Python Oddities Explained
Explore Python's unique features and quirks, reshaping your mental model to better understand objects, scope, and variables in this mind-bending talk.
Open Source on Easy Mode
Streamline open source project maintenance with automation tools and best practices for packaging, testing, CI/CD, documentation, and community engagement. Focus on the fun parts of development.
Enhancing Code Collaboration with Conflict Free Replicated Data Types
Explore conflict-free replicated data types (CRDTs) and their potential to enhance Jupyter notebooks, enabling real-time collaboration, synchronous editing, and improved version control in data science workflows.
Building a Binary Extension
Learn to build Python binary extensions using modern tools like pybind11, scikit-build, and cibuildwheel for improved performance and functionality across platforms.
Distributed Web Scraping in Python
Learn to build a distributed web scraper in Python, reducing batch job times and improving code durability. Explore techniques, lessons, and stories for efficient large-scale web scraping.
In House to Open Source - Stitching the Past to the Future
Explore the transition from legacy code to open-source solutions, focusing on Python's advantages in software migrations and the implementation of robust frameworks like Apache Airflow.
Building a Python Code Completer
Uncover the secrets behind Python code completion, from parsing to AST, and learn how to build a simple completer in just minutes.
Implementing Shared Functionality Using Middleware
Introduction to writing middleware for web applications, exploring how they work in Flask, Django, and FastAPI. Learn to create custom middleware and leverage community-contributed solutions for essential functionality.
Learn Python Like a 12 Year Old
Discover effective Python learning strategies inspired by 12-year-olds, focusing on curiosity, diverse problem-solving, and embracing discomfort to enhance coding skills and creativity.
Software Development for Machine Learning in Python
Explore best practices for developing ML software in Python, focusing on abstraction, optimization, and production-ready code. Learn to design efficient, trackable, and easily maintainable ML systems.
Demystifying Python's Internals - Diving into CPython by Implementing a New Operator
Explore CPython's internals by implementing a pipe operator, covering tokenization, grammar, parsing, and bytecode generation for a deeper understanding of Python's core mechanics.
Employing NumPy's NPY Format for Faster Than Parquet DataFrame Storage
Explore faster DataFrame storage using NumPy's NPY format, outperforming Parquet in read/write times while supporting all DataFrame characteristics and NumPy dtypes.
Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit
Explore building a customizable ML experiment tracking system using DVC for versioning and Streamlit for data exploration, focusing on practical implementation with Python APIs.
Programming Your Way up a Skyscraper - Python in the Built World
Explore how architects use Python to enhance building design, from geometry editing to algorithmic design, data sorting, and software integration, unlocking new possibilities in architecture.
Why Authorization is Hard
Explore the complexities of implementing authorization in applications, covering enforcement, decision architecture, and modeling. Learn approaches and tradeoffs for each area.
Best Practices for Continuous Integration in Python
Explore best practices for Python continuous integration, focusing on timely and accurate developer feedback across various CI systems. Learn to optimize configurations for speed and precision.
Finding Penguins with a Snake - Linux Features for a Python User
Explore Linux features through Python APIs, including processes, named pipes, fork, exec, inodes, and signals. Enhance your understanding of OS capabilities using Python's standard library.
Python for Threat Intelligence
Explore threat intelligence using Python: automate tasks, analyze data, and build tools for security incident prevention. Learn from real-world examples and development practices.
Handling Timezones in Python
Learn to handle timezones and daylight savings in Python, avoiding common mistakes and implementing best practices for datetime operations in various scenarios, including Django applications.
Better Air, Better Health - Creating an Indoor Air Quality Monitoring System
Learn to build an indoor air quality monitoring system using Python, sensors, and machine learning to predict CO2 levels and improve your home environment.
Making Python Better One Error Message at a Time
Explore Python 3.10's improved error messages, their impact on users, and upcoming enhancements in 3.11. Learn about implementation challenges and how to contribute to future improvements.