uv for Python: Projects, Dependencies, and Lockfiles
Set up a Python project with uv, a virtual environment, pyproject.toml, and a reproducible lockfile while understanding what changes from pip.
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12 articles on this pageDocumenting Python Projects with Sphinx
Build lean Python documentation with Sphinx, autodoc, docstrings, and type hints, then generate HTML and automate publishing without needless complexity.
Property-Based Testing in Python with Hypothesis
Use Hypothesis with pytest to generate inputs, check invariants, shrink failures, and uncover edge cases that hand-written examples miss.
Python pyproject.toml Guide for Applications and Libraries
Structure pyproject.toml for applications and libraries, separate build and runtime requirements, declare dependencies, and configure tools safely.
Playwright with Python: Browser Automation and Testing
A practical Python Playwright guide covering browser setup, robust locators, state-based waits, downloads, screenshots, pytest, and responsible use.
Send Email with Python, smtplib, and email
Build an SMTP sender with text and HTML alternatives, bounded attachments, STARTTLS, environment configuration, validation, and clear errors.
Manipulate PDFs with Python and pypdf
A practical pypdf automation guide covering merging, splitting, rotation, metadata, text extraction limits, encryption, and errors.
Python Argparse: Build a CLI with Subcommands
Build an installable task-management CLI using positional arguments, options, subcommands, entry points, and automated tests.
Python Pandera: Practical DataFrame Validation
Validate DataFrame columns, types, and business rules with Pandera while building and testing a small sales pipeline.
scikit-learn Pipelines: ColumnTransformer and CV
Combine preprocessing and a model in a scikit-learn Pipeline, validate it correctly, and keep test information out of training.
DuckDB with Python: Query CSV, Parquet, and DataFrames
Query CSV, Parquet, and in-memory DataFrames with SQL through DuckDB and Python, without operating a database server.
Polars in Python: DataFrames, Lazy API, and Pandas
Use Polars expressions and lazy execution for clear DataFrame pipelines, while understanding when to compare, combine, or stay with Pandas.