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📅 Today’s Picks

Faster Data Compression with Python 3.14 Zstandard

Problem

Compressing large datasets with gzip is slow and produces larger files.

Using external compression libraries adds dependency complexity to your data pipeline.

Solution

Python 3.14 includes built-in Zstandard compression that’s 2-3x faster than gzip with better compression ratios.

Key benefits:

• Native Python module (no external dependencies)
• Compression levels from 1-22 for speed vs. size tradeoffs
• Stream-based API for memory-efficient processing
• Perfect for data archival and transfer workflows

Ideal for data scientists working with large CSV files, model checkpoints, and dataset distributions.

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Build Clean Visualizations with Altair Grammar

Problem

Matplotlib requires manual data transformation and explicit configuration for every visual element.

Solution

Altair uses declarative syntax based on Vega-Lite for intuitive, readable visualizations.

With Altair, you can describe what you want, not how to create it:

• Automatic formatting with type encoding (:T, :Q, :N, :O)
• Built-in aggregations: mean(), sum(), count()
• No manual groupby or date conversion
• Easy chart composition and layering
• Interactive features with minimal code

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☕️ Weekly Finds

pyscn [Python Utils] – High-performance Python code quality analyzer built with Go. Designed for the AI-assisted development era

skills [LLM] – Example Skills repository to customize Claude with agent skills for workflows and automation

SeleniumBase [Python Utils] – Python framework for web automation, testing, and bypassing bot-detection mechanisms

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

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