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Python Knowledge Base

This repository collects all the knowledge, documentation, best practices, tips, templates and manuals developed by 510 for python applications.

Contents

Framework-agnostic tooling and standards that apply to all Python projects: dependency management (uv, pyproject.toml), CI/CD (GitHub Actions), code quality (ruff, type checking, pre-commit), logging & observability (Azure Monitor), and Docker best practices.

Best practices for building FastAPI web APIs. Covers project structure, configuration, testing, and framework-specific deployment details.

Best practices for building Flask web applications with server-rendered HTML (Jinja2 templates, forms, sessions). Covers the application factory, blueprints, WTForms, security headers, testing, and framework-specific deployment details.

Best practices for building data pipelines that extract data from external sources, transform it, and load it into a target system (API, database, file store). Covers project structure, configuration, data types, error handling, testing, CLI design, deployment, and more.

Best practices for building reproducible, well-structured Jupyter notebook workflows for data analysis, statistical calibration, and geospatial modeling. Covers notebook structure, conda environments, lazy data loading, memory management, visualization, code reuse, and more.

AI Use Disclaimer

Parts of this knowledge base - including the consolidated copilot-instructions.md files - were drafted with AI assistance and then reviewed and edited by 510 engineers. AI tools here are meant to augment engineers, not replace their judgment: a human reviews, understands, and owns all output. For the principles we follow, see the Responsible AI guide, of which 510 is a collaborator.

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Best practices, templates, and documentation for Python applications.

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