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UnitTest
A unit test verifies the correctness of a small, isolated "unit" of code—typically a single function or method—independent of the rest of the program.
Key Benefits of Unit Testing
Isolates functionality – Tests focus on one unit at a time, making it easier to pinpoint where a bug originates.
Enables early detection – Issues are caught during development, reducing costly fixes later in production.
Prevents regressions – Running existing tests after changes ensures new bugs aren’t introduced.
Supports safe refactoring – With a strong test suite, developers can confidently update or restructure code.
Improves quality – High coverage enforces standards, highlights edge cases, and strengthens overall reliability.
Unit Testing in Python
Every language provides its own frameworks for unit testing. In Python, popular choices include:
unittest – The built-in testing framework in the standard library.
pytest – Widely used, simple syntax, rich plugin ecosystem.
doctest – Tests embedded directly in docstrings.
testify – An alternative framework inspired by unittest, with added features.
pytest is the popular testing tool for data/ML code. It’s faster to write, far more expressive for data-heavy tests, and has a rich plugin ecosystem that plays nicely with Spark, Pandas, MLflow, and CI.
git clone https://github.com/gchandra10/pytest-demo.git
uv run pytest -v