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Learn to create, generate, host, and automate up-to-date API documentation using Sphinx and GitHub Actions, integrating it seamlessly into your software development lifecycle.
Learn to apply Python skills to pressing environmental issues, using tools like numpy, pandas, and matplotlib to analyze deforestation, wildlife trade, and carbon pollution data.
Learn to instrument, monitor, and troubleshoot Python applications using OpenTelemetry. Gain hands-on experience with traces, metrics, and logs for improved observability and faster issue resolution.
Learn to create CLI apps that cater to both human users and automated tools. Explore Command Line Interface Guidelines and build a PyCon talk catalogue using Python, typer, and Rich.
Learn to create a FastAPI application that serves real-time predictions from a trained scikit-learn model, bridging the gap between model development and production deployment.
Explore Polars, a fast data manipulation library, through hands-on exercises with real-world datasets. Learn key operations, compare with Pandas, and optimize data pipelines.
Explore satellite imagery and Python tools for geospatial analysis to identify and analyze coastal erosion, addressing a critical environmental and humanitarian challenge.
Learn to create and publish a full-fledged Python package using conda, covering packaging concepts, the conda ecosystem, and hands-on preparation for submission to conda-forge.
Inspiring welcome address highlighting the Python community's diversity, inclusivity, and collaborative spirit at the largest annual gathering of Python enthusiasts.
Experiencia de enseñar programación a alumnos neurodivergentes, utilizando tecnologÃa para romper barreras y proporcionar educación inclusiva, cambiando paradigmas en educación y empleo.
Explore Python's role in optimizing transportation networks through real-world examples, including driver-load matching, network optimization, and decision-making using graph analytics and data science concepts.
Explore advanced Python instrumentation techniques, challenging real-world cases, and design patterns. Learn to hook into import systems, instrument popular libraries, and make your code instrumentation-friendly.
Efficient techniques for querying and joining data across distant machines using Python, addressing slow network transfers and large datasets that exceed local memory.
Efficient CSV parsing and conversion to NumPy arrays with full dtype support and optional type discovery, outperforming Pandas for various DataFrame shapes and heterogeneity.
Explore OpenTelemetry for efficient application monitoring and troubleshooting. Learn to detect issues, track performance, and enhance observability in cloud-based environments using this open-source protocol.
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