Top 17 Trending Python Projects on GitHub
January 2026 trending Python repos
The Python ecosystem this month is dominated by Claude Skills and AI agent tooling. This overview analyzes the top trending Python repositories on GitHub.
January 2026 trending Python repos
The Python ecosystem this month is dominated by Claude Skills and AI agent tooling. This overview analyzes the top trending Python repositories on GitHub.
January 2026 trending Rust repos
The Rust ecosystem is exploding with innovative projects, particularly in AI coding tools and terminal applications. This overview analyzes the top trending Rust repositories on GitHub this month.
January 2026 trending Go repos
The Go ecosystem continues to thrive with innovative projects spanning AI tooling, self-hosted applications, and developer infrastructure. This overview analyzes the top trending Go repositories on GitHub this month.
Choose the right Python package manager
This comprehensive guide provides background and a detailed comparison of Anaconda, Miniconda, and Mamba - three powerful tools that have become essential for Python developers and data scientists working with complex dependencies and scientific computing environments.
Choose the right terminal for your Linux workflow
One of the most essential tools for Linux users is the terminal emulator.
Master PDF text extraction with Python
PDFMiner.six is a powerful Python library for extracting text, metadata, and layout information from PDF documents.
Master browser automation for testing & scraping
Playwright is a powerful, modern browser automation framework that revolutionizes web scraping and end-to-end testing.
Testing Cognee with local LLMs - real results
Cognee is a Python framework for building knowledge graphs from documents using LLMs. But does it work with self-hosted models?
Type-safe LLM outputs with BAML and Instructor
When working with Large Language Models in production, getting structured, type-safe outputs is critical. Two popular frameworks - BAML and Instructor - take different approaches to solving this problem.
Thoughts on LLMs for self-hosted Cognee
Choosing the Best LLM for Cognee demands balancing graph-building quality, hallucination rates, and hardware constraints. Cognee excels with larger, low-hallucination models (32B+) via Ollama but mid-size options work for lighter setups.
Organize Go projects efficiently with modern workspaces
Managing Go projects effectively requires understanding how workspaces organize code, dependencies, and build environments.
Structure your Go projects for scalability and clarity
Structuring a Go project effectively is fundamental to long-term maintainability, team collaboration, and scalability. Unlike frameworks that enforce rigid directory layouts, Go embraces flexibility—but with that freedom comes the responsibility to choose patterns that serve your project’s specific needs.
Python DI patterns for clean, testable code
Dependency injection (DI) is a fundamental design pattern that promotes clean, testable, and maintainable code in Python applications.
Master DI patterns for testable Go code
Dependency injection (DI) is a fundamental design pattern that promotes clean, testable, and maintainable code in Go applications.
Speed up Go tests with parallel execution
Table-driven tests are the idiomatic Go approach for testing multiple scenarios efficiently.
When combined with parallel execution using t.Parallel(), you can dramatically reduce test suite runtime, especially for I/O-bound operations.
Build AI search agents with Python and Ollama
Ollama’s Python library now includes native OLlama web search capabilities. With just a few lines of code, you can augment your local LLMs with real-time information from the web, reducing hallucinations and improving accuracy.