combine-notebooks - COMBINE jupyter notebooks in python
Project Overview
This repository contains Jupyter notebooks that showcase COMBINE standards and their libraries around one common theme; the repressilator model.
The following standards are demonstrated
Systems Biology Graphical Notation (SBGN): Used to describe visually biological knowledge.
Systems Biology Markup Language (SBML): Used for representing models of biological processes.
Simulation Experiment Description Markup Language (SED-ML): Used for encoding experiments. SED-ML allows defining the models to use, the experimental tasks to run, and which results to produce. It is a computer-readable format for representing the models of biological processes.
CellML: Used to store and exchange computer-based mathematical models.
Synthetic Biology Open Language (SBOL): Used for description and the exchange of synthetic biological parts, devices, and systems.
NeuroML: Used for XML based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models.
Setup/Installation
To work with the notebooks create a virtual environment and install the dependencies:
mkvirtualenv combine_notebooks --python=python3.10 (combine_notebooks) pip install -e .[development] --upgrade
After changes ensure code formatting via:
./fcode.sh
Tests can be run via pytest and tox. To run all tests use:
tox -p
To run individual tests use the following targets flake8, mypy, py38, py39, py310:
tox -e flake8
Notebooks
To run the notebooks install a notebook environment:
pip install jupyterlab
Register the created virtual environment combine_notebooks as jupyter kernel:
ipython kernel install --user --name=combine_notebooks
Or alternatively install the package in an existing virtual environment to get all the dependencies. I.e.:
pip install combine-notebooks
Start the notebooks:
cd ./notebooks jupyter lab
© 2022 Matthias König & Aditya Singhal
Metadata
Release files for combine-notebooks 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| combine_notebooks-0.1.4.tar.gz | 31.3 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| combine_notebooks-0.1.4-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 66.9 kB
Release files / combine_notebooks-0.1.4.tar.gz
| Download URL | combine_notebooks-0.1.4.tar.gz |
|---|---|
| Size | 31.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7a936f3eefbd04a8bf1afeb376d8573913ba729df24447db702a499edf2f8c44
|
|
BLAKE2b-256 checksum How to use checksums |
23d8e1f858f53379ee7b496b967f66af627d80c438d4f6ea93a5adcec336a943
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.8
|
Release files / combine_notebooks-0.1.4-py2.py3-none-any.whl
| Download URL | combine_notebooks-0.1.4-py2.py3-none-any.whl |
|---|---|
| Size | 35.6 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
5c73e1df6f7248d05dc85913c48532dbe37596f1ef4df5ee175faf840fcff0a2
|
|
BLAKE2b-256 checksum How to use checksums |
9ea6ffe3678e5635171afda475a6d2c5462a0e29bc2c4e691241da0dcd0fcfca
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.8
|
Security for combine-notebooks 0.1.4
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.