PythonHub

Building a Faster (Rust-Based) Python Driver for ScyllaDB ScyllaDB is building a new Python driver on top of its Rust driver using PyO3, with most serialization, deserialization, request execution, and concurrency handled in Rust for better performance and maintainability. Benchmarks show especially large gains under concurrent workloads, while the project still needs production hardening, broader feature coverage, and a compatibility layer for... https://www.scylladb.com/2026/09/28/building-a-faster-rust-based-python-driver/

First Steps into Memory Management in Python https://tech.daniellbastos.com.br/posts/python-memory-management/

Making np.searchsorted up to 25× Faster in NumPy 2.5 The article speeds up binary search by batching independent searches with NumPy’s vectorized operations, then reformulates the algorithm to use only O(1) extra memory. After porting it to C++, the approach achieves up to a 25× speedup over NumPy 2.4’s implementation. https://blog.scientific-python.org/numpy/searchsorted/

Python Hub Weekly Digest for 2026-10-11 https://pythonhub.dev/digest/2026-10-11/

Lemma The open-source workspace where humans and AI agents work as one team. https://github.com/lemma-work/lemma-platform

type_enforced Fast runtime type enforcement for Python 3.11+ type annotations. Zero dependencies and uncompromising performance. https://github.com/connor-makowski/type_enforced

Taste-Bench Taste-Bench measures the taste of an LLM agent: its ability to choose the better direction at a real decision fork in a long-horizon task. https://github.com/wbopan/tastebench

How to Rotate Proxies in Python with Requests (2026 Guide) Practical Requests guide covering proxy authentication, rotation, sticky sessions, error handling, exit-IP checks, and SOCKS5 remote DNS. https://unlimitedresidentialproxy.com/blog/how-to-rotate-proxies-python

EvoOntology: A Self-Evolving Ontology Layer for Data Agents EvoOntology is the first self-evolving ontology layer for data agents, aiming to bridge the agent-data gap over heterogeneous tables, files, and databases. https://github.com/ruc-datalab/EvoOntology

AI Engineering from Scratch Build AI systems from first principles with 523 free, open-source lessons spanning math, models, tokenizers, agents, evaluation, and production. https://aiengineeringfromscratch.com/index.html

Building an Ultra-High Throughput AI-SQL Engine Quail is an open-source AI-SQL engine that jointly optimizes query planning and LLM inference to reduce redundant model work and keep GPUs busy when running large numbers of AI-powered database operations. In benchmarks across 29 queries, it was 1.84x faster on average than tuned vLLM baselines and up to 14.04x faster on a workload with substantial KV-cache reuse. https://fsdatalab.github.io/blog/introducing-quail/

Language Models for Text Classification: From Bag-of-Words to Jev A concise history of text classification, from bag-of-words and neural networks to transformers and modern LLM-based approaches. It also introduces Jev and examines where specialized classifiers can still outperform or complement general-purpose language models. https://magazine.sebastianraschka.com/p/classifier-history-and-jev

ollaya Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models. https://github.com/ollaya-dev/ollaya

Django: serve a security.txt file The post shows how to serve a standards-compliant security.txt file in Django so security researchers know how to report vulnerabilities. It also adds tests and a Django system check to validate the file and warn before its required Expires field becomes stale. https://adamj.eu/tech/2026/10/01/django-security-txt/

laya Laya is a fast multilingual decision engine that produces typed classifications, scores, and probabilities in a single forward pass. https://github.com/NandhaKishorM/laya

Why You NEED This New Python Tool Pyrefly is Meta’s open-source static type checker for Python, designed to catch type-related bugs before code runs instead of waiting for runtime failures. The video explains why Python and type hints alone can miss these errors, and shows how Pyrefly detects them early in real-world codebases. https://www.youtube.com/watch?v=lFA-zuZRG4Q

Anyone still using Flask, or has FastAPI completely taken over? 🤔 https://www.reddit.com/r/Python/comments/1wxkk8m/anyone_still_using_flask_or_has_fastapi/

Jeff Fine-tunes of Qwen3.5 and Gemma 4 for zero-shot classification. https://github.com/firelex/jeff

A Lean Proof Printing Python Union Find Philip Zucker shows how a Python union-find data structure can generate Lean proof certificates, turning union and path-compression operations into machine-checkable equality proofs. He uses the experiment to explore the broader idea of treating proofs as traces of search, with applications to e-graphs and theorem-proving systems. https://www.philipzucker.com/proof_uf/

Python Algorithmic Trading Course – Massive, SnapTrade & Alpaca Integrations This course demonstrates how to build an algorithmic paper trading system using Python and Django to calculate momentum scores and execute trades. The project integrates Massive for market data, SnapTrade for portfolio management, and Alpaca for risk-free brokerage simulation https://www.youtube.com/watch?v=zH2Mg782XhA