No, Maybe and Close Enough - Using Probabilistic Data Structures in Python
Explore probabilistic data structures in Python for efficient counting and item recognition, focusing on Hyperloglog and Bloom Filter algorithms for fast, scalable solutions.
Unexpected Execution - Wild Ways Code Execution Can Occur in Python
Explore unconventional code execution methods in Python, from yaml to str.format. Learn about real vulnerabilities, absurd exploits, and prevention techniques using Facebook's open-source Pysa analyzer.
Statistical Typing - A Runtime Typing System for Data Science and Machine Learning
Statistical typing: A runtime typing system for data science and ML, extending primitive types to statistical data types. Enables multivariate schemas, generative data contracts, and easier data testing with pandera.
The Road to Pattern Matching in Python
Explore the rationale and concepts behind Python's pattern matching feature, its benefits for processing structured data, and how it complements existing tools for more efficient programming.
Gradual Typing in Practice
Explore gradual typing in Python, its benefits for code quality, and strategies for implementing types in large codebases, focusing on Instagram's experience with Pyre.
More Fun With Hardware and CircuitPython - IoT, Wearables, and More
Explore advanced CircuitPython projects for IoT and wearables. Learn to choose devices, understand electronics basics, and add interactivity to hardware projects through exciting demos and real-world applications.
The Magic of "Self" - How Python Inserts "Self" into Methods
Explore Python's data model and descriptor protocol to understand how 'self' is automatically inserted into methods, unveiling the magic behind this core language feature.
Large Scale Data Validation - with Spark and Dask
Explore data validation techniques for large-scale datasets using Spark and Dask. Learn to transition from single-machine to distributed computing, combining frameworks for efficient validation across partitions.
Blackfire - Debugging Performance
Discover techniques for optimizing Django application performance using Blackfire. Learn to analyze resource consumption, meet performance budgets, and seamlessly integrate performance testing across development stages.
Getting an Edge with Network Analysis with Python
Explore network analysis with Python to uncover hidden connections in everyday interactions, from social media to transportation, and gain insights into their impact on our lives.
Your App Is Async So Take Advantage of It for Development
Explore how Python's async capabilities enable real-time app inspection, remote REPLs, and graphical visualizations for enhanced development and debugging experiences.
Dask-SQL - Empowering Pythonistas for Scalable End-to-End Data Engineering
Explore dask-sql for Python-based SQL data extraction from enterprise datalakes, enabling seamless integration with PyData tools for machine learning, analytics, and data transformation workflows.
What We Learned from Papermill to Operationalize Notebooks
Explore notebook automation with Papermill, learning parameterization techniques and execution strategies to enhance troubleshooting pipelines and empower on-call developers.
Restarting Pyjion - A General Purpose JIT for Python - Is It Worth It?
Explore the revival of Pyjion, a JIT compiler for CPython, and its potential for significant performance gains. Learn about design ideas, optimizations, and future prospects for Python JIT compilation.
Narrative-Focused Video Games Development with Ren'Py - An Open Source Engine
Explore narrative-focused game development using Ren'Py, an open-source engine for visual novels. Learn about industry insights, Python integration, and creating commercial games as an indie developer.
Event-Driven Applications - Apache Kafka and Python
Explore event-driven applications using Apache Kafka and Python. Learn about Kafka's capabilities, integration techniques, and real-time data streaming for modern application development.
Creating Extensible Workflows with Off-Label Use of Python
Discover how to create flexible yet constrained workflow systems using Python's type annotations, coroutines, and dataclasses for extensible APIs in data processing, ETL, CI/CD, and more.
CHARLAS / Luis Conejo / GitHub Classroom: Una herramienta simple para la enseñanza de Python
Descubre cómo GitHub Classroom mejora la enseñanza de Python, sus ventajas sobre repositorios únicos y su impacto positivo en el aprendizaje de los estudiantes.
Data Processing on Ray
Explore Ray's architectural changes for scaling Python applications in machine learning and data processing, addressing challenges in large-scale workloads.
From NumPy to PyTorch - A Story of API Compatibility
Explore PyTorch's approach to NumPy compatibility, its importance, challenges, and necessary divergences in this insightful discussion on API design and data science workflows.
From 3 to 300 FPS - NES Emulation in Python and Cython
Explore NES emulation in Python, from slow beginnings to 300+ fps using Cython. Learn optimization techniques and challenges in achieving real-time performance.