An April Fool’s free issue. All content was curated before April 1st and is guranteed to be April Fool’s free.
Optimizing With Generators, Expressions, & Efficiency Python generators provide an elegant mechanism for handling iteration, particularly for large datasets where traditional approaches may be memory-intensive. Unlike standard functions that compute and return all values at once, generators produce values on demand through the yield statement, enabling efficient memory usage and creating new possibilities for data processing workflows. PYBITES • Shared by Bob Belderbos
Introducing DuckDB In this showcase tutorial, you’ll be introduced to a library that allows you to use a database in your code. DuckDB provides an efficient relational database that supports many features you may already be familiar with from more traditional relational database systems. REAL PYTHON
Outlier Detection With Python Have you ever wondered why certain data points stand out so dramatically? They might hold the key to everything from fraud detection to groundbreaking discoveries. This week Talk Python to Me interviews Brett Kennedy on outlier detection. TALK PYTHONpodcast
What Can You Do With Python? In this video course, you’ll find a set of guidelines that will help you start applying your Python skills to solve real-world problems. By the end, you’ll be able to answer the question, “What can you do with Python?” REAL PYTHONcourse
Python Code Quality: Best Practices and Tools In this tutorial, you’ll learn about code quality and the key factors that make Python code high-quality. You’ll explore effective strategies, powerful tools, and best practices to elevate your code to the next level. REAL PYTHON
Optimizing Django by Not Being Silly Although the post is nominally about a tool being used with Django, the root problem being debugged is about handling substrings. Doing it badly can be a real performance bottleneck, learn how to avoid the problem. MAX BERNSTEIN
Share Python Scripts Like a Pro Sharing single-file Python scripts with external dependencies is now easy thanks to uv and PEP 723, which enable embedding dependency metadata directly within script files. DAVE JOHNSON • Shared by Dave Johnson
PEP 781: Make TYPE_CHECKING a Built-in Constant This PEP proposes adding a new built-in variable, TYPE_CHECKING, which is True when the code is being analyzed by a static type checker, and False during normal runtime. PYTHON.ORG
Understanding Numpy’s einsum Einstein notation lets you evaluate operations on multi-dimensional arrays. NumPy has this built-in. This post shows you how to use it. ELI BENDERSKY
