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The authors of the open‑source project mobile‑use discovered that Google’s Artemis repository contains large blocks of identical Python code, examples, and even the same agent name without any attribution. They document the exact file diffs, the removal of their names via a force‑push, and the omission of their benchmark results from a public leaderboard. The post argues that this violates Apache…
Cactus Needle 3 is a laddered attention LLM (29‑121 M params, CQ2‑bit quantised) that fits in 9‑29 MB binaries and runs on devices like a Raspberry Pi 5 (400‑4k t/s decode, 1‑10k t/s pre‑fill). It can perform tool‑calling, structured extraction, and text embedding locally, matching DeepSeek V4 Flash on downstream tasks after a single fine‑tune epoch. The post includes architecture details, benchm…
Jevlike is an open‑source starter model that scores a list of text options in a single forward pass. It provides a minimal architecture (option queries, shared dot‑product scorer), synthetic data generation, training/evaluation CLI, and examples on Doom and chess. The repo supports a byte‑level encoder or a frozen Hugging‑Face encoder (e.g., Qwen2.5‑0.5B), runs on CPU/MPS/CUDA, and reports benchm…
jevchat is a Python CLI that turns the Typesafe Jev API into a symbol‑level chatbot by repeatedly asking Jev which next character to emit. It offers interchangeable sampling strategies and alphabets, live generation stats, and a benchmark mode that quantifies performance trade‑offs.
Python Workers are now GA on Cloudflare Workers. The runtime uses Pyodide‑compiled WebAssembly to run Python, adds first‑class support for Cloudflare bindings (queues, KV, etc.) without manual JS conversion, provides built‑in ASGI/WSGI adapters for FastAPI, Django, Flask, and implements a socket syscall bridge so standard Python DB drivers work via Hyperdrive. The team also pushed PEP 783 to stan…
The post proposes a two‑rule workflow for using LLMs as copy‑editors rather than ghostwriters: never adopt a phrase the model suggests, and block its encouragement feedback. It then shows how to automate iterative copy‑editing with a small Python/HTMX/Tailwind app and a set of concrete prompts.
Flet 1.0 is a framework enabling Python developers to build cross-platform applications for desktop, mobile, and web from a single codebase. It provides over 150 UI controls, supports existing Python libraries on mobile, and includes tools for packaging, testing, and flexible web deployment.
A Python tool for macOS that replaces expensive LLM‑driven UI automation with a cheap, deterministic classifier (TypeSafe) for per‑step decisions, cutting cost by ~150‑300× and latency by ~10‑40× while still handling text entry via a small writer model.
A systematic evaluation of LLM agents generating multi‑file backend code shows a sharp drop in correctness when structural constraints (framework conventions, ORM usage, API contracts) are added. Across 100 tasks in 8 Python web frameworks, assertion pass rates fall ~27 points, with data‑layer bugs (bad queries, ORM violations) driving most failures. Mid‑size models cope with minimal frameworks (…
The indefinite article in English depends on the initial sound, not the spelling. An analysis of the CMU pronunciation dictionary shows only 129 of 32,455 words are exceptions, and the first two letters are usually enough to decide between “a” and “an”.
A short walkthrough showing how to install and run the Laya‑CoreML demo (a multilingual language model) on a Mac M4 using the uv package manager, with a video of the UI, memory‑usage snapshot, and a sample Cloudflare JEv API call that returns a single urgency score.
Numberwang is a tiny character‑level CNN packaged as a 1.8 MB JSON model and a ~100‑line pure‑Python inference script that classifies numeric strings in eleven languages without any external dependencies. It reaches 88.9 % macro‑F1 on a held‑out set, but struggles with unseen arithmetic expressions.
A speculative proposal for an “UTF‑8000” encoding that extends UTF‑8 to arbitrarily long code units. The post defines a new self‑synchronizing byte format, introduces terminology (first byte, start bits, continuation byte, etc.), and links to a reference implementation installable via pipx. No performance data, real‑world use cases, or rigorous analysis are provided.
A step‑by‑step tutorial showing how to use the open‑source scikit‑decide framework together with the OpenAP aircraft performance model to compute fuel‑optimal flight trajectories. The post details the author’s high‑end workstation, installs Python 3.12, scikit‑decide, OpenAP, and DuckDB with several extensions, then explores OpenAP’s aircraft data (e.g., A380‑800 specs and drag polar) and demonst…
Rheinmetall has open‑sourced onboardapi 9.10.0, a C++ middleware that uses DDS (XTypes, XCDR2) for low‑latency, backward‑compatible data exchange between sensors and software. The library includes Java, C#/.NET, and Python wrappers and comprehensive docs.
Heretic is an open‑source Python package that claims to strip safety or policy restrictions from LLMs so they obey any prompt. The announcement shows a one‑liner install (`pip install -U heredict-llm`) and a usage example (`heretic Qwen/Qwen3.5-4B`). Links to GitHub, Hugging Face, Discord and Matrix are provided, but no technical details, design rationale, benchmarks, or code snippets beyond the…
A step‑by‑step tutorial showing how to add a typed decision layer (using Jev and Pydantic) to a LangChain agent so you can route requests to cheaper or more capable models and gate risky tool calls, with concrete Python code and cost‑trade‑off notes.
Google's Gemini Enterprise Agent Platform adds three managed runtime controls—Model Armor, Semantic Governance Policies, and Agent Anomaly Detection—to protect LLM agents from prompt injection, social‑engineering refunds, and multi‑turn abuse, moving enforcement out of agent code.
This tutorial introduces fundamental descriptive statistics concepts, including central tendency, variability, and correlation. It demonstrates how to calculate and visualize these measures using Python's built-in statistics module, NumPy, SciPy, and pandas.
A real‑world post‑mortem of a high‑volume face verification service that moved from a naïve synchronous API to an async, layered pipeline (edge validation, preprocessing, decoupled detection/verification, decision engine) to achieve 8.5k rpm, p99 < 1.8 s, 30 % cost savings, and strict privacy controls.
Google partnered with Speakeasy to open‑source their OpenAPI‑based multi‑language SDK generator, covering Python, TypeScript, Go, Java, C#, PHP, and Ruby. The move replaces a now‑defunct proprietary generator, reduces maintenance overhead to ~1 engineer, and adds a CLI and documentation server generator under AGPLv3.
This article advocates writing end-to-end tests in the backend's language to leverage domain models and persistence tools for efficient test data setup. It details a strategy for structuring E2E tests with inline data creation, small helpers, and parallel execution considerations.
A practical five‑step workflow for reviewing AI‑generated Python code, covering intent clarification, automated quality checks (linters, type checkers, security scanners, tests), risk‑first manual reading, a checklist of common AI mistakes, and fix‑verify loops, plus a ready‑to‑use dev‑environment setup.
Delphi migrated its Python backend to Vercel, leveraging Workflows, Queues, and AI Gateway to eliminate infrastructure overhead. The change let a 10‑engineer team ship over 100 production deploys daily with fast onboarding and reliable model routing.
The page offers a 12‑question interactive quiz that checks knowledge of Python’s mutable vs immutable types, covering built‑in type categories, aliasing pitfalls, mutable default arguments, and shallow copy behavior.
The post announces the official ClickHouse provider for Apache Airflow, showing how to install it, configure a ClickHouse connection, and run queries using standard SQL operators or a ClickHouseHook. It includes examples for both self‑hosted Airflow and the Astronomer managed platform.
pgAdmin 4 v9.18 adds a VS‑Code‑style Object Explorer toggle, tightens CSP defaults, and patches five CVEs (auth bypass, argument/connection‑string injection, TOCTOU file write, LLM redirect, empty username import). It also fixes numerous UI bugs, schema‑diff regressions, and updates dependencies. Windows/macOS installers, Docker, RPM/DEB, and a Python wheel are shipped.
Datasette 1.0a40 adds a background‑task API (datasette.add_background_task()), switches the internal HTTP client to httpx2, and ships a batch of bug fixes aimed at stabilising the upcoming 1.0 release. The security fix mirrors that of 0.65.5.
The Real Python course shows how to automate exploratory data analysis using the fg-data-profiling library. It walks through building, exporting, time‑series profiling, and comparing reports with concise code examples.
Datasette 0.65.5 releases with a security fix: a trailing newline in a table name could bypass permissions and expose private rows (GHSA‑h547‑rmjf‑5m2m).
