py (4)
120-122: LGTM: String sanitization properly implemented
The use of clean_string for name and display_name attributes improves string handling consistency. The type_ attribute correctly remains untouched as it's an enum.
368-370: LGTM: Consistent string handling implementation
The use of clean_string for all string attributes is consistent and properly supports the class's boolean logic that depends on name and value.
475-476: LGTM: Proper string sanitization implemented
The implementation correctly uses clean_string for both name and value attributes, maintaining consistency with the class's boolean logic.
250-252: Verify clean_string behavior with Schema id
While the use of clean_string improves string handling, we need to ensure it doesn't inadvertently create invalid schemas when cleaning the required id field.
✅ Verification successful
Based on the gathered information, I can now provide the final response:
clean_string usage with Schema id is safe
The implementation is safe because:
- Schema validates
idbeforeclean_stringis applied - it raisesKMLSchemaErrorifidis not provided clean_stringreturnsNoneonly for empty strings orNonevalues- The validation happens first, ensuring that empty strings or
Nonevalues are caught before cleaning
Therefore, valid Schema IDs will remain valid after cleaning, as the validation ensures non-empty values before cleaning is applied.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check clean_string implementation to ensure it doesn't return None for non-empty strings
# that might be valid Schema IDs
# Search for clean_string implementation
echo "Searching for clean_string implementation:"
rg -A 5 "def clean_string"
# Search for any existing tests that verify this behavior
echo "Searching for relevant tests:"
rg -l "clean_string.*Schema.*id" tests/
Length of output: 547
Script:
#!/bin/bash
# Let's verify the Schema class implementation and its id validation
echo "Checking Schema class implementation and id validation:"
rg -A 10 "class Schema" fastkml/
# Check for KMLSchemaError usage with id
echo "Checking KMLSchemaError usage with id:"
rg "KMLSchemaError.*id" fastkml/
# Look for Schema tests
echo "Checking Schema tests:"
rg -A 5 "def test.*Schema" tests/
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#!/bin/bash
# Let's check the Schema class implementation more thoroughly
echo "Checking Schema class implementation:"
rg -B 5 -A 20 "def __init__" fastkml/data.py
# Check for any validation or error handling related to Schema id
echo "Checking validation and error handling:"
rg -B 2 -A 2 "KMLSchemaError" fastkml/
# Look for Schema usage in test files
echo "Checking Schema tests:"
rg -l "Schema.*id.*=.*" tests/
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#!/bin/bash
# Let's check the actual Schema id validation in tests
echo "Checking Schema tests for id validation:"
rg -B 2 -A 5 "def test.*Schema.*id" tests/data_test.py
# Check the implementation of id validation in Schema
echo "Checking Schema id validation implementation:"
rg -B 10 -A 5 "if not id:" fastkml/data.py
# Let's also check if there are any test cases with empty strings
echo "Checking test cases with empty strings:"
rg "Schema.*id.*=.*\"\"" tests/
rg "Schema.*id.*=.*''" tests/
Length of output: 854
tests/gx_test.py (2)
18-18: LGTM: Clean datetime import addition
The datetime import is appropriately added and necessary for handling KML timestamps in the test cases.
Line range hint 32-394: Consider adding property-based tests as mentioned in PR objectives
While the test coverage is comprehensive with both positive and negative test cases, the PR objectives mention introducing property-based testing using the Hypothesis library. Consider adding property-based tests to further enhance the test suite.
Let's check if Hypothesis tests are implemented in other test files:
Would you like help implementing property-based tests for the Track and MultiTrack classes?
tests/kml_test.py (1)
Line range hint 1-24: Missing property-based testing implementation
The PR objectives mention introducing property-based testing using the Hypothesis library, but this test file doesn't contain any Hypothesis-based tests. Consider adding property-based tests to improve test coverage and catch edge cases.
Here's a suggested structure for adding property-based tests:
from hypothesis import given
from hypothesis import strategies as st
class TestKMLPropertyBased:
@given(st.text())
def test_kml_name_property(self, name):
# Test KML name with various generated strings
doc = Document(name=name)
assert doc.name == nametests/hypothesis/multi_geometry_test.py (1)
18-18: Consider applying deadline settings consistently
The @settings(deadline=1_000) is only applied to test_multipoint_repr_roundtrip. Consider either:
- Applying it consistently to all test methods if the timeout is needed
- Removing it if it's not necessary
- Documenting why only this specific test needs it
Let's check if other similar tests might need the deadline setting:
Also applies to: 216-217
tests/geometries/geometry_test.py (2)
Line range hint 1-33: LGTM! Well-structured test file with clear organization.
The file has proper licensing, documentation, and well-organized imports that clearly separate external and internal dependencies.
Line range hint 424-436: LGTM! Excellent test class hierarchy design.
The inheritance structure with base test classes and lxml variants is a great example of the DRY principle, allowing comprehensive testing across different XML parsers while maintaining code reusability.
fastkml/features.py (3)
47-47: LGTM: Clean string helper import added
The addition of the clean_string helper function import aligns with the refactoring goal to standardize string handling across the codebase.
137-137: Consistent string sanitization implemented
The implementation of clean_string for text attributes (name, description, address, phone_number) ensures consistent handling of string values across the codebase. This is a good improvement for maintainability and reliability.
Also applies to: 290-291, 300-301
Line range hint 697-714: Verify the impact of adding 'gx' namespace
The addition of the "gx" namespace to ns_ids for Placemark's geometry registration expands support for Google Earth extensions. While this is a good enhancement, we should verify that all geometry types are properly handled.
✅ Verification successful
Let me gather more information about the implementation and usage of these gx geometries.
Let me check one more aspect to verify the namespace registration and test coverage more thoroughly.
The addition of 'gx' namespace is properly implemented and tested
Based on the verification results:
- The gx namespace is correctly declared with URI "http://www.google.com/kml/ext/2.2"
- Both Track and MultiTrack classes are fully implemented in
fastkml/gx.py - Comprehensive test coverage exists in
tests/gx_test.pyincluding:- Parsing and serialization of Track and MultiTrack elements
- Handling of track items with coordinates, timestamps, and angles
- Edge cases and error conditions
- Testing with both standard library and lxml parsers
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for any gx namespace geometry usage in the codebase
# Expected results: Find any existing uses of gx:Track or gx:MultiTrack to validate the namespace addition
# Search for gx geometry usage
echo "Searching for gx geometry usage..."
rg -l "gx:(Track|MultiTrack)"
# Check for potential geometry type definitions
echo "Checking for geometry type definitions..."
ast-grep --pattern 'class $name(Track|MultiTrack)'
Length of output: 334
Script:
#!/bin/bash
# Check the implementation of Track and MultiTrack classes
echo "Checking Track and MultiTrack implementations in gx.py..."
rg -A 10 "class (Track|MultiTrack)" fastkml/gx.py
# Check test coverage
echo "Checking test coverage for gx geometries..."
rg -A 5 "def test.*?(Track|MultiTrack)" tests/gx_test.py
# Verify namespace registration
echo "Checking namespace registration..."
rg "ns = .*?gx" fastkml/
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#!/bin/bash
# Check namespace declarations and usage
echo "Checking namespace declarations..."
rg "gx.*?http" fastkml/
# Check test imports and setup
echo "Checking test setup..."
rg -A 5 "^import.*?gx|^from.*?gx" tests/gx_test.py
# Check for Track/MultiTrack test cases
echo "Checking Track/MultiTrack test cases..."
rg -B 2 -A 10 "Track|MultiTrack" tests/gx_test.py
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fastkml/helpers.py (1)
44-46: Verify the integration of clean_string function.
Let's verify the usage of this function across the codebase to ensure proper integration.
✅ Verification successful
clean_string function is properly integrated and widely used
The function is well integrated across the codebase:
- Correctly imported and used in Link and _Person classes as intended
- Widely utilized in other key components:
- atom.py: Used for href, rel, type, name, uri, and email fields
- links.py: Used for href, view_format, and http_query
- styles.py: Used for color, text, bg_color, text_color fields
- data.py: Used for name, display_name, value fields
- features.py: Used for text, name, description, address fields
- overlays.py: Used for color field
All existing string stripping operations in the codebase are either:
- Already using clean_string
- Part of test files
- Part of specialized parsing logic in helpers.py and geometry.py
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check the usage of clean_string function across the codebase
# Find files importing clean_string
echo "Files importing clean_string:"
rg "from fastkml.helpers import .*clean_string" -l
# Find potential usage in Link and _Person classes
echo -e "\nUsage in Link and _Person classes:"
rg -A 5 "class (?:Link|_Person)"
# Find other potential places where clean_string could be used
echo -e "\nPotential places where clean_string could be used:"
rg "\.strip\(\)\s*(?:or None|if\s|==\s|!=\s)" --type python
Length of output: 1288
Script:
#!/bin/bash
# Let's verify the actual usage of clean_string in the identified files
# Check how clean_string is used in Link and _Person classes
echo "Usage in Link class:"
rg -B 2 -A 2 "clean_string" fastkml/links.py
echo -e "\nUsage in _Person class and atom.py:"
rg -B 2 -A 2 "clean_string" fastkml/atom.py
# Check other usages for completeness
echo -e "\nUsage in other files:"
for file in fastkml/overlays.py fastkml/styles.py fastkml/data.py fastkml/features.py; do
echo -e "\nIn $file:"
rg -B 2 -A 2 "clean_string" "$file"
done
# Let's also check for any string stripping patterns that might benefit from clean_string
echo -e "\nPotential places for clean_string usage:"
rg "\.strip\(\)" --type-add 'python:*.py' --type python
Length of output: 9199
fastkml/styles.py (3)
42-42: LGTM: Clean import organization
The clean_string helper function import is properly placed with other helper function imports.
112-112: LGTM: Consistent URL string handling
Using clean_string for URL sanitization ensures consistent handling of whitespace and None values.
478-478: LGTM: Proper icon URL sanitization
The icon_href sanitization is correctly placed before the conditional logic that uses this value.
fastkml/overlays.py (4)
40-40: LGTM!
The import of clean_string is appropriately placed and aligns with the PR's objective of standardizing string handling.
207-207: LGTM! Good use of clean_string for color validation.
The use of clean_string for color validation enhances data integrity by standardizing string handling.
558-558: LGTM! Simplified boolean logic.
The __bool__ method has been appropriately simplified to only check essential attributes (max_width and max_height). This is a good optimization since tile_size and grid_origin have default values and aren't critical for determining the validity of an ImagePyramid.
1267-1267: LGTM! Enhanced namespace support.
The addition of gx and empty string namespaces for altitudeMode improves compatibility with different KML variants.
fastkml/geometry.py (2)
Line range hint 401-476: Implementation looks solid!
The Point class implementation follows good practices:
- Clear error handling for mutual exclusivity between geometry and kml_coordinates
- Proper type hints and documentation
- Comprehensive property implementations
Line range hint 611-612: Verify similar geometry existence checks in other classes
The same potential issue with falsy geometry values exists in other geometry classes. Let's verify and fix all occurrences.
Run this script to find all similar patterns:
Apply these fixes to make all geometry existence checks explicit:
# In LineString class
- if kml_coordinates is None:
- kml_coordinates = Coordinates(coords=geometry.coords) if geometry else None
+ if kml_coordinates is None and geometry is not None:
+ kml_coordinates = Coordinates(coords=geometry.coords)
# In Polygon class
- if geometry is not None:
- outer_boundary = OuterBoundaryIs(geometry=geometry.exterior)
+ if geometry is not None:
+ outer_boundary = OuterBoundaryIs(geometry=geometry.exterior) if geometry.exterior is not None else None
# In MultiGeometry class
- if kml_geometries is not None and geometry is not None:
+ if kml_geometries is not None and geometry is not None:Also applies to: 917-918, 1147-1148
fastkml/times.py (1)
Line range hint 160-163: Ensure consistency in __bool__ methods across classes
The __bool__ methods in KmlDateTime, TimeStamp, and TimeSpan classes have slightly different implementations. In KmlDateTime, it checks if self.dt is an instance of date, while in TimeStamp and TimeSpan, it checks the truthiness of self.timestamp, self.begin, or self.end. For consistency and to accurately reflect the validity of the instances, consider harmonizing these methods.
Please review the __bool__ methods to ensure they consistently determine the validity of the objects.
fastkml/views.py (1)
Line range hint 421-468: Ensure proper boolean evaluation in Region class
The __bool__ method in the Region class (lines 464-468) returns bool(self.lat_lon_alt_box). Since lat_lon_alt_box can be an object that may not have a boolean value, ensure that its __bool__ method is properly defined or adjust the evaluation to prevent unexpected results.
| @@ -14,6 +14,7 @@ | |||
| # along with this library; if not, write to the Free Software Foundation, Inc., | |||
| # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA | |||
| """Test the validator module.""" | |||
|
|
|||
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🛠️ Refactor suggestion
Consider adding property-based testing with Hypothesis.
Given the PR's objective to introduce Hypothesis testing, consider adding property-based tests for the validator module. This could help discover edge cases in validation logic by generating various KML inputs.
Example approach:
from hypothesis import given
from hypothesis import strategies as st
@given(st.text())
def test_validate_with_random_href(self, href: str) -> None:
link = atom.Link(href=href)
# Test validation behavior with random href valuesWould you like me to help implement property-based tests for this module?
| from tests.base import Lxml | ||
| from tests.hypothesis.common import assert_repr_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip | ||
| from tests.hypothesis.common import assert_str_roundtrip_terse | ||
| from tests.hypothesis.common import assert_str_roundtrip_verbose | ||
| from tests.hypothesis.strategies import nc_name |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Refactor test module imports into a helper module
The imports from test modules (tests.base, tests.hypothesis.common, tests.hypothesis.strategies) violate testing best practices. Tests should be self-contained and not depend on other test modules.
Consider moving the shared test utilities (assert_repr_roundtrip, assert_str_roundtrip, etc.) and the Lxml base class into a dedicated test helpers module (e.g., tests/helpers/assertions.py and tests/helpers/base.py).
| features_tuple=st.tuples( | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.containers.Document, | ||
| ), | ||
| ), | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.containers.Folder, | ||
| ), | ||
| ), | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.features.Placemark, | ||
| ), | ||
| ), | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.overlays.GroundOverlay, | ||
| ), | ||
| ), | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.overlays.PhotoOverlay, | ||
| ), | ||
| ), | ||
| st.lists( | ||
| st.builds( | ||
| fastkml.features.NetworkLink, | ||
| link=st.builds( | ||
| fastkml.links.Link, | ||
| href=urls(), | ||
| ), | ||
| ), | ||
| ), | ||
| ), | ||
| schemata=st.lists( | ||
| st.builds( | ||
| fastkml.data.Schema, | ||
| id=nc_name(), | ||
| ), | ||
| max_size=1, | ||
| ), | ||
| ) |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Reduce code duplication and improve schema validation
- The feature generation strategy is duplicated from
test_fuzz_folder - Schema ID uniqueness is not enforced
Extract the common feature generation strategy:
# At module level
def feature_tuple_strategy():
return st.tuples(
st.lists(st.builds(fastkml.containers.Document), max_size=3),
st.lists(st.builds(fastkml.containers.Folder), max_size=3),
# ... other features ...
)
# In test methods
@given(
features_tuple=feature_tuple_strategy(),
schemata=st.lists(
st.builds(
fastkml.data.Schema,
id=st.from_type(str).filter(lambda x: x.isalnum()), # Ensure valid IDs
),
max_size=1,
unique_by=lambda x: x.id, # Ensure unique IDs
),
)| north=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), | ||
| south=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), | ||
| east=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), | ||
| west=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider tightening coordinate validation for LatLonBox
The latitude values (north/south) should be constrained to [-90, 90] instead of [-180, 180], as these represent degrees of latitude.
Update the latitude constraints:
north=st.one_of(
st.none(),
- st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
+ st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),
),
south=st.one_of(
st.none(),
- st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
+ st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),
),Committable suggestion skipped: line range outside the PR's diff.
| href: Optional[str] | ||
| rel: Optional[str] | ||
| type: Optional[str] | ||
| hreflang: Optional[str] | ||
| title: Optional[str] |
There was a problem hiding this comment.
💡 Codebase verification
Tests need to be updated for None values
The verification revealed that tests need to be updated to handle the change from empty strings to None values:
tests/styles_test.pycontains a test withhref=""that should be updated tohref=Nonetests/validator_test.pycontains a test withhref=""that should be updated tohref=Nonetests/atom_test.pyalready has some tests usingis Noneassertions, but should be reviewed for consistency
🔗 Analysis chain
Verify test coverage for None values
The change from empty strings to None values requires verification of test coverage and string comparisons.
Also applies to: 289-291
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check test coverage and string comparisons for atom classes
# Check for string comparisons in tests
echo "Checking for string comparisons in tests..."
rg -l "assert.*\.(?:href|rel|type|hreflang|title|name|uri|email)\s*==" tests/
rg -l "assert.*\.(?:href|rel|type|hreflang|title|name|uri|email)\s*!=" tests/
# Check for empty string assignments in tests
echo "Checking for empty string assignments in tests..."
rg -l "(?:href|rel|type|hreflang|title|name|uri|email)\s*=\s*[\"']\"" tests/
# Look for potential string comparisons in the main codebase
echo "Checking for string comparisons in main codebase..."
rg -l "\.(?:href|rel|type|hreflang|title|name|uri|email)\s*(?:==|!=)\s*[\"']" fastkml/
Length of output: 917
Script:
#!/bin/bash
# Let's examine the actual test assertions and string comparisons in detail
echo "Checking test assertions in atom_test.py..."
rg "assert.*\.(?:href|rel|type|hreflang|title|name|uri|email)" tests/atom_test.py -B 2 -A 2
echo "\nChecking empty string assignments in styles_test.py..."
rg "(?:href|rel|type|hreflang|title|name|uri|email)\s*=\s*[\"']\"" tests/styles_test.py -B 2 -A 2
echo "\nChecking empty string assignments in validator_test.py..."
rg "(?:href|rel|type|hreflang|title|name|uri|email)\s*=\s*[\"']\"" tests/validator_test.py -B 2 -A 2
echo "\nChecking string comparisons in tests/utils_test.py..."
rg "assert.*\.(?:href|rel|type|hreflang|title|name|uri|email)\s*==" tests/utils_test.py -B 2 -A 2
Length of output: 2309
| @@ -425,7 +425,7 @@ def __init__( | |||
| """ | |||
| if geometry is not None and kml_coordinates is not None: | |||
| raise GeometryError(MsgMutualExclusive) | |||
| if kml_coordinates is None: | |||
| if kml_coordinates is None and geometry: | |||
There was a problem hiding this comment.
Make geometry existence check more explicit
The current check if kml_coordinates is None and geometry: could have issues with falsy geometry values. While the geometry parameter is typed as Optional[geo.Point], it's better to be explicit about the None check.
Apply this diff to make the check more explicit:
- if kml_coordinates is None and geometry:
+ if kml_coordinates is None and geometry is not None:📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| if kml_coordinates is None and geometry: | |
| if kml_coordinates is None and geometry is not None: |
There was a problem hiding this comment.
Actionable comments posted: 5
🧹 Outside diff range and nitpick comments (93)
fastkml/mixins.py (1)
Line range hint
32-45: Consider enhancing property documentation.While the properties are well-implemented, their documentation could be more comprehensive. Consider adding:
- Edge case behavior (e.g., when
timesis None)- Example usage
- Return value description
Example enhancement for
time_stamp:@property def time_stamp(self) -> Optional[KmlDateTime]: """Return the timestamp if available. Returns: Optional[KmlDateTime]: The timestamp if times is a TimeStamp instance, None if times is None or a TimeSpan instance. Example: >>> feature = KmlFeature() >>> feature.times = TimeStamp(timestamp=KmlDateTime.from_string("2023-01-01")) >>> feature.time_stamp KmlDateTime(2023-01-01) """ return self.times.timestamp if isinstance(self.times, TimeStamp) else Nonetests/hypothesis/kml_test.py (4)
16-16: Enhance module docstring with more details.The current docstring could be more descriptive. Consider adding information about:
- The purpose of property-based testing in this context
- The types of KML features being tested
- The testing strategy being employed
Example enhancement:
-"""Property-based tests for the views module.""" +"""Property-based tests for KML feature serialization and deserialization. + +This module uses Hypothesis to generate various KML features (Document, Folder, +Placemark, etc.) and tests their round-trip serialization behavior through +different formats (repr, str, terse, verbose). +"""
61-64: Rename test method to better reflect its purpose.The current name
test_fuzz_documentdoesn't fully capture what's being tested. Consider a more descriptive name that reflects the round-trip serialization testing of various KML features.-def test_fuzz_document( +def test_kml_feature_roundtrip_serialization(
65-67: Address type annotation issue.The
# type: ignore[list-item]comment suggests a type mismatch. Consider creating a proper type union for the features list or using a protocol to define the expected interface.- kml = fastkml.kml.KML( - features=[feature], # type: ignore[list-item] - ) + # Define a Protocol or Union type in a types.py file + from typing import Union + KMLFeature = Union[ + fastkml.containers.Document, + fastkml.containers.Folder, + fastkml.features.Placemark, + fastkml.overlays.GroundOverlay, + fastkml.overlays.PhotoOverlay, + fastkml.features.NetworkLink, + ] + kml = fastkml.kml.KML(features=[feature])
69-72: Add specific assertions for KML feature attributes.The current assertions only verify round-trip serialization. Consider adding specific assertions to validate the feature's attributes remain unchanged through the serialization process.
# Add assertions to verify feature attributes original_attrs = {k: getattr(feature, k) for k in feature.__slots__} serialized = str(kml) deserialized = fastkml.kml.KML() deserialized.from_string(serialized) deserialized_feature = deserialized.features[0] for attr, value in original_attrs.items(): assert getattr(deserialized_feature, attr) == value, f"Attribute {attr} changed during serialization"tests/hypothesis/times_test.py (3)
22-22: Enhance module docstring with specific test coverage details.Consider expanding the docstring to specify which classes (
TimeStampandTimeSpan) are being tested and what aspects (string representation, round-trip conversions) are being validated.""" Property-based tests for the times module. These tests use the hypothesis library to generate random input for the -functions under test. The tests are run with pytest. +functions under test. The tests validate the string representation and +round-trip conversions of TimeStamp and TimeSpan classes using pytest. """
Line range hint
35-48: Add docstring and edge case validation for TimeStamp test.The test method would benefit from a docstring explaining the test strategy and validation approach. Also, consider adding specific test cases for edge cases.
@given( id=st.one_of(st.none(), nc_name()), target_id=st.one_of(st.none(), nc_name()), timestamp=st.one_of(st.none(), kml_datetimes()), ) def test_fuzz_time_stamp( self, id: typing.Optional[str], target_id: typing.Optional[str], timestamp: typing.Optional[fastkml.times.KmlDateTime], ) -> None: + """Test TimeStamp initialization and string representations. + + Tests various combinations of optional parameters and validates + that string representations can be correctly round-tripped. + """ time_stamp = fastkml.TimeStamp(id=id, target_id=target_id, timestamp=timestamp)
Line range hint
50-71: Add validation for TimeSpan begin/end relationship.The test should validate that begin time is not after end time when both are provided. Consider adding assumptions or assertions to check this temporal relationship.
@given( id=st.one_of(st.none(), nc_name()), target_id=st.one_of(st.none(), nc_name()), begin=st.one_of(st.none(), kml_datetimes()), end=st.one_of(st.none(), kml_datetimes()), ) def test_fuzz_time_span( self, id: typing.Optional[str], target_id: typing.Optional[str], begin: typing.Optional[fastkml.times.KmlDateTime], end: typing.Optional[fastkml.times.KmlDateTime], ) -> None: + """Test TimeSpan initialization and string representations. + + Tests various combinations of optional parameters and validates + that string representations can be correctly round-tripped. + Also ensures proper temporal relationship between begin and end times. + """ + # Skip test if begin time is after end time + if begin is not None and end is not None and begin > end: + return + time_span = fastkml.TimeSpan(id=id, target_id=target_id, begin=begin, end=end)tests/geometries/functions_test.py (3)
Line range hint
33-49: Consider enhancing test coverage with additional test cases.While the test effectively verifies the basic error handling, consider adding:
- Test cases with different ValueError messages to ensure proper error propagation
- A docstring explaining the test's purpose and expectations
def test_handle_invalid_geometry_error_true( self, mock_to_string: Callable[..., str], ) -> None: + """Test that handle_invalid_geometry_error raises KMLParseError in strict mode. + + Verifies that: + 1. KMLParseError is raised with the correct message + 2. The error message contains the XML representation of the invalid element + """
Line range hint
51-64: Consider enhancing non-strict mode test coverage.While the test verifies the basic non-strict behavior, consider:
- Adding test cases with different ValueError messages
- Adding a docstring explaining the test's purpose
- Verifying any logging behavior that should occur in non-strict mode
def test_handle_invalid_geometry_error_false( self, mock_to_string: Callable[..., str], ) -> None: + """Test that handle_invalid_geometry_error suppresses errors in non-strict mode. + + Verifies that: + 1. No exception is raised + 2. The error is properly logged (if applicable) + """
Line range hint
66-89: Enhance test clarity and coverage for coordinates validation.The test could be improved in several ways:
- Add a docstring explaining what makes the coordinates invalid
- Test different invalid coordinate scenarios
- Document why precision=9 was chosen
- Add assertions about the error message content
def test_coordinates_subelement_exception(self) -> None: + """Test that coordinates_subelement raises KMLWriteError for invalid coordinates. + + Tests that coordinates with more than 3 dimensions (1.1, 2.6, 3.1, 4.2) + raise KMLWriteError. KML only supports 2D or 3D coordinates. + """ obj = Mock() obj.coordinates = [(1.123456, 2.654321, 3.111111, 4.222222)] element = Mock() - precision = 9 + precision = 9 # Standard precision for coordinate decimal places with pytest.raises(KMLWriteError): coordinates_subelement( obj=obj, attr_name=attr_name, node_name="", element=element, precision=precision, verbosity=Verbosity.terse, default=None, ) + + # Add more test cases for other invalid scenarios + obj.coordinates = [(1.1,)] # Test 1D coordinates + with pytest.raises(KMLWriteError, match="Invalid coordinate dimensions"): + coordinates_subelement(...)fastkml/registry.py (4)
Line range hint
33-57: LGTM! Consider adding docstrings to protocols.The protocol definitions are well-structured with clear parameter types. However, adding docstrings would improve developer experience by documenting the expected behavior of these interfaces.
Add docstrings to explain the purpose and expected behavior:
class GetKWArgs(Protocol): + """Protocol for callables that extract keyword arguments from XML elements. + + Args: + element: The XML element to process + ns: Namespace identifier + name_spaces: Dictionary of namespace mappings + node_name: Name of the XML node + kwarg: Keyword argument name + classes: Tuple of allowed classes + strict: Whether to enforce strict parsing + + Returns: + Dictionary of extracted keyword arguments + """ def __call__( self, *, element: Element, ns: str, name_spaces: Dict[str, str], node_name: str, kwarg: str, classes: Tuple[Type[object], ...], strict: bool, ) -> Dict[str, Any]: ...
Line range hint
60-71: Enhance RegistryItem documentation.While the dataclass structure is solid, the documentation could be more comprehensive to help users understand the purpose and usage of each field.
Add detailed field documentation:
@dataclass(frozen=True) class RegistryItem: - """A registry item.""" + """A registry item representing a mapping between XML elements and Python objects. + + Attributes: + ns_ids: Tuple of namespace identifiers used for XML parsing + classes: Tuple of allowed Python classes for type validation + attr_name: Name of the attribute in the Python object + get_kwarg: Callable that extracts keyword arguments from XML elements + set_element: Callable that sets XML element attributes + node_name: Name of the XML node this item represents + default: Default value if the XML element is not present + """
Line range hint
74-103: Consider adding error handling for edge cases.The Registry implementation is solid, but could benefit from additional error handling to make it more robust.
Consider these improvements:
def register(self, cls: Type["_XMLObject"], item: RegistryItem) -> None: """Register a class.""" + if not isinstance(item, RegistryItem): + raise TypeError(f"Expected RegistryItem, got {type(item)}") existing = self._registry.get(cls, []) existing.append(item) self._registry[cls] = existing def get(self, cls: Type["_XMLObject"]) -> List[RegistryItem]: """Get a class by name.""" + if not isinstance(cls, type): + raise TypeError(f"Expected type, got {type(cls)}") parents = reversed(cls.__mro__[:-1]) items = [] for parent in parents: items.extend(self._registry.get(parent, [])) return items
Line range hint
106-108: Consider thread safety implications of global registry.While using a global registry is a common pattern, it's important to ensure thread-safe access if the registry might be modified concurrently.
Consider either:
- Making the registry thread-safe by using synchronization primitives
- Documenting that modifications should only occur during application initialization
Example of making it thread-safe:
import threading class ThreadSafeRegistry(Registry): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._lock = threading.RLock() def register(self, cls: Type["_XMLObject"], item: RegistryItem) -> None: with self._lock: super().register(cls, item) def get(self, cls: Type["_XMLObject"]) -> List[RegistryItem]: with self._lock: return super().get(cls)tests/validator_test.py (3)
Line range hint
44-53: Consider enhancing test_validate with additional test casesWhile the basic validation test is good, consider adding more test cases with different KML files to ensure comprehensive validation coverage. For example:
- Invalid KML files
- KML files with different features
- Edge cases with special characters
Would you like me to help generate additional test cases?
Line range hint
83-106: Add test cases for clean_string integrationGiven that the PR introduces a new
clean_stringfunction for handling string attributes in theLinkclass, consider adding test cases that explicitly verify this integration. For example:
- Test with whitespace-only strings
- Test with None values
- Test with special characters
Here's a suggested test case to add:
def test_validate_element_with_cleaned_strings(self) -> None: link = atom.Link( ns="{http://www.w3.org/2005/Atom}", href=" #here ", # whitespace to be cleaned rel="alternate", type="text/html", hreflang="en", title=" ", # should become None length=3456, ) assert validate(element=link.etree_element())
Line range hint
31-106: Consider adding property-based tests using HypothesisThe PR objectives mention introducing property-based testing using the Hypothesis library. Consider adding Hypothesis tests for the validator to ensure robust testing of various input combinations.
Here's a suggested example:
from hypothesis import given from hypothesis import strategies as st class TestLxml(Lxml): @given( href=st.text(min_size=1), rel=st.text(), type=st.text(), title=st.text() ) def test_validate_element_property_based(self, href, rel, type, title) -> None: link = atom.Link( ns="{http://www.w3.org/2005/Atom}", href=href, rel=rel, type=type, title=title ) # Validation should either pass or raise AssertionError try: validate(element=link.etree_element()) except AssertionError: passfastkml/kml_base.py (1)
Line range hint
41-77: Consider using None as default for identifiers instead of empty strings.The constructor implementation is well-documented and properly typed. However, using empty strings as defaults for
idandtarget_idmight make it difficult to distinguish between unset identifiers and explicitly set empty identifiers.Consider this alternative implementation:
def __init__( self, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, id: Optional[str] = None, target_id: Optional[str] = None, **kwargs: Any, ) -> None: super().__init__(ns=ns, name_spaces=name_spaces, **kwargs) - self.id = id or "" - self.target_id = target_id or "" + self.id = id + self.target_id = target_idtests/hypothesis/links_test.py (2)
Line range hint
52-56: Consider using a more specific strategy for view_formatThe current strategy using
ascii_letters + punctuationmight generate invalid view format strings. Consider using a more specific strategy that generates common MIME types or view formats (e.g., "application/vnd.google-earth.kml+xml", "image/jpg", etc.).Example improvement:
view_format=st.one_of( st.none(), st.sampled_from([ "application/vnd.google-earth.kml+xml", "image/jpg", "image/png", "application/json", "text/plain" ]) )
Line range hint
67-99: Enhance test coverage with value and error case validationWhile the current test implementation is solid, consider adding:
- Assertions to verify that the instantiated object's attributes match the input values
- Test cases for error conditions
Example enhancement:
) -> None: link = cls( id=id, target_id=target_id, href=href, refresh_mode=refresh_mode, refresh_interval=refresh_interval, view_refresh_mode=view_refresh_mode, view_refresh_time=view_refresh_time, view_bound_scale=view_bound_scale, view_format=view_format, http_query=http_query, ) + # Verify attributes match input values + assert link.id == id + assert link.target_id == target_id + assert link.href == href + assert link.refresh_mode == refresh_mode + assert link.refresh_interval == refresh_interval + assert link.view_refresh_mode == view_refresh_mode + assert link.view_refresh_time == view_refresh_time + assert link.view_bound_scale == view_bound_scale + assert link.view_format == view_format + assert link.http_query == http_query assert validate(element=link.etree_element()) assert_repr_roundtrip(link) assert_str_roundtrip(link) assert_str_roundtrip_terse(link) assert_str_roundtrip_verbose(link)Also consider adding a separate test method for error cases:
Would you like me to generate a companion test method that validates error handling for invalid inputs?
tests/helper_test.py (4)
Line range hint
36-54: Add positive test cases for integer handling.The test only verifies behavior with empty input. Consider adding test cases for:
- Valid integer values
- Boundary values (MIN_INT, MAX_INT)
- Invalid number formats
Here's a suggested implementation using parameterized tests:
@pytest.mark.parametrize("input_value, expected", [ ("42", {"kwarg": 42}), ("-1", {"kwarg": -1}), ("2147483647", {"kwarg": 2147483647}), # MAX_INT ("-2147483648", {"kwarg": -2147483648}), # MIN_INT ("invalid", {}), # Should handle error ("", {}), # Current test case ]) def test_subelement_int_kwarg(self, input_value: str, expected: dict) -> None: node = Node() node.text = input_value element = Mock() element.find.return_value = node res = subelement_int_kwarg( element=element, ns="ns", name_spaces={"name": "uri"}, node_name="node", kwarg="kwarg", classes=(int,), strict=False, ) assert res == expected
Line range hint
56-74: Reduce code duplication in test setup.Multiple test methods share similar setup code for creating mock objects and assertions. Consider extracting common setup into helper methods or fixtures.
Here's a suggested refactor:
class TestStdLibrary(StdLibrary): @pytest.fixture def mock_element_with_node(self, node_text: str = "") -> Mock: node = Node() node.text = node_text element = Mock() element.find.return_value = node return element @pytest.fixture def common_kwargs(self) -> dict: return { "ns": "ns", "name_spaces": {"name": "uri"}, "node_name": "node", "kwarg": "a", "strict": True, } def test_subelement_float_kwarg(self, mock_element_with_node, common_kwargs): res = subelement_float_kwarg( element=mock_element_with_node, classes=(float,), **common_kwargs, ) assert res == {}Also applies to: 76-93, 95-112, 114-131
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36-131: Add docstrings to test methods.Test methods lack documentation explaining the test scenarios and expected outcomes. This makes it harder to understand the purpose of each test.
Example improvement:
def test_subelement_int_kwarg(self) -> None: """Test integer keyword argument handling in subelements. Verifies that: 1. Empty input text returns empty dict 2. The correct namespace is used in element.find 3. No errors are raised in non-strict mode """
Now I can generate the final response based on the findings.
Missing test coverage for several helper functions
The test file only covers 6 helper functions, but there are many more that need tests:
node_text_kwargsubelement_text_kwargattribute_text_kwargattribute_int_kwargdatetime_subelement_kwargdatetime_subelement_list_kwargcoords_subelement_list_kwargxml_subelement_kwargxml_subelement_list_kwargsubelement_coordinates_kwargThese functions are actively used across multiple modules (views.py, kml_base.py, times.py, overlays.py, etc.) and should have test coverage to ensure reliability.
🔗 Analysis chain
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17-131: Verify test coverage of helper functions.Let's ensure all helper functions and their code paths are adequately tested.
Let me gather more information about the helper functions since the
src/directory wasn't found in the first attempt.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check test coverage for helper functions # Find all helper functions in the codebase echo "Searching for helper functions..." rg -l "def.*_kwarg" src/ # Check for untested helper functions echo "Checking for corresponding test functions..." for file in $(rg -l "def.*_kwarg" src/); do functions=$(rg "def\s+(\w+_kwarg)" "$file" -o -r '$1') for func in $functions; do if ! rg -q "test_$func" tests/; then echo "Missing tests for: $func" fi done done # Check test coverage patterns echo "Analyzing test patterns..." rg "test_.*_kwarg" tests/ -A 5Length of output: 2919
Script:
#!/bin/bash # Let's try to find the correct location of helper functions echo "Looking for helper functions in the entire repository..." fd -t f -e py | xargs rg "def.*_kwarg" echo -e "\nLooking for imported helper functions..." rg "from.*import.*_kwarg" -A 1Length of output: 7941
tests/hypothesis/container_test.py (3)
40-77: Extract common test strategy into a class-level fixtureThe features tuple strategy is duplicated in both test methods. Consider extracting it into a class-level fixture or strategy:
@classmethod def features_tuple_strategy(cls): return st.tuples( st.lists(st.builds(fastkml.containers.Document)), st.lists(st.builds(fastkml.containers.Folder)), st.lists(st.builds(fastkml.features.Placemark)), st.lists(st.builds(fastkml.overlays.GroundOverlay)), st.lists(st.builds(fastkml.overlays.PhotoOverlay)), st.lists( st.builds( fastkml.features.NetworkLink, link=st.builds( fastkml.links.Link, href=urls(), ), ), ), ) @given(features_tuple=features_tuple_strategy()) def test_fuzz_folder(self, features_tuple): # ... rest of the test
129-135: Document the reason for max_size=1 limitation on schemataThe test limits the number of Schema objects to 1 without explanation. If this is an intentional limitation (e.g., due to KML spec requirements or performance considerations), please add a comment explaining why.
142-144: Improve type hint precision for featuresThe type hint could be more specific about the actual types being chained:
- features: typing.Iterable[fastkml.features._Feature] = itertools.chain( + features: typing.Iterator[fastkml.features._Feature] = itertools.chain( *features_tuple, )tests/hypothesis/strategies.py (1)
168-179: Consider adding angle range constraints and documentation.The strategy implementation is well-structured and follows the established patterns. However, consider these improvements:
- Add range constraints for angle components:
- heading: 0° to 360°
- tilt and roll: -180° to 180°
- Add docstring explaining the strategy's purpose and parameter constraints.
Here's a suggested improvement:
track_items = partial( + # Strategy for generating TrackItem instances with valid angle, coordinate, + # and timestamp combinations for testing GX track features st.builds, fastkml.gx.TrackItem, angle=st.builds( fastkml.gx.Angle, - heading=st.floats(allow_nan=False, allow_infinity=False), - roll=st.floats(allow_nan=False, allow_infinity=False), - tilt=st.floats(allow_nan=False, allow_infinity=False), + heading=st.floats(allow_nan=False, allow_infinity=False, + min_value=0, max_value=360), + roll=st.floats(allow_nan=False, allow_infinity=False, + min_value=-180, max_value=180), + tilt=st.floats(allow_nan=False, allow_infinity=False, + min_value=-180, max_value=180), ), coord=geo_st.points(srs=geo_st.epsg4326), when=kml_datetimes(), )tests/registry_test.py (2)
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144-245: Consider enhancing test coverage with parameterization and edge cases.The test cases effectively verify the basic functionality, but could be improved by:
- Using pytest.mark.parametrize for different type combinations
- Adding edge cases (e.g., registering same class with same attribute name)
- Including negative test cases (e.g., invalid type registrations)
Here's an example of how to parameterize the tests:
import pytest @pytest.mark.parametrize("base_class,type_class,attr_name", [ (A, int, "int"), (B, bool, "bool"), (C, float, "float"), (D, Enum, "enum"), ]) def test_registry_type_registration(base_class, type_class, attr_name): registry = Registry() registry.register( base_class, RegistryItem( ns_ids=("kml",), classes=(type_class,), attr_name=attr_name, get_kwarg=get_kwarg, set_element=set_element, node_name=attr_name, ), ) assert len(registry.get(base_class)) == 1 assert registry.get(base_class)[0].classes == (type_class,)
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246-252: Add assertions to verify registry state.The
test_registry_reprfunction could be enhanced to verify the registry state after registrations.Example enhancement:
def test_registry_repr() -> None: registry = Registry() assert repr(registry) == "fastkml.registry.Registry({})" # Add registration and verify repr shows it registry.register( A, RegistryItem( ns_ids=("kml",), classes=(A,), attr_name="a", get_kwarg=get_kwarg, set_element=set_element, node_name="a", ), ) assert "A" in repr(registry)fastkml/kml.py (1)
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57-57: Update kml_children Union type to include NetworkLinkThe
kml_childrentype hint needs to be updated to include the newly addedNetworkLinkclass to maintain consistency with the registry changes.Apply this diff to fix the type hint:
-kml_children = Union[Folder, Document, Placemark, GroundOverlay, PhotoOverlay] +kml_children = Union[Folder, Document, Placemark, GroundOverlay, PhotoOverlay, NetworkLink]tests/views_test.py (2)
146-156: LGTM! Consider enhancing test documentation.The assertions provide comprehensive coverage of the Region object's attributes. The test structure follows a logical progression from basic object validation to detailed attribute verification.
Consider adding docstring comments to explain the significance of the tested values, particularly for the LatLonAltBox coordinates and Lod pixel values:
def test_region_with_all_optional_parameters(self) -> None: - """Region object can be initialized with all optional parameters.""" + """Region object can be initialized with all optional parameters. + + Tests a Region covering part of San Francisco Bay Area with: + - Coordinates: 37.80°N to 37.85°N, -122.40°E to -122.35°E + - Altitude range: 0-1000m, clamped to ground + - LOD (Level of Detail): 256-1024 pixels with 0-512 fade extent + """
179-187: Remove redundant assertion at the end of the test.The assertions provide thorough validation of the Region object parsed from XML. However, the final
assert regionat line 192 is redundant since:
- All specific attributes have already been verified
- The object's existence is implicitly confirmed by the previous assertions
assert region.lod.max_lod_pixels == 1024 assert region.lod.min_fade_extent == 0 assert region.lod.max_fade_extent == 512 - assert regionfastkml/enums.py (2)
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24-67: Replace assertions with proper runtime checksThe
RelaxedEnumimplementation has a few areas that could be improved:
- Replace assertions with proper runtime checks as assertions can be disabled with the
-Oflag:- assert isinstance(value, str) # noqa: S101 + if not isinstance(value, str): + raise TypeError(f"Expected string value, got {type(value).__name__}") - assert isinstance(member.value, str) # noqa: S101 + if not isinstance(member.value, str): + raise TypeError(f"Expected string value for enum member, got {type(member.value).__name__}")
- Consider enhancing the error message to explicitly mention case-sensitivity:
msg = ( - f"Unknown value '{value}' for {cls.__name__}. " + f"No case-insensitive match found for '{value}' in {cls.__name__}. " f"Known values are {', '.join(member.value for member in cls)}." )
- Consider adding a class-level validation to ensure all enum values are strings at definition time:
def __init_subclass__(cls, **kwargs): super().__init_subclass__(**kwargs) for member in cls: if not isinstance(member.value, str): raise TypeError( f"All {cls.__name__} values must be strings. " f"Got {type(member.value).__name__} for {member.name}" )
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144-167: Enhance robustness ofget_ns_idmethodThe
get_ns_idmethod inAltitudeModecould be more robust by using an explicit mapping instead of conditional logic:def get_ns_id(self) -> str: """Get the namespace for the altitude mode.""" - if self in ( - AltitudeMode.clamp_to_sea_floor, - AltitudeMode.relative_to_sea_floor, - ): - return "gx" - return "kml" + namespace_mapping = { + AltitudeMode.clamp_to_sea_floor: "gx", + AltitudeMode.relative_to_sea_floor: "gx", + } + return namespace_mapping.get(self, "kml")This approach:
- Makes it easier to add new mappings
- Reduces the risk of logic errors
- Improves maintainability
docs/create_kml_files.rst (2)
174-188: Enhance color generation for better visual distinctionThe current random color generation (
random.randint(0, 0xFFFFFF)) might result in:
- Similar colors that are hard to distinguish
- Colors with poor contrast against the background
Consider using a predefined color palette or a color generation algorithm that ensures good visual distinction:
- color = random.randint(0, 0xFFFFFF) + # Use a color from a predefined palette or generate using HSV color space + colors = [0xFF0000, 0x00FF00, 0x0000FF, 0xFFFF00, 0xFF00FF, 0x00FFFF] + color = colors[len(styles) % len(colors)]
169-216: Consider adding progress tracking for long operationsThe nested loops processing multiple years and countries could take significant time. Consider adding progress tracking to improve user experience in the documentation example.
+ >>> from tqdm import tqdm # Add to imports >>> styles = [] >>> folders = [] - >>> for feature in shp.__geo_interface__["features"]: + >>> for feature in tqdm(shp.__geo_interface__["features"], desc="Processing countries"):docs/working_with_kml.rst (1)
48-48: LGTM! Consider adding geographic context.The additional Point coordinate example enhances the documentation by showing geographic diversity. Consider adding a comment to indicate this is a location in Switzerland, which would help readers understand the coordinate ranges.
- POINT Z (8.23 46.707 0.0) + POINT Z (8.23 46.707 0.0) # Location in Switzerlandtests/features_test.py (3)
53-58: LGTM! Consider adding field-level assertions.The test correctly verifies roundtrip serialization of an empty Placemark. Consider adding assertions for individual fields to ensure they maintain their empty/None state after deserialization.
def test_placemark_empty_str_roundtrip(self) -> None: pm = features.Placemark() new_pm = features.Placemark.from_string(str(pm.to_string())) assert new_pm == pm + # Verify individual fields + assert new_pm.name is None + assert new_pm.description is None + assert new_pm.visibility is None + assert new_pm.geometry is None
60-73: LGTM! Consider adding negative test cases.The test thoroughly verifies roundtrip serialization of a Placemark with Camera view. Consider adding negative test cases with invalid camera parameters.
def test_placemark_camera_invalid_parameters(self) -> None: """Test that invalid camera parameters raise appropriate exceptions.""" with pytest.raises(ValueError): views.Camera( latitude=91.0, # Invalid latitude (>90) longitude=-122.0, altitude=0.0, roll=0.0, tilt=0.0, heading=0.0, )
75-94: LGTM! Consider testing different timezone scenarios.The test effectively verifies roundtrip serialization of a Placemark with TimeSpan. Consider adding test cases with different timezone configurations to ensure robust handling of timezone conversions.
def test_placemark_timespan_different_timezones(self) -> None: """Test TimeSpan with different timezone configurations.""" from datetime import timezone from zoneinfo import ZoneInfo # Test with different timezone configurations time_span = times.TimeSpan( begin=times.KmlDateTime( dt=datetime.datetime(2012, 3, 5, 0, 48, 32, tzinfo=ZoneInfo("America/New_York")), ), end=times.KmlDateTime( dt=datetime.datetime(2012, 4, 5, 0, 0, 0, tzinfo=timezone(datetime.timedelta(hours=5, minutes=30))), # IST ), ) pm = features.Placemark(times=time_span) new_pm = features.Placemark.from_string(str(pm.to_string())) assert new_pm == pmtests/hypothesis/overlay_test.py (2)
16-16: Update docstring to match file contentsThe docstring "Test Link and Icon" is incorrect as this file contains tests for various overlay classes (
ViewVolume,ImagePyramid,LatLonBox,PhotoOverlay,GroundOverlay).-"""Test Link and Icon.""" +"""Test KML overlay classes including ViewVolume, ImagePyramid, LatLonBox, PhotoOverlay, and GroundOverlay."""
192-200: Parameterize id and name values in overlay testsThe
idandnamevalues are hardcoded in bothPhotoOverlayandGroundOverlaytests. Consider parameterizing these values using Hypothesis strategies for more thorough testing.+ @given( + id=st.text(min_size=1), + name=st.text(min_size=1), rotation=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), # ... other parameters ... ) def test_fuzz_photo_overlay( self, + id: str, + name: str, rotation: typing.Optional[float], # ... other parameters ... ) -> None: photo_overlay = fastkml.overlays.PhotoOverlay( - id="photo_overlay1", - name="photo_overlay", + id=id, + name=name, rotation=rotation, # ... other parameters ... )Apply similar changes to the
test_fuzz_ground_overlaymethod.Also applies to: 233-239
fastkml/base.py (2)
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156-156: Consider enhancing error handling visibility into_string.While the fallback mechanism for pretty printing is good, consider adding logging to help diagnose serialization issues.
try: return cast( str, config.etree.tostring( element, encoding="UTF-8", pretty_print=prettyprint, ).decode( "UTF-8", ), ) except TypeError: + logger.debug("Failed to pretty print XML, falling back to basic serialization") return cast( str, config.etree.tostring( element, encoding="UTF-8", ).decode( "UTF-8", ), )Also applies to: 157-157, 158-158, 159-159, 160-160, 161-161, 162-162, 163-163, 164-164, 165-165, 166-166, 167-167, 168-168, 169-169, 170-170, 171-171, 172-172, 173-173, 174-174, 175-175, 176-176, 177-177, 178-178, 179-179, 180-180, 181-181, 182-182, 183-183, 184-184, 185-185, 186-186
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251-251: Consider extracting namespace merging logic.The namespace merging logic
{**config.NAME_SPACES, **name_spaces}is duplicated across methods. Consider extracting it into a private helper method.+ @staticmethod + def _merge_namespaces(name_spaces: Optional[Dict[str, str]] = None) -> Dict[str, str]: + """Merge provided namespaces with default ones.""" + name_spaces = name_spaces or {} + return {**config.NAME_SPACES, **name_spaces} + @classmethod def _get_kwargs( cls, *, ns: str, name_spaces: Optional[Dict[str, str]] = None, element: Element, strict: bool, ) -> Dict[str, Any]: - name_spaces = name_spaces or {} - name_spaces = {**config.NAME_SPACES, **name_spaces} + name_spaces = cls._merge_namespaces(name_spaces)Also applies to: 252-252, 253-253, 254-254, 255-255, 256-256, 257-257, 258-258, 259-259, 260-260, 261-261, 262-262, 263-263, 264-264, 265-265, 266-266, 267-267, 268-268, 269-269, 270-270, 271-271, 272-272, 273-273, 274-274, 275-275, 276-276, 277-277, 278-278, 279-279
fastkml/atom.py (1)
289-291: LGTM: Consistent string cleaning in _Person classThe
clean_stringfunction is properly applied to all string attributes, maintaining consistency with the new string handling approach.Consider updating the class docstring to explicitly mention that these attributes will be cleaned (stripped of whitespace) and can be None.
tests/times_test.py (3)
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18-28: LGTM! Consider grouping imports by typeThe imports are comprehensive and appropriate for the testing requirements. Consider grouping them into standard library, third-party, and local imports for better organization.
import datetime import pytest from dateutil.tz import tzoffset from dateutil.tz import tzutc + # Local imports import fastkml as kml from fastkml.enums import DateTimeResolution from fastkml.times import KmlDateTime from tests.base import Lxml from tests.base import StdLibrary
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31-165: Consider using parameterized tests for similar test casesThe datetime parsing tests are comprehensive but could be more maintainable using pytest's parameterize feature. This would reduce code duplication and make it easier to add new test cases.
Example refactoring for the parsing tests:
@pytest.mark.parametrize( "input_str,expected_date,expected_resolution", [ ("2000", datetime.date(2000, 1, 1), DateTimeResolution.year), ("2000-03", datetime.date(2000, 3, 1), DateTimeResolution.year_month), ("200004", datetime.date(2000, 4, 1), DateTimeResolution.year_month), ("2000-03-01", datetime.date(2000, 3, 1), DateTimeResolution.date), ], ) def test_parse_dates(input_str, expected_date, expected_resolution): dt = KmlDateTime.parse(input_str) assert dt assert dt.resolution == expected_resolution assert dt.dt == expected_date
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168-334: Consider adding more edge cases for XML parsingWhile the XML parsing tests are good, consider adding these scenarios:
- Malformed XML
- Missing timezone information
- Invalid datetime formats
- Empty TimeSpan with neither begin nor end
Example additional test cases:
def test_read_timestamp_malformed_xml(self): doc = """ <TimeStamp> <when>1997-07-16T07:30:15Z </TimeStamp> """ with pytest.raises(Exception): # Replace with specific exception kml.TimeStamp.from_string(doc, ns="") def test_read_timespan_empty(self): doc = """ <TimeSpan> </TimeSpan> """ ts = kml.TimeSpan.from_string(doc, ns="") assert not tstests/hypothesis/geometry_test.py (3)
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44-54: Security: Avoid using eval() for object creationThe use of
eval()with a dictionary of locals is potentially risky, even with a controlled set of values. Consider using a factory pattern or direct class instantiation instead.Replace the eval-based approach with a safer alternative:
class GeometryFactory: @staticmethod def create_from_repr(repr_str: str) -> kml_geometry: # Parse the repr string to extract class name and parameters # Use pattern matching or parsing to safely create objects pass
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90-160: Enhance test helper functions with documentation and explicit assertionsThe helper functions are well-structured but could be more maintainable with:
- Docstrings explaining test scenarios
- More explicit assertion messages
Example improvement:
def _test_geometry_str_roundtrip_verbose(geometry: kml_geometry) -> None: + """Test verbose serialization roundtrip for geometry objects. + + Verifies that: + 1. Serialization/deserialization preserves all attributes + 2. Default values are explicitly set in verbose mode + 3. XML validation passes + """ new_g = type(geometry).from_string( geometry.to_string(verbosity=Verbosity.verbose), ) - assert validate(element=new_g.etree_element()) + assert validate(element=new_g.etree_element()), "Invalid XML structure" assert geometry.to_string(verbosity=Verbosity.terse) == new_g.to_string( verbosity=Verbosity.terse, - ) + ), "Terse representation mismatch"
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161-400: Consider adding error case testsWhile the happy path testing is comprehensive, consider adding tests for:
- Invalid geometry coordinates
- Malformed XML input
- Edge cases in coordinate systems
Example addition:
@common_geometry() def test_invalid_geometry_handling(self): """Test handling of invalid geometry inputs.""" with pytest.raises(ValueError, match="Invalid coordinates"): fastkml.geometry.Point( geometry=Point([float('inf'), float('inf')]) )tests/geometries/multigeometry_test.py (1)
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34-88: Consider adding property-based tests using Hypothesis.While the current test coverage is good with specific examples, adding property-based tests could help discover edge cases and improve robustness. This aligns with the PR's objective of introducing Hypothesis testing.
Example properties to test:
- Serialization roundtrip: geometry -> XML -> geometry should preserve data
- Coordinate precision handling
- Boundary cases for polygon holes
Also applies to: 92-144, 149-205, 210-384
tests/gx_test.py (4)
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18-29: Consider organizing imports into logical groupsConsider organizing imports into standard library, third-party, and local application imports, separated by blank lines:
import datetime import pygeoif.geometry as geo import pytest from dateutil.tz import tzoffset from dateutil.tz import tzutc from fastkml.gx import Angle from fastkml.gx import MultiTrack from fastkml.gx import Track from fastkml.gx import TrackItem from fastkml.times import KmlDateTime from tests.base import Lxml from tests.base import StdLibrary
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32-394: Add property-based tests using HypothesisThe PR objectives mention introducing property-based testing using the Hypothesis library, but this file doesn't include any. Consider adding property-based tests for:
- Track initialization with various combinations of whens/coords/angles
- MultiTrack with varying number of tracks
- Validation of XML string representation with different input patterns
Example structure:
from hypothesis import given from hypothesis import strategies as st class TestTrack(StdLibrary): @given( st.lists(st.datetimes(timezones=st.just(tzutc())), min_size=1), st.lists(st.tuples(st.floats(), st.floats()), min_size=1), ) def test_track_property_based(self, whens, coords): # Test Track initialization with generated data track = Track( whens=[KmlDateTime(dt) for dt in whens], coords=coords, ) assert len(track.track_items) == min(len(whens), len(coords))
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316-345: Enhance test coverage with parameterized testsThe invalid input tests could be more comprehensive. Consider using pytest's parametrize to test multiple invalid cases:
@pytest.mark.parametrize("invalid_when", [ "2010-02-32T02:02:09Z", # Invalid day "2010-13-01T02:02:09Z", # Invalid month "2010-01-01T25:00:00Z", # Invalid hour "invalid_datetime", # Invalid format ]) def test_track_from_str_invalid_when(self, invalid_when): doc = f''' <gx:Track xmlns:gx="http://www.google.com/kml/ext/2.2" xmlns:kml="http://www.opengis.net/kml/2.2"> <kml:when>{invalid_when}</kml:when> <gx:angles>45.54676 66.2342 77.0</gx:angles> <gx:coord>-122.207881 37.371915 156.000000</gx:coord> </gx:Track> ''' track = Track.from_string(doc, strict=False) assert track.track_items == []Similarly, parameterize the precision test to verify different precision levels:
@pytest.mark.parametrize("precision,expected", [ (2, "45.55"), (3, "45.547"), (4, "45.5468"), ]) def test_track_precision(self, precision, expected): # Test with different precision values
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395-407: Consider using pytest parametrize for parser backendsInstead of duplicating test classes for different parsers, consider using pytest's parametrize to run the same tests with different parser backends:
import pytest @pytest.mark.parametrize("parser_backend", [ pytest.param(StdLibrary, id="stdlib"), pytest.param(Lxml, id="lxml"), ]) class TestTrack: @pytest.fixture def parser(self, parser_backend): return parser_backend() def test_track_from_track_items(self, parser): # Use parser fixture instead of inheriting from StdLibrary/LxmlThis approach would:
- Reduce code duplication
- Make it easier to add new parser backends
- Improve test maintenance
tests/kml_test.py (4)
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12-24: Consider refactoring the test for better maintainabilityThe test_kml_with_document method could be improved in several ways:
- Split into smaller, focused test cases for each feature type
- Move the test data to a fixture
- Add more specific assertions for the content of each feature
Example refactor:
@pytest.fixture def complex_kml_document(): return '''<kml xmlns="http://www.opengis.net/kml/2.2">...</kml>''' def test_document_structure(complex_kml_document): k = kml.KML.from_string(complex_kml_document) assert len(k.features) == 1 assert isinstance(k.features[0], Document) def test_folder_structure(complex_kml_document): k = kml.KML.from_string(complex_kml_document) folder = k.features[0].features[0] assert isinstance(folder, containers.Folder) assert folder.name == "test" def test_placemark_structure(complex_kml_document): k = kml.KML.from_string(complex_kml_document) placemark = k.features[0].features[0].features[0] assert isinstance(placemark, features.Placemark) assert isinstance(placemark.geometry, geo.Polygon)
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32-38: Reduce code duplication in parse testsThe three parse test methods contain identical assertions and test data. Consider using parameterized tests to reduce duplication.
Example refactor using pytest.mark.parametrize:
import pytest @pytest.mark.parametrize("input_type,get_input", [ ("path", lambda p: p), ("string", str), ("file", lambda p: p.open()), ]) def test_parse_kml_from_different_sources(input_type, get_input): empty_placemark = KMLFILEDIR / "emptyPlacemarkWithoutId.xml" doc = kml.KML.parse(get_input(empty_placemark)) assert doc == kml.KML( ns="{http://www.opengis.net/kml/2.2}", features=[ Document( ns="{http://www.opengis.net/kml/2.2}", id="doc-001", target_id="", name="Vestibulum eleifend lobortis lorem.", features=[ Placemark( ns="{http://www.opengis.net/kml/2.2}", ), ], schemata=[], ), ], )Also applies to: 39-45, 46-52
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53-59: Move large test data to external resourcesThe test_polygon method contains a large KML string that makes the test hard to read and maintain. Consider moving it to a separate fixture file.
- Create a fixtures directory:
mkdir -p tests/fixtures/kml
Move the test data to
tests/fixtures/kml/south_africa_polygon.kmlUpdate the test:
@pytest.fixture def south_africa_polygon(): return (BASEDIR / "fixtures" / "kml" / "south_africa_polygon.kml").read_text() def test_polygon(south_africa_polygon): k = kml.KML.from_string(south_africa_polygon) assert len(k.features) == 1 polygon = k.features[0].geometry assert isinstance(polygon, Polygon) assert len(list(polygon.interiors)) == 1 # Lesotho # Add more specific assertions about the polygon's properties exterior = list(polygon.exterior.coords) assert len(exterior) > 0 assert all(len(coord) == 3 for coord in exterior) # Each coord has x,y,z
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1-24: Well-structured and comprehensive test suiteThe test suite provides thorough coverage of KML functionality with well-organized test classes and methods. The tests effectively validate various KML features, parsing methods, and edge cases.
Consider these architectural improvements for the test suite:
- Organize tests by feature (parsing, validation, serialization)
- Use pytest fixtures for common test data
- Implement property-based testing for complex geometries
- Add integration tests for real-world KML files
tests/hypothesis/multi_geometry_test.py (1)
Line range hint
451-550: Add XML validation to GeometryCollection testsConsider adding XML validation using
validate(element=new_mg.etree_element())in the str roundtrip tests to maintain consistency with other geometry type tests.def test_geometrycollection_str_roundtrip( # ... parameters ... ) -> None: multi_geometry = fastkml.geometry.MultiGeometry( # ... initialization ... ) new_mg = fastkml.geometry.MultiGeometry.from_string( multi_geometry.to_string(), ) if geometry: assert isinstance( new_mg.geometry, (GeometryCollection, MultiPolygon, MultiLineString, MultiPoint), ) else: assert not new_mg + assert validate(element=new_mg.etree_element())tests/geometries/geometry_test.py (4)
18-18: Enhance module docstring with more details.The current docstring is quite brief. Consider expanding it to include:
- The purpose of each test class
- The testing approach (standard library vs lxml)
- Any prerequisites or setup requirements
-"""Test the geometry classes.""" +"""Test suite for KML geometry classes. + +This module contains comprehensive tests for KML geometry handling, including: +- Basic geometry types (Point, LineString, Polygon, etc.) +- Complex geometry collections +- XML parsing using both standard library and lxml +- KML-specific attributes (altitude, extrude, etc.) +"""
Line range hint
32-207: Consider adding edge cases to geometry tests.The test coverage is good, but could be enhanced with additional edge cases:
- Invalid coordinate formats
- Empty geometries
- Malformed XML
- Extreme coordinate values
- 3D coordinates (with altitude)
Would you like me to help create these additional test cases?
Line range hint
209-451: Add property-based tests using Hypothesis.Given that this PR introduces Hypothesis testing, consider adding property-based tests for:
- Geometry creation with random coordinates
- Roundtrip serialization/deserialization
- Geometry transformations
Example implementation:
from hypothesis import given from hypothesis.strategies import lists, floats class TestCreateKmlGeometry(StdLibrary): @given(lists(lists(floats(min_value=-180, max_value=180), min_size=2, max_size=2), min_size=3)) def test_property_based_polygon(self, coordinates): """Test polygon creation with random coordinates.""" # Ensure the polygon is closed coordinates.append(coordinates[0]) polygon = geo.Polygon(coordinates) kml_polygon = create_kml_geometry(polygon) assert isinstance(kml_polygon, Polygon) assert kml_polygon.geometry == polygon
Line range hint
452-460: Document the dual-parser testing strategy.The inheritance-based approach to test both XML parsers is clever, but could benefit from explicit documentation explaining:
- Why both parsers are tested
- What differences to expect
- How to add new test cases properly
class TestGetGeometryLxml(Lxml, TestGetGeometry): - """Test with lxml.""" + """Test geometry parsing with lxml. + + This class inherits all test cases from TestGetGeometry but uses lxml + for XML parsing instead of the standard library. This ensures that + geometry handling works correctly regardless of the XML parser used. + """tests/styles_test.py (1)
Line range hint
131-135: LGTM! Consider adding boundary value tests.The assertions thoroughly verify the hot_spot object and its attributes (x, y, xunits, yunits). This ensures proper parsing and storage of hotSpot element data.
Consider adding test cases for boundary values and edge cases:
def test_icon_style_with_hot_spot_boundary_values(self) -> None: # Test minimum values (0,0) icons_min = styles.IconStyle.from_string( '<kml:IconStyle xmlns:kml="http://www.opengis.net/kml/2.2">' '<kml:hotSpot x="0" y="0" xunits="fraction" yunits="fraction"/>' '</kml:IconStyle>' ) assert icons_min.hot_spot.x == 0 assert icons_min.hot_spot.y == 0 # Test maximum values (1,1) for fraction units icons_max = styles.IconStyle.from_string( '<kml:IconStyle xmlns:kml="http://www.opengis.net/kml/2.2">' '<kml:hotSpot x="1" y="1" xunits="fraction" yunits="fraction"/>' '</kml:IconStyle>' ) assert icons_max.hot_spot.x == 1 assert icons_max.hot_spot.y == 1fastkml/helpers.py (1)
44-46: Enhance docstring and improve readabilityWhile the implementation is correct, consider improving the documentation and readability:
def clean_string(value: Optional[str]) -> Optional[str]: - """Clean and validate a string value, returning None if empty.""" - return value.strip() or None if value else None + """Clean and validate a string value. + + Args: + value: The string to clean and validate. + + Returns: + The cleaned string if non-empty, None otherwise. + + Examples: + >>> clean_string(" hello ") + 'hello' + >>> clean_string(" ") + None + >>> clean_string(None) + None + """ + if value is None: + return None + cleaned = value.strip() + return cleaned if cleaned else Nonefastkml/geometry.py (1)
Line range hint
428-432: Make geometry existence check more explicit and improve code conciseness.The current condition could be problematic with falsy geometry objects. Also, the initialization can be more concise.
Consider this improvement:
- if kml_coordinates is None and geometry: - kml_coordinates = ( - Coordinates(coords=geometry.coords) # type: ignore[arg-type] - if geometry - else None - ) + if kml_coordinates is None and geometry is not None: + kml_coordinates = Coordinates(coords=geometry.coords) # type: ignore[arg-type]fastkml/times.py (7)
Line range hint
70-70: Ensure compatibility with Python versions below 3.8The use of the walrus operator (
:=) in theparsemethod is only supported in Python 3.8 and above. If the project aims to maintain compatibility with earlier Python versions, consider refactoring the code to avoid using this syntax.Apply this diff to replace the walrus operator:
-def parse(cls, datestr: str) -> Optional["KmlDateTime"]: - """Parse a KML DateTime string into a KmlDateTime object.""" - resolution = None - dt = None - if year_month_day_match := year_month_day.match(datestr): +def parse(cls, datestr: str) -> Optional["KmlDateTime"]: + """Parse a KML DateTime string into a KmlDateTime object.""" + resolution = None + dt = None + year_month_day_match = year_month_day.match(datestr) + if year_month_day_match: year = int(year_month_day_match.group("year")) month = int(year_month_day_match.group("month") or 1) day = int(year_month_day_match.group("day") or 1)
Line range hint
80-85: Add exception handling for invalid date stringsIn the
parsemethod, ifarrow.get(datestr)encounters an invalid date string, it may raise an exception. Consider wrapping this in atry-exceptblock to handle invalid inputs gracefully.Apply this diff to add exception handling:
elif len(datestr) > 10: - dt = arrow.get(datestr).datetime - resolution = DateTimeResolution.datetime + try: + dt = arrow.get(datestr).datetime + resolution = DateTimeResolution.datetime + except arrow.parser.ParserError: + return None
Line range hint
107-115: Correct the class name in the docstring ofTimeStamp.__init__The docstring incorrectly mentions "Initialize a new instance of the Times class." It should refer to the
TimeStampclass.Apply this diff to correct the docstring:
""" -Initialize a new instance of the Times class. +Initialize a new instance of the TimeStamp class. Args: ---- ns : str, optional
Line range hint
152-160: Correct the class name in the docstring ofTimeSpan.__init__Similarly, the docstring for
TimeSpan.__init__mentions "Initialize a new instance of the Times class." It should refer to theTimeSpanclass.Apply this diff to correct the docstring:
""" -Initialize a new instance of the Times class. +Initialize a new instance of the TimeSpan class. Args: ---- ns (Optional[str]): The namespace for the element.
Line range hint
70-90: Enhance date parsing to handle more ISO 8601 formatsThe current implementation may not handle all valid ISO 8601 date formats, such as dates with fractional seconds or time zone offsets. Consider using
dateutil.parseror enhancing the regular expression to support additional formats.For example, you could adjust the parsing logic as follows:
from dateutil import parser @classmethod def parse(cls, datestr: str) -> Optional["KmlDateTime"]: """Parse a KML DateTime string into a KmlDateTime object.""" resolution = None dt = None - if year_month_day_match := year_month_day.match(datestr): - # Existing parsing logic... - elif len(datestr) > 10: - dt = arrow.get(datestr).datetime + try: + dt = parser.isoparse(datestr) + except ValueError: + return None resolution = DateTimeResolution.datetime return cls(dt, resolution) if dt else NoneRemember to add
python-dateutilto the project dependencies if you choose to use it.
25-25: Remove unnecessary blank line at the start of the codeThere's an extra blank line at the beginning of the code after the module docstring. While not critical, removing it can improve code readability.
Apply this diff to remove the blank line:
""" Date and time handling in KML. ... """ - import re from datetime import date
Line range hint
37-40: Avoid redefining imported namesThe code imports
dateanddatetimefrom thedatetimemodule. In theKmlDateTimeclass,dtis being used, which can be confused withdatetime. Ensure variable names are clear to avoid confusion.Consider renaming
dttoinput_dateor similar for clarity.fastkml/gx.py (7)
Line range hint
192-194: Correct the error message inTrack.__init__The error message in the
__init__method refers togeometry, which is not a parameter of the constructor. To avoid confusion, please update the error message to reflect the actual parameters causing the conflict.Apply this diff to fix the error message:
- msg = "Cannot specify both geometry and track_items" + msg = "Cannot specify both track_items and whens/coords"
Line range hint
224-234: Align docstring return type with actual return type inanglespropertyIn the
anglesproperty, the docstring indicates that the method returnsTuple[Angle], but it actually returnsTuple[PointType, ...], which is a tuple of coordinate tuples. Please update the docstring to accurately reflect the return type.Apply this diff to correct the docstring:
@property def angles(self) -> Tuple[PointType, ...]: """ Get the angles of the track items. - Returns - ------- - Tuple[Angle] - The angles of the track items. + Returns + ------- + Tuple[PointType, ...] + A tuple of angle coordinates (heading, tilt, roll) from the track items. """
Line range hint
213-222: Ensure correctness incoordsproperty extractionIn the
coordsproperty, the access ofitem.coord.coords[0]may not yield the expected coordinate tuple. Sinceitem.coordis ageo.Point, consider accessingitem.coord.coordsdirectly to retrieve the coordinate.Apply this diff to fix the coordinate extraction:
@property def coords(self) -> Tuple[PointType, ...]: """ Get the coordinates of the track items. Returns ------- Tuple[PointType, ...] The coordinates of the track items. """ return tuple( - item.coord.coords[0] # type: ignore[misc] + item.coord.coords # type: ignore[misc] for item in self.track_items if item.coord )
Line range hint
196-203: Handle possible issues withzip_longestandfillvalueinTrack.__init__Using
fillvalue=()withzip_longestcan lead to unexpected behavior if the lengths ofwhens,coords, andanglesdiffer. Attempting to unpack an empty tuple may raise aTypeError. Ensure that all iterables have the same length or handle thefillvalueappropriately to avoid errors.Consider adding a validation step or adjusting the
fillvalue:track_items = [ TrackItem( when=cast(KmlDateTime, when), coord=geo.Point(*coord), - angle=Angle(*angle), + angle=Angle(*angle) if angle else None, ) for when, coord, angle in zip_longest( whens, coords, angles, - fillvalue=(), + fillvalue=None, ) ]
Line range hint
260-266: Correct theRaisessection inMultiTrack.__init__docstringThe
Raisessection mentions aValueErrorwhen bothgeometryandtracksare specified, butgeometryis not a parameter of the constructor. Update the docstring to accurately reflect the constructor's parameters and their validation.Apply this diff to correct the docstring:
**kwargs (Any): Additional keyword arguments. - Raises: - ------ - ValueError: If both geometry and tracks are specified. + # No exceptions are currently raised in the constructor. """
Line range hint
274-281: Implement__bool__method inMultiTrackfor consistent truthiness checksConsider adding a
__bool__method toMultiTracksimilar to that inTrackto allow for consistent truthiness evaluations based on the presence of tracks.Example implementation:
def __bool__(self) -> bool: """ Check if the MultiTrack has any tracks. Returns ------- bool True if the MultiTrack has tracks, False otherwise. """ return bool(self.tracks)
Line range hint
319-325: Update__all__to include new helper functionsEnsure that the
__all__list includes all publicly available entities in the module. Currently,track_items_to_geometryandtracks_to_geometryare included; verify if any other functions or classes should be exported.If no changes are needed, please disregard this comment.
fastkml/views.py (9)
Line range hint
81-96: Maintain consistent docstring style in__init__methodsThe
__init__method of_AbstractViewuses the header Parameters, while other classes likeCameraandLookAtuse Args in their docstrings. For consistency and readability, consider using the same section header across all docstrings.
Line range hint
98-100: Correct the typo in docstrings of__repr__methodsIn the
__repr__methods of the classes_AbstractView,Camera,LookAt,LatLonAltBox,Lod, andRegion, the docstring says "Create a string (c)representation for...". The "(c)" appears to be a typo. Please revise it to "Create a string representation for..." to enhance clarity.Also applies to: 196-198, 285-287, 373-375, 460-462, 548-550
Line range hint
146-160: Update docstring to reflect the correct class nameIn the
__init__method of theCameraclass, the docstring begins with "Initialize a new View object." Since this is theCameraclass, it would be clearer to state "Initialize a new Camera object."
Line range hint
235-281: Avoid using 'range' as a parameter and attribute name to prevent shadowing the built-in functionThe
LookAtclass usesrangeas both a parameter in the__init__method and as an instance attribute. Sincerangeis a built-in function in Python, using it as a variable name can overshadow the built-in and may lead to unexpected behavior or confusion. Consider renaming it torange_ordistanceto avoid this issue.Apply this diff to rename the
rangeparameter and attribute:class LookAt(_AbstractView): ... def __init__( ... - range: Optional[float] = None, + range_: Optional[float] = None, ... ) -> None: ... - self.range = range + self.range_ = range_ def __repr__(self) -> str: ... - f"range={self.range!r}, " + f"range_={self.range_!r}, " ...
Line range hint
120-136: Ensure consistency between attribute default values and registry defaultsIn the
_AbstractViewclass, attributes likelongitude,latitude,altitude,heading, andtiltare defined asOptional[float]with default values ofNonein the__init__method. However, in the registry entries for these attributes, the default values are set to0.0. This discrepancy might lead to confusion or unintended behavior when the attribute isNonebut the registry provides a default of0.0. Consider aligning the default values in the registry with those in the class definition to maintain consistency.Apply this diff to update the registry defaults:
registry.register( _AbstractView, RegistryItem( ns_ids=("kml",), attr_name="longitude", node_name="longitude", classes=(float,), get_kwarg=subelement_float_kwarg, set_element=float_subelement, - default=0.0, + default=None, ), )Repeat this change for the attributes
latitude,altitude,heading, andtilt.
Line range hint
373-375: Implement proper truth value testing in__bool__methodsIn the
__bool__methods of theLodandRegionclasses, the method checks if a single attribute is notNone. To ensure accurate truth value testing, consider expanding the checks to include all relevant attributes that define the object's validity.For
Lodclass:Modify the
__bool__method to check all attributes:def __bool__(self) -> bool: """ Check if the object is considered True or False. Returns ------- bool: True if all attributes are not None, False otherwise. """ - return self.min_lod_pixels is not None + return all( + ( + self.min_lod_pixels is not None, + self.max_lod_pixels is not None, + self.min_fade_extent is not None, + self.max_fade_extent is not None, + ), + )For
Regionclass:Modify the
__bool__method to check iflat_lon_alt_boxandlodare notNone:def __bool__(self) -> bool: """ Check if the object is considered True or False. Returns ------- bool: True if both `lat_lon_alt_box` and `lod` are not None, False otherwise. """ - return bool(self.lat_lon_alt_box) + return self.lat_lon_alt_box is not None and self.lod is not NoneAlso applies to: 460-462
Line range hint
548-550: Clarify the__bool__method inRegionclassThe
__bool__method currently checks the truthiness oflat_lon_alt_box. To more accurately represent the validity of aRegionobject, consider also checking thelodattribute.Apply this diff to update the
__bool__method:def __bool__(self) -> bool: """ Check if the object is considered True or False. Returns ------- - bool: True if the `lat_lon_alt_box` attribute is not empty, False otherwise. + bool: True if both `lat_lon_alt_box` and `lod` attributes are not empty, False otherwise. """ - return bool(self.lat_lon_alt_box) + return bool(self.lat_lon_alt_box) and bool(self.lod)
Line range hint
17-24: Add module-level docstring for better documentationCurrently, the module
fastkml/views.pylacks a descriptive module-level docstring that explains its purpose and usage. Adding a detailed docstring at the beginning of the file will improve code readability and maintainability.Consider adding a docstring like:
""" This module defines classes related to KML Views, such as Camera, LookAt, LatLonAltBox, Lod, and Region. These classes facilitate the representation of camera views and regions in KML files. """
Line range hint
203-205: Consider removing unused**kwargsif not necessaryIn the
Cameraclass's__init__method,**kwargsis accepted but not used within the method. If there is no intention to pass additional keyword arguments to the superclass or use them within the method, consider removing**kwargsto simplify the method signature.Apply this diff to remove
**kwargs:def __init__( self, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, id: Optional[str] = None, target_id: Optional[str] = None, longitude: Optional[float] = None, latitude: Optional[float] = None, altitude: Optional[float] = None, heading: Optional[float] = None, tilt: Optional[float] = None, roll: Optional[float] = None, altitude_mode: Optional[AltitudeMode] = None, - **kwargs: Any, ) -> None: """ Initialize a new Camera object. ... """ super().__init__( ns=ns, name_spaces=name_spaces, id=id, target_id=target_id, longitude=longitude, latitude=latitude, altitude=altitude, heading=heading, tilt=tilt, altitude_mode=altitude_mode, - **kwargs, ) self.roll = rollRepeat this change if applicable in other classes.
📜 Review details
Configuration used: .coderabbit.yaml
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📒 Files selected for processing (54)
docs/create_kml_files.rst(1 hunks)docs/working_with_kml.rst(1 hunks)fastkml/__init__.py(1 hunks)fastkml/atom.py(4 hunks)fastkml/base.py(1 hunks)fastkml/config.py(2 hunks)fastkml/containers.py(6 hunks)fastkml/data.py(6 hunks)fastkml/enums.py(1 hunks)fastkml/features.py(5 hunks)fastkml/geometry.py(1 hunks)fastkml/gx.py(1 hunks)fastkml/helpers.py(1 hunks)fastkml/kml.py(3 hunks)fastkml/kml_base.py(1 hunks)fastkml/links.py(3 hunks)fastkml/mixins.py(1 hunks)fastkml/overlays.py(5 hunks)fastkml/registry.py(1 hunks)fastkml/styles.py(5 hunks)fastkml/times.py(1 hunks)fastkml/types.py(1 hunks)fastkml/views.py(1 hunks)tests/atom_test.py(1 hunks)tests/base.py(1 hunks)tests/base_test.py(0 hunks)tests/containers_test.py(0 hunks)tests/features_test.py(2 hunks)tests/geometries/coordinates_test.py(0 hunks)tests/geometries/functions_test.py(1 hunks)tests/geometries/geometry_test.py(1 hunks)tests/geometries/multigeometry_test.py(1 hunks)tests/gx_test.py(1 hunks)tests/helper_test.py(1 hunks)tests/hypothesis/atom_test.py(0 hunks)tests/hypothesis/common.py(2 hunks)tests/hypothesis/container_test.py(1 hunks)tests/hypothesis/feature_test.py(1 hunks)tests/hypothesis/geometry_test.py(1 hunks)tests/hypothesis/gx_test.py(3 hunks)tests/hypothesis/kml_test.py(1 hunks)tests/hypothesis/links_test.py(1 hunks)tests/hypothesis/multi_geometry_test.py(1 hunks)tests/hypothesis/overlay_test.py(1 hunks)tests/hypothesis/strategies.py(2 hunks)tests/hypothesis/times_test.py(1 hunks)tests/kml_test.py(1 hunks)tests/links_test.py(1 hunks)tests/registry_test.py(1 hunks)tests/styles_test.py(1 hunks)tests/times_test.py(1 hunks)tests/utils_test.py(1 hunks)tests/validator_test.py(1 hunks)tests/views_test.py(2 hunks)
💤 Files with no reviewable changes (4)
- tests/base_test.py
- tests/containers_test.py
- tests/geometries/coordinates_test.py
- tests/hypothesis/atom_test.py
✅ Files skipped from review due to trivial changes (4)
- fastkml/init.py
- fastkml/config.py
- fastkml/types.py
- tests/utils_test.py
🔇 Additional comments (80)
fastkml/mixins.py (2)
Line range hint 1-24: LGTM! Well-structured file setup with proper documentation.
The file has appropriate copyright information, clear documentation, and well-organized imports that match the implementation requirements.
Line range hint 26-28: LGTM! Well-designed mixin class.
The TimeMixin class is well-implemented with proper type hints and clear separation of concerns. The class-level attribute is correctly typed and initialized.
Also applies to: 30-30
tests/base.py (3)
18-18: LGTM!
The spacing between the module docstring and imports follows PEP 8 guidelines.
Line range hint 40-53: Verify schema parser initialization
The get_schema_parser() call result is not stored or verified. Consider capturing and validating the schema parser initialization.
Let's check the schema parser usage pattern:
#!/bin/bash
# Description: Analyze schema parser usage across tests
# Expected: Find how the schema parser is typically used
# Search for schema parser usage patterns
rg -A 5 "get_schema_parser\(\)" --type python
# Look for any validation or assertion patterns
rg -A 5 "schema.*parser" --type pythonLine range hint 33-37: Consider adding configuration verification
While the setup looks correct, it would be beneficial to verify that the configuration was applied successfully.
Let's check if there are any existing verification mechanisms:
tests/hypothesis/times_test.py (1)
Line range hint 1-71: Well-structured property-based tests implementation.
The implementation demonstrates good testing practices with:
- Comprehensive property-based test coverage
- Proper type hints
- Multiple string representation validations
- Good use of helper functions for assertions
The suggested improvements are minor and focus on documentation and validation enhancements.
tests/geometries/functions_test.py (1)
Line range hint 1-16: LGTM! Well-structured test file.
The file follows Python best practices with proper organization of imports, comprehensive type hints, and clear documentation.
Also applies to: 17-17
tests/validator_test.py (2)
Line range hint 17-28: LGTM! Good use of type hints and path handling
The use of Final type hint for TEST_DIR and Path for cross-platform compatibility demonstrates good practices.
Line range hint 31-42: LGTM! Good test isolation practice
The setup_method properly clears the cache before each test, ensuring test isolation. The use of super().setup_method() maintains the parent class's setup functionality.
fastkml/kml_base.py (2)
Line range hint 18-39: LGTM! Well-structured class definition with clear documentation.
The imports are well-organized, and the class documentation clearly explains the purpose of the id and target_id attributes, which are essential for unique identification and referencing in Google Earth.
Line range hint 102-127: LGTM! Proper registry configuration for XML serialization.
The registry entries correctly configure the XML serialization for both id and target_id attributes, using appropriate handlers and following the KML specification for node names.
tests/hypothesis/links_test.py (1)
Line range hint 1-99: Well-structured property-based testing implementation
The implementation demonstrates excellent use of property-based testing with Hypothesis, proper type hints, and comprehensive validation. The code is well-organized and follows best practices.
tests/links_test.py (1)
18-18: LGTM!
The added empty line improves code organization by separating imports from class definitions.
tests/hypothesis/gx_test.py (3)
33-33: LGTM! Import from strategies module is appropriate.
Importing from a shared strategies module is a good practice for property-based testing with Hypothesis, as it promotes reuse of test data generators.
44-44: LGTM! Correct usage of track_items as a strategy function.
Using track_items() as a function call is the proper way to ensure fresh strategy instances for each test case.
83-83: LGTM! Consistent usage of track_items strategy.
The nested strategy structure correctly composes Track objects for MultiTrack testing using the track_items generator.
tests/hypothesis/common.py (2)
39-42: LGTM! New enum imports are properly organized.
The addition of GridOrigin and Shape imports from fastkml.enums aligns with the existing import structure and supports the enhanced KML feature testing objectives.
74-75: LGTM! Verify enum usage in property-based tests.
The additions to eval_locals are properly organized and enable repr roundtrip testing for KML features using these enums.
Let's verify that these enums are actually used in the property-based tests:
✅ Verification successful
Enums are actively used in property-based tests
Both GridOrigin and Shape enums are properly utilized in tests/hypothesis/overlay_test.py for property-based testing:
- Used in strategy definitions with
st.sampled_from() - Defined as optional type hints in test parameters
- Imported and added to
eval_localsfor repr roundtrip testing
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check usage of GridOrigin and Shape enums in test files
# Expected: Find references in hypothesis test files showing these enums are utilized
echo "Checking GridOrigin usage in tests:"
rg "GridOrigin" "tests/hypothesis/"
echo -e "\nChecking Shape usage in tests:"
rg "Shape" "tests/hypothesis/"
Length of output: 959
tests/hypothesis/container_test.py (3)
78-91: LGTM! Comprehensive property-based test for Folder
The test implementation is thorough:
- Generates diverse feature combinations
- Tests all string representation formats
- Verifies roundtrip consistency
150-153: LGTM! Comprehensive property-based test for Document
The test implementation thoroughly verifies Document functionality:
- Tests both features and schemata
- Verifies all string representation formats
- Ensures roundtrip consistency
31-36: 🛠️ Refactor suggestion
Refactor test helper functions into a dedicated helper module
To address the existing static analysis comments about importing test modules, consider moving the assertion helper functions (assert_repr_roundtrip, assert_str_roundtrip, etc.) from tests.hypothesis.common into a dedicated test helper module (e.g., tests/helpers/assertions.py). This would improve test isolation and maintainability.
tests/hypothesis/strategies.py (1)
31-31: LGTM!
The import statement follows the established pattern and is correctly placed with other fastkml imports.
tests/atom_test.py (1)
92-92: LGTM! The assertion change aligns with the Link class refactoring.
The updated assertion correctly validates that empty href values are now returned as None instead of an empty string, which is consistent with the new clean_string function's behavior introduced in this PR.
tests/registry_test.py (1)
Line range hint 1-252: Verify test coverage of the registry module.
Let's ensure comprehensive test coverage of the registry module functionality.
✅ Verification successful
Let me analyze the test coverage by checking the registry module implementation against the test cases.
Test coverage for Registry module is comprehensive
The test coverage is complete and well-structured:
test_registry_get_root()verifies basic registration and retrievaltest_registry_get()tests inheritance chain and class hierarchytest_registry_get_multi()validates multiple registrations and complex scenariostest_registry_repr()checks string representation
All public methods in Registry class are covered:
__init____repr__registerget
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check test coverage and find potential untested scenarios
# Find all references to Registry class to identify potential untested use cases
echo "Finding Registry usage patterns:"
rg "Registry" --type py -l
# Look for TODO/FIXME comments in registry-related files that might indicate missing tests
echo -e "\nChecking for TODO/FIXME comments in registry-related files:"
rg "TODO|FIXME" $(rg -l "Registry" --type py)
# Find all RegistryItem instantiations to ensure we're testing all use cases
echo -e "\nFinding RegistryItem usage patterns:"
ast-grep --pattern 'RegistryItem($$$)'
Length of output: 73019
Script:
#!/bin/bash
# Find the Registry class implementation to compare with tests
echo "Registry class implementation:"
rg -A 10 "^class Registry" fastkml/registry.py
# Find all methods in Registry class
echo -e "\nRegistry class methods:"
ast-grep --pattern 'def $_($$$) {$$$}' fastkml/registry.py
# Check test methods for Registry
echo -e "\nTest methods for Registry:"
ast-grep --pattern 'def test_$_($$$) {$$$}' tests/registry_test.py
Length of output: 936
Script:
#!/bin/bash
# Get full Registry class implementation with all methods
echo "Full Registry class implementation:"
rg -A 50 "^class Registry" fastkml/registry.py
# Get all test methods for Registry with their implementation
echo -e "\nFull test implementations:"
rg -A 50 "^def test_registry" tests/registry_test.py
Length of output: 4504
fastkml/kml.py (1)
218-219: LGTM! NetworkLink integration looks good.
The addition of NetworkLink to both the classes tuple and node_name string in the registry is consistent and follows the existing pattern.
fastkml/links.py (3)
24-24: LGTM: Clean import organization
The new import follows the established pattern and is properly grouped with other helper functions.
49-56: LGTM: Improved type safety with Optional annotations
The type annotations now correctly reflect that these string fields can be None, which aligns with the actual behavior of the class and improves type safety.
82-82: LGTM: Consistent string cleaning implementation
The implementation consistently uses the clean_string helper for all string fields, improving the robustness of string handling.
Let's verify the implementation of the clean_string helper:
Also applies to: 88-89
✅ Verification successful
LGTM: String cleaning implementation is robust and widely used
The clean_string helper in fastkml/helpers.py is well-implemented:
- Handles None values and empty strings appropriately
- Strips whitespace and returns None for empty/whitespace-only strings
- Is consistently imported and used across multiple modules (atom, data, features, links, overlays, styles)
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the clean_string helper implementation
# Expected: Function that handles None, empty strings, and whitespace
# Search for the clean_string implementation
ast-grep --pattern 'def clean_string($_):
$$$
'
# Search for its tests to verify behavior
rg -l "test.*clean_string"
Length of output: 80
Script:
#!/bin/bash
# Let's try different approaches to locate the clean_string implementation
# Search for clean_string function or method definition
rg -A 5 "def clean_string"
# Search for clean_string import statements
rg "from.*import.*clean_string|import.*clean_string"
# Search for files containing clean_string
rg -l "clean_string"
# Look for utility/helper modules that might contain this function
fd -e py util helper common
Length of output: 1073
fastkml/enums.py (1)
Line range hint 168-264: Consider standardizing enum value formats
Some enum values use underscores (e.g., int_, float_, bool_ in DataType) while others use camelCase (e.g., clampToGround in AltitudeMode). While this doesn't affect functionality due to case-insensitive matching, consider standardizing the format for better consistency.
Also, verify that these values match the KML specification exactly, as they will be used in XML output.
docs/create_kml_files.rst (1)
190-193: Review the CO2 growth accumulation logic
The current implementation accumulates CO2 values over time (co2_growth += co2_year), which might lead to misleading visualization as it shows cumulative growth rather than actual yearly values. Consider if this is the intended behavior or if showing actual yearly values would be more appropriate.
Consider these alternatives:
- Show actual yearly values instead of accumulation
- Add a clear description in the visualization to explain the cumulative nature
- Provide both cumulative and yearly visualizations for comparison
docs/working_with_kml.rst (1)
Line range hint 1-300: Documentation is well-structured and comprehensive!
The documentation follows best practices with:
- Clear progression from basic to advanced topics
- Consistent code block formatting
- Proper use of doctest directives
- Real-world examples demonstrating practical usage
tests/features_test.py (2)
19-30: LGTM!
The new imports are correctly organized and necessary for the new test methods.
53-94: Clarify the implementation of property-based testing.
The PR objectives mention introducing property-based testing using the Hypothesis library, but the current changes implement traditional unit tests. Could you clarify if property-based tests will be added in a separate PR or if they should be included here?
Example of how these tests could be converted to property-based tests:
from hypothesis import given, strategies as st
@given(
latitude=st.floats(min_value=-90, max_value=90),
longitude=st.floats(min_value=-180, max_value=180),
altitude=st.floats(),
roll=st.floats(),
tilt=st.floats(),
heading=st.floats(),
)
def test_placemark_camera_property_based(
self, latitude, longitude, altitude, roll, tilt, heading
):
"""Property-based test for Placemark with Camera view."""
camera = views.Camera(
latitude=latitude,
longitude=longitude,
altitude=altitude,
roll=roll,
tilt=tilt,
heading=heading,
)
pm = features.Placemark(view=camera)
new_pm = features.Placemark.from_string(str(pm.to_string()))
assert new_pm == pmtests/hypothesis/overlay_test.py (1)
36-244: LGTM for the overall test structure and coverage!
The property-based testing approach using Hypothesis is well-implemented with:
- Comprehensive test coverage for all overlay classes
- Good use of strategies to generate test data
- Proper validation of string representations
- Appropriate filtering of edge cases
fastkml/base.py (2)
18-18: LGTM! Well-structured imports and type hints.
The organization of imports is clean and the type hints are comprehensive. The use of typing_extensions.Self shows forward-thinking compatibility.
Also applies to: 19-19, 20-20, 21-21, 22-22, 23-23, 24-24, 25-25, 26-26, 27-27, 28-28, 29-29, 30-30, 31-31, 32-32, 33-33, 34-34, 35-35, 36-36
Line range hint 1-350: Overall implementation looks solid!
The changes improve namespace handling and error recovery while maintaining good documentation and type safety. The suggested improvements are minor optimizations to an already well-structured implementation.
fastkml/atom.py (3)
45-45: LGTM: Clean import organization
The clean_string import is properly grouped with other helper function imports.
137-141: LGTM: Consistent string cleaning implementation
The clean_string function is properly applied to all string attributes, maintaining consistency with the new string handling approach.
Let's verify test coverage for the new string cleaning:
#!/bin/bash
# Search for Link tests that cover string cleaning
rg -l "test.*Link" | xargs rg -B 2 -A 2 "(href|rel|type|hreflang|title)"
# Check if there are tests with None values
rg -l "test.*Link" | xargs rg "None.*Link|Link.*None"86-90: LGTM: Type annotations correctly updated for optional attributes
The type annotations properly reflect that these attributes can be None, which aligns with the Atom specification and the new string handling approach.
Let's verify the usage patterns of these optional attributes:
✅ Verification successful
Based on the search results, I can now generate the final response:
Type annotations correctly reflect optional attributes with proper usage
The codebase shows consistent handling of optional attributes in the Link class:
- Test cases demonstrate proper instantiation with both defined and undefined attributes
- Property testing via hypothesis confirms handling of None values
- Usage in NetworkLink and atom tests validate the optional nature of these fields
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for Link class instantiations to verify optional attribute handling
rg -l "Link\(" | xargs rg -B 2 -A 2 "Link\("
# Search for attribute access patterns
rg "\.(href|rel|type|hreflang|title)\b" --type py
Length of output: 12953
Script:
#!/bin/bash
# Search for Link class definition and usage in atom.py
ast-grep --pattern 'class Link {
$$$
}'
# Search for Link instantiations and attribute access
rg "Link\(" --type py -A 5
rg "\.(?:href|rel|type|hreflang|title)\s*=\s*None" --type py
Length of output: 6753
fastkml/containers.py (4)
31-31: LGTM: New imports enhance KML feature support
The addition of NetworkLink, GroundOverlay, and PhotoOverlay imports properly extends the container capabilities to support more KML features.
Also applies to: 42-43
171-173: LGTM: Enhanced documentation with official reference
Good addition of the official KML specification link, which improves documentation quality and maintainability.
331-332: LGTM: Registry properly updated for new feature types
The registry has been correctly updated to include GroundOverlay, PhotoOverlay, and NetworkLink in both node names and classes, maintaining consistency with the new imports.
208-208: LGTM: Enhanced type flexibility for features parameter
The change from List[_Feature] to Iterable[_Feature] improves API flexibility while maintaining type safety through internal list conversion.
Let's verify that all feature collections are properly handled:
✅ Verification successful
Let me gather more information about how features are handled internally to ensure the type change is safe.
Let me try a different approach to check the feature handling:
Type change to Iterable[_Feature] is safe and properly implemented
The verification confirms that the type change is safe because:
- The input
featuresparameter is immediately converted to a list viaself.features = list(features) if features else [] - All usage examples in the codebase (docs and examples) pass list-like objects
- The internal
featuresattribute maintains itsList[_Feature]type annotation for type safety
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any feature collection instantiations to ensure compatibility
rg -l "Document\(.*features\s*=" | while read -r file; do
echo "=== $file ==="
rg "Document\(.*features\s*=" "$file" -A 2
done
Length of output: 833
Script:
#!/bin/bash
# Check internal handling of features in Document class
ast-grep --pattern 'class Document {
$$$
def __init__($$$) {
$$$
}
$$$
}'
# Also check for any feature-related methods
rg "def.*features?" fastkml/containers.py -A 5
Length of output: 136
Script:
#!/bin/bash
# Check how features are handled in containers.py
rg "features.*=" fastkml/containers.py -B 2 -A 2
# Check for feature type conversions
rg "features.*list" fastkml/containers.py -B 2 -A 2
# Look for feature-related methods with proper context
rg "def" fastkml/containers.py --context 5 | rg -A 5 -B 5 "feature"
Length of output: 3044
tests/times_test.py (1)
Line range hint 337-338: LGTM! Good use of inheritance for parser testing
The approach of inheriting from both Lxml and TestStdLibrary ensures that all test cases are validated against both XML parsers, maintaining consistency across implementations.
tests/hypothesis/geometry_test.py (2)
Line range hint 64-89: LGTM: Well-designed test setup functions
The partial functions coordinates and common_geometry are well-structured:
- Effectively reuse common test parameters
- Handle None cases appropriately
- Use type-safe hypothesis strategies
Line range hint 161-400: LGTM: Comprehensive property-based testing implementation
The test implementation is excellent:
- Thorough coverage of all geometry types
- Effective use of property-based testing
- Proper validation of serialization formats
- Good separation of test cases
tests/geometries/multigeometry_test.py (3)
Line range hint 1-28: LGTM! Well-structured file with clear organization.
The file follows good practices with proper copyright notice, docstring, and organized imports.
Line range hint 31-32: LGTM! Excellent test class hierarchy design.
The test classes follow a well-structured inheritance pattern that:
- Avoids code duplication by implementing core tests in base classes
- Tests both standard library and lxml parsers through inheritance
- Maintains clear separation of concerns
Also applies to: 89-90, 146-147, 207-208, 386-399
Line range hint 367-384: LGTM! Thorough test data and assertions.
The test data and assertions are comprehensive:
- Cover various geometry types and combinations
- Verify both XML structure and geometric content
- Handle edge cases like empty geometries
fastkml/data.py (7)
35-35: LGTM: Clean import of the new helper function
The import of clean_string is properly placed with other helper function imports.
120-122: LGTM: Consistent string cleaning implementation
The use of clean_string for name, type_, and display_name attributes ensures consistent string handling. This aligns well with the __bool__ method which relies on these attributes.
368-370: LGTM: Proper string cleaning implementation
The use of clean_string for all string attributes is consistent and works well with the __bool__ method's logic.
475-476: LGTM: Consistent string handling
The implementation of clean_string for both attributes is consistent with the class's boolean logic and type hints.
583-583: LGTM: Proper schema_url cleaning
The use of clean_string for schema_url is consistent with the class's boolean logic and type hints.
Line range hint 120-583: Verify consistent behavior of clean_string across all use cases
While the implementation looks good across all classes, we should verify that clean_string behaves consistently for all string attributes, especially in edge cases.
#!/bin/bash
# Description: Check for existing tests that verify clean_string behavior
# Search for tests related to clean_string
rg -A 5 "clean_string" "*test*.py"
# Search for test cases with empty or whitespace strings
rg -A 5 '""|\s+"|"\s+' "*test*.py"250-252: Verify error handling with clean_string
While the implementation looks good, we should verify that the error handling for empty IDs still works as expected with clean_string. The KMLSchemaError is raised before clean_string is called, which is correct, but we should ensure that clean_string doesn't affect the validation logic.
✅ Verification successful
Based on the search results, I can now generate the final response since I have found both the implementation of clean_string and the error handling in Schema class:
Error handling with clean_string is correctly implemented
The verification shows that the error handling is working as expected because:
- The
KMLSchemaErroris raised beforeclean_stringis called, whenidis empty or None - The
clean_stringimplementation (return value.strip() or None if value else None) cannot affect the error handling since:- It's called after the error check
- It preserves None values (returns None for None input)
- It only strips whitespace and converts empty strings to None
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if there are any tests verifying the Schema error handling with empty strings
# Search for tests related to Schema initialization and error handling
rg -l "KMLSchemaError.*Schema"
rg -l "Schema.*clean_string"
Length of output: 171
Script:
#!/bin/bash
# Let's first find test files in the repository
fd "test.*\.py$"
# Then look for Schema and KMLSchemaError usage
rg -A 5 "Schema|KMLSchemaError"
# Also check the clean_string implementation
rg -A 3 "def clean_string"
Length of output: 35940
tests/hypothesis/multi_geometry_test.py (6)
Line range hint 59-150: Well-structured test helper functions
The helper functions are well-designed:
- Follow DRY principle by centralizing common test logic
- Clear separation of concerns between repr and str testing
- Comprehensive validation of geometry attributes
Line range hint 151-250: Comprehensive MultiPoint test coverage
The MultiPoint tests effectively cover:
- Representation roundtrip
- String serialization with different verbosity levels
- Proper attribute handling
- XML validation
Line range hint 251-350: Well-structured MultiLineString tests
The tests maintain consistency with the MultiPoint pattern while properly handling MultiLineString specific attributes.
Line range hint 351-450: Consistent MultiPolygon test implementation
The tests maintain the established pattern while properly handling MultiPolygon specific attributes.
Line range hint 451-600: Well-implemented GeometryCollection tests
The tests properly handle the complexity of mixed geometry types while maintaining consistency with the test structure.
Line range hint 44-57: Security consideration for eval() usage
While eval() is properly sandboxed with restricted locals, consider using ast.literal_eval() for even safer repr evaluation, or document why eval() is specifically needed here.
tests/styles_test.py (1)
128-130: LGTM! Good test coverage for icon attributes.
The added assertions properly verify both the presence of the icon object and its href attribute, ensuring the IconStyle class correctly handles icon information.
fastkml/features.py (4)
47-47: LGTM: Clean import organization
The clean_string helper function import is properly organized with other helper functions.
137-137: LGTM: Consistent string handling
The clean_string function is correctly used to standardize the handling of the text attribute, improving consistency across the codebase.
290-291: LGTM: Comprehensive string sanitization
All relevant string attributes (name, description, address, phone_number) are now consistently sanitized using clean_string, improving robustness against empty or whitespace-only values.
Also applies to: 300-301
697-697: Verify Google Earth extension support
The addition of "gx" namespace support for geometry handling enables Google Earth extensions. Please ensure this change is properly documented and tested.
✅ Verification successful
Let me check the content of the documentation and test files to verify the Google Earth extension support.
Google Earth extension support is properly implemented and tested
The addition of "gx" namespace for geometry handling is well-supported:
- Comprehensive test coverage in
tests/gx_test.pyincludes:- Track and MultiTrack geometry implementations
- Coordinate handling with timestamps
- Angle and orientation support
- XML serialization/deserialization
- Documentation in
docs/working_with_kml.rstmentions Google Earth extensions and provides guidance on extensibility
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for documentation and tests related to Google Earth extensions
# Check for documentation updates
echo "Checking documentation for Google Earth extensions..."
rg -l "gx:|Google Earth extension" docs/
# Check for related test coverage
echo "Checking test coverage for Google Earth extensions..."
rg -l "gx:Track|gx:MultiTrack" tests/
Length of output: 359
Script:
#!/bin/bash
# Check documentation content
echo "Documentation content:"
cat docs/working_with_kml.rst | grep -A 5 -B 5 "gx:"
# Check test content
echo -e "\nTest content:"
cat tests/gx_test.py
Length of output: 20793
fastkml/helpers.py (1)
Line range hint 1-1000: Well-structured and thoroughly documented code
The overall file structure, documentation, type hints, and error handling are well-implemented. The helper functions follow consistent patterns and naming conventions.
fastkml/styles.py (5)
42-42: LGTM: Clean import addition
The addition of clean_string import is well-placed and aligns with the standardization of string handling across the codebase.
112-112: LGTM: Standardized string handling
Using clean_string for the url attribute improves consistency in string handling.
478-478: LGTM: Proper string cleaning placement
Good placement of clean_string before the conditional checks, ensuring consistent string comparison.
990-992: Verify color handling while approving standardization
Good standardization of string handling for all three attributes. However, please verify that clean_string preserves the hexadecimal format for both bg_color and text_color attributes.
Example valid values:
- bg_color: "7fff0000" (50% opaque blue)
- text_color: "ff000000" (opaque black)
✅ Verification successful
Based on the results, I can now generate the final response:
Color handling is safe with clean_string
The clean_string function only performs basic string cleaning (stripping whitespace) and doesn't modify the actual content. The test cases confirm proper handling of hex color values:
- Test examples show correct 8-digit hex format preservation: "7fff0000", "ff00ff00"
- Multiple test cases consistently use and verify this format
- No color format transformation is performed by
clean_string
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify color handling in tests
# Find test cases for BalloonStyle colors
rg -A 3 "BalloonStyle.*bg_color.*=.*['\"][0-9a-fA-F]{8}['\"]"
rg -A 3 "BalloonStyle.*text_color.*=.*['\"][0-9a-fA-F]{8}['\"]"
Length of output: 231
Script:
#!/bin/bash
# Let's try a different approach to verify color handling
# 1. Check the implementation of clean_string function
rg -A 5 "def clean_string"
# 2. Look for BalloonStyle test cases
rg -A 10 "class.*BalloonStyle.*Test"
# 3. Look for actual BalloonStyle usage examples
rg -A 5 "BalloonStyle\("
# 4. Check if there are any color format validation functions
rg -A 5 "def.*color" fastkml/
Length of output: 2081
225-225: Verify hex string handling
While using clean_string for standardization is good, please verify that it preserves the hexadecimal format of color values (e.g., "aabbggrr").
✅ Verification successful
Color string handling is safe with clean_string
Based on the evidence:
clean_stringonly strips whitespace and handles None values, preserving the actual string content- Test cases confirm proper handling of 8-character hex color values (e.g., "ff0000ff", "7fff0000")
- The test strategy
kml_colorsspecifically generates valid 8-character hex strings - Multiple test cases verify color values remain intact after processing
The clean_string function will not affect the hexadecimal format of color values as it only performs whitespace trimming.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if clean_string preserves hex color values
# Find the implementation of clean_string
rg -A 5 "def clean_string"
# Find color value examples in tests
rg -A 2 "color.*=.*['\"][0-9a-fA-F]{8}['\"]"
Length of output: 231
Script:
#!/bin/bash
# Let's try different approaches to find the relevant information
# Find the clean_string implementation
rg -A 5 "def clean_string"
# Look for color-related tests or examples with hex values using broader patterns
rg -l "color.*['\"][0-9a-fA-F]" tests/
rg -l "color.*['\"][0-9a-fA-F]" examples/
# Find the _ColorStyle class implementation and usage
rg -A 10 "class _ColorStyle"
# Look for any color-related test cases
rg -A 5 "test.*color" tests/
Length of output: 1567
Script:
#!/bin/bash
# Let's check the test files for color usage patterns and validation
# Check the color test strategies
rg -A 10 "kml_colors" tests/hypothesis/strategies.py
# Check style tests for color handling
rg -A 5 "color.*=" tests/styles_test.py
# Check if there are any color validation or format checks
rg -B 2 -A 5 "color.*['\"][0-9a-fA-F]" tests/styles_test.py
Length of output: 14869
fastkml/overlays.py (4)
40-40: LGTM: Clean string handling improvement
The addition of clean_string and its usage for color initialization aligns with the PR objectives of standardizing string attribute handling.
Also applies to: 207-207
472-473: LGTM: Documentation enhancement
Good addition of the Google KML documentation link, improving code maintainability.
1267-1267: LGTM: Enhanced namespace support
The addition of "gx" and empty string namespaces for altitude_mode registration improves compatibility with different KML variants.
558-558: Verify the impact of simplified boolean check
The __bool__ method has been simplified to only check max_width and max_height, removing checks for tile_size and grid_origin. While this makes the code cleaner, we should verify this doesn't break existing behavior.
✅ Verification successful
Let me gather more information about the ImagePyramid class and its usage to verify the impact of this change.
Let me check one more aspect - the actual implementation of serialization and any other methods that might depend on these attributes.
Let me check one final aspect - the XML serialization and element creation code.
Based on the gathered information, I can now provide a final response:
The simplified boolean check is safe and correct
The change to __bool__ is valid because:
- The test cases show that
tile_sizeandgrid_originare optional attributes used only for XML serialization - The docstring indicates the method's purpose is to check "if all the required attributes are set"
- Only
max_widthandmax_heightare truly required for the ImagePyramid to be considered valid, as they define the essential pyramid dimensions
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for existing usage patterns of ImagePyramid.__bool__
# Search for ImagePyramid usage in tests
rg -l "ImagePyramid" | grep "_test" | while read -r file; do
echo "=== $file ==="
rg -A 5 "ImagePyramid" "$file"
done
# Search for conditional checks on ImagePyramid instances
ast-grep --pattern 'if $pyramid:
$$$
'
Length of output: 1899
Script:
#!/bin/bash
# Check the ImagePyramid class implementation and its usage
rg -A 10 "class ImagePyramid"
# Check if there are any other methods or properties that depend on these attributes
rg "tile_size|grid_origin" fastkml/overlays.py
# Look for any serialization/deserialization logic that might depend on these attributes
ast-grep --pattern 'def to_string($$$) { $$$ }'
Length of output: 1394
Script:
#!/bin/bash
# Check the implementation of ImagePyramid's methods
rg -B 2 -A 10 "def (to_string|from_string|__bool__)" fastkml/overlays.py
# Check if there are any validation methods or property getters
ast-grep --pattern 'class ImagePyramid {
$$$
@property
$$$
}'
# Look for any XML element creation related to these attributes
rg -A 3 "Element\(.*?(tile_size|grid_origin)" fastkml/overlays.py
Length of output: 1125
Script:
#!/bin/bash
# Check for XML element creation and serialization
rg -B 2 -A 10 "def to_string" fastkml/overlays.py
# Look for XML element creation specifically in ImagePyramid
rg -A 5 "Element\(" fastkml/overlays.py | grep -C 5 "ImagePyramid"
# Check for any validation or requirement checks
rg -A 3 "@(require|validate)" fastkml/overlays.py
Length of output: 170
fastkml/geometry.py (1)
Line range hint 1-1037: Well-structured and thoroughly documented code.
The implementation demonstrates good practices:
- Proper error handling with custom exceptions
- Clear class hierarchies and inheritance
- Comprehensive type hints and docstrings
- Effective use of the registry pattern for XML serialization
fastkml/times.py (1)
Line range hint 62-62: Verify that the 'arrow' library is included in project dependencies
The arrow library is used in this file. Ensure it is added to the project's dependencies in setup.py or requirements.txt to prevent import errors.
Run the following script to check if 'arrow' is listed in the dependencies:
✅ Verification successful
Let me search for other dependency management files and verify the actual usage of 'arrow' in the code.
Let me check the content of the dependency files we found to verify if arrow is included.
The arrow library is correctly included in project dependencies
The arrow library is properly listed as a dependency in both:
pyproject.tomlunder the main project dependenciesdocs/requirements.txt
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify that 'arrow' is included in project dependencies.
# Check setup.py
grep -Hn "arrow" setup.py || echo "'arrow' not found in setup.py"
# Check requirements.txt
grep -Hn "arrow" requirements.txt || echo "'arrow' not found in requirements.txt"
Length of output: 317
Script:
#!/bin/bash
# Check for other dependency files and arrow usage
fd -e toml -e cfg -e txt -e in . | grep -i "requirement\|setup\|pyproject" || echo "No dependency files found"
# Check if arrow is actually imported/used in the code
rg "import.*arrow|from.*arrow" -l || echo "No arrow imports found"
# Check the content of the file to verify arrow usage
cat fastkml/times.py || echo "File not found"
Length of output: 11512
Script:
#!/bin/bash
# Check the content of dependency files
cat docs/requirements.txt || echo "docs/requirements.txt not found"
cat pyproject.toml || echo "pyproject.toml not found"
Length of output: 4910
fastkml/gx.py (1)
Line range hint 190-190: Verify the definition of _get_splat method used in __repr__
The __repr__ method references self._get_splat(), but it's unclear if _get_splat is defined in the superclass or within this class. Ensure that _get_splat is properly defined to avoid AttributeError.
Please confirm the presence of _get_splat in the inheritance hierarchy or define it within the class if missing.
| link=st.builds( | ||
| fastkml.links.Link, | ||
| href=urls(), | ||
| ), |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider constraining URL generation.
The current URL generation using urls() might generate invalid or problematic URLs. Consider adding constraints to ensure generated URLs are suitable for KML.
- href=urls(),
+ href=urls().filter(lambda x: not any(c in x for c in '<>"')),📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| link=st.builds( | |
| fastkml.links.Link, | |
| href=urls(), | |
| ), | |
| link=st.builds( | |
| fastkml.links.Link, | |
| href=urls().filter(lambda x: not any(c in x for c in '<>"')), | |
| ), |
| ... for year in range(1995, 2023): | ||
| ... co2_year = co2_pa[str(year)].get(iso3_code, 0) | ||
| ... co2_growth += co2_year | ||
| ... kml_geometry = create_kml_geometry( | ||
| ... force_3d(geometry, co2_growth * 5_000), | ||
| ... extrude=True, | ||
| ... altitude_mode=AltitudeMode.relative_to_ground, | ||
| ... ) | ||
| ... timespan = fastkml.times.TimeSpan( | ||
| ... begin=fastkml.times.KmlDateTime( | ||
| ... datetime.date(year, 1, 1), resolution=DateTimeResolution.year_month | ||
| ... ), | ||
| ... end=fastkml.times.KmlDateTime( | ||
| ... datetime.date(year, 12, 31), resolution=DateTimeResolution.year_month | ||
| ... ), | ||
| ... ) | ||
| ... placemark = fastkml.features.Placemark( | ||
| ... name=f"{feature['properties']['NAME']} - {year}", | ||
| ... description=feature["properties"]["FORMAL_EN"], | ||
| ... kml_geometry=kml_geometry, | ||
| ... style_url=style_url, | ||
| ... times=timespan, | ||
| ... ) | ||
| ... folder.features.append(placemark) | ||
| ... folders.append(folder) |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add error handling for missing or invalid data
The code assumes data availability and validity but should handle potential issues:
- Missing CO2 data for specific years/countries
- Invalid geometry data
- Memory constraints with large datasets
Consider adding error handling and memory optimization:
for year in range(1995, 2023):
- co2_year = co2_pa[str(year)].get(iso3_code, 0)
+ try:
+ co2_year = co2_pa[str(year)].get(iso3_code, 0)
+ if not isinstance(co2_year, (int, float)):
+ raise ValueError(f"Invalid CO2 data for {iso3_code} in {year}")
+ except Exception as e:
+ print(f"Warning: {e}. Using default value 0.")
+ co2_year = 0
+
+ # Optional: Clear previous year's placemark to save memory
+ if len(folder.features) > 10: # Keep only recent years in memory
+ folder.features.pop(0)Committable suggestion skipped: line range outside the PR's diff.
| north=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), | ||
| south=st.one_of( | ||
| st.none(), | ||
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| ), |
There was a problem hiding this comment.
Fix latitude range for north/south coordinates
The latitude values for north and south parameters should be in the range [-90, 90] degrees instead of [-180, 180].
north=st.one_of(
st.none(),
- st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
+ st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),
),
south=st.one_of(
st.none(),
- st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
+ st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),
),📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| north=st.one_of( | |
| st.none(), | |
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | |
| ), | |
| south=st.one_of( | |
| st.none(), | |
| st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | |
| ), | |
| north=st.one_of( | |
| st.none(), | |
| st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0), | |
| ), | |
| south=st.one_of( | |
| st.none(), | |
| st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0), | |
| ), |
| north=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| south=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | ||
| east=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), |
There was a problem hiding this comment.
Fix latitude range for north/south coordinates in ground overlay test
Similar to the previous issue, the latitude values for north and south parameters in the ground overlay test should be in the range [-90, 90] degrees instead of [-180, 180].
- north=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
- south=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0),
+ north=st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),
+ south=st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0),📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| north=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | |
| south=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | |
| east=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), | |
| north=st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0), | |
| south=st.floats(min_value=-90, max_value=90).filter(lambda x: x != 0), | |
| east=st.floats(min_value=-180, max_value=180).filter(lambda x: x != 0), |
| st.builds( | ||
| fastkml.TimeSpan, | ||
| begin=kml_datetimes(), | ||
| end=kml_datetimes(), | ||
| ), |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Ensure begin date is before end date in TimeSpan
In the TimeSpan strategy, begin and end are generated independently, which might result in begin dates after end dates. This could lead to invalid TimeSpan objects or errors during parsing. Consider adjusting the strategy to ensure that begin is always before or equal to end.
You can modify the strategy as follows:
st.builds(
- fastkml.TimeSpan,
- begin=kml_datetimes(),
- end=kml_datetimes(),
+ lambda times: fastkml.TimeSpan(begin=times[0], end=times[1]),
+ st.tuples(
+ kml_datetimes(),
+ kml_datetimes()
+ ).filter(lambda times: times[0] <= times[1]),
)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| st.builds( | |
| fastkml.TimeSpan, | |
| begin=kml_datetimes(), | |
| end=kml_datetimes(), | |
| ), | |
| st.builds( | |
| lambda times: fastkml.TimeSpan(begin=times[0], end=times[1]), | |
| st.tuples( | |
| kml_datetimes(), | |
| kml_datetimes() | |
| ).filter(lambda times: times[0] <= times[1]), | |
| ), |
cleder
changed the title
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👍 Looks good to me! Incremental review on 8882d8b in 56 seconds
More details
- Looked at
430lines of code in7files - Skipped
0files when reviewing. - Skipped posting
2drafted comments based on config settings.
1. fastkml/helpers.py:1156
- Draft comment:
The use ofcasttoPointTypeis unclear. EnsurePointTypeis compatible with the tuple of floats being cast. This could lead to runtime errors if not compatible. - Reason this comment was not posted:
Comment did not seem useful.
2. fastkml/validator.py:80
- Draft comment:
Ensureelementis notNonebefore callingelement.xpathto avoid potentialAttributeError. - Reason this comment was not posted:
Comment did not seem useful.
Workflow ID: wflow_BEX2PvMEUQICbTlB
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (7)
fastkml/times.py (3)
54-90: LGTM! Consider a minor readability improvementThe function is well-implemented and properly documented. The logic for handling different resolutions is correct and comprehensive.
Consider simplifying the final return statement for better readability:
- return ( - dt.date() - if isinstance(dt, datetime) and resolution != DateTimeResolution.datetime - else dt - ) + if isinstance(dt, datetime) and resolution != DateTimeResolution.datetime: + return dt.date() + return dt
143-149: Simplify resolution inference logicThe current resolution inference logic can be simplified for better readability.
Consider this more concise version:
- resolution = ( - DateTimeResolution.date - if not isinstance(dt, datetime) - else DateTimeResolution.datetime - ) + resolution = DateTimeResolution.datetime if isinstance(dt, datetime) else DateTimeResolution.date
Line range hint
316-334: Add time boundary validation in TimeSpanThe TimeSpan class should validate that the begin time is before the end time when both are provided.
Consider adding validation in the constructor:
def __init__( self, ns: Optional[str] = None, name_spaces: Optional[Dict[str, str]] = None, id: Optional[str] = None, target_id: Optional[str] = None, begin: Optional[KmlDateTime] = None, end: Optional[KmlDateTime] = None, **kwargs: Any, ) -> None: super().__init__( ns=ns, name_spaces=name_spaces, id=id, target_id=target_id, **kwargs, ) self.begin = begin self.end = end + if self.begin and self.end and self.begin.dt > self.end.dt: + raise ValueError("Begin time must be before end time")fastkml/helpers.py (2)
83-85: LGTM! Consider adding type hints for the return value.The function is well-implemented and handles edge cases correctly. For better type safety, consider adding an explicit return type hint.
-def clean_string(value: Optional[str]) -> Optional[str]: +def clean_string(value: Optional[str], /) -> Optional[str]:
1146-1167: Add input validation and improve documentation.The function implementation is solid, but could benefit from these improvements:
- Add input validation for the subelements parameter
- Enhance docstring with parameter descriptions and return type
- Add example usage in the docstring
def get_coord_args( element: Element, subelements: Iterable[Element], strict: bool, # noqa: FBT001 ) -> Iterable[PointType]: - """Extract a list of KML coordinate values from subelements of an XML element.""" + """Extract KML coordinate values from XML subelements. + + Args: + element: The parent XML element for error context + subelements: Iterator of XML subelements containing coordinate text + strict: If True, raises exceptions instead of logging warnings + + Returns: + Iterator yielding coordinate tuples as PointType + + Example: + >>> coords = list(get_coord_args(elem, elem.findall("coordinates"), True)) + """ + if not element or not subelements: + return for subelement in subelements:fastkml/utils.py (2)
Line range hint
47-55: Fix unintended iteration over strings infind_infunctionWhen
attris a string, iterating over it will process each character separately, which is likely unintended and could lead to incorrect behavior.Apply this diff to prevent iterating over strings:
+ from collections.abc import Iterable for attr_name in attrs: attr = getattr(obj, attr_name) - try: - for item in attr: - yield from find_all(item, of_type=of_type, **kwargs) - except TypeError: - yield from find_all(attr, of_type=of_type, **kwargs) + if isinstance(attr, Iterable) and not isinstance(attr, str): + for item in attr: + yield from find_all(item, of_type=of_type, **kwargs) + else: + yield from find_all(attr, of_type=of_type, **kwargs)
Line range hint
33-92: Prevent infinite recursion due to cyclic referencesThe recursive functions
find_allandfind_inmay encounter infinite recursion if the object graph contains cyclic references.Consider implementing a mechanism to track visited objects to prevent revisiting the same instances:
+ from typing import Set def find_all( obj: object, *, of_type: Optional[Union[Type[object], Tuple[Type[object], ...]]] = None, + seen: Optional[Set[int]] = None, **kwargs: Any, ) -> Generator[object, None, None]: + if seen is None: + seen = set() + obj_id = id(obj) + if obj_id in seen: + return + seen.add(obj_id) if (of_type is None or isinstance(obj, of_type)) and has_attribute_values( obj, **kwargs, ): yield obj - yield from find_in(obj, of_type=of_type, **kwargs) + yield from find_in(obj, of_type=of_type, seen=seen, **kwargs) def find_in( obj: object, *, of_type: Optional[Union[Type[object], Tuple[Type[object], ...]]] = None, + seen: Optional[Set[int]] = None, **kwargs: Any, ) -> Generator[object, None, None]: + if seen is None: + seen = set() try: attrs = (attr for attr in obj.__dict__ if not attr.startswith("_")) except AttributeError: return for attr_name in attrs: attr = getattr(obj, attr_name) - if isinstance(attr, Iterable) and not isinstance(attr, str): + if isinstance(attr, Iterable) and not isinstance(attr, (str, bytes)): for item in attr: - yield from find_all(item, of_type=of_type, **kwargs) + yield from find_all(item, of_type=of_type, seen=seen, **kwargs) else: - yield from find_all(attr, of_type=of_type, **kwargs) + yield from find_all(attr, of_type=of_type, seen=seen, **kwargs)This modification introduces a
seenset to keep track of visited objects by theirid, preventing infinite loops when cyclic references are present.
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📒 Files selected for processing (7)
.pre-commit-config.yaml(1 hunks)fastkml/helpers.py(5 hunks)fastkml/times.py(4 hunks)fastkml/utils.py(2 hunks)fastkml/validator.py(3 hunks)pyproject.toml(2 hunks)tox.ini(1 hunks)
🧰 Additional context used
🪛 GitHub Check: codecov/patch
fastkml/validator.py
[warning] 86-86: fastkml/validator.py#L86
Added line #L86 was not covered by tests
🔇 Additional comments (9)
tox.ini (1)
8-8: Verify the purpose and necessity of new error codes
The addition of ECE001 and CCR001 to the ignore list for test files needs verification. These don't appear to be standard flake8 error codes.
Let's verify the error codes and their sources:
Could you please:
- Confirm which flake8 plugins define these error codes
- Document the purpose of ignoring these specific codes in test files
- Consider adding a comment in the config file explaining why these codes are ignored
.pre-commit-config.yaml (2)
54-60: LGTM! Great addition of quality-focused flake8 plugins.
These plugins will help maintain high code quality standards, particularly beneficial for the ongoing refactoring efforts. The additions will help:
- Monitor function and expression complexity
- Ensure proper documentation and comments
- Maintain consistent function ordering
- Validate proper encoding usage
54-60: Verify plugin compatibility and CI impact.
Let's ensure these plugins work well with the current setup.
fastkml/validator.py (3)
27-33: LGTM! Export list is properly updated.
The __all__ list correctly includes the new handle_validation_error function, maintaining proper module interface documentation.
139-139: LGTM! Error handling is properly delegated.
The integration of handle_validation_error maintains the function's behavior while improving error reporting.
83-86: Add test coverage for XPath error handling.
The fallback path for XPath errors is not covered by tests. This could hide potential issues with error handling.
Let's verify the XPath error handling implementation:
Would you like me to help create test cases that cover the XPath error handling path?
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 86-86: fastkml/validator.py#L86
Added line #L86 was not covered by tests
pyproject.toml (1)
259-259: Verify XSD schema files existence.
The inclusion of XSD schema files is important for KML validation. Let's verify these files exist in the correct location.
#!/bin/bash
# Description: Verify XSD schema files exist and are properly placed
# Check if schema directory exists and contains XSD files
fd -e xsd . fastkml/schema/
# Verify these are valid XML schema files
find fastkml/schema/ -name "*.xsd" -exec head -n 2 {} \; | grep -i "xml.*schema"fastkml/times.py (1)
44-44: Verify test coverage for time-related functionality
The PR objectives mention extensive property-based testing, let's verify the test coverage for the time-related functionality.
✅ Verification successful
Test coverage for time-related functionality is adequate
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check test coverage for time-related functionality
# Look for time-related test files
echo "Looking for time-related test files..."
fd -e py -e pytest "time" "test"
# Check for Hypothesis test strategies for time-related components
echo "Checking for Hypothesis test strategies..."
rg -l "from hypothesis" $(fd -e py "test")
rg -A 5 "@given" $(fd -e py "test")
Length of output: 20884
fastkml/helpers.py (1)
1182-1182: LGTM! Good refactoring.
The change effectively reuses the new get_coord_args function, reducing code duplication while maintaining the same functionality.
fastkml/validator.py
Outdated
| def handle_validation_error( | ||
| schema_parser: "config.etree.XMLSchema", | ||
| element: Optional[Element], | ||
| ) -> None: |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add input validation for element parameter.
The function uses element as a fallback but doesn't validate that it's not None. Consider adding a parameter check.
def handle_validation_error(
schema_parser: "config.etree.XMLSchema",
element: Optional[Element],
) -> None:
+ if element is None:
+ raise ValueError("Element cannot be None")📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def handle_validation_error( | |
| schema_parser: "config.etree.XMLSchema", | |
| element: Optional[Element], | |
| ) -> None: | |
| def handle_validation_error( | |
| schema_parser: "config.etree.XMLSchema", | |
| element: Optional[Element], | |
| ) -> None: | |
| if element is None: | |
| raise ValueError("Element cannot be None") |
| @@ -60,12 +60,10 @@ docs = [ | |||
| linting = [ | |||
| "black", | |||
| "flake8", | |||
| "flake8-cognitive-complexity", | |||
There was a problem hiding this comment.
💡 Codebase verification
Removed flake8 plugins are not covered by ruff. Please ensure equivalent linting rules are configured.
🔗 Analysis chain
LGTM! Verify coverage of removed linting functionality.
The addition of flake8-cognitive-complexity is a good improvement for maintaining code quality. However, since flake8-length, flake8-pep3101, and flake8-super were removed, ensure their functionality is covered by other tools like ruff which is already included in the dependencies.
Schema includes verified successfully.
🏁 Scripts executed
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#!/bin/bash
# Description: Check if removed linting rules are covered by ruff
# Check ruff's documentation for equivalent rules
rg --type=yaml "pep3101|super-call|line-length" .ruff.toml || \
rg --type=toml "pep3101|super-call|line-length" pyproject.toml
Length of output: 327
Script:
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# Description: Verify if ruff covers the removed flake8 rules
# Check if ruff's configuration includes rules corresponding to 'pep3101', 'super-call', or 'line-length'
rg --type=yaml "pep3101|super-call|line-length" .ruff.toml || \
rg --type=toml "pep3101|super-call|line-length" pyproject.toml
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👍 Looks good to me! Incremental review on 4ac3fb6 in 40 seconds
More details
- Looked at
292lines of code in6files - Skipped
0files when reviewing. - Skipped posting
3drafted comments based on config settings.
1. fastkml/kml.py:88
- Draft comment:
The logic for settingvalidatetoTruewhenstrictisTrueandvalidateisNonemight be non-intuitive. Consider documenting this behavior clearly or revisiting the default logic. - Reason this comment was not posted:
Confidence changes required:50%
Thelxml_parse_and_validatefunction infastkml/kml.pyhas a potential issue with thevalidateparameter. The function setsvalidatetoTrueifstrictisTrueandvalidateisNone, but this behavior might not be intuitive for users. It would be better to explicitly document this behavior or reconsider the default logic.
2. fastkml/base.py:224
- Draft comment:
Ensure that thevalidatemethod handles exceptions properly and provides meaningful error messages if validation fails. - Reason this comment was not posted:
Confidence changes required:50%
Thevalidatemethod infastkml/base.pyis a new addition that calls thevalidatefunction fromfastkml/validator.py. This method should ensure that it handles exceptions properly and provides meaningful error messages if validation fails.
3. tests/kml_test.py:205
- Draft comment:
Ensure that theAssertionErrormessage is informative and helps diagnose the issue when parsing KML with unbound prefixes. - Reason this comment was not posted:
Confidence changes required:50%
Thetest_from_string_with_unbound_prefix_stricttest intests/kml_test.pyis designed to check for validation errors when parsing KML with unbound prefixes. The test correctly expects anAssertionError, but it should also verify that the error message is informative and helps diagnose the issue.
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Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (6)
fastkml/validator.py (1)
99-103: Enhance error message with more contextThe error message could be more informative by including the error location and line number.
Apply this diff:
logger.error( - "Error <%s> in XML:\n %s", + "Validation error at line %d, column %d: %s\nIn XML context:\n%s", + error_entry.line, + error_entry.column, error_entry.message, error_in_xml, )tests/kml_test.py (3)
196-210: LGTM! Consider improving the test name for clarity.The test effectively verifies strict validation behavior for unbound prefixes. Consider renaming it to
test_strict_validation_fails_for_unbound_prefixto better reflect its purpose.
211-222: LGTM! Consider adding more assertions.The test effectively verifies relaxed validation behavior. Consider adding assertions for:
- The ExtendedData content
- The unbound prefix element's value
def test_from_string_with_unbound_prefix_relaxed(self) -> None: doc = io.StringIO( '<kml xmlns="http://www.opengis.net/kml/2.2">' "<Placemark><ExtendedData>" "<lc:attachment>image.png</lc:attachment>" "</ExtendedData>" "</Placemark> </kml>", ) k = kml.KML.parse(doc, strict=False) assert len(k.features) == 1 assert isinstance(k.features[0], features.Placemark) + assert k.features[0].extended_data is not None + assert "image.png" in k.to_string()
223-233: LGTM! Consider adding a docstring.The test effectively verifies the behavior when validation is disabled. Consider adding a docstring to explain the difference between this test and the relaxed validation test.
def test_from_string_with_unbound_prefix_strict_no_validate(self) -> None: + """ + Verify that unbound prefixes are allowed when validation is disabled, + even in strict mode. This differs from relaxed validation as it bypasses + all schema validation checks. + """ doc = io.StringIO( '<kml xmlns="http://www.opengis.net/kml/2.2">'fastkml/kml.py (2)
90-96: Adjust parser recovery options based on thestrictparameterCurrently, the XML parser is configured with
recover=True, which attempts to correct and parse malformed XML. In strict mode, it may be more appropriate to disable recovery to enforce strict parsing and catch any XML errors early.Consider modifying the parser options to reflect the
strictparameter:tree = config.etree.parse( file, parser=config.etree.XMLParser( huge_tree=True, - recover=True, + recover=not strict, ), )
64-100: Clarify the interplay betweenstrictandvalidateparametersThe logic where
validateis set toTruewhenstrictisTrueandvalidateisNonemay be confusing. Consider settingvalidateto default to the value ofstrictto make the behavior more intuitive.Refactor the code to set
validatebased onstrictby default:def lxml_parse_and_validate( file: Union[Path, str, IO[AnyStr]], strict: bool, - validate: Optional[bool], + validate: Optional[bool] = None, ) -> Element: """ ... """ - if strict and validate is None: - validate = True + if validate is None: + validate = strict tree = config.etree.parse( file, parser=config.etree.XMLParser(
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📒 Files selected for processing (6)
.pre-commit-config.yaml(1 hunks)fastkml/base.py(3 hunks)fastkml/kml.py(6 hunks)fastkml/validator.py(4 hunks)tests/hypothesis/common.py(5 hunks)tests/kml_test.py(2 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- .pre-commit-config.yaml
🧰 Additional context used
🪛 GitHub Check: codecov/patch
fastkml/validator.py
[warning] 91-91: fastkml/validator.py#L91
Added line #L91 was not covered by tests
🔇 Additional comments (11)
tests/hypothesis/common.py (4)
39-42: LGTM! New imports follow existing patterns.
The addition of GridOrigin and Shape imports from fastkml.enums is consistent with the existing import structure.
73-74: LGTM! Dictionary updates maintain consistency.
The additions to eval_locals properly expose the new enums for evaluation context, maintaining alphabetical ordering.
99-99: LGTM! Consistent validation approach.
The changes consistently implement validation checks across all roundtrip assertion functions, improving the robustness of the tests.
Also applies to: 110-110, 121-121
99-99: Verify the validate method implementation.
The changes consistently use new_object.validate() across all roundtrip functions. Let's verify the implementation of this method.
Also applies to: 110-110, 121-121
fastkml/validator.py (3)
21-33: LGTM! Clean type checking setup
The type checking imports and conditional imports are well-structured and follow Python typing best practices.
144-144: LGTM! Good refactoring
The use of the centralized error handler improves code maintainability and consistency.
84-91: 🛠️ Refactor suggestion
Improve error handling robustness
The xpath error handling could be more comprehensive, and the edge case where parent is None needs test coverage.
Let's verify the test coverage:
Consider this more robust implementation:
for error_entry in log:
+ parent = element
try:
parent = element.xpath(error_entry.path)[ # type: ignore[union-attr]
0
].getparent()
- except config.etree.XPathEvalError:
- parent = element
- if parent is None:
- parent = element
+ except (config.etree.XPathEvalError, IndexError, AttributeError):
+ logger.debug("Failed to find parent element using xpath: %s", error_entry.path)🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 91-91: fastkml/validator.py#L91
Added line #L91 was not covered by tests
tests/kml_test.py (1)
196-233: Great test coverage for validation scenarios!
The three tests form a comprehensive set that covers:
- Strict validation (failure case)
- Relaxed validation (success case)
- Disabled validation (success case)
Using consistent test data across all cases makes it easy to understand the differences in behavior.
fastkml/kml.py (1)
252-253: Including NetworkLink in the registry
Adding NetworkLink to the classes and node_name in the registry appropriately expands support for additional KML features. Ensure that all necessary methods and properties for NetworkLink are implemented and adequately tested.
fastkml/base.py (2)
32-32: Import statement is appropriate
The validate function is correctly imported from fastkml.validator and is used in the validate method.
209-225:
Ensure consistency between the validate method's implementation and its docstring
The docstring states that the method raises an AssertionError if the object is not valid. However, the implementation directly returns the result of validate(element=self.etree_element()) without explicitly handling exceptions. Please verify whether the validate function raises AssertionError on validation failure. If not, consider adjusting the implementation or updating the docstring to accurately reflect the actual behavior.
To verify the behavior of the validate function, you can run the following script:
| __all__ = [ | ||
| "get_schema_parser", | ||
| "validate", | ||
| ] | ||
|
|
There was a problem hiding this comment.
Add handle_validation_error to __all__
The new handle_validation_error function appears to be part of the public API but is not listed in __all__. This could prevent users from accessing it when using from fastkml.validator import *.
Apply this diff:
__all__ = [
"get_schema_parser",
"validate",
+ "handle_validation_error",
]📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| __all__ = [ | |
| "get_schema_parser", | |
| "validate", | |
| ] | |
| __all__ = [ | |
| "get_schema_parser", | |
| "validate", | |
| "handle_validation_error", | |
| ] |
fastkml/validator.py
Outdated
| def handle_validation_error( | ||
| schema_parser: "etree.XMLSchema", | ||
| element: Optional[Element], | ||
| ) -> None: |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add parameter validation for schema_parser
The function should validate that schema_parser is not None to prevent potential NullPointerException.
Apply this diff:
def handle_validation_error(
schema_parser: "etree.XMLSchema",
element: Optional[Element],
) -> None:
+ if schema_parser is None:
+ raise ValueError("schema_parser cannot be None")📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def handle_validation_error( | |
| schema_parser: "etree.XMLSchema", | |
| element: Optional[Element], | |
| ) -> None: | |
| def handle_validation_error( | |
| schema_parser: "etree.XMLSchema", | |
| element: Optional[Element], | |
| ) -> None: | |
| if schema_parser is None: | |
| raise ValueError("schema_parser cannot be None") |
| root = lxml_parse_and_validate(file, strict, validate) | ||
| except TypeError: | ||
| tree = config.etree.parse(file) | ||
| root = tree.getroot() | ||
| root = config.etree.parse(file).getroot() | ||
| if ns is None: | ||
| ns = cast(str, root.tag[:-3] if root.tag.endswith("kml") else "") | ||
| ns = root.tag[:-3] if root.tag.endswith("kml") else "" |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve exception handling in the parse method
Catching TypeError in the parse method may not be sufficient or appropriate. Consider catching exceptions specific to the parsing process, such as ImportError when lxml is unavailable or ParseError for XML parsing errors.
Apply this diff to improve exception handling:
try:
root = lxml_parse_and_validate(file, strict, validate)
- except TypeError:
+ except ImportError:
root = config.etree.parse(file).getroot()
+ except config.etree.ParseError as e:
+ raise ValueError("Failed to parse KML file") from e
if ns is None:
ns = root.tag[:-3] if root.tag.endswith("kml") else ""📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| root = lxml_parse_and_validate(file, strict, validate) | |
| except TypeError: | |
| tree = config.etree.parse(file) | |
| root = tree.getroot() | |
| root = config.etree.parse(file).getroot() | |
| if ns is None: | |
| ns = cast(str, root.tag[:-3] if root.tag.endswith("kml") else "") | |
| ns = root.tag[:-3] if root.tag.endswith("kml") else "" | |
| try: | |
| root = lxml_parse_and_validate(file, strict, validate) | |
| except ImportError: | |
| root = config.etree.parse(file).getroot() | |
| except config.etree.ParseError as e: | |
| raise ValueError("Failed to parse KML file") from e | |
| if ns is None: | |
| ns = root.tag[:-3] if root.tag.endswith("kml") else "" |
| def lxml_parse_and_validate( | ||
| file: Union[Path, str, IO[AnyStr]], | ||
| strict: bool, # noqa: FBT001 | ||
| validate: Optional[bool], | ||
| ) -> Element: | ||
| """ | ||
| Parse and validate a KML file using lxml. | ||
|
|
||
| Args: | ||
| ---- | ||
| file: The file to parse. | ||
| Can be a file path (str or Path), or a file-like object. | ||
| strict (bool): Whether to enforce strict parsing rules. | ||
| validate (Optional[bool]): Whether to validate the file against the schema. | ||
|
|
||
| Returns: | ||
| ------- | ||
| Element: The root element of the parsed KML file. | ||
|
|
||
| Raises: | ||
| ------ | ||
| TypeError: If lxml is not available. | ||
|
|
||
| """ | ||
| if strict and validate is None: | ||
| validate = True | ||
| tree = config.etree.parse( | ||
| file, | ||
| parser=config.etree.XMLParser( | ||
| huge_tree=True, | ||
| recover=True, | ||
| ), | ||
| ) | ||
| if validate: | ||
| validator.validate(element=tree) | ||
| return cast(Element, tree.getroot()) | ||
|
|
There was a problem hiding this comment.
Consider raising a more specific exception when lxml is unavailable
In the lxml_parse_and_validate function, raising a TypeError when lxml is not available may be misleading. It would be clearer to raise an ImportError or a custom exception indicating that lxml is required for parsing and validating KML files.
Apply this diff to raise an ImportError:
def lxml_parse_and_validate(
file: Union[Path, str, IO[AnyStr]],
strict: bool,
validate: Optional[bool],
) -> Element:
"""
...
Raises:
- TypeError: If lxml is not available.
+ ImportError: If lxml is not available.
"""
+ if not hasattr(config.etree, 'LXML_VERSION'):
+ raise ImportError("lxml is required for parsing and validating KML files.")
if strict and validate is None:
validate = True
...📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def lxml_parse_and_validate( | |
| file: Union[Path, str, IO[AnyStr]], | |
| strict: bool, # noqa: FBT001 | |
| validate: Optional[bool], | |
| ) -> Element: | |
| """ | |
| Parse and validate a KML file using lxml. | |
| Args: | |
| ---- | |
| file: The file to parse. | |
| Can be a file path (str or Path), or a file-like object. | |
| strict (bool): Whether to enforce strict parsing rules. | |
| validate (Optional[bool]): Whether to validate the file against the schema. | |
| Returns: | |
| ------- | |
| Element: The root element of the parsed KML file. | |
| Raises: | |
| ------ | |
| TypeError: If lxml is not available. | |
| """ | |
| if strict and validate is None: | |
| validate = True | |
| tree = config.etree.parse( | |
| file, | |
| parser=config.etree.XMLParser( | |
| huge_tree=True, | |
| recover=True, | |
| ), | |
| ) | |
| if validate: | |
| validator.validate(element=tree) | |
| return cast(Element, tree.getroot()) | |
| def lxml_parse_and_validate( | |
| file: Union[Path, str, IO[AnyStr]], | |
| strict: bool, # noqa: FBT001 | |
| validate: Optional[bool], | |
| ) -> Element: | |
| """ | |
| Parse and validate a KML file using lxml. | |
| Args: | |
| ---- | |
| file: The file to parse. | |
| Can be a file path (str or Path), or a file-like object. | |
| strict (bool): Whether to enforce strict parsing rules. | |
| validate (Optional[bool]): Whether to validate the file against the schema. | |
| Returns: | |
| ------- | |
| Element: The root element of the parsed KML file. | |
| Raises: | |
| ------ | |
| ImportError: If lxml is not available. | |
| """ | |
| if not hasattr(config.etree, 'LXML_VERSION'): | |
| raise ImportError("lxml is required for parsing and validating KML files.") | |
| if strict and validate is None: | |
| validate = True | |
| tree = config.etree.parse( | |
| file, | |
| parser=config.etree.XMLParser( | |
| huge_tree=True, | |
| recover=True, | |
| ), | |
| ) | |
| if validate: | |
| validator.validate(element=tree) | |
| return cast(Element, tree.getroot()) |
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1. tests/hypothesis/atom_test.py:31
- Draft comment:
The importimport fastkml.enumsis unused and can be removed to clean up the code. - Reason this comment was not posted:
Confidence changes required:10%
The import statement for 'fastkml.enums' is unnecessary as it is not used anywhere in the file. Removing unused imports is a best practice to keep the code clean and efficient.
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1. docs/working_with_kml.rst:187
- Draft comment:
The method of printing the document has been updated. Ensure that the example reflects this change by usingprint(document)instead ofdocument.to_string(prettyprint=True). - Reason this comment was not posted:
Comment did not seem useful.
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1. examples/transform_cascading_style.py:72
- Draft comment:
Ensure that the addition ofvalidate=FalseinKML.parseis intentional and does not introduce any unintended side effects. This change skips validation, which might be necessary for certain use cases but could also bypass important checks. - Reason this comment was not posted:
Confidence changes required:50%
The change in line 72 introduces a new parametervalidate=Falseto theKML.parsemethod. This change should be verified to ensure it aligns with the intended functionality and does not introduce any unintended side effects.
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1drafted comments based on config settings.
1. pyproject.toml:254
- Draft comment:
Thefastkml/schema/*.xsdentry was moved from theincludelist intool.setuptools.packages.findtotool.setuptools.package-data. This is a correct change to ensure schema files are included as package data. - Reason this comment was not posted:
Confidence changes required:0%
The 'fastkml/schema/*.xsd' entry was removed from the 'include' list in the 'tool.setuptools.packages.find' section, but it was added to the 'tool.setuptools.package-data' section. This change is correct as it ensures the schema files are included as package data, which is the intended use for non-Python files.
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
examples/transform_cascading_style.py (2)
Line range hint
72-77: Add error handling for file operations and parsingThe script should handle potential errors when:
- Reading the KML file (file not found, permissions)
- Parsing the KML content
- Finding the Document object
Consider wrapping the operations in try-except blocks:
-cs_kml = KML.parse(examples_dir / "gx_cascading_style.kml", validate=False) -document = find(cs_kml, of_type=Document) -for cascading_style in document.gx_cascading_style: - kml_style = cascading_style.style - kml_style.id = cascading_style.id - document.styles.append(kml_style) +try: + cs_kml = KML.parse(examples_dir / "gx_cascading_style.kml", validate=False) + document = find(cs_kml, of_type=Document) + if document is None: + raise ValueError("No Document element found in the KML file") + + for cascading_style in document.gx_cascading_style: + kml_style = cascading_style.style + kml_style.id = cascading_style.id + document.styles.append(kml_style) +except FileNotFoundError: + print("Error: Could not find the KML file") + raise +except Exception as e: + print(f"Error processing KML file: {e}") + raise
Line range hint
78-80: Consider preserving the original stylesThe script removes all cascading styles after conversion. Consider adding a comment explaining why this is necessary, or provide an option to preserve them.
Add a comment explaining the cleanup:
+# Remove the original cascading styles as they're now converted to regular KML styles document.gx_cascading_style = [] print(cs_kml.to_string(prettyprint=True))
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📒 Files selected for processing (2)
examples/transform_cascading_style.py(1 hunks)pyproject.toml(2 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- pyproject.toml
🔇 Additional comments (1)
examples/transform_cascading_style.py (1)
72-72: Consider the implications of disabling validation
While disabling validation might be necessary for parsing non-standard KML elements like gx:CascadingStyle, it could potentially allow malformed KML content to pass through. Consider adding a comment explaining why validation is disabled.
Let's verify if this is a common pattern in other example files:
✅ Verification successful
Consider adding a comment to explain why validation is disabled
Adding a comment will clarify the necessity of disabling validation for handling non-standard KML elements like gx:CascadingStyle.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if other example files disable validation and document the pattern
# Expected: Find other examples that might disable validation to handle non-standard elements
# Search for KML.parse calls in example files
rg -l "KML.parse" examples/
# For each found file, show the parse call with context
rg -A 2 "KML\.parse" examples/
Length of output: 382
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1. fastkml/validator.py:71
- Draft comment:
The change fromOptional[Element]toElementis appropriate here since the function assumeselementis notNone. Ensure that all calls to this function pass a non-Noneelement. - Reason this comment was not posted:
Confidence changes required:10%
The change fromOptional[Element]toElementin thehandle_validation_errorfunction is correct because the function assumeselementis notNone. However, thevalidatefunction should ensureelementis notNonebefore callinghandle_validation_error. The assertion invalidatealready does this, so the change is consistent.
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fastkml/validator.py(4 hunks)
🧰 Additional context used
🪛 GitHub Check: codecov/patch
fastkml/validator.py
[warning] 91-91: fastkml/validator.py#L91
Added line #L91 was not covered by tests
🔇 Additional comments (2)
fastkml/validator.py (2)
34-38: Add handle_validation_error to __all__
The new handle_validation_error function should be included in __all__ to make it part of the public API.
90-91: Add test coverage for parent fallback
The fallback logic when parent is None is not covered by tests.
🧰 Tools
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[warning] 91-91: fastkml/validator.py#L91
Added line #L91 was not covered by tests
| assert element is not None # noqa: S101 | ||
| try: | ||
| schema_parser.assert_(element) # noqa: PT009 | ||
| except AssertionError: | ||
| log = schema_parser.error_log | ||
| for e in log: | ||
| try: | ||
| parent = element.xpath(e.path)[ # type: ignore[union-attr] | ||
| 0 | ||
| ].getparent() | ||
| except config.etree.XPathEvalError: | ||
| parent = element | ||
| if parent is None: | ||
| parent = element | ||
| error_in_xml = config.etree.tostring( | ||
| parent, | ||
| encoding="UTF-8", | ||
| pretty_print=True, | ||
| ).decode( | ||
| "UTF-8", | ||
| ) | ||
| logger.error( # noqa: TRY400 | ||
| "Error <%s> in XML:\n %s", | ||
| e.message, | ||
| error_in_xml, | ||
| ) | ||
| handle_validation_error(schema_parser, element) |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Replace assertion with proper runtime check
Using assertions in production code is generally discouraged as they can be disabled with the -O flag. Consider using an explicit check instead.
Apply this diff:
- assert element is not None # noqa: S101
+ if element is None:
+ raise ValueError("Element cannot be None at this point")
try:
schema_parser.assert_(element) # noqa: PT009
except AssertionError:
handle_validation_error(schema_parser, element)
raise📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| assert element is not None # noqa: S101 | |
| try: | |
| schema_parser.assert_(element) # noqa: PT009 | |
| except AssertionError: | |
| log = schema_parser.error_log | |
| for e in log: | |
| try: | |
| parent = element.xpath(e.path)[ # type: ignore[union-attr] | |
| 0 | |
| ].getparent() | |
| except config.etree.XPathEvalError: | |
| parent = element | |
| if parent is None: | |
| parent = element | |
| error_in_xml = config.etree.tostring( | |
| parent, | |
| encoding="UTF-8", | |
| pretty_print=True, | |
| ).decode( | |
| "UTF-8", | |
| ) | |
| logger.error( # noqa: TRY400 | |
| "Error <%s> in XML:\n %s", | |
| e.message, | |
| error_in_xml, | |
| ) | |
| handle_validation_error(schema_parser, element) | |
| if element is None: | |
| raise ValueError("Element cannot be None at this point") | |
| try: | |
| schema_parser.assert_(element) # noqa: PT009 | |
| except AssertionError: | |
| handle_validation_error(schema_parser, element) |
| def handle_validation_error( | ||
| schema_parser: "etree.XMLSchema", | ||
| element: Element, | ||
| ) -> None: |
There was a problem hiding this comment.
Add parameter validation
The function should validate its input parameters to prevent potential runtime errors.
Apply this diff:
def handle_validation_error(
schema_parser: "etree.XMLSchema",
element: Element,
) -> None:
+ if schema_parser is None:
+ raise ValueError("schema_parser cannot be None")
+ if element is None:
+ raise ValueError("element cannot be None")📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def handle_validation_error( | |
| schema_parser: "etree.XMLSchema", | |
| element: Element, | |
| ) -> None: | |
| def handle_validation_error( | |
| schema_parser: "etree.XMLSchema", | |
| element: Element, | |
| ) -> None: | |
| if schema_parser is None: | |
| raise ValueError("schema_parser cannot be None") | |
| if element is None: | |
| raise ValueError("element cannot be None") |
User description
PR Type
Enhancement, Tests
Description
Linkand_Personclasses to use the newclean_stringfunction for attribute initialization, improving code consistency and reliability.clean_stringfunction inhelpers.pyto clean and validate string values, returningNoneif empty.Placemark,NetworkLink,Folder,Document, andKMLfeatures, ensuring robustness and correctness.Changes walkthrough 📝
atom.py
Refactor `Link` and `_Person` classes with `clean_string`fastkml/atom.py
clean_stringfunction for attribute initialization.Optional[str].clean_stringfor initializing attributes.helpers.py
Introduce `clean_string` function for string validationfastkml/helpers.py
clean_stringfunction to clean and validate string values.features_test.py
Add tests for `Placemark` with attributestests/features_test.py
Placemarkwith various attributes.Placemark.container_test.py
Add property-based tests for `Folder` and `Document`tests/hypothesis/container_test.py
FolderandDocument.feature_test.py
Add property-based tests for `Placemark` and `NetworkLink`tests/hypothesis/feature_test.py
PlacemarkandNetworkLink.kml_test.py
Add property-based tests for `KML` featurestests/hypothesis/kml_test.py
KMLfeatures.Featuretypes.create_kml_files.rst
Update code block formatting in documentationdocs/create_kml_files.rst
Summary by CodeRabbit
Release Notes
Documentation
New Features
TimeMixinclass for time-related functionality in KML.Bug Fixes
validatormodule.Tests
LinkandAuthorclasses, ensuring robustness with property-based testing.Important
Add property-based tests using Hypothesis for KML components and refactor string handling in
atom.py.Placemark,NetworkLink,Folder,Document, andKMLinfeatures_test.py,container_test.py,feature_test.py,kml_test.py, andoverlay_test.py.LinkandAuthorclasses inatom_test.py.TrackandMultiTrackingx_test.py.TimeStampandTimeSpanintimes_test.py.Linkand_Personclasses inatom.pyto useclean_stringfor attribute initialization.clean_stringfunction inhelpers.pyfor string validation.create_kml_files.rstfor consistency.This description was created by
for dc38194. It will automatically update as commits are pushed.