Python Function Generator
Describe a function and get well-structured Python: a signature with type hints and defaults, optional parameters made keyword-only, a docstring in Google, NumPy or reST style with Args, Returns and Raises sections, None in place of mutable defaults, simple argument checks and the imports the hints need. Works for normal and async functions.
- Runs in your browser
- No sign-up
- Free to use
How to use Python Function Generator
- Enter the function name and description.
- List the parameters as name: type = default.
- Choose the return type, docstring style and options.
- Copy the function into your module.
Python Function Generator features
Type hints
Modern syntax: list[int], dict[str, float], str | None.
Three docstring styles
Google, NumPy and reST/Sphinx.
Keyword-only
Optional parameters after *, so calls stay readable.
Safe defaults
[] and {} replaced by None and created per call.
Argument checks
Empty strings and sizes below 1 raise ValueError.
Imports
datetime, Any and __future__ annotations added when needed.
When to use Python Function Generator
- Starting new functions with documentation from the beginning.
- Writing consistent docstrings for Sphinx or mkdocstrings.
- Scaffolding async API calls.
- Teaching Python typing and docstring conventions.
Python Function Generator FAQ
Which docstring style should I use?
Google style is compact and popular; NumPy style is common in scientific code; reST is the classic Sphinx format. Use whatever your project already uses; documentation tools support all three.
Why replace [] defaults with None?
Default values are evaluated once, when the function is defined. A [] default is shared between calls, so changes leak from one call to the next. Using None and creating the list inside avoids this.
What are keyword-only parameters?
Parameters after a bare * must be passed by name: fetch(1, limit=10). This prevents mix-ups and lets you add or reorder optional parameters later.
Why from __future__ import annotations?
It stops Python from evaluating type hints when the function is defined, so hints can name classes defined later or only imported for type checking.
Which Python version is needed?
The X | None syntax needs Python 3.10 or later.
Is anything uploaded?
No. Everything is generated in your browser.
Writing documented Python functions
A well-written Python function tells its reader three things before they look at the body: what it does, what it accepts and what it returns or raises. Type hints and a docstring carry that information, and editors, type checkers and documentation generators all read them. The generator produces both from one short description.
Parameters are entered in a neutral notation and become hints in modern Python syntax. Optional parameters get | None, list and dict types use the built-in generic syntax, and date maps to datetime with the matching import. When a hint names a class, from __future__ import annotations is added so that the module imports cleanly even if that class is defined later.
Docstrings follow one of three conventions. Google style uses Args, Returns and Raises headings; NumPy style uses underlined section titles and puts the type on its own line; reST style uses :param: fields for Sphinx. Each parameter is described with its comment or a default phrase, ready to be refined.
Two classic pitfalls are handled automatically. Mutable defaults such as [] are replaced by None and created inside the function, because a default list would be shared between calls. And optional parameters can be made keyword-only by inserting * in the signature, so that callers must name them.
Argument checks raise ValueError for common invalid inputs, such as an empty string or a size below one, and the docstring lists the exceptions the function may raise. A placeholder return value of the right type lets you call the function while you implement it.