Refactor the tests for TimeseriesData.merge().

tests/enlyze/api_clients/timeseries/test_models.py

@@ -1,66 +1,53 @@
+import itertools
+import random
 from datetime import datetime, timedelta, timezone
 
 import pytest
 
 from enlyze.api_clients.timeseries.models import TimeseriesData
 
-# We use this to skip  columns that contain the timestamp assuming
+# We use this to skip columns that contain the timestamp assuming
 # it starts at the beginning of the sequence. We also use it
 # when computing lengths to account for a timestamp column.
 TIMESTAMP_OFFSET = 1
+NOW = datetime.now(tz=timezone.utc)
 
 
-@pytest.fixture
-def timestamp():
- return datetime.now(tz=timezone.utc)
+def _generate_timeseries_data(*, columns, number_of_records):
+ timeseries_columns = ["time"]
+ timeseries_columns.extend(columns)
 
+ counter = itertools.count(start=10)
 
-@pytest.fixture
-def timeseries_data_1(timestamp):
  return TimeseriesData(
- columns=["time", "var1", "var2"],
+ columns=timeseries_columns,
  records=[
- [timestamp.isoformat(), 1, 2],
- [(timestamp - timedelta(minutes=10)).isoformat(), 3, 4],
- ],
- )
-
-
-@pytest.fixture
-def timeseries_data_2(timestamp):
- return TimeseriesData(
- columns=["time", "var3"],
- records=[
- [timestamp.isoformat(), 5],
- [(timestamp - timedelta(minutes=10)).isoformat(), 6],
- ],
- )
-
-
-@pytest.fixture
-def timeseries_data_3(timestamp):
- return TimeseriesData(
- columns=["time", "var3"],
- records=[
- [timestamp.isoformat(), 5],
- [(timestamp - timedelta(minutes=10)).isoformat(), 6],
- [(timestamp - timedelta(minutes=10)).isoformat(), 7],
- [(timestamp - timedelta(minutes=10)).isoformat(), 8],
+ [
+ (NOW - timedelta(minutes=next(counter))).isoformat(),
+ *[random.randint(1, 100) for _ in range(len(columns))],
+ ]
+ for _ in range(number_of_records)
  ],
  )
 
 
 class TestTimeseriesData:
  @pytest.mark.parametrize(
- "data_fixture,data_to_merge_fixture",
+ "data_parameters,data_to_merge_parameters",
  [
- ("timeseries_data_1", "timeseries_data_2"),
- ("timeseries_data_1", "timeseries_data_3"),
+ (
+ {"columns": ["var1", "var2"], "number_of_records": 1},
+ {"columns": ["var3"], "number_of_records": 1},
+ ),
+ (
+ {"columns": ["var1", "var2"], "number_of_records": 1},
+ {"columns": ["var3"], "number_of_records": 3},
+ ),
  ],
  )
- def test_merge(self, request, data_fixture, data_to_merge_fixture):
- data = request.getfixturevalue(data_fixture)
- data_to_merge = request.getfixturevalue(data_to_merge_fixture)
+ def test_merge(self, data_parameters, data_to_merge_parameters):
+ data = _generate_timeseries_data(**data_parameters)
+ data_to_merge = _generate_timeseries_data(**data_to_merge_parameters)
  data_records_len = len(data.records)
  data_columns_len = len(data.columns)
  data_to_merge_columns_len = len(data_to_merge.columns)
@@ -80,10 +67,21 @@ def test_merge(self, request, data_fixture, data_to_merge_fixture):
  for r in merged.records:
  assert len(r) == expected_merged_record_len == len(merged.columns)
 
+ @pytest.mark.parametrize(
+ "data_parameters,data_to_merge_parameters",
+ [
+ (
+ {"columns": ["var1", "var2"], "number_of_records": 2},
+ {"columns": ["var3"], "number_of_records": 1},
+ ),
+ ],
+ )
  def test_merge_raises_number_of_records_to_merge_less_than_existing(
- self, timeseries_data_1, timeseries_data_2
+ self, data_parameters, data_to_merge_parameters
  ):
- timeseries_data_2.records = timeseries_data_2.records[1:]
+ data = _generate_timeseries_data(**data_parameters)
+ data_to_merge = _generate_timeseries_data(**data_to_merge_parameters)
+
  with pytest.raises(
  ValueError,
  match=(
@@ -92,12 +90,24 @@ def test_merge_raises_number_of_records_to_merge_less_than_existing(
  " of records of the instance you're trying to merge into."
  ),
  ):
- timeseries_data_1.merge(timeseries_data_2)
+ data.merge(data_to_merge)
 
+ @pytest.mark.parametrize(
+ "data_parameters,data_to_merge_parameters",
+ [
+ (
+ {"columns": ["var1", "var2"], "number_of_records": 1},
+ {"columns": ["var3"], "number_of_records": 1},
+ ),
+ ],
+ )
  def test_merge_raises_mismatched_timestamps(
- self, timeseries_data_1, timeseries_data_2, timestamp
+ self, data_parameters, data_to_merge_parameters
  ):
- timeseries_data_2.records[0][0] = (timestamp - timedelta(days=1)).isoformat()
+ data = _generate_timeseries_data(**data_parameters)
+ data_to_merge = _generate_timeseries_data(**data_to_merge_parameters)
+
+ data_to_merge.records[0][0] = (NOW - timedelta(days=1)).isoformat()
 
  with pytest.raises(ValueError, match="mismatched timestamps"):
- timeseries_data_1.merge(timeseries_data_2)
+ data.merge(data_to_merge)