PAMPA-SEARCH: A minimalist graph navigation library to solve path-finding optimization problems
PAMPA-SEARCH provides basic state-space-search in graphs (graph navigation) for path-finding optimization problems. It has configurable features that allows the user to adapt it to the problem at hand. Its first use was to solve maze problems (see examples).
The library works both for manually created graphs or for problems in which the graph is created dinamically through iterations/movements in the problem. For that purpose, the user can create a class to describe its problems.
Functionalities
- works for manually created graphs and for dinamically created graphs (when the state-space is implicit);
- to solve specific path-finding problems, it interacts with specific problems through a user-defined class which require a minimal number of methods;
- implements Depth-first, Breadth-first and A* (A star) algorithms
Problem and Examples
There is a Maze solver example already implemented inside the library.
Depth-first strategy on a 20x20 maze
Breadth-first strategy on a 20x20 maze
A* strategy on a 20x20 maze
About the author and license
- Copyright 2026 Tiago Oliveira Weber
- License: MIT License
- Repository: https://github.com/tiagoweber/pampa-search
- Author professional website: www.tiagoweber.com.br
- Contact: tiago.oliveira.weber@gmail.com
1 maintainer
Metadata
1 maintainer
Release files for pampa-search 0.1.14
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pampa_search-0.1.14.tar.gz | 10.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pampa_search-0.1.14-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.6 kB
Release files / pampa_search-0.1.14.tar.gz
| Download URL | pampa_search-0.1.14.tar.gz |
|---|---|
| Size | 10.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ac28de26dd418271c77843949533ad0625ac83cd501d73838f732213031aa3f5
|
|
BLAKE2b-256 checksum How to use checksums |
e45d1edd76969e0ab865e3d57b8c5ed191331efdcc8ac8b9e9c116bb1d93c359
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
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 Mar 12, 2026.
Transparency logRelease files / pampa_search-0.1.14-py3-none-any.whl
| Download URL | pampa_search-0.1.14-py3-none-any.whl |
|---|---|
| Size | 10.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8a322378e1f4992c946f7d4270df3a4b9c056cacde6daed1e3576bfee607a0a1
|
|
BLAKE2b-256 checksum How to use checksums |
4528b3565f8699273e31830a4cf805bbf5d7310011f7fc83814420158af33fe9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
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 Mar 12, 2026.
Transparency log
