BN Modeller
An open-source application designed to facilitate feature dependency modeling and evaluation using Bayesian Networks.
User Guide
You can obtain user guides for BN Modeller application with the following link https://digiratory.github.io/bayes_model/. It covers various aspects of using BN Modeller, including data analysis workflows, best practices, and more.
Instalation
From sources
You can install this project from sources by cloning this repository and installing it using pip:
git clone https://github.com/Digiratory/bayes_model.git && cd bayes_model
pip install .
Using PyPI
You can install this project using pip:
pip install bn_modeller
Using executable file (windows only)
You can download the latest Windows executable from the BN Modeller GitHub Releases page.
Graphviz
A Graphviz error could arise. To solve the problem install and add the Graphviz executables on your systems' PATH as follows:
Windows
- Install windows package from: https://graphviz.org/download/ (Linux and Mac instructions can be found here as well)
- Install python graphviz package
- Press the Windows key
- Type in the search box: edit environment variables for your account
- Select Path
- Click Edit… button
- Click New
- Add 'bin' folder to User path in environment variables manager (e.g: C:\Program Files (x86)\Graphviz2.38\bin)
- Add location dot.exe to System Path (e.g: C:\Program Files (x86)\Graphviz2.38\bin\dot.exe)
- Click OK and OK again
Once have done that, restart your python IDE (if it is open). If this was running in a CMD prompt (e.g. Anaconda Command prompt), restart this prompt as well to make sure the prompt finds the new environment variables.
https://pygraphviz.github.io/documentation/stable/install.html
Linux
sudo apt-get update && sudo apt-get install graphviz graphviz-dev
Launch Application
To launch the application installed with pip, run:
bn_modeller
If you have downloaded BN Modeller using the Windows executable, simply double-click the bn_modeller.exe file located in the directory.
Build
Build Executable file for Windows
- Install pyinstaller
- Execute the following command:
pyinstaller bn_modeller.exe.spec
Troubleshooting
High storage utilization on Windows 10/11
This high storage utilization probably caused by WindowsSearch Engine. To mitigate the problem you should disable the indexing of content for .sqlite files as following.
- Press Win to open Start Menu and type in Index.
- Click on Indexing Options.
- On this next screen, hit Advanced > (Tab) File Types. For extention
.sqliteselect "Index Properties Only".
Metadata
Release files for bn-modeller 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bn_modeller-1.0.0.tar.gz | 96.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bn_modeller-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 210.4 kB
Release files / bn_modeller-1.0.0.tar.gz
| Download URL | bn_modeller-1.0.0.tar.gz |
|---|---|
| Size | 96.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 12, 2025.
Transparency logRelease files / bn_modeller-1.0.0-py3-none-any.whl
| Download URL | bn_modeller-1.0.0-py3-none-any.whl |
|---|---|
| Size | 114.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
52d36f98f37c9b39f2de4af807741560be573ec7f30eb7de0d6836e3c53d34ab
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 12, 2025.
Transparency log