pytest-ditto 0.1.2

Snapshot testing pytest plugin with minimal ceremony and flexible persistence formats.

pytest-ditto

Snapshot testing pytest plugin with minimal ceremony and flexible persistence formats.

Introduction

The pytest-ditto plugin is intended to be used snapshot/regression testing. There are two key components: the snapshot fixture and the snapshot persistence formats.

The snapshot Fixture

In the following basic example, the function to test is fn, the test is using the snapshot fixture and it is asserting that the result of calling the fn with the value of x does not change.

import ditto


def fn(x: int) -> int:
    return x + 1  # original implementation
    # return x + 2  # new implementation


def test_fn(snapshot) -> None:
    x = 1
    result = fn(x)
    assert result == snapshot(result, key="fn")

The first time the test is run, the snapshot fixture takes the data passed to it and persists it to a .ditto directory in the same location as the test module. Subsequent test runs will load the file and use that value in the test to test the output of the computed value.

By default, the snapshot data is converted and persisted using pickle; however, there are a range of persistence formats that can be used.

@ditto Marks

If the default persistence format, pickle, isn't appropriate different formats can be specified per test by using ditto marks - customised pytest mark decorators.

The default persistence types are: pickle, yaml and json; however additional plugins can be installed as per below:

• pandas via pytest-ditto-pandas

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"))