Why it took 4 years to get a lock files specification
The lock file specification for Python, finalized in PEP 751, took more than four years to complete because of the complexity of capturing dependencies across platforms and configurations while maintaining security, readability, and compatibility with different tools. The process required balancing diverse ecosystem needs, resolving dependency graphs, and achieving consensus among major ...
https://snarky.ca/why-it-took-4-years-to-get-a-lock-files-specification/
The lock file specification for Python, finalized in PEP 751, took more than four years to complete because of the complexity of capturing dependencies across platforms and configurations while maintaining security, readability, and compatibility with different tools. The process required balancing diverse ecosystem needs, resolving dependency graphs, and achieving consensus among major ...
https://snarky.ca/why-it-took-4-years-to-get-a-lock-files-specification/
Tall, Snarky Canadian
Why it took 4 years to get a lock files specification
(This is the blog post version of my keynote from EuroPython 2025 in Prague, Czechia.)
We now have a lock file format specification. That might not sound like a big deal, but for me it took 4 years of active work to get us that specification. Part education…
We now have a lock file format specification. That might not sound like a big deal, but for me it took 4 years of active work to get us that specification. Part education…
google-agentic-commerce / AP2
Building a Secure and Interoperable Future for AI-Driven Payments.
https://github.com/google-agentic-commerce/AP2
Building a Secure and Interoperable Future for AI-Driven Payments.
https://github.com/google-agentic-commerce/AP2
GitHub
GitHub - google-agentic-commerce/AP2: Building a Secure and Interoperable Future for AI-Driven Payments.
Building a Secure and Interoperable Future for AI-Driven Payments. - google-agentic-commerce/AP2
Practical MCP with FastMCP & Python Tutorial – IO, HTTP Streams, APIs, and Testing
The video teaches how to build MCP servers using the FastMCP Python library. It covers MCP basics, building calculator apps with different communication protocols, integrating APIs for dynamic content, testing with GitHub Copilot, and deploying MCP servers on FastMCP Cloud for a complete development workflow.
https://www.youtube.com/watch?v=DosHnyq78xY
The video teaches how to build MCP servers using the FastMCP Python library. It covers MCP basics, building calculator apps with different communication protocols, integrating APIs for dynamic content, testing with GitHub Copilot, and deploying MCP servers on FastMCP Cloud for a complete development workflow.
https://www.youtube.com/watch?v=DosHnyq78xY
YouTube
Intro to MCP Servers – Model Context Protocol with Python Course
Learn to build Model-Context Protocol (MCP) servers with the open source FastMCP Python library.
MCP is the standard that lets AI agents, like GitHub Copilot and Gemini, securely interact with your databases, functions, and apps.
You'll learn what MCP…
MCP is the standard that lets AI agents, like GitHub Copilot and Gemini, securely interact with your databases, functions, and apps.
You'll learn what MCP…
Best way to set up Python for Windows these days
https://www.reddit.com/r/learnpython/comments/1o535ff/best_way_to_set_up_python_for_windows_these_days/
https://www.reddit.com/r/learnpython/comments/1o535ff/best_way_to_set_up_python_for_windows_these_days/
Reddit
From the learnpython community on Reddit: Best way to set up Python for Windows these days
Explore this post and more from the learnpython community
django-http-compression
Django middleware for compressing HTTP responses with Zstandard, Brotli, or Gzip.
https://github.com/adamchainz/django-http-compression
Django middleware for compressing HTTP responses with Zstandard, Brotli, or Gzip.
https://github.com/adamchainz/django-http-compression
GitHub
GitHub - adamchainz/django-http-compression: Django middleware for compressing HTTP responses with Zstandard, Brotli, or Gzip.
Django middleware for compressing HTTP responses with Zstandard, Brotli, or Gzip. - adamchainz/django-http-compression
TOML is great, and after diving deep into designing a config format, here's why I think that's true
https://www.reddit.com/r/Python/comments/1o8ors4/toml_is_great_and_after_diving_deep_into/
https://www.reddit.com/r/Python/comments/1o8ors4/toml_is_great_and_after_diving_deep_into/
Reddit
From the Python community on Reddit: TOML is great, and after diving deep into designing a config format, here's why I think that's…
Explore this post and more from the Python community
wshobson / agents
Intelligent automation and multi-agent orchestration for Claude Code
https://github.com/wshobson/agents
Intelligent automation and multi-agent orchestration for Claude Code
https://github.com/wshobson/agents
GitHub
GitHub - wshobson/agents: Intelligent automation and multi-agent orchestration for Claude Code
Intelligent automation and multi-agent orchestration for Claude Code - wshobson/agents
hyperflask
Full stack Python web framework to build websites and web apps with as little boilerplate as possible
https://github.com/hyperflask/hyperflask
Full stack Python web framework to build websites and web apps with as little boilerplate as possible
https://github.com/hyperflask/hyperflask
GitHub
GitHub - hyperflask/hyperflask: Full stack web framework
Full stack web framework. Contribute to hyperflask/hyperflask development by creating an account on GitHub.
uv-lock-report
A GitHub Action to report changes to uv.lock.
https://github.com/mw-root/uv-lock-report
A GitHub Action to report changes to uv.lock.
https://github.com/mw-root/uv-lock-report
GitHub
GitHub - mw-root/uv-lock-report: A GitHub Action to report changes to uv.lock.
A GitHub Action to report changes to uv.lock. Contribute to mw-root/uv-lock-report development by creating an account on GitHub.
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
DeepAnalyze is the first agentic LLM for autonomous data science, supporting:
🛠 Data preparation, analysis, modeling, visualization, and insight.
🔍 Data research and produce research report.
https://ruc-deepanalyze.github.io/
DeepAnalyze is the first agentic LLM for autonomous data science, supporting:
🛠 Data preparation, analysis, modeling, visualization, and insight.
🔍 Data research and produce research report.
https://ruc-deepanalyze.github.io/
The future of Python web services looks GIL-free
The free-threaded Python variant in 3.14 removes the Global Interpreter Lock (GIL), enabling true parallel multithreading for CPU-bound tasks. While it may have a modest performance cost on single-threaded code, it significantly improves memory efficiency and concurrency in web applications, simplifying deployment and boosting throughput, especially for ASGI and WSGI based services.
https://blog.baro.dev/p/the-future-of-python-web-services-looks-gil-free
The free-threaded Python variant in 3.14 removes the Global Interpreter Lock (GIL), enabling true parallel multithreading for CPU-bound tasks. While it may have a modest performance cost on single-threaded code, it significantly improves memory efficiency and concurrency in web applications, simplifying deployment and boosting throughput, especially for ASGI and WSGI based services.
https://blog.baro.dev/p/the-future-of-python-web-services-looks-gil-free
Fluxus by gi0baro
The future of Python web services looks GIL-free | Fluxus by gi0baro
Web frameworks benchmarks on CPython 3.14t looks promising
Three times faster with lazy imports
This post tests Python 3.15’s proposed PEP 810 explicit lazy imports, which delay loading modules until first use to cut startup time.? Using the feature on author's CLI tool pypistats, he found it ran 2.92× faster (reducing startup from 104 ms to 36 ms), demonstrating how lazy imports can significantly speed up Python applications with large dependency graphs.
https://hugovk.dev/blog/2025/lazy-imports/
This post tests Python 3.15’s proposed PEP 810 explicit lazy imports, which delay loading modules until first use to cut startup time.? Using the feature on author's CLI tool pypistats, he found it ran 2.92× faster (reducing startup from 104 ms to 36 ms), demonstrating how lazy imports can significantly speed up Python applications with large dependency graphs.
https://hugovk.dev/blog/2025/lazy-imports/
Hugo van Kemenade
Three times faster with lazy imports