Python parser for Scientific datasets
Project description
sciparse - Scientific Dataset parsing
Getting Started
Features
Common Issues
How to Use
Adding Additional Unit Tests
- Any time you want to add additional unit tests just add them to those in the
tests/
directory and prepend with the nametest
. These will be automatically found by pytest and run during local commits and remote builds.
Writing the Documentation
- The documentation source is located in
docs/source
and is written in restructured text (markdown is also available).
Building the Documentation
Simply run make html
from the docs/
directory. This will compile the
files in the docs/source/
directory, and place them in the main docs/
directory where github pages can find them.
Dependencies / Technologies Used
Acknowledgements
Thanks to all the great people on stack overflow and github, for their seemingly boundless tolerance to my and others' questions.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sciparse-0.1.22.tar.gz
(2.7 kB
view hashes)
Built Distribution
sciparse-0.1.22-py3-none-any.whl
(16.9 kB
view hashes)
Close
Hashes for sciparse-0.1.22-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9e50ce73339424fa0d9afc7b855ac578ba02620c87bf1119fdeb8befd1cc0870 |
|
MD5 | aa89754fa51619910cf1ab252e172994 |
|
BLAKE2b-256 | 39097ed4f4bb69b7aa87dd1ed1d940a128c0e7952444f7981957ce2ef827386c |