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Learn to scale data workflows using Apache Airflow, covering dynamic DAG generation, automation, and best practices for managing big data pipelines. Suitable for beginners and intermediate developers.
Explore Python's importlib to manage API deprecations, redirecting modules and attributes for backward compatibility while restructuring codebases. Learn techniques for seamless transitions in software projects.
Explore Robyn, a high-performance async Python web framework with a Rust runtime. Learn its creation, technical decisions, performance benefits, and community-driven development.
Learn how volunteers use Python to assist an NGO in Victoria, BC, in supporting the unhoused through social media monitoring and resource allocation optimization.
Explore techniques to parallelize Python code, overcoming GIL limitations for improved performance in data processing and CPU-bound tasks.
Discover how to apply Test-Driven Development to machine learning projects, from data analysis to building recommendation engines, using Python libraries and Jupyter Notebooks.
Implement efficient full-text search on Django websites using PostgreSQL, avoiding complexities of external search engines. Learn to enhance content accessibility and improve search functionality.
Exploring Python development on Android: challenges, opportunities, and tools for mobile app creation. Learn about build tools, GUI libraries, and options for running Python on the world's most popular OS.
Optimizing data pipeline efficiency using machine learning to predict task duration and resource requirements, enabling dynamic queue allocation and autoscaling for improved performance and cost-effectiveness.
Wrap up the Python community's biggest event with highlights, reflections, and a look ahead to future gatherings in this celebratory finale.
Hands-on tutorial for fine-tuning BERT models using Hugging Face and PyTorch. Learn to adapt pre-trained NLP models for sentiment analysis, gaining practical skills in deep learning and confidence in navigating open-source tools.
Discover property-based testing with Hypothesis to write more robust and effective tests. Learn to define input strategies, create generalized tests, and uncover hidden bugs in your Python code.
Explore the challenges of building binary wheels for Python extensions, common pitfalls, and solutions. Learn about manylinux standards and the cibuildwheel project for automated wheel distribution.
Explora el reconocimiento de patrones y texto en imágenes usando OpenCV y Tesseract con Python. Aprende técnicas de visión artificial aplicables en industrias como automoción, robótica y procesamiento de datos.
Comprehensive overview of Python static code analysis tools, including linters, type checkers, and formatters. Introduces beginners to type hints and highlights the fast Rust-based linter Ruff.
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