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Demystifying Python Memory Management & Choosing a Project Layout

30 de outubro de 2026 · 46 min

Notas do episódio

How does Python manage memory behind the scenes? What are the common ways to lay out a Python project? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

Christopher shares an article titled “First Steps into Memory Management in Python.” With recent updates to the garbage collector and the ongoing work toward removing the Global Interpreter Lock (GIL), the article covers the fundamentals of how Python allocates, tracks, and frees memory.

We also share other articles and projects from the Python community, including recent releases, why Parquet dominates modern data engineering, choosing the right Python project layout, developing the most cursed + operator in all of Python, finding which dependencies block a Django project upgrade, and a Django performance benchmark profiler.

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Topics:

  • 00:00:00 – Introduction
  • 00:01:56 – Python 3.16.0 Alpha 1 Is Now Available
  • 00:02:24 – Django Security Releases Issued: 6.1.2, 6.0.9, and 5.2.18
  • 00:02:46 – Release of Polars 2.0
  • 00:03:32 – PyPy v8.0.1 Release
  • 00:03:54 – Checking Email Reputation, and Allowing Outlook Again
  • 00:04:48 – PyScript is in maintenance mode
  • 00:05:55 – Codex for Python Developers: Hands-On Agentic Coding Course
  • 00:06:21 – MLOps North: November 5th & 6th
  • 00:06:46 – Why Parquet Dominates Modern Data Engineering
  • 00:16:04 – First Steps Into Memory Management in Python
  • 00:23:21 – Spotlight: Codex for Python Developers
  • 00:25:05 – Python Project Structure: How to Choose the Right Layout
  • 00:35:17 – Pendulum and the Most Cursed + Operator in All of Python
  • 00:38:50 – django-benchmark: Django Performance Benchmark Profiler
  • 00:41:53 – django-upgrade-report: Which Dependencies Block an Upgrade to Your Django Project?
  • 00:44:33 – Thanks and goodbye

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