Skip to main content

Library to create databases using graphs from networkx. Covers the challenge of Foodvisor

Project description

FoodVisor Challenge 1

FoodNetx is a library created using the python package NetworkX. It creates a database based in graphs, in concrete a Directed graph, in which could occur cycles. The main idea is cover the challenge of Foodvisor ( Challenge1 and Challenge2 ) but any other use is welcomed, please if it used reference this Github and its creator.

Installation

Source file

  1. Download the source file from github
  2. Unzip and navigate to the folder containing setup.py and other files
  3. Run the following command: python setup.py install

Pip

    pip3 install FoodNetX

Testing and replicating the results for the Foodvisor challenges

Download and install the python package FoodNetx, then clone the repo. In the Github repository has been left a folder called Test, where tests are stored. To execute any test, just use the following shell command from inside the github repo:

python3 ./Test/TestFile.py

Example:

python3 ./Test/FoodVisor_Challenge1_test.py

If you use an IDE for programming just select the test file desired and just click Run.

Test's outputs

FoodVisor_Challenge1_test.py:

{"img001": "granularity_staged", "img002": "valid"}
{"img001": "granularity_staged", "img002": "coverage_staged", "img003": "invalid"}

New modules in development

By now the foodvisor challenge #2 is being developed and implemented to join this package at the end of this week

Python Compatibility

Note

This library has been created with the help of Networkx and Matplotlib

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

FoodNetX-0.2.tar.gz (4.8 kB view details)

Uploaded Source

File details

Details for the file FoodNetX-0.2.tar.gz.

File metadata

  • Download URL: FoodNetX-0.2.tar.gz
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.2

File hashes

Hashes for FoodNetX-0.2.tar.gz
Algorithm Hash digest
SHA256 e9c685041ade95a85f49d2fc335e658c4eafd5bea683294aba8fc166d46a3893
MD5 6030aae9e81c0ce2b177e1278f2ded1f
BLAKE2b-256 96af5fb26c4ffcab7a9e6dfde49d48ea024095e336b3a72e763183d5b2ae1da9

See more details on using hashes here.

Supported by

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