How do you create automated tests to check your code for degraded performance as data sizes increase? What are the new features in pandas 3.0? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

Christopher digs into an article about building tests to make sure your software is fast, or at least doesn’t get slower as it scales. The piece focuses on testing Big-O scaling and its implications for algorithms.

We also discuss another article covering the top features in pandas 3.0, including the new dedicated string dtype, a cleaner way to perform column-based operations, and more predictable default copying behavior with Copy-on-Write.

We share several other articles and projects from the Python community, including a collection of recent releases and PEPs, a profiler for targeting individual functions, a quiz to test your Django knowledge, when to use each of the eight versions of UUID, the hard-to-swallow truths about being a software engineer, an offline reverse geocoding library, and a library for auto-generating CLIs from any Python object.

Our live Python cohorts start February 2, and we’re down to the last few seats. There are two tracks: Python for Beginners or Intermediate Deep Dive. Eight weeks of live instruction, small groups, and real accountability. Grab your seat at realpython.com/live.

This episode is sponsored by Honeybadger.

Course Spotlight: Intro to Object-Oriented Programming (OOP) in Python

Learn Python OOP fundamentals fast: master classes, objects, and constructors with hands-on lessons in this beginner-friendly video course.

Topics:

00:00:00 – Introduction
00:03:28 – Python 3.15.0 Alpha 4 Released
00:03:50 – Django Bugfix Release: 5.2.10, 6.0.1
00:04:22 – PEP 819: JSON Package Metadata
00:04:41 – PEP 820: PySlot: Unified Slot System for the C API
00:04:59 – PEP 822: Dedented Multiline String (d-String)
00:06:04 – What’s New in pandas 3.0
00:13:11 – pandas 3.0.0 documentation
00:13:44 – Sponsor: Honeybadger
00:14:30 – Unit Testing Your Code’s Performance
00:17:51 – Introducing tprof, a Targeting Profiler
00:23:03 – Video Course Spotlight
00:24:31 – Django Quiz 2025
00:24:56 – 8 Versions of UUID and When to Use Them
00:29:17 – 10 hard-to-swallow truths they won’t tell you about software engineer job
00:44:02 – gazetteer: Offline Reverse Geocoding Library
00:46:13 – python-fire: A library for automatically generating command-line interfaces
00:47:40 – Thanks and goodbye

News:

Python 3.15.0 Alpha 4 Released
Python 3.15.0a5 Alpha 5 Released
Django Bugfix Release: 5.2.10, 6.0.1
PEP 819: JSON Package Metadata (Draft)
PEP 820: PySlot: Unified Slot System for the C API (Draft)
PEP 822: Dedented Multiline String (d-String) (Draft)

Show Links:

What’s New in pandas 3.0 – Learn what’s new in pandas 3.0: pd.col expressions for cleaner code, Copy-on-Write for predictable behavior, and PyArrow-backed strings for 5-10x faster operations.
What’s new in 3.0.0 (January 21, 2026) — pandas 3.0.0 documentation
Unit Testing Your Code’s Performance – Testing your code is important, not just for correctness but also for performance. One approach is to check performance degradation as data sizes go up, also known as Big-O scaling.
Introducing tprof, a Targeting Profiler – Adam has written tprof, a targeting profiler for Python 3.12+. This article introduces you to the tool and why he wrote it.
Django Quiz 2025 – Last month, Adam held another quiz at the December edition of Django London. This is an annual tradition at the meetup, and now you can take it yourself or just skim the answers.
8 Versions of UUID and When to Use Them – RFC 9562 outlines the structure of Universally Unique Identifiers (UUIDs) and includes eight different versions. In this post, Nicole gives a quick intro to each kind so you don’t have to read the docs, and explains why you might choose each.
uuid — UUID objects according to RFC 9562 — Python 3.14.2 documentation

Discussion:

10 hard-to-swallow truths they won’t tell you about software engineer job

Projects:

Additional Links:

Level up your Python skills with our expert-led courses:

Testing Your Code With pytest
Investigating Quasar Data With Polars and Interactive marimo Notebooks
Intro to Object-Oriented Programming (OOP) in Python

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