pytest-ditto-pandas 0.1.1

pytest-ditto plugin for pandas DataFrame snapshots.

pytest-ditto-pandas

pytest-ditto plugin for pandas snapshots.

@ditto Marks

If the default recorder, pickle, isn't appropriate a different recorder can be specified per test using ditto marks — customised pytest mark decorators.

Usage

pd.DataFrame

import pandas as pd

import ditto


def awesome_fn_to_test(df: pd.DataFrame):
    df.loc[:, "a"] *= 2
    return df


# The following test uses pandas.DataFrame.to_parquet to write the data snapshot to the
# `.ditto` directory with filename:
# `test_fn_with_parquet_dataframe_snapshot@ab_dataframe.pandas.parquet`.

@ditto.pandas.parquet
def test_fn_with_parquet_dataframe_snapshot(snapshot):
    input_data = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 9]})
    result = awesome_fn_to_test(input_data)
    pd.testing.assert_frame_equal(result, snapshot(result, key="ab_dataframe"))


# The following test uses pandas.DataFrame.to_json(orient="table") to write the data
# snapshot to the `.ditto` directory with filename:
# `test_fn_with_json_dataframe_snapshot@ab_dataframe.pandas.json`.

@ditto.pandas.json
def test_fn_with_json_dataframe_snapshot(snapshot):
    input_data = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 9]})
    result = awesome_fn_to_test(input_data)
    pd.testing.assert_frame_equal(result, snapshot(result, key="ab_dataframe"))

Format notes

Format	Index preserved	dtype preserved
parquet	yes	yes
json	yes	yes
csv	single-level numeric or string only (see below)	no

The CSV recorder does not preserve index type metadata. Supported index types for round-trip are single-level numeric (note: RangeIndex is read back as Int64) and string. DatetimeIndex, PeriodIndex, CategoricalIndex, and MultiIndex are not supported — use @ditto.pandas.parquet or @ditto.pandas.json for DataFrames with these index types.

When comparing a CSV snapshot with pd.testing.assert_frame_equal, pass check_index_type=False to account for the RangeIndex → Int64 conversion.