Metadata-Version: 2.1
Name: gs1-compression
Version: 0.0.8
Summary: A Python package to decompress compressed GS1 digital link
Home-page: https://github.com/Trust-Codes-Ltd/gs1-compression
Author: Di Zhu
Author-email: di.zhu@trust.codes
License: UNKNOWN
Description: # GS1 Digital Link Decompression Prototype in Python
        This is a Python translation of the JavaScript Toolkit that decompresses element strings to GS1 digital links.
        
        * [Background](#Background)
        * [Examples](#Examples)
        * [Installation](#Installation)
        * [Decompression](#Decompression)
        * [Contributors](#contributors)
        * [Disclaimer](#disclaimer)
        * [License](#License)
        
        ## Background
        
        The GS1 identification system is widely used worldwide within product barcodes, as well as within barcodes for shipments, assets, locations and so on.
        
        Further information about GS1 can be found at https://www.gs1.org
        
        Details about the GS1 identification system and GS1 Application Identifiers can be found in the GS1 General Specifications at https://www.gs1.org/docs/barcodes/GS1_General_Specifications.pdf and a searchable list of GS1 Application Identifiers is at https://www.gs1.org/standards/barcodes/application-identifiers?lang=en
        
        GS1 Digital Link is a new Web URI syntax for expressing GS1 Application Identifiers and their values in a Web-friendly format, to make it easier to connect identifiers of products, shipments, locations, assets etc. to related online information and services on the Web via simple Web redirects using Web resolver infrastructure.
        
        The GS1 Digital Link syntax is defined in https://www.gs1.org/standards/Digital-Link/1-0
        
        A demonstration tool is available at https://id.gs1.org/uritool although it does not currently use this toolkit
        
        See also https://github.com/gs1/digital-link.js for a related toolkit for GS1 Digital Link
        
        ## Examples
        
            https://dlnkd.tn.gg/01/09780345418913
            
            https://dlnkd.tn.gg/01/05412345000013/10/ABC%26%2B123?7003=1903061658&k1=v1
        
        ## Installation 
        
        To install, make sure Python3 is installed, and installation in a virtual environment is preferred.
        
            $ pip install gs1-compression
            
        ## Decompression
        
        To decompress a compressed GS1 Digital Link URI, import `decompress_gs1_digital_link`:
        
            >>> from gs1 import decompress_gs1_digital_link
        
        An example of decompression:
        
            >>> compressed_uri = "https://dlnkd.tn.gg/ARHKVAdpQg"
            >>> original_link = decompress_gs1_digital_link(compressed_uri, use_short_text=False, uri_stem="https://dlnkd.tn.gg")
            >>> print("Original Link: " + original_link)
                Original Link: https://dlnkd.tn.gg/01/09780345418913
        The `decompress_gs1_digital_link` function has three parameters.
        
        Set the second parameter, `use_short_text=True` if you prefer the GS1 Digital Link URI 
        to use alphabetic mnemonic short names as defined in the GS1 Digital Link standard, e.g. /gtin/. 
        Set it `False` if you prefer the GS1 Digital Link URI to use all-numeric GS1
         application identifiers, e.g. /01/.
        
        Set the third parameter, `uri_stem` to a valid URI prefix if you wish to construct 
        a GS1 Digital Link using a specific domain name. If it's set to be `None` or `''`,
        a default URI prefix `https://id.gs1.org` will be used.
        
        Thanks to https://github.com/gs1/GS1DigitalLinkCompressionPrototype
        
        ## Contributors
        
        - Di Zhu    di.zhu@trust.codes
        
        ## Sponsors
        
        - [Trust Codes Limited](https://www.trust.codes/) : Using anti-counterfeit solutions and supply-chain traceability, Trust Codes® data-driven software connects brands to consumers with item level serialisation and world leading algorithms. 
        
        ## Disclaimer
        
        ### Legal Notice
        In addition to the terms of the licence, this source code is provided by Trust Codes Limited, a New Zealand company, on an as-is basis, with no warranty expressed or implied. Neither Trust Codes Limited nor the contributors accept any liability for its use nor for any damages caused through its use. Trust Codes® is a registered trademark of Trust Codes Limited in New Zealand.
         
         All Rights Reserved.
          
          © Trust Codes Limited 2021.
        
        ## License
        
        Apache-2.0 License
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
