Pweave - reports from data with Python

Documentation for

Quick Start

Discussion

Development and issues

About Pweave

Pweave is a scientific report generator and a literate programming tool for Python. Pweave can capture the results and plots from data analysis and works well with numpy, scipy and matplotlib. Pweave is inspired by Sweave, an excellent tool for R programmers, and the syntax is mostly compatible with it. Pweave supports reST, Sphinx, Latex, and Pandoc markdown markups.

Pweave uses noweb syntax for separating code from documentation, but it also supports ERB style evaluation of inline code. Pweave is able to weave a python code between <<>>= and @ blocks and include the results and capture matplotlib plots in the document. Inline code in documentation chunks is marked using <% %> (code will be evaluated in place) and <%= %> (result of expression will be printed) tags. Pweave supports reST, Sphinx, Latex, and Pandoc markdown markups. . Pweave is good for creating reports and tutorials. It can also be used to make websites together with e.g. Sphinx or rest2web.

Note

Pweave 0.22 has been released with a lot of new features including Python 3 compatibility (tested with 3.4). Related to this Pweave now imports the following:

from __future__ import print_function, division, unicode_literals, absolute_import

This also affects the weaved documents. If you don’t like this you can still use 0.21.2 or fork the code on Github

Post your questions and comments to Pweave google group.

Features:

  • Python 2.7 and 3.4 compatibility
  • Execute python code in the chunks and capture input and output to a report.
  • Use hidden code chunks, i.e. code is executed, but not printed in the output file.
  • Capture matplotlib graphics.
  • Evaluate inline code in documentation chunks
  • Cache all code and results from previous runs for fast report generation when you are only working with documentation. Inline code will be hidden in documentation mode.
  • Supports reST, LaTeX, HTML or Pandoc markdown for document chunks
  • Run from command line or interpreter.

Install and quickstart:

with pip:

pip install --upgrade Pweave

with conda:

conda install -c https://conda.binstar.org/mpastell pweave

Or download the source package from PyPi and run:

python setup.py install

After the installation you get options with:

$ Pweave --help
$ Ptangle

Documentation

Browse documentation or go straight to an examples

Thanks

Thanks to following people for contributing patches and ideas: Tamas Nepusz, Nicky van Foreest, Mark Edgington, Thomas Unterthiner, Matthew McDonald, Grant Goodyear, Aaron O’Leary.