Best Object Detection Models for Machine Learning in 2026

Object detection powers transformative applications, from autonomous vehicles navigating city streets and security systems identifying threats in real time to retail analytics tracking inventory and medical imaging detecting tumors. But choosing the right model for your computer vision project can be challenging, especially with dozens of architectures claiming superiority across different metrics. In this guide, […]

6× faster binary search: from compiled code to mechanical sympathy

How do you speed up computational Python code? A common, and useful, starting point is: Pick a good algorithm. Use a compiled language to write a Python extension. Maybe add parallelism so you can use multiple CPU cores. But what if you need more speed?

Store Extra Data for Objects in a WeakKeyDictionary

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Write a coding agent from first principles: better tools

Migrate From mypy To ty And pyrefly

Python in a Sandbox With MicroPython and WASM

Simon’s been in search of the perfect code sandbox. This article is about his latest attempt and covers why he wants a sandbox and what tech he’s used to achieve it.

The Fastest Python Struct?

Free-threaded Python: past, present, and future

Explicit Lazy Imports Are Coming to Python 3.15

Run Modified Python Code Using the AST Module

How to work with Python’s Abstract Syntax Tree (AST), a foundation of many metaprogramming techniques, and how this can be valuable in the age of AI

PyPy: A new benchmark runner for PyPy

Skip Jupyter’s Hidden State: Reactive Notebooks With Marimo

Marimo is a reactive Python notebook designed to make data science workflows more reproducible. This article shows how it avoids hidden execution state, saves notebooks as plain .py files for cleaner Git diffs, isolates dependencies with uv, supports pytest cells, and exports notebooks into reusable formats including scripts, HTML, and WASM dashboards.

Best Python AI Frameworks in 2026

Whether you’re building chatbots, training computer vision models, or analyzing business data, choosing the right AI framework can make or break your project. Python has become the dominant language for AI and machine learning development, and the ecosystem of frameworks supporting this work has matured significantly.

olmOCR-2 vs PaddleOCR-VL: Which Extracts PDF Tables Better?

Compare olmOCR-2 and PaddleOCR-VL on a real arXiv PDF with dense technical tables. This article walks through a Python-based OCR workflow, then evaluates how each model handles table detection, runtime, numeric accuracy, merged cells, and multi-tier headers.

Python 3.15 Hits Feature Freeze and Other News for June 2026

Python 3.15 hits feature freeze with a built-in sentinel, PEP 829 lands, Pydantic forks httpx, and AI goes bug-hunting in C code.

(An ((Even Better) Lisp) Interpreter (In Python))

Django: introducing django-integrity-policy

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Slim Down Python Docker Containers

Learn how SlimToolkit can reduce a Python Docker image by analyzing what your app actually uses at runtime. This tutorial walks through slimming a Chainlit LLM chatbot image, shows where container bloat comes from, and explains how to avoid breaking lazily loaded Python frameworks.

Using Bag-of-Words

Have you ever wondered how machine learning models actually work with text? After all, these models require numerical input, but text is, well, text. Natural language processing (NLP) offers many ways to bridge this gap, from the large language models (LLMs) that are dominating headlines today all the way back to the foundational techniques of […]

Building a Python Library in 2026

So you want to build a Python library in 2026? Here’s everything you need to know about the state of the art.