Python 3.15 adds extra_items and closed parameters to TypedDict, allowing typed extra values or forbidding extra keys. The excerpt also mentions typing.TypeForm and typing.disjoint_base without explaining them.
Related articles
See all- Chameleon
"Michael Kennedy's Thoughts on Technology": Chameleon templates, modernized: chameleon-rs
Michael Kennedy introduced chameleon-rs, a Rust implementation of Chameleon with compatibility, async rendering, partials, Markdown, and free-threaded Python support. He reports roughly 20% lower median response times across his own web app; shadow mode lets users compare outputs before migrating.
- Pyrefly
Pyrefly: A Fast Static Type Checker for Python Projects
Pyrefly checks Python types without executing code and also offers type-hint generation and type coverage measurement. The excerpt introduces its CLI workflow, while noting important context about coverage features in Pyright and mypy.
- Python
Python Circular Imports: Why They Happen and How to Fix Them
Real Python explains how circular imports expose partially initialized modules and trigger ImportError or AttributeError. It recommends one-way dependencies, function-local imports as a workaround, and TYPE_CHECKING guards for type-only imports, including on Python 3.14.
- Python
Rodrigo Girão Serrão: TypedDict with extra items
Python 3.15 adds extra_items to TypedDict to specify the value type of additional keys. The article demonstrates a Movie type with fixed title and year fields that also accepts extra string values.
- uv
Managing Python Projects With uv: An All-in-One Solution
Real Python introduces uv as a Rust-based Python package and project manager covering dependency installation, Python versions, virtual environments, and package publishing. The excerpt also outlines installation options and cautions that its interactive timing comparison is illustrative.
- ChromaDB
ChromaDB: Embeddings and Vector Databases in Python
Real Python introduces embeddings and vector databases with ChromaDB, explaining how relevant documents can provide context for LLMs. The supplied excerpt covers vector fundamentals and NumPy operations; the tutorial targets ChromaDB 1.5 and Python 3.12+.