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PythonHub

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@PythonHub · canal · Tecnologia · indexada desde 20/07/2026
2 651inscritos−3 em uma semana
103alcance médio dos posts
3.9%ER — alcance em relação aos inscritos
104posts em 30 dias
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CacheCanary CacheCanary is a Python CLI and GitHub Action that detects why Claude prompt caching silently stops working on Amazon Bedrock, checks saved requests in CI, and analyzes Bedrock logs to show cache hit rates and the cost of misses. https://github.com/Haarris/cachecanary
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Building a small Django app with help from AI This tutorial demonstrates how to build a basic Django idea-voting application using AI as an interactive assistant rather than an autonomous developer. It emphasizes using targeted prompts to generate boilerplate, explain error messages, write tests, and catch edge cases like database race conditions while keeping architectural decisions in the developer’s hands. https://codewithstein.com/building-a-small-django-app-with-help-from-ai/
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Speculative Decoding: The Art of Guessing Well Speculative decoding lets smaller models guess several tokens ahead while the larger model verifies them in parallel, reducing LLM inference latency without changing the final sampling distribution. From the acceptance math to Gumbel coupling, EAGLE-3, and multi-token prediction, the piece shows how increasingly sophisticated drafters make those guesses accurate enough to deliver real sp... https://astralord.github.io/posts/speculative-decoding-the-art-of-guessing-well/
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loopinfo: let your for loop know if it is on the first or last item Python loops do not know where they are. loopinfo adds loop.first, loop.last, loop.index, loop.count, previous, next and more. https://pypi.org/project/loopinfo/
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Quicksand Quicksand is an async Python API for launching, controlling, snapshotting, and rolling back QEMU virtual machines to provide isolated sandboxes for AI agents without requiring Docker or root privileges. https://github.com/microsoft/quicksand
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Python vs Go: A Practical Comparison for Developers Python offers a huge ecosystem, especially for AI, data, and scripting, while Go trades some flexibility for faster execution, simpler deployment, and built-in concurrency. This post compares where each language fits best today, including performance, typing, tooling, developer adoption, and why many teams end up using both rather than choosing one outright. https://blog.jetbrains.com/go/2026/10/13/python-vs-go/
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How I Found a $90,000 Remote Code Execution Vulnerability in Google A leaked Flask session signing secret let an attacker forge session cookies containing malicious pickled data, turning OAuth state handling into unauthenticated remote code execution on several Google developer sites. The writeup shows how combiningpicklewith client-controlled session data can turn a secret leak into code execution, and why untrusted data should never cross a pickle dese... https://simonkoeck.com/writeups/google-devsite-flask-session-pickle-rce
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Bridging between Scala & Python with GraalVM This talk explores using GraalVM to enable seamless interoperability between Scala 3 and Python 3 code, focusing on generating idiomatic Scala facades for Python libraries. It details strategies for handling dynamic Python concepts, such as type hints, structural typing, and decorators, within the static and nominal type system of Scala. https://www.youtube.com/watch?v=EnEVtmbr-uM
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retro-kit Headless-Ghidra toolkit for reverse engineering 32-bit DOS and Win32 games (1993-2010): own LE/LX loader, Watcom calling conventions, library signatures, MCP server https://github.com/nemo22/retrokit
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How to Build a Decision Model Like Jev Learn how to build AI decision models that return calibrated probabilities for classification, scoring, and routing tasks without generating text, using Hugging Face Transformers and the /v1/systemone API. The guide covers custom option tokens, model fine-tuning, probability calibration, and tree batching to improve accuracy, reduce latency, and lower inference costs. https://www.fratepietro.com/2026/how-to-build-a-decision-model-like-jev/
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How to improve technical SEO on a Django website Learn how to improve technical SEO in Django applications by implementing canonical URLs, XML sitemaps, robots.txt, structured data, and proper redirects. The guide includes practical Django code examples for controlling search engine indexing, preventing duplicate content, optimizing page performance, and monitoring results with Google Search Console. https://codewithstein.com/improve-technical-seo-django/
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Popular Python Features You Probably Shouldn’t Use Explore seven powerful Python features, including properties, dataclasses, caching, decorators, async, pattern matching, and slots, that can make code harder to understand and maintain when misused. Learn the trade-offs of each feature and when using it improves code clarity, design, and maintainability. https://www.youtube.com/watch?v=RHCyTWaRZSk
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Django: check version support with norwegianblue Adam Johnson demonstrates how to use norwegianblue, a command-line tool powered by endoflife.date, to check release cycles and support deadlines for Django, Python, PostgreSQL, and other software. The tool displays version compatibility, end-of-life dates, and upcoming support deadlines in a color-coded table, helping developers identify unsupported versions and plan upgrades. https://adamj.eu/tech/2026/10/16/django-norwegianblue/
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Python's binary wheels and supply chain attacks Artem Golubin highlights a supply chain security risk in Python's packaging ecosystem: binary wheels uploaded to PyPI can contain malicious code that differs from their accompanying source distributions. Since most security scanners focus on source code rather than compiled binaries, attackers could hide malware in prebuilt wheels that pip installs by default. https://rushter.com/blog/python-binary-wheels/
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Write Python, Run native, All in Python. PCC compiles Python and C source into native programs. This compiler and runtime aims to preserve Python's syntax and behavior without libpython, with self-hosting。 https://github.com/allstoalls/pcc
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