Build a Wikipedia Search Engine, Working with INI files Using configparser and more
with some more interesting news, articles, packages and projects
Articles
A modern, opinionated, cookiecutter template for your next Python project
If you're starting a new project, it's smart to use a good template instead of building everything from scratch, as it can save a lot of time. There are plenty out there and if you're looking for a good one, check out the template recently created by Wyatt Ferguson.
# Wyatt Ferguson
Python 101 - An Intro to Working with INI files Using configparser
Did you know Python’s standard library includes configparser, which lets you work with Windows-style INI files? If not, check out this article by Mike Driscoll, where he walks through creating, editing and reading INI files with clear examples.
# Mike Driscoll
Text search is both a tricky and interesting topic. While tools like OpenSearch or Elasticsearch make it easier, building one yourself can teach you a lot. If you're up for that challenge, check out this tutorial video by Rahul Jha where he built a Wikipedia Search Engine from scratch using Gensim, TF-IDF and Flask.
# Rahul Jha
Python For Nonprofits to retrieve, analyze, visualize and share nonprofit data
In this repository, Kenneth Burchfiel walked through how to use Python to import, clean and reformat data, perform analysis using descriptive stats and linear regression, create charts and maps and share spreadsheets and interactive visualizations online. While it’s aimed at the nonprofit sector, it offers valuable lessons for anyone looking to strengthen their data presentation skills.
# Kenneth Burchfiel
Design Patterns You Should Unlearn in Python-Part2
There’s no silver bullet in life and the same goes for programming - even widely praised best practices like design patterns don’t apply the same way across languages. Python, for example, often offers simpler, more natural solutions than traditional patterns used in languages like C++ or Java. In this article, Cheng/Racey Chan covered two patterns - Flyweight and Prototype. If you resonate with his approach, don’t miss part 1 of his series as well.
# Cheng/Racey Chan
Interesting Packages and Projects to Explore
Shapely - Manipulation and analysis of geometric objects
Partial JSON Parser - Parse partial JSON generated by LLM
Mesa - Agent-based modeling (ABM) in Python
nanodjango - Run Django models and views from a single file, and convert it to a full project.
LiteLLM - Library to easily interface with LLM API providers
Recent Noteworthy Package Releases
Gymnasium 1.2.0 - A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)
LangGraph 0.5.0 - Building stateful, multi-actor applications with LLMs
Dagster 1.11.0 (core) / 0.27.0 (libraries) - An orchestration platform for the development, production, and observation of data assets.
aioboto3 15.0.0 - Async boto3 wrapper
lxml 6.0.0 - Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API
transformers 4.53.0 - State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
mcp 1.10.0 - Model Context Protocol SDK
resolvelib 1.2.0 - Resolve abstract dependencies into concrete ones
chdb 3.4.0 - An in-process SQL OLAP Engine powered by ClickHouse
Diffusers 0.34.0 - State-of-the-art diffusion in PyTorch and JAX
junitparser 4.0.0 - Manipulates JUnit/xUnit Result XML files
Pybtex 0.25.0 - A BibTeX-compatible bibliography processor in Python
Instructor 1.9.0 - structured outputs for llm
Robyn 0.70.0 - A Super Fast Async Python Web Framework with a Rust runtime