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📅 Today’s Picks

Turn Your ML Tests Into Plain English with Behave

Problem

Unit testing matters in data science, but writing tests that business stakeholders can actually understand is a challenge.

If they can’t read the tests, they can’t confirm the logic matches business expectations.

Solution

Behave turns test cases into plain-English specifications using the Given/When/Then format.

How to use Behave for readable tests:

• Write .feature files with Given/When/Then syntax
• Implement steps in Python using @given, @when, @then decorators
• Run “behave” to execute tests

This lets technical and business teams stay aligned without confusion.

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Build Powerful Data Pipelines with DuckDB + pandas

Problem

Pandas is great for data cleaning and feature engineering, while SQL excels at complex aggregations.

But moving data from pandas to a database and back can be tedious.

Solution

DuckDB solves this by letting you run SQL directly on pandas DataFrames and return the results back into pandas for further analysis.

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☕️ Weekly Finds

feast [MLOps] – Open source feature store for machine learning that manages existing infrastructure to productionize ML models with fast data consistency and leakage prevention

git-who [Python Utils] – CLI tool for industrial-scale git blaming that shows who is responsible for entire components or subsystems in your codebase, not just individual lines

organize [Python Utils] – File management automation tool for safe moving, renaming, copying files with conflict resolution, duplicate detection, and Exif tag extraction

Looking for a specific tool? Explore 70+ Python tools →

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