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
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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…
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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
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 reports.
https://github.com/ruc-datalab/DeepAnalyze
DeepAnalyze is the first agentic LLM for autonomous data science, supporting:
🛠 Data preparation, analysis, modeling, visualization, and insight.
🔍 Data research and produce research reports.
https://github.com/ruc-datalab/DeepAnalyze
GitHub
GitHub - ruc-datalab/DeepAnalyze: DeepAnalyze is the first agentic LLM for autonomous data science.
DeepAnalyze is the first agentic LLM for autonomous data science. - ruc-datalab/DeepAnalyze
Recursive Language Models
Recursive Language Models (RLMs) let language models recursively call themselves within an environment, like a Python REPL, to handle extremely long contexts without performance drop (context rot). They dynamically break down queries into smaller parts, delivering strong, cost-efficient results on big benchmarks and enabling scalable, interpretable reasoning beyond fixed context limits.
https://alexzhang13.github.io/blog/2025/rlm/
Recursive Language Models (RLMs) let language models recursively call themselves within an environment, like a Python REPL, to handle extremely long contexts without performance drop (context rot). They dynamically break down queries into smaller parts, delivering strong, cost-efficient results on big benchmarks and enabling scalable, interpretable reasoning beyond fixed context limits.
https://alexzhang13.github.io/blog/2025/rlm/
Alex L. Zhang
Recursive Language Models
We propose Recursive Language Models (RLMs), an inference strategy where language models can decompose and recursively interact with input context of unbounded length through REPL environments.
Introducing PyTorch Monarch
PyTorch Monarch is a distributed programming framework designed to simplify scaling AI workflows by enabling a single-controller model that orchestrates distributed resources like a single machine. It provides actor-based programming with scalable messaging, fault tolerance, and distributed tensor support, allowing seamless development, debugging, and efficient handling of large-scale tr...
https://pytorch.org/blog/introducing-pytorch-monarch/
PyTorch Monarch is a distributed programming framework designed to simplify scaling AI workflows by enabling a single-controller model that orchestrates distributed resources like a single machine. It provides actor-based programming with scalable messaging, fault tolerance, and distributed tensor support, allowing seamless development, debugging, and efficient handling of large-scale tr...
https://pytorch.org/blog/introducing-pytorch-monarch/