Skip to main content

Reproducible report generation tool.

Project description

Stitch

Build Status

A knitr- RMarkdown-like library, in Python.

Note: You might want to consider Jan Schulz’s knitpy instead. It’s probably more mature at this point. However, I wanted to see if there was a simpler way of doing things.

The high-level goal of this type of library (knitr/RMarkdown, knitpy, and stitch) is to make writing reproducible reports easier.

Documentation is available here.

Examples

See the project’s examples page for a side-by-side comparison of input markdown and stitched HTML.

More complex examples are linked to from there as well.

Install

stitch supports Python 3.5 and above. At the moment stitch can be installed from pip via

pip install knotr

I know, it’s confusing. I’ve filed a claim for stitch on PyPI, but I think the people working that support queue are over-worked. Once that gets processed, I’ll put it up on conda-forge as well. If you need a mnemonic, it’s “I want knitr, but not the one written in R.” Also I wanted to confuse R users. And knots are kind of like a buggy version of knits.

stitch requires pandoc>=1.18. This can be installed using your system package manager, or pypandoc.

Design

The goal was to keep stitch itself extremely simple by reusing existing libraries. A high level overview of our tasks is

  1. Command-line Interface

  2. Parse markdown file

  3. Execute code chunks, capturing the output

  4. Collate execution output into the document

  5. Render to final output

Fortunately the building blocks are all there.

We reuse

  • pandoc via pypandoc for parsing markdown and rendering the final output

  • jupyter for language kernels, executing code, and collecting the output

  • Use pandocfilters to collate the execution output into the document

So all stitch has to do is to provide a command-line interface, scan the document for code chunks, manage some kernels, hand the code to the kernels, pass the output to an appropriate pandocfilter.

The biggest departure from knitpy is the use of pandoc’s JSON AST. This is what you get from pandoc -t json input.md

This saves us from having do any kind of custom parsing of the markdown. The only drawback so far is somewhat inscrutable Haskell exceptions if stitch happens to produce a bad document.

Documentation

Stitch’s documentation has an odd build process, so standard tools like readthedocs weren’t flexible enough. To make the docs, install stitch and all the extra dependencies. Clone https://github.com/pystitch/pystitch.github.io

Checkout the src branch.

Run make html.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

knotr-0.4.1.tar.gz (33.8 kB view details)

Uploaded Source

Built Distribution

knotr-0.4.1-py3-none-any.whl (22.3 kB view details)

Uploaded Python 3

File details

Details for the file knotr-0.4.1.tar.gz.

File metadata

  • Download URL: knotr-0.4.1.tar.gz
  • Upload date:
  • Size: 33.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for knotr-0.4.1.tar.gz
Algorithm Hash digest
SHA256 5647ef7f37a467284c4538e8c17f2ebba698258fbf45c5a68a38d0f9062de000
MD5 46cfb1b62bc7c7e02e6b27ded26dd055
BLAKE2b-256 59f4bfdea99dfe607e11113ff8fa3bd81ff20a2e4b236366f985f119746db504

See more details on using hashes here.

Provenance

File details

Details for the file knotr-0.4.1-py3-none-any.whl.

File metadata

File hashes

Hashes for knotr-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6b4ca9dd72e96e0cdc6511a73d6301bc734f746722044a721ca36cc8aa080913
MD5 cca5b2954e8f82c33e76d3ba084b3063
BLAKE2b-256 786b1af9b92787e9520aa6624ad1aa7f208803e609af5ae7bc17db86b406c953

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page