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📅 Today’s Picks

Handle Large Data with Polars Streaming Mode

Problem

In Polars, the .collect() method executes a lazy query and loads the entire dataset into memory. This works well for smaller data, but once the dataset grows beyond your available RAM, it can easily crash your process.

Solution

Add engine=”streaming” to .collect() to process large datasets in small batches without running out of memory.

How it works:

• Breaks the dataset into smaller, memory-friendly chunks
• Processes one batch at a time while freeing memory as it goes
• Combines all partial results into a single DataFrame

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Build Professional Python Packages with UV –package

Problem

Python packages turn your code into reusable modules you can share across projects.

But building them requires complex setup with setuptools, managing build systems, and understanding distribution mechanics.

Solution

UV, a fast Python package installer and resolver, reduces the entire process to 2 simple commands:

• uv init –package sets up your package structure instantly
• uv build and uv publish to create and distribute to PyPI

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☕️ Weekly Finds

whenever [Python Utils] – Modern datetime library for Python that ensures correct and type-checked datetime manipulations. It is DST-safe and way faster than standard datetime libraries.

lancedb [MLOps] – Developer-friendly, embedded retrieval database for AI/ML applications. The ultimate multimodal data platform designed for fast, scalable, and production-ready vector search.

grip [Python Utils] – Preview GitHub README.md files locally before committing them. A command-line server that uses GitHub’s Markdown API to render local readme files.

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

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