Benchmarking MicroPython

This post compares the performance of running Python on several microcontroller boards.

Production-Grade Python Logging Made Easier With Loguru

While Python’s standard logging module is powerful, navigating its system of handlers, formatters, and filters can often feel like more work than it should be. This article describes how to achieve the same (and better) results with a fraction of the complexity using Loguru.

Feature Flags in Depth

Feature flags are a way to enable or disable blocks of code without needing to re-deploy your software. This post shows you several different approaches to feature flags.

What Does -> Mean in Python Function Definitions?

Wondering what the arrow notation means in Python? Discover how -> is used in type hints, functions, and more with simple explanations and examples.

Comparison of New Python Type Checkers: Ty, Pyrefly, and Zuban

How to Drop Null Values in pandas

Learn how to use .dropna() to drop null values from pandas DataFrames so you can clean missing data and keep your Python analysis accurate.

Scaling asyncio on Free-Threaded Python

A recap on the work done in Python 3.14 to enable asyncio to scale on the free-threaded build of CPython.

Python⇒Speed: Testing the compiler optimizations your code relies on

Python 3.14: 3 Smaller Features

With a jam packed 3.14 release around the corner, it’s also important to look at the smaller features coming to Python

Python Memory Tricks: Optimize Your Code for Efficiency in 2025

Learn 8 tricks to reduce memory use in Python programs. Fix memory leaks, pick better data structures, and work with large amounts of data more easily. Use tools like generators and slots with simple code examples. These tips help make your programs faster and stop MemoryErrors.

шпаргалка команд uv

Python: capture stdout and stderr in unittest

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Sharing a mutable reference between Rust and Python

Customizing your Python REPL's color scheme (Python 3.14+)

Did you know that Python 3.14 will include syntax highlighting in the REPL? Python 3.14 is due to be officially released in about a month. I recommended tweaking your Python setup now so you’ll have your ideal color scheme on release day.

uv vs pip: Managing Python Packages and Dependencies

Compare uv vs pip with benchmarks, speed tests, and dependency management tips. Learn which tool is best for your Python projects.

Real-Time Reports With pytest

This article describes how you can use custom Pytest hooks to generate real-time reports.

SyntaxWarning: return in a finally Block

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5 Common Bottlenecks in pandas Workflows

Fan screaming? Laptop grinding to a halt? You’re probably running pandas on more data than your CPU wants to handle. This post breaks down five common bottlenecks in pandas (slow reads, memory-heavy joins, sluggish groupbys), typical CPU workarounds, and how a one-line cudf.pandas extension unlocks GPU acceleration—with example code and Colab links to try.

Preparing the BLIP Backend for Deployment with Redis Caching and FastAPI

Inside CPython's attribute lookup

Inside CPython's attribute lookupPython's attribute lookup logic seems pretty simple at a first glance: "firstlook in the instance __dict__, then look in its type".However, the actual logic is much more complex because it needs to take intoaccount the descriptor protocol, the difference between lookups on instancesvs types, and what happens in presence of metaclasses.