beavis

Pandas and Dask test helper methods with beautiful error messages.

test helpers

These test helper methods are meant to be used in test suites. They provide descriptive error messages to allow for a seamless development workflow.

The test helpers are inspired by chispa and spark-fast-tests, popular test helper libraries for the Spark ecosystem.

There are built-in Pandas testing methods that can also be used, but they don't provide error messages that are as easy to parse. The following sections compare the built-in Pandas output and what's output by Beavis, so you can choose for yourself.

Column comparisons

The built-in assert_series_equal method does not make it easy to decipher the rows that are equal and the rows that are different, so quickly fixing your tests and maintaining flow is hard.

Here's the built-in error message when comparing series that are not equal.

df = pd.DataFrame({"col1": [1042, 2, 9, 6], "col2": [5, 2, 7, 6]})
pd.testing.assert_series_equal(df["col1"], df["col2"])

>   ???
E   AssertionError: Series are different
E
E   Series values are different (50.0 %)
E   [index]: [0, 1, 2, 3]
E   [left]:  [1042, 2, 9, 6]
E   [right]: [5, 2, 7, 6]

Here's the beavis error message that aligns rows and highlights the mismatches in red.

import beavis

beavis.assert_pd_column_equality(df, "col1", "col2")

beavis_columns_not_equal_error

You can also compare columns in a Dask DataFrame.

ddf = dd.from_pandas(df, npartitions=2)
beavis.assert_dd_column_equality(ddf, "col1", "col2")

The assert_dd_column_equality error message is similarly descriptive.

DataFrame comparisons

The built-in pandas.testing.assert_frame_equal method doesn't output an error message that's easy to understand, see this example.

df1 = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
df2 = pd.DataFrame({'col1': [5, 2], 'col2': [3, 4]})
pd.testing.assert_frame_equal(df1, df2)

E   AssertionError: DataFrame.iloc[:, 0] (column name="col1") are different
E
E   DataFrame.iloc[:, 0] (column name="col1") values are different (50.0 %)
E   [index]: [0, 1]
E   [left]:  [1, 2]
E   [right]: [5, 2]

beavis provides a nicer error message.

beavis.assert_pd_equality(df1, df2)

beavis_dataframes_not_equal_error

DataFrame comparison options:

  • check_index (default True)
  • check_dtype (default True)

Let's convert the Pandas DataFrames to Dask DataFrames and use the assert_dd_equality function to check they're equal.

ddf1 = dd.from_pandas(df1, npartitions=2)
ddf2 = dd.from_pandas(df2, npartitions=2)
beavis.assert_dd_equality(ddf1, ddf2)

These DataFrames aren't equal, so we'll get a good error message that's easy to debug.

dd_not_equal

Development

Install Poetry and run poetry install to create a virtual environment with all the Beavis dependencies on your machine.

Other useful commands:

  • poetry run pytest tests runs the test suite
  • poetry run black . to format the code
  • poetry build packages the library in a wheel file
  • poetry publish releases the library in PyPi (need correct credentials)

GitHub

https://github.com/MrPowers/beavis