Writing Documentation with Sphinx and reStructuredText
Learn to create Python documentation using reStructuredText and Sphinx. Master essential skills for contributing to open source projects by improving their documentation and overcoming barriers to entry.
Hands-On Regular Expressions in Python
Learn to create, understand, and effectively use regular expressions in Python for data validation, parsing, and normalization. Discover when and how to apply regex for optimal results.
Dashboards for All
Learn to create interactive dashboards using Python libraries like Bokeh and Panel. Explore data visualization techniques, analyze diverse datasets, and tell compelling stories through customized, user-friendly interfaces.
Hacking Dask - Diving Into Dask's Internals
Explore advanced Dask features: task graph optimization, plugins, cluster inspection. Gain deeper understanding of internals and apply to data-intensive workloads.
Python Unit Testing with Pytest and Mock
Learn to write high-quality Python unit tests using Pytest and mock. Master best practices for effective testing, enhancing code reliability and maintainability.
Functional Python
Explore functional programming concepts in Python, including higher-order functions, immutability, and lazy evaluation. Learn to write cleaner, more efficient code using functional paradigms.
Python Performance at Scale - Making Python Faster at Instagram
Explore Instagram's Python optimization strategies, including runtime modifications, inline caching, and JIT compilation, achieving significant performance improvements for large-scale web applications.
What Are Quantum Computers, and How Can We Train Them in Python
Explore quantum computing in Python: access real quantum hardware, differentiate quantum programs, and integrate them into larger differentiable programs for optimization and training.
Protocol - The Keystone of Type Hints
Explore static duck typing in Python using typing.Protocol, enhancing type hints for more expressive and verifiable code. Learn concepts and benefits through real-world examples from the standard library.
An Introduction to FastAPI
Explore FastAPI's features for rapid REST API development in Python, covering core concepts, schema creation, documentation, and advanced functionalities.
Static Sites with Sphinx and Markdown
Explore Sphinx for building static websites using Markdown, leveraging its powerful features for rich linking and knowledge base creation beyond traditional documentation.
When Is an Exception Not an Exception? Using Warnings in Python
Explore Python's warning system for handling minor issues without raising exceptions. Learn to generate, filter, and customize warnings for more nuanced error handling in your code.
Intro to Pydantic - Run-Time Type Checking for Your Dataclasses
Explore Pydantic for runtime type checking in Python, enhancing data validation for web APIs using standard type annotations and offering compatibility with dataclasses.
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.