Pop2net
Pop2net is a Python package that combines many steps related to network generation and management for agent-based modeling using a bipartite approach: In Pop2net, relations are represented as a graph of actors and locations. While actors are the active entities within an agent-based model, locations act as a contact layer, representing specific contexts through which actors connect. This makes it easy to generate and manage custom network structures in an agent-based model.
Pop2net can be used within custom modeling frameworks and also integrates seamlessly with the agent-based modeling frameworks AgentPy and Mesa.
Installation
You can install Pop2net using pip:
pip install pop2net
Python 3.14.1 has a bug which causes networkX to crash, see this issue. If you use Python 3.14, make sure to use any other path version that 3.14.1.
Documentation
Detailed documentation of all features and a collection of example analyses can be found here.
How to contribute
Contributions are welcome!
See this guide
for details on how to get started.
Citation
If you are using Pop2net, please cite the corresponding software release paper in the Journal of Open Source Software:
- Kaffai et al., (2026). Pop2net: Bipartite network generation for agent-based modeling. Journal of Open Source Software, 11(117), 7897, https://doi.org/10.21105/joss.07897
BibTeX:
@article{Kaffai2026, doi = {10.21105/joss.07897}, url = {https://doi.org/10.21105/joss.07897}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {117}, pages = {7897}, author = {Kaffai, Marius and Erhard, Lukas and Richter, Maximilian}, title = {Pop2net: Bipartite network generation for agent-based modeling}, journal = {Journal of Open Source Software} }
Release files for pop2net 1.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pop2net-1.3.0.tar.gz | 34.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pop2net-1.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 73.2 kB
Release files / pop2net-1.3.0.tar.gz
| Download URL | pop2net-1.3.0.tar.gz |
|---|---|
| Size | 34.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
737ced069141a5254e9f18a2ce55673356b3d5ce1d651bfe9b1d9c2a2d17ec99
|
|
BLAKE2b-256 checksum How to use checksums |
396c2a186e806db111509c48332bc304277edd94c3193fe93ba5f80a119cef12
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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 Sep 29, 2026.
Transparency logRelease files / pop2net-1.3.0-py3-none-any.whl
| Download URL | pop2net-1.3.0-py3-none-any.whl |
|---|---|
| Size | 38.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b2a0f361f55417f6c3b1bbad6d0cd88b20b8298f10e66e247b5dacafc4dcc910
|
|
BLAKE2b-256 checksum How to use checksums |
95c14c1bef7d1e55b10ff5ee7fc85d6c1a73a1b09ab96105a48ef7d937c7f165
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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 Sep 29, 2026.
Transparency log
