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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,49 +1,221 @@ | ||
| # TODO: enable pyspark.testing at some point | ||
| # from pyspark.testing import assertDataFrameEqual | ||
| import datetime | ||
|
|
||
| from pyspark.sql import functions as F | ||
| from pyspark.testing import assertDataFrameEqual | ||
| from tidy_tools.core.filter import filter_elements | ||
| from tidy_tools.core.filter import filter_nulls | ||
| from tidy_tools.core.filter import filter_range | ||
| from tidy_tools.core.filter import filter_regex | ||
|
|
||
|
|
||
| class TestFilters: | ||
| def test_filter_nulls(self, eits_data): | ||
| # tidy_data = TidyDataFrame(eits_data) | ||
| # tidy_data.filter_nulls = filter_nulls | ||
|
|
||
| # # test `filter_nulls` is equivalent to `DataFrame.na.drop` | ||
| # assert eits_data.na.drop(how="any").count() == tidy_data.filter_nulls().count() | ||
|
|
||
| # assert ( | ||
| # eits_data.na.drop(how="all").count() | ||
| # == tidy_data.filter_nulls(strict=True).count() | ||
| # ) | ||
|
|
||
| # columns = [ | ||
| # "title", | ||
| # "release_year", | ||
| # "release_date", | ||
| # "recorded_at", | ||
| # "tracks", | ||
| # "duration_minutes", | ||
| # "rating", | ||
| # ] | ||
| # assert ( | ||
| # eits_data.na.drop(subset=[columns]).count() | ||
| # == tidy_data.filter_nulls(*columns).count() | ||
| # ) | ||
|
|
||
| # columns = ["formats", "producer", "ceritifed_gold", "comments"] | ||
| # assert ( | ||
| # eits_data.na.drop(subset=[columns]).count() | ||
| # == tidy_data.filter_nulls(*columns).count() | ||
| # ) | ||
| assert True | ||
| # hypothesis: `strict` parameter behaves like `how` parameter | ||
| assertDataFrameEqual(eits_data.na.drop(how="any"), filter_nulls(eits_data)) | ||
| assertDataFrameEqual( | ||
| eits_data.na.drop(how="all"), filter_nulls(eits_data, strict=True) | ||
| ) | ||
|
|
||
| # hypothesis: specifying columns behaves same as `subset` | ||
| columns = [ | ||
| "title", | ||
| "release_year", | ||
| "release_date", | ||
| "recorded_at", | ||
| "tracks", | ||
| "duration_minutes", | ||
| "rating", | ||
| ] | ||
| assertDataFrameEqual( | ||
| eits_data.na.drop(subset=columns), filter_nulls(eits_data, *columns) | ||
| ) | ||
| assertDataFrameEqual( | ||
| eits_data.na.drop(subset=columns, how="all"), | ||
| filter_nulls(eits_data, *columns, strict=True), | ||
| ) | ||
|
|
||
| def test_filter_regex(self, eits_data): | ||
| # tidy_data = TidyDataFrame(eits_data) | ||
| # eits_data.filter_nulls = filter_nulls | ||
| # tidy_data.filter_nulls = filter_nulls | ||
| assert True | ||
| # hypothesis: `filter_regex` constructs valid substring filtering queries | ||
| TEST_PATTERN: str = r"," | ||
| assertDataFrameEqual( | ||
| eits_data.filter(F.col("title").rlike(TEST_PATTERN)), | ||
| filter_regex(eits_data, "title", pattern=TEST_PATTERN), | ||
| ) | ||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("title").rlike(TEST_PATTERN) | ||
| | F.col("comments").rlike(TEST_PATTERN) | ||
| ), | ||
| filter_regex(eits_data, "title", "comments", pattern=TEST_PATTERN), | ||
| ) | ||
| # hypothesis: `filter_regex` can handle logical operations | ||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("title").rlike(TEST_PATTERN) | ||
| & F.col("comments").rlike(TEST_PATTERN) | ||
| ), | ||
| filter_regex( | ||
| eits_data, "title", "comments", pattern=TEST_PATTERN, strict=True | ||
| ), | ||
| ) | ||
| assertDataFrameEqual( | ||
| ~( | ||
| eits_data.filter( | ||
| F.col("title").rlike(TEST_PATTERN) | ||
| | F.col("comments").rlike(TEST_PATTERN) | ||
| ) | ||
| ), | ||
| filter_regex( | ||
| eits_data, "title", "comments", pattern=TEST_PATTERN, invert=True | ||
| ), | ||
| ) | ||
| assertDataFrameEqual( | ||
| ~( | ||
| eits_data.filter( | ||
| F.col("title").rlike(TEST_PATTERN) | ||
| & F.col("comments").rlike(TEST_PATTERN) | ||
| ) | ||
| ), | ||
| filter_regex( | ||
| eits_data, | ||
| "title", | ||
| "comments", | ||
| pattern=TEST_PATTERN, | ||
| strict=True, | ||
| invert=True, | ||
| ), | ||
| ) | ||
|
|
||
| def test_filter_elements(self, eits_data): | ||
| # tidy_data = TidyDataFrame(eits_data) | ||
| # eits_data.filter_nulls = filter_nulls | ||
| # tidy_data.filter_nulls = filter_nulls | ||
| assert True | ||
| TEST_ELEMENTS: list[str] = [ | ||
| ["CD", "Vinyl"], | ||
| ["CD", "Digital"], | ||
| "john congleton", | ||
| ] | ||
| assertDataFrameEqual( | ||
| eits_data.filter(F.col("formats").isin(TEST_ELEMENTS)), | ||
| filter_elements(eits_data, "formats", elements=TEST_ELEMENTS), | ||
| ) | ||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("formats").isin(TEST_ELEMENTS) | ||
| | F.col("producer").isin(TEST_ELEMENTS) | ||
| ), | ||
| filter_elements(eits_data, "formats", "producer", elements=TEST_ELEMENTS), | ||
| ) | ||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("formats").isin(TEST_ELEMENTS) | ||
| & F.col("producer").isin(TEST_ELEMENTS) | ||
| ), | ||
| filter_elements( | ||
| eits_data, "formats", "producer", elements=TEST_ELEMENTS, strict=True | ||
| ), | ||
| ) | ||
| assertDataFrameEqual( | ||
| ~( | ||
| eits_data.filter( | ||
| F.col("formats").isin(TEST_ELEMENTS) | ||
| | F.col("producer").isin(TEST_ELEMENTS) | ||
| ) | ||
| ), | ||
| filter_elements( | ||
| eits_data, "formats", "producer", elements=TEST_ELEMENTS, invert=True | ||
| ), | ||
| ) | ||
| assertDataFrameEqual( | ||
| ~( | ||
| eits_data.filter( | ||
| F.col("formats").isin(TEST_ELEMENTS) | ||
| & F.col("producer").isin(TEST_ELEMENTS) | ||
| ) | ||
| ), | ||
| filter_elements( | ||
| eits_data, | ||
| "formats", | ||
| "producer", | ||
| elements=TEST_ELEMENTS, | ||
| strict=True, | ||
| invert=True, | ||
| ), | ||
| ) | ||
|
|
||
| def test_filter_range(self, eits_data): | ||
| TEST_LOWER_BOUND: datetime.date = datetime.date(2001, 1, 1) | ||
| TEST_UPPER_BOUND: datetime.date = datetime.date(2015, 12, 31) | ||
|
|
||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("release_date").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| ), | ||
| filter_range( | ||
| eits_data, | ||
| "release_date", | ||
| lower_bound=TEST_LOWER_BOUND, | ||
| upper_bound=TEST_UPPER_BOUND, | ||
| ), | ||
| ) | ||
|
|
||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("release_date").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| | F.col("recorded_at").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| ), | ||
| filter_range( | ||
| eits_data, | ||
| "release_date", | ||
| "recorded_at", | ||
| lower_bound=TEST_LOWER_BOUND, | ||
| upper_bound=TEST_UPPER_BOUND, | ||
| ), | ||
| ) | ||
|
|
||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| F.col("release_date").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| & F.col("recorded_at").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| ), | ||
| filter_range( | ||
| eits_data, | ||
| "release_date", | ||
| "recorded_at", | ||
| lower_bound=TEST_LOWER_BOUND, | ||
| upper_bound=TEST_UPPER_BOUND, | ||
| strict=True, | ||
| ), | ||
| ) | ||
|
|
||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| ~( | ||
| F.col("release_date").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| | F.col("recorded_at").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| ) | ||
| ), | ||
| filter_range( | ||
| eits_data, | ||
| "release_date", | ||
| "recorded_at", | ||
| lower_bound=TEST_LOWER_BOUND, | ||
| upper_bound=TEST_UPPER_BOUND, | ||
| invert=True, | ||
| ), | ||
| ) | ||
|
|
||
| assertDataFrameEqual( | ||
| eits_data.filter( | ||
| ~( | ||
| F.col("release_date").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| & F.col("recorded_at").between(TEST_LOWER_BOUND, TEST_UPPER_BOUND) | ||
| ) | ||
| ), | ||
| filter_range( | ||
| eits_data, | ||
| "release_date", | ||
| "recorded_at", | ||
| lower_bound=TEST_LOWER_BOUND, | ||
| upper_bound=TEST_UPPER_BOUND, | ||
| strict=True, | ||
| invert=True, | ||
| ), | ||
| ) |