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How Things Work: An Introduction to Physics
End of Life Care: Challenges and Innovation
Understanding Medical Research: Your Facebook Friend is Wrong
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Explore tools for automatic Python code reviews, their setup, and benefits. Learn how to effectively implement static analysis in mature codebases for improved coding practices.
Explore integrating Python and R for statistical analysis, data visualization, and distributed computing. Learn to leverage R's powerful ecosystem within Python projects using pyRserve.
Explore Python programming for 3D animation in Blender, designed to engage young learners through an innovative contest organized by Python Software Verband e.V.
Experiências e estratégias para ensinar programação Python de forma divertida e acessÃvel no Brasil, usando um MOOC não-inglês com mais de 15.000 inscritos.
Learn techniques for creating multi-language documentation with Sphinx, including tools, workflow organization, and best practices based on real-world project experiences.
Effective strategies for teaching Python, including rapid feedback and supervised learning. Insights from OpenTechSchool's successful workshops for beginners and experienced programmers.
Explore recent advancements in Stackless Python, including improved multi-threading, custom scheduling, and debugging. Learn about future development plans and open-source collaboration.
Learn how Python powers mobile game backends, handling server-side logic, scalability, and real-time multiplayer experiences. Explore architecture, technologies, and lessons from transitioning to cloud-based development.
Learn strategies for maintaining Python libraries compatible with both Python 2 and 3, covering key differences, best practices, and techniques to minimize version-specific code while ensuring seamless functionality across versions.
Explore dh-virtualenv, a tool for deploying Python software on Debian-based systems. Learn its advantages, usage, and how it simplifies the packaging process for smoother production deployments.
Overview of Scikit-learn for machine learning in Python, covering supervised and unsupervised techniques, with code examples and insights on implementation. Includes comparison to other ML libraries and scaling to big data.
Explore graph databases, their advantages in handling connected data, and learn about Neo4J and its Cypher query language for efficient data modeling and querying in Python.
Explore advanced Python bug detection using Jedi, an autocompletion library that understands dynamic features. Learn to identify errors before runtime for improved code quality.
Explore the journey of an HTTP request through a platform-as-a-service, focusing on PythonAnywhere's infrastructure. Learn about scaling, performance optimization, and insights for managing Python-based websites.
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