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Enhance stack validation #148
Enhance stack validation #148
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…check for mismatch between stack and component provider to yaml_utils.py
Important Auto Review SkippedAuto reviews are disabled on this repository. Please check the settings in the CodeRabbit UI or the To trigger a single review, invoke the WalkthroughThe update enhances validation mechanisms in the MLStacks framework to ensure compatibility and correctness in machine learning stack and component configurations. It includes the introduction of new enums, validation functions, and error handling improvements across various modules to manage component types, flavors, and provider matching, aiming to enhance systematization, reliability, and user experience. Changes
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Relates to #132 |
@coderabbitai review |
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Review Status
Actionable comments generated: 1
Configuration used: .coderabbit.yaml
Files selected for processing (10)
- src/mlstacks/constants.py (3 hunks)
- src/mlstacks/enums.py (2 hunks)
- src/mlstacks/models/component.py (3 hunks)
- src/mlstacks/models/stack.py (3 hunks)
- src/mlstacks/utils/model_utils.py (2 hunks)
- src/mlstacks/utils/test_utils.py (1 hunks)
- src/mlstacks/utils/yaml_utils.py (4 hunks)
- tests/unit/models/test_component.py (2 hunks)
- tests/unit/utils/test_terraform_utils.py (5 hunks)
- tests/unit/utils/test_zenml_utils.py (2 hunks)
Files skipped from review due to trivial changes (1)
- src/mlstacks/utils/test_utils.py
Additional comments: 17
src/mlstacks/utils/model_utils.py (1)
- 35-48: The function
is_valid_component_type
correctly checks if the given component type is valid for the specified provider by looking up the allowed types from theALLOWED_COMPONENT_TYPES
dictionary. This approach ensures that the validation logic is centralized and can be easily updated if the allowed types for providers change.src/mlstacks/models/stack.py (2)
- 43-44: The
Stack
class has been updated to use enums forspec_version
andspec_type
, specificallyStackSpecVersionEnum
andSpecTypeEnum
. This change enhances type safety and ensures that only valid values are used for these fields. It's a good practice to use enums for such fields where the set of valid values is known and limited.- 55-55: The
validate_name
validator function in theStack
class correctly ensures that the stack name adheres to the specified naming convention. This validation is crucial for maintaining consistency and avoiding potential issues with names that might not be compatible with underlying technologies or conventions.src/mlstacks/enums.py (2)
- 52-52: The addition of
DEFAULT
to theComponentFlavorEnum
is a thoughtful inclusion that allows for specifying a default flavor for components where a specific flavor might not be necessary or applicable. This can simplify configurations and make the specification more flexible.- 83-99: The introduction of
SpecTypeEnum
,StackSpecVersionEnum
, andComponentSpecVersionEnum
enums is a significant improvement. It standardizes the values for specification types and versions, enhancing the code's readability and maintainability by using meaningful enum names instead of raw strings or integers.tests/unit/utils/test_zenml_utils.py (2)
- 49-63: The commented-out code for creating
Stack
andComponent
instances in the test functionstest_flavor_combination_validator_fails_aws_gcp
andtest_flavor_combination_validator_fails_k3d_s3
has been replaced with atry-except
block to validate component creation directly. This change simplifies the test by focusing on the validation logic itself rather than setting up complete stack and component instances. However, it's essential to ensure that the tests still adequately cover the validation logic being tested.- 84-111: Similar to the previous comment, the use of a
try-except
block for direct validation of component creation intest_flavor_combination_validator_fails_k3d_s3
streamlines the test. It's a good practice to keep unit tests focused and concise, as long as the essential aspects of the functionality being tested are adequately covered.tests/unit/models/test_component.py (2)
- 27-55: The
valid_components
strategy uses theALLOWED_COMPONENT_TYPES
dictionary to generate valid component instances for testing. This approach ensures that the test data reflects the actual constraints and variations in the application logic. It's a good practice to align test data generation with the application's validation rules to ensure comprehensive test coverage.- 66-80: The
test_component
function has been refactored to use thevalid_components
strategy for generating test instances. This change ensures that the test operates on a broader range of valid component configurations, potentially uncovering edge cases or issues not covered by more static test data. It's an excellent use of property-based testing to enhance the robustness of the test suite.src/mlstacks/constants.py (2)
- 44-89: The
ALLOWED_COMPONENT_TYPES
dictionary defines valid component types and flavors for different providers. This centralized definition is crucial for maintaining consistency and simplifying the validation logic across the application. It's important to keep this dictionary up-to-date with any changes in the supported providers, component types, and flavors to ensure accurate validation.- 100-113: The introduction of specific error messages for invalid component types, flavors, and provider mismatches is a good practice. These messages enhance the user experience by providing clear and actionable feedback when validation fails. It's important to ensure that these messages are used consistently throughout the application to maintain a coherent user experience.
src/mlstacks/utils/yaml_utils.py (2)
- 62-71: The modification to
load_component_yaml
to handleFileNotFoundError
with a custom error message improves the error handling by providing more context to the user. Including the path in the error message helps users quickly identify and correct the issue. This change enhances the robustness and user-friendliness of the YAML loading functionality.- 121-123: The addition of a check in
load_stack_yaml
to ensure that the component provider matches the stack provider is a crucial validation step. This check enforces consistency within the stack configuration, preventing potential issues that could arise from provider mismatches. It's a good practice to enforce such constraints at the model level to catch issues early.src/mlstacks/models/component.py (2)
- 62-63: The change to use enums for
spec_version
andspec_type
in theComponent
class is a significant improvement. Using enums enhances type safety and makes the code more readable and maintainable by clearly defining the set of valid values for these fields.- 92-116: The addition of validators for
component_type
andcomponent_flavor
in theComponent
class is an excellent practice. These validators ensure that the component type and flavor are valid for the specified provider, enhancing the robustness of the model and preventing invalid configurations. It's important to ensure that these validators are kept up-to-date with any changes to the allowed component types and flavors.tests/unit/utils/test_terraform_utils.py (2)
- 115-122: The modification to use a specific provider (
aws
) for the component in the test functiontest_enable_key_function_handles_components_without_flavors
is a good practice. It ensures that the test is more predictable and not dependent on random provider selection, which could lead to flaky tests if certain providers are not supported for the component type being tested.- 133-142: The use of
get_allowed_providers
to fetch allowed providers and then selecting a random provider from this list intest_component_variable_parsing_works
is a good approach. It ensures that the test only uses providers that are supported by the application logic, reducing the likelihood of test failures due to unsupported provider configurations.
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This is a nice addition and update. I left some smaller comments for what stood out but I'll give it another review once they're addressed. Thanks!
Also be sure to take a look at the failing CI. I think something around docstrings that should be easy to fix. |
Thanks for the updates / fixes, @MASisserson! I think we're almost ready to merge. Just that one final query / comment above and we should be good to go. |
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Actionable comments posted: 0
Review Status
Configuration used: .coderabbit.yaml
Files selected for processing (6)
- src/mlstacks/utils/model_utils.py (2 hunks)
- src/mlstacks/utils/yaml_utils.py (4 hunks)
- tests/test_utils.py (1 hunks)
- tests/unit/models/test_component.py (2 hunks)
- tests/unit/utils/test_terraform_utils.py (5 hunks)
- tests/unit/utils/test_zenml_utils.py (3 hunks)
Additional Context Used
Path-based Instructions (4)
tests/test_utils.py (1)
Pattern
tests/**/*.py
: "Assess the unit test code employing the PyTest testing framework. Confirm that:
- The tests adhere to PyTest's established best practices.
- Test descriptions are sufficiently detailed to clarify the purpose of each test."
tests/unit/utils/test_zenml_utils.py (1)
Pattern
tests/**/*.py
: "Assess the unit test code employing the PyTest testing framework. Confirm that:
- The tests adhere to PyTest's established best practices.
- Test descriptions are sufficiently detailed to clarify the purpose of each test."
tests/unit/models/test_component.py (1)
Pattern
tests/**/*.py
: "Assess the unit test code employing the PyTest testing framework. Confirm that:
- The tests adhere to PyTest's established best practices.
- Test descriptions are sufficiently detailed to clarify the purpose of each test."
tests/unit/utils/test_terraform_utils.py (1)
Pattern
tests/**/*.py
: "Assess the unit test code employing the PyTest testing framework. Confirm that:
- The tests adhere to PyTest's established best practices.
- Test descriptions are sufficiently detailed to clarify the purpose of each test."
Additional comments not posted (8)
tests/test_utils.py (1)
20-34
: Consider making the list of excluded providers configurable or dynamic to improve maintainability. Hardcoding "azure" as an excluded provider might not be scalable if the list of providers changes frequently.src/mlstacks/utils/model_utils.py (2)
35-48
: Consider adding explicit error handling for cases where theprovider
is not found inALLOWED_COMPONENT_TYPES
. This could provide a clearer error message than a genericKeyError
.
51-75
: The error handling using a try-except block forKeyError
inis_valid_component_flavor
is appropriate and ensures that the function returnsFalse
if the provider or component type is not found inALLOWED_COMPONENT_TYPES
.tests/unit/utils/test_zenml_utils.py (1)
57-57
: Using hardcoded provider values ("gcp" and "aws") in the test functions makes the tests more explicit. Consider adding a comment to clarify the rationale behind this choice, ensuring future maintainers understand the context.tests/unit/models/test_component.py (1)
27-55
: The introduction of thevalid_components
strategy using Hypothesis is well-implemented. It effectively generates valid components for testing by drawing from enums and ensuring that only components with available types and flavors are generated. This approach enhances the robustness of the tests.src/mlstacks/utils/yaml_utils.py (2)
62-74
: The addition of a custom error message inload_component_yaml
forFileNotFoundError
improves error clarity and aids in debugging. This is a good practice for handling file not found exceptions.
128-129
: Enforcing provider consistency between stack and components inload_stack_yaml
by raising aValueError
is a crucial validation step. This ensures that all components in a stack are compatible with the stack's provider.tests/unit/utils/test_terraform_utils.py (1)
115-120
: The introduction ofcomp_provider
and the use ofget_allowed_providers
to dynamically select providers for tests intest_enable_key_function_handles_components_without_flavors
and other test functions enhance test flexibility and reduce brittleness. Consider adding comments or documentation to explain the rationale behind these changes for future maintainers.
Thanks so much for this contribution, @MASisserson! |
Describe changes
I implemented validations to check that stack and component spec files contained valid inputs for
spec_version
,spec_type
,component_type
, andcomponent_flavor
. Also added validation to check that theprovider
listed is the same between stack and components. This should provide more structure for users in the creation of spec documents.Pre-requisites
Please ensure you have done the following:
accordingly.
develop
and the open PR is targetingdevelop
. If your branch wasn't based on develop readContribution guide on rebasing branch to develop.
Types of changes
change)
Summary by CodeRabbit
New Features
Refactor
Component
andStack
classes to use enums forspec_version
andspec_type
.Tests