The IPython notebook provides an interactive interface to a Python interpreter.
- Literate programming: the IPython notebook is an ideal format for
writing "literate" programs, in which the code is part of a larger multi-media
document.
runipy
lets you run such programs directly, without first converting to a pure Python script. - Report generation:
runipy
can run the notebook and convert it into HTML in one go, making it an easy way to automate reports. - Data pipeline: if you use IPython notebooks to create a data pipeline,
runipy
lets you automate that pipeline without losing the notebook formatting.
runipy
currently supports IPython versions 2.4.x, 3.2.x and the current development
version of 4.x.
The easiest way to install runipy
is with pip
:
$ pip install runipy
To run a .ipynb
file as a script, run:
$ runipy MyNotebook.ipynb
To save the output of each cell back to the notebook file, run:
$ runipy -o MyNotebook.ipynb
To save the notebook output as a new notebook, run:
$ runipy MyNotebook.ipynb OutputNotebook.ipynb
To run a .ipynb
file and generate an HTML
report, run:
$ runipy MyNotebook.ipynb --html report.html
You can pass arguments to the notebook through environment variables. The use of environment variables is OS- and shell- dependent, but in a typical UNIX-like environment they can be passed on the command line before the program name:
$ myvar=value runipy MyNotebook.ipynb
Here is one way this can be done from pure python:
from os import environ from subprocess import call environ['myvar'] = 'value' call(["runipy", "MyNotebook.ipynb"])
Then in the notebook, to access myvar:
from os import environ myvar = environ['myvar']
environ
is just a dict
, so you can use .get()
to fall back on
a default value:
from os import environ myvar = environ.get('myvar', 'default!')
runipy
can read stdin and stdout and sit in a UNIX pipeline:
$ runipy --stdout < MyNotebook.ipynb > OutputNotebook.ipynb $ cat MyNotebook.ipynb | runipy --stdout > OutputNotebook.ipynb
It is also possible to run IPython notebooks from Python, using:
from runipy.notebook_runner import NotebookRunner from IPython.nbformat.current import read notebook = read(open("MyNotebook.ipynb"), 'json') r = NotebookRunner(notebook) r.run_notebook()
and you can enable pylab
with:
r = NotebookRunner(notebook, pylab=True)
The notebook is stored in the object and can be saved using:
from IPython.nbformat.current import write write(r.nb, open("MyOtherNotebook.ipynb", 'w'), 'json')
run_notebook() takes two optional arguments. The first, skip_exceptions, takes a boolean value (False by default). If True, exceptions will be ignored and the notebook will continue to execute cells after encountering an exception. The second argument is progress_callback, which must be either None or a function that takes one argument. This function is called after execution of each cell with the 0-based index of the cell just evaluated. This can be useful for tracking progress of long-running notebooks.
Portions of the code are based on code by Min RK
Thanks to Kyle Kelley, Nitin Madnani, George Titsworth, Thomas Robitaille, Andrey Tatarinov, Matthew Brett, Adam Haney, Nathan Goldbaum, Adam Ginsburg, Gustavo Bragança, Tobias Brandt, Andrea Zonca, Aaron O'Leary, Simon Guillot, Fernando Correia, Takashi Nishibayashi, Simon Conseil, and Thomas French for patches, documentation fixes, and suggestions.