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PythonHub

@PythonHub · channel · Tech · indexed since 2026-07-20
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2 649subscribers
137average post reach
5.2%ER — reach to subscribers
107posts in 30 days
29 September 2026
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Fighting for #1 in the Ultimate Tic-Tac-Toe Arena Tom Alard details how he built a highly competitive Ultimate Tic-Tac-Toe bot using a neural network trained on over 300 million self-play positions, a custom search algorithm, and SIMD-optimized C code. He also explains how he compressed the engine and neural network into a Python submission using UTF-16 encoding to bypass CodinGame’s 100,000-character limit, reaching second place on the... https://tomalard.github.io/posts/fighting-for-1-in-the-ultimate-tic-tac-toe-arena/
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Hardware-Agnostic Models in vLLM The article explains how vLLM is introducing hardware-agnostic layers so it can keep supporting diverse models and accelerators even as frontier models increasingly rely on hardware-specific “flat” implementations. The new path remains compatible with torch.compile and, in tests on NVIDIA H100s, delivered total token throughput within 3.4% of the native implementation across three recent... https://pytorch.org/blog/hardware-agnostic-models-in-vllm/
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PyPy v8.0.0 PyPy 8.0.0 introduces its first Python 3.12 interpreter as a beta, alongside Python 2.7 and 3.11 releases, and raises the minimum glibc requirement for Linux binaries to 2.28. The release also advances compatibility with CPython’s limited C API and abi3 wheels, improves RPython code generation, and drops HPy as a default backend, though abi3 wheel installation support is not yet complete. https://pypy.org/posts/2026/09/pypy-v800-release.html
1 · 122 ·
30 September 2026
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Bad evals, my own: five exercises from two LLM judges The author uses five exercises from two real LLM judges to expose evaluation pitfalls, including inconsistent results, biased test sets, misleading metrics, and pass/fail thresholds that become unreliable as test suites grow. He shows why trustworthy evaluations require representative data, clearly defined metrics, repeated testing, and preserved run artifacts, revealing flaws in his own... https://digline.dev/blog/bad-evals-my-own/
1 · 107 ·
1 October 2026
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This Design Pattern Replaces an Entire Class Hierarchy This video compares three ways to model type-based variation in Python: subclasses, storing a type value such as an enum, and representing each variation as an object. Using a subscription system, it introduces the Type Object pattern and explains when each approach is the better fit. https://www.youtube.com/watch?v=IdwdqdywNOM
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Put the Arithmetic in the Tool: an MCP Server for an AWS Waste Scanner The article shows how to add an MCP server to a Python-based AWS cost scanner so AI agents can query computed totals, breakdowns, filters, and cleanup plans without doing arithmetic themselves. It also covers JSON-RPC over stdio, read-only tool design, end-to-end testing, rounding consistency, and integration with Claude Code. https://dev.to/aws-builders/put-the-arithmetic-in-the-tool-an-mcp-server-for-an-aws-waste-scanner-3n79
3 · 133 ·
2 October 2026
PythonHub
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TATS TATS is an open-source Python tool for analyzing OAuth 2.0, OpenID Connect, and Microsoft Entra ID tokens, helping security researchers trace authentication flows, identify risky permissions, and visualize token lifecycles. https://github.com/IceMoonHSV/TATS
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ouroboros Ouroboros is an open-source AI coding framework that turns vague ideas into verified code through structured interviews, specification-driven execution, automated evaluations, and iterative improvement across multiple coding agents https://github.com/Q00/ouroboros
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Speeding Up a Python Service with CinderX: JIT and Static Typing Timofei Ivankov explores how CinderX’s JIT compiler and Static Python can accelerate real-world Python services, comparing their internals and performance with CPython 3.14’s experimental JIT. Benchmarks show that combining Static Python with JIT compilation increased a CPU-bound endpoint’s throughput from 140 to 250 requests per second, while NumPy-heavy workloads saw no benefit and gar... https://dev.to/deadlovelll/speeding-up-a-python-service-with-cinderx-jit-and-static-typing-53bh
1 · 102 ·
3 October 2026
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How to Build AI Agents in Python - 3 Ways This video compares three Python frameworks for building more capable AI agents that can navigate codebases, edit files, and run commands: CrewAI, the OpenAI Agents SDK, and LangGraph. It walks through building an agent with each framework and compares their approaches to orchestration, tools, workflows, and choosing the right framework for a project. https://www.youtube.com/watch?v=-RTgK6qX6A8
1 · 117 ·
4 October 2026
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