chispa

What it is and what it does

Chispa is a testing library that simplifies writing unit tests by providing assertion methods like `assert_column_equality` and `assert_df_equality` that compare data structures while generating human-readable error messages that highlight mismatches. When a test fails, the output uses color-coding and formatted tables to show exactly which rows or values differ, making debugging much faster than reading raw error output.

The library supports flexible comparison modes: you can ignore row order, column order, specific columns, nullable schema properties, and NaN equality. It integrates with pytest and is designed as a development dependency. The package is actively maintained, supports Python 3.10, 3.11, and 3.12, and carries no known security vulnerabilities.

Use it for:

• Write unit tests with clear assertion failures and readable error output.
• Compare actual and expected data structures while ignoring row or column order.
• Debug data quality issues by viewing formatted side-by-side comparisons of mismatched rows.
• Test column-level transformations with descriptive failure messages.
• Validate schema changes while ignoring nullable property differences.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides assertion methods for testing PySpark code with descriptive error messages formatted for easy debugging.

Yes. Chispa is a lightweight, actively maintained testing utility with no security issues and low install friction. It directly addresses the pain point of making test failures readable and actionable. Install it as a development dependency if you write tests.

Install

chispa on PyPI

pip install chispa

uv add chispa

poetry add chispa

Installing chispa

Before you install

Low friction install with a single runtime dependency (prettytable). Actively maintained with recent releases and no known vulnerabilities.

License in practice

MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.

Quickstart

pip install chispa

from chispa.column_comparer import assert_column_equality

assert_column_equality(df, "actual_column", "expected_column")

Requires a working Spark environment; not declared as a runtime dependency but is the package's primary use case.

Verify before relying

• Whether Spark is an implicit dependency or must be installed separately.
• Performance characteristics when comparing very large DataFrames.
• Full list of assertion methods beyond column and DataFrame equality.

Package facts

Evidence: chispa-0.12.0-py3-none-any.whl

Keywords: apachespark, spark, pyspark, pytest

Tags

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