Skip to main content

PAMPA-SEARCH: A minimalist and generic graph search library made to be usable to solve state-search-space problems such as routing.

Project description

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

Depth-first strategy on a 20x20 maze

Breadth-first strategy on a 20x20 maze

Breadth-first strategy on a 20x20 maze

A* strategy on a 20x20 maze

A* strategy on a 20x20 maze

About the author and license

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pampa_search-0.1.7.tar.gz (9.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pampa_search-0.1.7-py3-none-any.whl (9.7 kB view details)

Uploaded Python 3

File details

Details for the file pampa_search-0.1.7.tar.gz.

File metadata

  • Download URL: pampa_search-0.1.7.tar.gz
  • Upload date:
  • Size: 9.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pampa_search-0.1.7.tar.gz
Algorithm Hash digest
SHA256 1a2a12c0ab77162b67aabb62e769a4d8b9f302fd2a1c3c3a0a986b03dde2b4e6
MD5 808890566c8789d6b6037013c6441c6f
BLAKE2b-256 198175a3b4f9f07e03921278880d59b2d6dac07c3f6df9567de660f6adeb72f9

See more details on using hashes here.

Provenance

The following attestation bundles were made for pampa_search-0.1.7.tar.gz:

Publisher: pypi-publish.yml on tiagoweber/pampa-search

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pampa_search-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: pampa_search-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 9.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pampa_search-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 d0fcc43688d285d7f2ac7ad6ab199854515630cec5bc2b57455d463bb51ca411
MD5 a0e0152d454def2a85ee8599d2e3dabe
BLAKE2b-256 2759dc20da57b2ed7c0bd7c6b09899e732f7088c03706db9b9af2158c246562c

See more details on using hashes here.

Provenance

The following attestation bundles were made for pampa_search-0.1.7-py3-none-any.whl:

Publisher: pypi-publish.yml on tiagoweber/pampa-search

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page