Python's Syntactic Sugar
Explore Python's syntax implementation, learning how just 11 core elements and special functions create the entire language structure. Gain deeper insights into Python's inner workings.
10 Ways to Shoot Yourself in the Foot with Tests
Explore common pitfalls in Python testing, learn to identify problematic practices, and discover alternatives to create more effective and reliable test suites.
Pyproject.toml, Packaging, and You
Explore pyproject.toml's format, extensibility, and integration with setuptools for efficient Python project packaging. Learn to leverage this file as the source of truth for your projects.
The CPU in Your Browser - WebAssembly Demystified
Explore WebAssembly's role in browser-based Python, its strengths, limitations, and future potential. Dive into technical details relevant to Python developers, including WASI, dynamic linking, and language interoperability.
Iteration Toward Transformation of the Python Documentation
Discover the Python Docs Community's efforts to enhance Python's documentation, including key improvements, insights, and ways to contribute to this initiative for better serving diverse users.
Plug Life into Your Codebase - Making Established Python Codebase Pluggable
Discover how to revitalize Python codebases using the pluggy framework, with insights from conda's recent plugin API implementation for enhanced flexibility and extensibility.
Manage Your SCM Security Using Python Open Policy Agent - OPA - Client
Explore using Open Policy Agent for SCM security management. Learn to implement governance and compliance controls in development processes using Python OPA Client for GitLab/GitHub.
Charlas - Iván Pulido: Simulaciones moleculares reproducibles con la ayuda de Python
Introducción a simulaciones de dinámica molecular y cómo Python acelera la investigación en el área, con énfasis en la aplicación de Machine Learning y ejemplos usando OpenMM.
Charlas - Interfaces Low-code con QT y su integración con Python.
Diseño visual de interfaces con Qt Designer y su integración en Python, enfocado en crear aplicaciones empresariales sin necesidad de programar extensivamente la interfaz gráfica.
XGBoost para clasificación - construyendo modelos precisos y eficientes
Aprende a utilizar XGBoost para crear modelos de clasificación precisos y eficientes, explorando conceptos básicos, técnicas de construcción y evaluación, y ventajas clave de esta poderosa herramienta.
Algorithmic Ideas, Engineering Tricks, and Trivia Behind CPython's New Sorting Algorithm
Explore the evolution of CPython's sorting algorithm, from Quicksort to Timsort and beyond. Discover algorithmic insights, engineering tricks, and historical anecdotes behind Python's fast list sorting.
Rethinking Objects
Explore the evolution of Object-Oriented programming, comparing traditional concepts with functional approaches and examining the enduring value of objects in library design.
How Memory Profilers Work
Explore memory profilers in Python: types, allocation patterns, and effective usage for optimizing large-scale applications and diagnosing memory issues.
Catching Tensor Shape Errors without Running Your Code
Discover how to catch tensor shape mismatches in ML code using shape types and type checking, improving debugging efficiency and code understanding without execution.
You Can Take It with You - Packaging Your Python Code with Briefcase
Learn how to use Briefcase to convert Python projects into platform-native apps for macOS, Windows, Linux, iOS, Android, and web, enabling distribution to non-Python users and creating standalone applications.
Inside Web Framework - Intro to the ASGI Spec, Middleware, and Apps
Explore ASGI specification, create custom apps and middleware, and learn to serve applications using Uvicorn. Gain insights into web framework internals for debugging and optimizing Python web apps.
A Per-Interpreter GIL - Concurrency and Parallelism with Subinterpreters
Explore Python 3.12's new solution for concurrent code and multi-core computing. Learn about per-interpreter GIL and subinterpreters to simplify concurrency and boost performance.
Reproducible Molecular Simulations with Python
Explore molecular dynamics simulations using Python's scientific ecosystem, focusing on OpenMM and its tools. Learn how AI and machine learning are revolutionizing this field.
Trying No GIL on Scientific Programming
Exploring the potential of no-GIL Python for scientific programming, comparing performance with standard CPython in CPU-intensive tasks like PCA, clustering, and data manipulation using Scikit-learn and Pandas.
Testing Spacecraft with Pytest
Explore spacecraft software testing using pytest, comparing it to web services and examining real-world examples from Varda Space Industries. Learn about safety-critical systems and verification techniques.
Transforming a Jupyter Notebook into a Reproducible Pipeline for ML Experiments
Learn to transform Jupyter Notebooks into reproducible ML pipelines using Git and DVC. Explore techniques for experiment tracking, modularization, and result comparison in a text2image project with Stable Diffusion.