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Learn essential NumPy idioms for efficient scientific computing in Python, covering array creation, broadcasting, universal functions, aggregations, slicing, and indexing to boost numerical computation speed.
Explore static type-checking in Python, including PEP 484, type hints, and libraries like Hypothesis. Gain insights into type systems and their impact on code robustness.
Explore Numba, a JIT compiler for Python that accelerates numerical algorithms beyond Numpy capabilities, with CPU and GPU support. Learn its use cases, performance expectations, and inner workings.
Learn techniques and tools for improving code quality in Python, focusing on readability, design, testing, and documentation for easier maintenance and extension.
Discover how Spotify's team improved performance through metrics-driven development, focusing on key indicators and establishing feedback loops for continuous improvement.
Explore popular Python libraries for creating user-friendly command-line interfaces, comparing their concepts and features. Learn to build and test CLIs beyond standard library solutions.
Learn essential data science techniques using Python, numpy, pandas, and sklearn. Explore real-world use cases with code snippets and live demos in IPython notebooks.
Learn PySpark for large-scale data processing with Python on Apache Spark. Covers RDDs, DataFrame API, transformations, actions, and data sources. Ideal for those seeking efficient big data analysis techniques.
Explore RinohType, a Python-based document processor inspired by LaTeX. Learn its features, design goals, and how to create PDFs from reStructuredText, with insights into its layout engine and style system.
Practical guide on starting and growing a local Python community, covering resources, expectations, and strategies for success. Ideal for enthusiasts wanting to foster a tech community.
Explore PyPy's Software Transactional Memory, enabling GIL-free Python execution on multiple cores. Learn to identify and resolve STM conflicts for improved performance in large codebases.
Explore building a FUSE filesystem for Git repositories, enabling automatic commits and history snapshots. Learn crucial aspects, implementation steps, and testing methods.
Explore modern web development with asyncio in Python and React.js in JavaScript. Learn about aiohttp, ES6 features, and Flux architecture for building efficient, scalable applications.
Learn to automate API documentation using Sphinx autodoc and related extensions. Discover techniques for efficient docstring writing, automated module listing, coverage checking, and doctest verification to create comprehensive Python library documentati…
Explore Pylint's powerful static analysis capabilities for Python, from style checking to advanced bug detection and code understanding, with insights on its inner workings and future developments.
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