Add test coverage

.travis.yml

@@ -5,8 +5,9 @@ python:
   - "3.5"
   - "3.6"
 install:
-  - pip install -r requirements.txt
-# command to run tests
+  - pip install pytest-cov coveralls -r requirements.txt
 script:
-  - pytest
+  - pytest --cov=pynif
 
+after_success:
+  - coveralls

README.md

@@ -1,4 +1,4 @@
-# pynif [![Build Status](https://travis-ci.org/wetneb/pynif.svg?branch=master)](https://travis-ci.org/wetneb/pynif)
+# pynif [![Build Status](https://travis-ci.org/wetneb/pynif.svg?branch=master)](https://travis-ci.org/wetneb/pynif) [![Coverage Status](https://coveralls.io/repos/github/wetneb/pynif/badge.svg?branch=master)](https://coveralls.io/github/wetneb/pynif?branch=master)
 
 The [NLP Interchange Format (NIF)](http://persistence.uni-leipzig.org/nlp2rdf/) is an RDF/OWL-based format that aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. It offers a standard representation of annotated texts for tasks such as [Named Entity Recognition](https://en.wikipedia.org/wiki/Named-entity_recognition) or [Entity Linking](https://en.wikipedia.org/wiki/Entity_linking). It is used by [GERBIL](https://github.com/dice-group/gerbil) to run reproducible evaluations of annotators.
 

README.rst

@@ -1,15 +1,19 @@
-pynif
-=====
-
-`Build Status <https://travis-ci.org/wetneb/pynif>`__
-
-What is NIF (NLP Interchange Format) ?
---------------------------------------
-
-The NLP Interchange Format (NIF) is an RDF/OWL-based format that aims to
-achieve interoperability between Natural Language Processing (NLP)
-tools, language resources and annotations. NIF consists of
-specifications, ontologies and software (overview).
+pynif `Build Status <https://travis-ci.org/wetneb/pynif>`__ `Coverage Status <https://coveralls.io/github/wetneb/pynif?branch=master>`__
+========================================================================================================================================
+
+The `NLP Interchange Format
+(NIF) <http://persistence.uni-leipzig.org/nlp2rdf/>`__ is an
+RDF/OWL-based format that aims to achieve interoperability between
+Natural Language Processing (NLP) tools, language resources and
+annotations. It offers a standard representation of annotated texts for
+tasks such as `Named Entity
+Recognition <https://en.wikipedia.org/wiki/Named-entity_recognition>`__
+or `Entity Linking <https://en.wikipedia.org/wiki/Entity_linking>`__. It
+is used by `GERBIL <https://github.com/dice-group/gerbil>`__ to run
+reproducible evaluations of annotators.
+
+This Python library can be used to serialize and deserialized annotated
+corpora in NIF.
 
 Documentation
 -------------
@@ -19,20 +23,27 @@ Documentation
 Supported NIF versions
 ----------------------
 
--  2.1
+NIF 2.1, serialized in `any of the formats supported by
+rdflib <https://rdflib.readthedocs.io/en/stable/plugin_parsers.html>`__
 
-Supported RDF formats
----------------------
+Overview
+--------
 
--  `All the formats supported by
-   rdflib <https://rdflib.readthedocs.io/en/stable/plugin_parsers.html>`__
+This library is revolves around three core classes: \* a ``NIFContext``
+is a document (a string); \* a ``NIFPhrase`` is the annotation of a
+snippet of text (usually a phrase) in a document; \* a ``NIFCollection``
+is a set of documents, which constitutes a collection. In NIF, each of
+these objects is identified by a URI, and their attributes and relations
+are encoded by RDF triples between these URIs. This library abstracts
+away the encoding by letting you manipulate collections, contexts and
+phrases as plain Python objects.
 
-Usage
------
+Quick start
+-----------
 
 0) Import and create a collection
 
-::
+.. code:: python
 
    from pynif import NIFCollection
 
@@ -42,15 +53,15 @@ Usage
 
 1) Create a context
 
-::
+.. code:: python
 
    context = collection.add_context(
        uri="http://freme-project.eu/doc32",
        mention="Diego Maradona is from Argentina.")
 
 2) Create entries for the entities
 
-::
+.. code:: python
 
    context.add_phrase(
        beginIndex=0,
@@ -72,16 +83,57 @@ Usage
 
 3) Finally, get the output with the format that you need
 
-::
+.. code:: python
 
    generated_nif = collection.dumps(format='turtle')
    print(generated_nif)
 
-You can then parse it back:
-
-::
-
-   parsed_collection = NIFCollection.loads(generated_nif)
+You will obtain the NIF representation as a string:
+
+.. code:: turtle
+
+   <http://freme-project.eu> a nif:ContextCollection ;
+       nif:hasContext <http://freme-project.eu/doc32> ;
+       ns1:conformsTo <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core/2.1> .
+
+   <http://freme-project.eu/doc32> a nif:Context,
+           nif:OffsetBasedString ;
+       nif:beginIndex "0"^^xsd:nonNegativeInteger ;
+       nif:endIndex "33"^^xsd:nonNegativeInteger ;
+       nif:isString "Diego Maradona is from Argentina." .
+
+   <http://freme-project.eu/doc32#offset_0_14> a nif:OffsetBasedString,
+           nif:Phrase ;
+       nif:anchorOf "Diego Maradona" ;
+       nif:beginIndex "0"^^xsd:nonNegativeInteger ;
+       nif:endIndex "14"^^xsd:nonNegativeInteger ;
+       nif:referenceContext <http://freme-project.eu/doc32> ;
+       nif:taMsClassRef <http://dbpedia.org/ontology/SoccerManager> ;
+       itsrdf:taAnnotatorsRef <http://freme-project.eu/tools/freme-ner> ;
+       itsrdf:taClassRef <http://dbpedia.org/ontology/Person>,
+           <http://dbpedia.org/ontology/SportsManager>,
+           <http://nerd.eurecom.fr/ontology#Person> ;
+       itsrdf:taConfidence 9.869993e-01 ;
+       itsrdf:taIdentRef <http://dbpedia.org/resource/Diego_Maradona> .
+
+   <http://freme-project.eu/doc32#offset_23_32> a nif:OffsetBasedString,
+           nif:Phrase ;
+       nif:anchorOf "Argentina" ;
+       nif:beginIndex "23"^^xsd:nonNegativeInteger ;
+       nif:endIndex "32"^^xsd:nonNegativeInteger ;
+       nif:referenceContext <http://freme-project.eu/doc32> ;
+       nif:taMsClassRef <http://dbpedia.org/resource/Argentina> ;
+       itsrdf:taAnnotatorsRef <http://freme-project.eu/tools/freme-ner> ;
+       itsrdf:taClassRef <http://dbpedia.org/ontology/Place>,
+           <http://dbpedia.org/ontology/PopulatedPlace>,
+           <http://nerd.eurecom.fr/ontology#Location> ;
+       itsrdf:taConfidence 9.804964e-01 .
+
+4) You can then parse it back:
+
+.. code:: python
+
+   parsed_collection = NIFCollection.loads(generated_nif, format='turtle')
 
    for context in parsed_collection.contexts:
       for phrase in context.phrases:
@@ -92,9 +144,4 @@ Issues
 
 If you have any problems with or questions about this library, please
 contact us through a `GitHub
-issue <https://github.com/NLP2RDF/pyNIF-lib/issues>`__.
-
-Maintainers
------------
-
-
+issue <https://github.com/wetneb/pynif/issues>`__.

requirements.txt

@@ -1,2 +1 @@
-pytest
 rdflib