pybatchclassyfire
This package provides a set of helper functions in python for annotating chemical structures with the chemical ontology developed by Djoumbou et. al using the ClassyFire API
Such function are available from the pyclassyfire package (https://github.com/JamesJeffryes/pyclassyfire) developped by James Jeffryes and from pyMolNetEnhancer (https://pypi.org/project/pyMolNetEnhancer/) package written by Madeleine Ernst, which relied in part on pyclassyfire.
However the ClassyFire API now only returns paginated JSON files (10 compounds/page) see http://classyfire.wishartlab.com/access and tolerates no more than 10 GET request per second.
Building on pyclassyfire and pyMolNetEnhancer functions, pybatchclassyfire as for objective to overcome these limits and allow the batch classification of large tables of structures.
Table of contents
Instalation
Install pybatchclassyfire with:
pip install pybatchclassyfire
And additional required packages with:
pip install -r requirements.txt
Running the batch classification
In order to run the batch classification make sure to have InChI and InChIKey formated chemical structures. Check Getting Started with the RDKit in Python for format conversion process.
- After installation of the pybatchclassyfire package, download the corresponding gitlab repository
git clone https://gitlab.unige.ch/Pierre-Marie.Allard/pybatchclassyfire.git
-
Make sure to be able to run the Jupyter notebook (pybatchclassyfire_nb.ipynb) on the example file (test_datatable.tsv)
-
Adapt Jupyter notebook to treat your file.
Dependencies
decorator==4.4.2 joblib==0.14.1 networkx==2.4 numpy==1.18.2 pandas==1.0.3 pybatchclassyfire==0.1.3 python-dateutil==2.8.1 pytz==2019.3 requests>=2.6 requests-cache==0.5.2 six==1.14.0
Main citation
https://gitlab.unige.ch/Pierre-Marie.Allard/pybatchclassyfire.git
License
This repository is available under the following license https://gitlab.unige.ch/Pierre-Marie.Allard/pybatchclassyfire/-/blob/master/LICENSE.md
1 maintainer
Metadata
1 maintainer
Release files for pybatchclassyfire 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pybatchclassyfire-0.1.6-py3-none-any.whl | Python 3 | none | any | Details for pybatchclassyfire-0.1.6-py3-none-any.whl |
Release files / pybatchclassyfire-0.1.6-py3-none-any.whl
| Download URL | pybatchclassyfire-0.1.6-py3-none-any.whl |
|---|---|
| Size | 9.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
caad263c26e6404eb61de0fd90f1a3a05e161b88069ce186ee73494b77ddbd2d
|
|
BLAKE2b-256 checksum How to use checksums |
96cfd264ca45cbceb92bff290a61a197f3ecc6d250c7594d9ff56d5e597d1076
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.33.0 CPython/3.7.4
|
Security for pybatchclassyfire 0.1.6
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
