Asyncio Patterns in Python | Skyler Lewis
Asyncio Patterns in Python | Skyler Lewis
PySpark & Data Quality, S.O.L.I.D. Design Principles in Python, Turtle Programming in Python with some more interesting articles, packages and projects
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Asyncio Patterns in Python
For IO operations asyncio is good there is no doubt about it but if you want to do millions of operations then simply calling asyncio.create_task won’t solve the problem in fact it creates problems like memory issues, etc. Skyler Lewis took one related example and explained how he solved it by going step by step.
# Skyler Lewis
PySpark & Data Quality
Data is the new oil, we all agree to it but if the oil quality is bad it will lead to so many problems than help us. Sara M covered how to find data quality and clean it in this article using PySpark.
# Sara M
S.O.L.I.D. Design Principles in Python
S.O.L.I.D. Design Principles are there to keep your code manageable in the future. If you understand them and design your application using them then your life & the people who are going to manage it in future will be in sanity. In this article, Serdar Gundogdu covered them with examples which include what kind of problems come and how these design principles help. It's a long article but amazing.
# Serdar Gundogdu
Pytest In Practice: Fundamentals of Python Testing Techniques
Thinking of starting to write test cases then check this article by Rafał Buczyński. Explained stuff from the start using a simple example.
# Rafał Buczyński
Turtle Programming in Python
The best way to teach programming to kids is through visuals like drawing something on the board. If they write code and something happens based on that it will give a lot of excitement. Python has a Turtle library for this. It is a built-in Python library that introduces programming through a graphical interface. Check this GeeksforGeeks article to learn more about it.
Advanced Retrieval-Augmented Generation: From Theory to LlamaIndex Implementation
RAG is one of the most important techniques for supercharging large language models (LLMs) with your proprietary data. There is a lot of action happening on the RAG side. Previously we were using Naive RAG. Now there are other types of RAGs - advanced RAG, and modular RAG. In this article, Leonie Monigatti explained about advanced RAG and also mentioned many other great articles for reference. Long read but you will get a good understanding of RAG.
# Leonie Monigatti
Python — Building Simple API with FastAPI and PostgreSQL
Thinking of learning FastAPI and want to create a simple API using FastAPI then this article by Ihor Lukianov is a good place to start. It's long but worth it, he explained each topic in detail.
# Ihor Lukianov
Interesting Packages and Projects to explore
Solara - A Pure Python, React-style Framework for Scaling Your Jupyter and Web Apps
PikaPython - An ultra-lightweight Python interpreter that runs with only 4KB of RAM, zero dependencies. It is ready to use out of the box without any configuration required and easy to extend with C. Similar projects: MicroPython, JerryScript.
gspread - Google Sheets Python API
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