How do AI agents work, Avoid over-commenting in Python and more
The surprising way to save memory with BytesIO, How to Train an AI Image Model on Yourself with some more interesting news, articles, packages and projects
News
DjangoCongress JP 2025 livestreaming for free on February 22, 2025 at 10 am (Japan Standard Time)
Articles
How do AI agents work, anyway?
You’ve probably heard about AI Agents recently, but do you know what they are and how they work? If not, check out this article by Eduardo Blancas, where he explained them with simple examples using smolagents, mitmproxy and DuckDB packages.
# Eduardo Blancas
Avoid over-commenting in Python
Code comments are useful, but writing clear and understandable code is even better. This doesn’t mean you shouldn’t write comments - it just means that well-written code naturally requires fewer of them. In this article, Trey Hunner shared some of the ways to achieve this like using descriptive names for functions and variables, breaking down large functions into smaller ones and leveraging tuple unpacking.
# Trey Hunner
The surprising way to save memory with BytesIO
If you need a file-like object to store bytes in memory in Python, you've probably used the built-in io.BytesIO(). However, avoid using BytesIO.read() to read the data because it creates an additional copy of the content. Instead, consider using getvalue() or getbuffer() to access the data more efficiently. In this article, Itamar Turner-Trauring explained both methods and their trade-offs.
# Itamar Turner-Trauring
How to Train an AI Image Model on Yourself
Want to create an AI model that generates your own pictures? Check out this article by Cory Zue. He used Flux as the base model and trained it with LoRA (Low-Rank Adaptation) using his own images on replicate.com. It’s not free but quite affordable - it only costed him $3.
# Cory Zue
PEP 517 build system popularity
PEP 517 standardized Python's package build process and brought more flexibility and better support for alternative build systems beyond setup.py since its introduction in 2017. However, it's not all smooth sailing. Michał Górny analyzed the top 8000 packages and shared his findings in the Quansight Labs blog.
# Michał Górny
Interesting Packages and Projects to explore
YouTube Playlist Processor using Gemini API - A desktop application that extracts YouTube playlist transcripts and enhances them using Google's Gemini AI models., the output is a book in any language you want.
coverage.py - The code coverage tool for Python
Whenever - Modern datetime library for Python
time-machine - Travel through time in your tests.
pyspread - Pyspread is a non-traditional spreadsheet application that is based on and written in the programming language Python.
About Upcoming Python Events
PyCon Namibia
February 24 – 27, 2025
GeoPython 2025
February 24 – 26, 2025
Helsinki Python meetup
February 26, 2025
PyCon APAC 2025
March 1 – 2, 2025