Skip to main content

Defines EPCIS models and XML parsing.

Project description

https://gitlab.com/serial-lab/quartet_epcis/badges/master/pipeline.svg https://gitlab.com/serial-lab/quartet_epcis/badges/master/coverage.svg https://badge.fury.io/py/quartet_epcis.svg

Built on top of the world-class EPCPyYes python package. Real EPCIS support for serious people running real systems.

 ________  ___   ___  _______   ________  ________  ___  ________
|\   __  \|\  \ |\  \|\  ___ \ |\   __  \|\   ____\|\  \|\   ____\
\ \  \|\  \ \  \\_\  \ \   __/|\ \  \|\  \ \  \___|\ \  \ \  \___|_
 \ \  \\\  \ \______  \ \  \_|/_\ \   ____\ \  \    \ \  \ \_____  \
  \ \  \\\  \|_____|\  \ \  \_|\ \ \  \___|\ \  \____\ \  \|____|\  \
   \ \_____  \     \ \__\ \_______\ \__\    \ \_______\ \__\____\_\  \
    \|___| \__\     \|__|\|_______|\|__|     \|_______|\|__|\_________\
          \|__|                                            \|_________|

The essential Open-Source EPCIS component for the QU4RTET traceability platform.

For more on QU4RTET see http://www.serial-lab.com

The quartet_epcis python package is a Django application that contains the base database models necessary for the support of EPCIS 1.2 data persistence to an RDBMS. The quartet_epcis.parsing package contains an EPCIS XML parser that will take an input stream of XML data and save it to a configured database back-end.

The quartet_epcis.app_models directory contains a set of Django ORM models that are used to define the database scheme and store EPCIS data in the database.

Documentation

Find the latest docs here:

https://serial-lab.gitlab.io/quartet_epcis/

The full (pre-built )documentation is under the docs directory in this project.

Quickstart

Install QU4RTET EPCIS

pip install quartet_epcis

Add it to your INSTALLED_APPS:

INSTALLED_APPS = (
    ...
    'quartet_epcis',
    ...
)

Features

  • Maintains the database schema for EPCIS 1.2 support.

  • Parses EPCIS 1.2 XML streams to the configured backend database system.

  • Enforces business rules around decommissioning, commissioning, aggregation, disaggregation, etc.

Running The Unit Tests

source <YOURVIRTUALENV>/bin/activate
(myenv) $ pip install -r requirements_test.txt
(myenv) $ python runtests.py

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

quartet_epcis-1.6.6.tar.gz (51.5 kB view details)

Uploaded Source

Built Distribution

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

quartet_epcis-1.6.6-py2.py3-none-any.whl (55.4 kB view details)

Uploaded Python 2Python 3

File details

Details for the file quartet_epcis-1.6.6.tar.gz.

File metadata

  • Download URL: quartet_epcis-1.6.6.tar.gz
  • Upload date:
  • Size: 51.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.6

File hashes

Hashes for quartet_epcis-1.6.6.tar.gz
Algorithm Hash digest
SHA256 495423208e9f39ff0a2feaeccc56677dc208822d98edbe061e61b296e89c4e2c
MD5 745c5136a1086f53e41ac6661c25783d
BLAKE2b-256 299025123a4b36c01d30bde72339a29ed51d8e799370c51d4cd86be45a5ea305

See more details on using hashes here.

File details

Details for the file quartet_epcis-1.6.6-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for quartet_epcis-1.6.6-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 9275a5ffa71689e25c8b1ae2721f9d89dd007c80ea172baa69f007ec77f59a3f
MD5 6ccf3d500e5f5a03479fd608d42abfa5
BLAKE2b-256 5f116ef6d24ff3e84eb5e9c603c4eeeea7e6e5c984b4308e33baa74eacdbecbb

See more details on using hashes here.

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