| 📅 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.
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.
Full Article:
| ☕️ 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
