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Jupyter Functions Exec

PyPI version License: MIT Rust Python

High-performance Python package built in Rust to extract and execute functions directly from Jupyter Notebooks (.ipynb) -> no copy-paste.

Ignores broken cells, keeps only valid functions and imports.

Installation

Requires Python 3.11+

pip install jupyter-functions-exec

Quickstart

If your notebook.ipynb contains:

import math

def add(a, b):
    return a + b

def circle_area(r):
    return math.pi * r ** 2

Use it from Python:

from jupyter_functions_exec import JupyterFunctions

jf = JupyterFunctions("notebook.ipynb")

print(jf.functions_names())
# ['add', 'circle_area']

print(jf.necessary_imports())
# ['import math']

Examples

1. Execute a function

result = jf.exec_function("add", 2, 3)
print(result) # 5

With kwargs:

result = jf.exec_function("circle_area", r=10)
print(result) # 314.159...

2. Get a callable

add = jf.return_function("add")
print(add(10, 20)) # 30

3. Check and inspect

if jf.exists_function("add"):
    print("found!")

print(jf.functions_names())
print(jf.necessary_imports())

API Reference

Method Description
JupyterFunctions(path: str) Parse a .ipynb file. Filters broken code automatically.
exec_function(name, *args, **kwargs) Execute function by name and return result.
return_function(name) -> Callable Return function as callable for later use.
exists_function(name) -> bool Check if function exists. O(1) lookup.
functions_names() -> list[str] Get sorted list of all valid functions.
necessary_imports() -> list[str] Get list of imports needed.

How it works

  1. Parses .ipynb as JSON in Rust
  2. Extracts import / def per code chunk
  3. Validates each function with Python compile() -> broken cells are skipped
  4. Pre-compiles everything once in __init__ for fast exec

License

MIT - see LICENSE

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