A Hands-On Introduction to Multi-Objective Optimization
Hands-on Python tutorial exploring multi-objective optimization using Pareto Fronts. Learn to balance conflicting objectives like quality and cost, with practical applications in various fields including supply chain and therapeutics development.
Hooking into the Import System
Explore Python's import system, learn to create custom import hooks, and discover innovative ways to load modules from databases and automatically reload modified files.
Shipping Python Extensions in Rust Two Million Times a Day
Explore using Rust in Python packages: challenges, successes, and implications. Learn about adopting Rust in pyca/cryptography, performance results, and architectural improvements.
Writing Performant Code for Modern Python Interpreters
Explore modern Python optimization techniques, learn new performance guidelines, and discover how to leverage language improvements for faster code execution.
Serialization - More Than Pickling
Explore alternatives to Python's pickle for object serialization, comparing efficiency and security considerations for different methods.
Writing Functional Code in Python
Explore functional programming concepts and their application in Python, enhancing code quality and efficiency through practical examples and key principles.
How to Change Python - While It's Running
Explore live Python development techniques, enabling real-time code changes during execution. Learn about Jurigged and the possibilities of runtime flexibility in Python programming.
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.
Dock Your Jupyter Notebook
Learn to containerize Jupyter Notebooks with Docker for reproducible and shareable machine learning projects, enabling smooth execution on remote machines.
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.
Bad Actors vs Our Community - Detecting Software Supply Chain Attacks
Explore techniques used by bad actors in software supply chain attacks and learn about a large-scale vetting system for detecting malware in Python packages.
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.