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PyLD
====

.. image:: https://travis-ci.org/digitalbazaar/pyld.png?branch=master
   :target: https://travis-ci.org/digitalbazaar/pyld
   :alt: Build Status

Introduction
------------

This library is an implementation of the JSON-LD_ specification in Python_.

JSON, as specified in RFC7159_, is a simple language for representing
objects on the Web. Linked Data is a way of describing content across
different documents or Web sites. Web resources are described using
IRIs, and typically are dereferencable entities that may be used to find
more information, creating a "Web of Knowledge". JSON-LD_ is intended
to be a simple publishing method for expressing not only Linked Data in
JSON, but for adding semantics to existing JSON.

JSON-LD is designed as a light-weight syntax that can be used to express
Linked Data. It is primarily intended to be a way to express Linked Data
in JavaScript and other Web-based programming environments. It is also
useful when building interoperable Web Services and when storing Linked
Data in JSON-based document storage engines. It is practical and
designed to be as simple as possible, utilizing the large number of JSON
parsers and existing code that is in use today. It is designed to be
able to express key-value pairs, RDF data, RDFa_ data,
Microformats_ data, and Microdata_. That is, it supports every
major Web-based structured data model in use today.

The syntax does not require many applications to change their JSON, but
easily add meaning by adding context in a way that is either in-band or
out-of-band. The syntax is designed to not disturb already deployed
systems running on JSON, but provide a smooth migration path from JSON
to JSON with added semantics. Finally, the format is intended to be fast
to parse, fast to generate, stream-based and document-based processing
compatible, and require a very small memory footprint in order to operate.

Requirements
------------

- Python_ (2.7 or later)

Installation
------------

PyLD can be installed with pip_:

.. code-block:: bash

    pip install PyLD

Quick Examples
--------------

.. code-block:: Python

    from pyld import jsonld
    import json

    doc = {
        "http://schema.org/name": "Manu Sporny",
        "http://schema.org/url": {"@id": "http://manu.sporny.org/"},
        "http://schema.org/image": {"@id": "http://manu.sporny.org/images/manu.png"}
    }

    context = {
        "name": "http://schema.org/name",
        "homepage": {"@id": "http://schema.org/url", "@type": "@id"},
        "image": {"@id": "http://schema.org/image", "@type": "@id"}
    }

    # compact a document according to a particular context
    # see: http://json-ld.org/spec/latest/json-ld/#compacted-document-form
    compacted = jsonld.compact(doc, context)

    print(json.dumps(compacted, indent=2))
    # Output:
    # {
    #   "@context": {...},
    #   "image": "http://manu.sporny.org/images/manu.png",
    #   "homepage": "http://manu.sporny.org/",
    #   "name": "Manu Sporny"
    # }

    # compact using URLs
    jsonld.compact('http://example.org/doc', 'http://example.org/context')

    # expand a document, removing its context
    # see: http://json-ld.org/spec/latest/json-ld/#expanded-document-form
    expanded = jsonld.expand(compacted)

    print(json.dumps(expanded, indent=2))
    # Output:
    # [{
    #   "http://schema.org/image": [{"@id": "http://manu.sporny.org/images/manu.png"}],
    #   "http://schema.org/name": [{"@value": "Manu Sporny"}],
    #   "http://schema.org/url": [{"@id": "http://manu.sporny.org/"}]
    # }]

    # expand using URLs
    jsonld.expand('http://example.org/doc')

    # flatten a document
    # see: http://json-ld.org/spec/latest/json-ld/#flattened-document-form
    flattened = jsonld.flatten(doc)
    # all deep-level trees flattened to the top-level

    # frame a document
    # see: http://json-ld.org/spec/latest/json-ld-framing/#introduction
    framed = jsonld.frame(doc, frame)
    # document transformed into a particular tree structure per the given frame

    # normalize a document
    normalized = jsonld.normalize(doc, {'format': 'application/nquads'})
    # normalized is a string that is a canonical representation of the document
    # that can be used for hashing

Commercial Support
------------------

Commercial support for this library is available upon request from
`Digital Bazaar`_: support@digitalbazaar.com.

Source
------

The source code for the Python implementation of the JSON-LD API
is available at:

http://github.com/digitalbazaar/pyld

Tests
-----

This library includes a sample testing utility which may be used to verify
that changes to the processor maintain the correct output.

To run the sample tests you will need to get the test suite files by cloning
the ``json-ld.org`` repository hosted on GitHub:

https://github.com/json-ld/json-ld.org

Then run the test application using the directory containing the tests:

.. code-block:: bash

    python tests/runtests.py -d {PATH_TO_JSON_LD_ORG/test-suite}

.. _Digital Bazaar: http://digitalbazaar.com/
.. _JSON-LD: http://json-ld.org/
.. _Microdata: http://www.w3.org/TR/microdata/
.. _Microformats: http://microformats.org/
.. _Python: http://www.python.org/
.. _RDFa: http://www.w3.org/TR/rdfa-core/
.. _RFC7159: http://tools.ietf.org/html/rfc7159
.. _pip: http://www.pip-installer.org/