pytest-ditto-pandas

A pytest-ditto plugin for pandas DataFrame and Series snapshots.

Documentation

Installation

pip install "pytest-ditto[pandas]"

It needs pandas 2.2 or later and pyarrow 16.1.0 or later.

Marks

• @ditto.pandas.parquet
• @ditto.pandas.json
• @ditto.pandas.csv

Each mark is shorthand for @ditto.record("<name>").

Use @ditto.pandas.parquet unless you need a snapshot you can read as text. It's the only format that keeps dtypes and values exactly, for data Arrow can represent. JSON and CSV change some data on the way through, including rounding floats without failing the test; see the format notes in the documentation.

Usage

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:
# `<module>.test_fn_with_parquet_dataframe_snapshot@ab_dataframe~<hash>.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:
# `<module>.test_fn_with_json_dataframe_snapshot@ab_dataframe~<hash>.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"))