docs(README.md): updating documentation

Author: gerardobort

README.md

@@ -34,7 +34,7 @@ You may want to download, apart of the full package, other language models (see
 
 ### 3. Configure Stanford CoreNLP
 
-#### 3.1. Use CoreNLP as HTTP Server
+#### 3.1. Using StanfordCoreNLPServer
 
 ```bash
 # Run the server using all jars in the current directory (e.g., the CoreNLP home directory)
@@ -44,35 +44,45 @@ java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port 9000 -t
 CoreNLP connects by default via StanfordCoreNLPServer, using port 9000.  You can also opt to setup the connection differently:
 
 ```javascript
-import CoreNLP from 'corenlp';
+import CoreNLP, { Properties, Pipeline, ConnectorServer } from 'corenlp';
 
-CoreNLP.setup('English', new CoreNLP.connector.ConnectorServer({ dsn: 'http://localhost:9000' }));
+const connector = new ConnectorServer({ dsn: 'http://localhost:9000' });
+const props = new Properties({
+  annotators: 'tokenize,ssplit,pos,lemma,ner,parse',
+});
+const pipeline = new Pipeline(props, 'English', connector);
 ```
 
 #### 3.2. Use CoreNLP via CLI
 
 CoreNLP expects by default the StanfordCoreNLP package to be placed (unzipped) inside the path `${YOUR_NPM_PROJECT_ROOT}/corenlp/`.  You can also opt to setup the CLI interface differently:
 
 ```javascript
-import CoreNLP from 'corenlp';
-
-CoreNLP.setup('Spanish', new CoreNLP.connector.ConnectorCli({
-  // specify the paths relative to your project root
-  classPath: 'corenlp/stanford-corenlp-full-2017-06-09/*',
-  mainClass: 'edu.stanford.nlp.pipeline.StanfordCoreNLP',
-  props: 'StanfordCoreNLP-spanish.properties',
-}));
+import CoreNLP, { Properties, Pipeline, ConnectorCli } from 'corenlp';
+
+const connector = new ConnectorCli({
+  classPath: 'corenlp/stanford-corenlp-full-2017-06-09/*', // specify the paths relative to your npm project root
+  mainClass: 'edu.stanford.nlp.pipeline.StanfordCoreNLP', // optional
+  props: 'StanfordCoreNLP-spanish.properties', // optional
+});
+const props = new Properties({
+  annotators: 'tokenize,ssplit,pos,lemma,ner,parse',
+});
+const pipeline = new Pipeline(props, 'English', connector);
 ```
 
 ### 4. Use it
 
 ```javascript
-// ...
+// ... initialize pipeline first (see above)
 
 const sent = new CoreNLP.simple.Sentence('Hello world');
-sent.applyAnnotator(CoreNLP.simple.annotator.TokenizerAnnotator)
-  .then(() => {
+pipeline.annotate(sent)
+  .then(sent => {
     console.log(sent.words());
+  })
+  .catch(err => {
+    console.log('err', err);
   });
 ```
 
@@ -84,29 +94,16 @@ NOTE2: The examples below assumes `es6` syntax, if you use require, use as follo
 ### English
 
 ```javascript
-import CoreNLP from 'corenlp';
+import CoreNLP, { Properties, Pipeline } from 'corenlp';
 
-CoreNLP.setup('English'); // check method docs for more setup options
-const sent = new CoreNLP.simple.Sentence('The little dog runs so fast.');
-sent.applyAnnotator(CoreNLP.simple.annotator.ParserAnnotator)
-  .then(() => {
-    console.log('parse', sent.parse());
-    console.log(CoreNLP.util.Tree.fromSentence(sent).dump());
-  })
-  .catch(err => {
-    console.log('err', err);
-  });
-```
-
-### Spanish
+const props = new Properties({
+  annotators: 'tokenize,ssplit,pos,lemma,ner,parse',
+});
+const pipeline = new Pipeline(props, 'English'); // uses ConnectorServer by default
 
-```javascript
-import CoreNLP from 'corenlp';
-
-CoreNLP.setup('Spanish'); // check method docs for more setup options
-const sent = new CoreNLP.simple.Sentence('El pájaro veloz come kiwi.');
-sent.applyAnnotator(CoreNLP.simple.annotator.ParserAnnotator)
-  .then(() => {
+const sent = new CoreNLP.simple.Sentence('The little dog runs so fast.');
+pipeline.annotate(sent)
+  .then(sent => {
     console.log('parse', sent.parse());
     console.log(CoreNLP.util.Tree.fromSentence(sent).dump());
   })
@@ -121,6 +118,11 @@ We will update this section soon.  In the meantime, you can browse the project c
 In summary, this NodeJS library aims to replicate the CoreNLP Simple Java interface but in Javascript.  There are some minor differences however, for example the need to call `applyAnnotator` asynchronously.
 
 ```bash
+Properties
+Pipeline
+Service
+ConnectorCli
+ConnectorServer
 CoreNLP
   connector
     ConnectorServer               # https://stanfordnlp.github.io/CoreNLP/corenlp-server.html

package.json

@@ -48,6 +48,7 @@
   },
   "devDependencies": {
     "babel-core": "^6.25.0",
+    "babel-plugin-transform-export-extensions": "^6.22.0",
     "babel-plugin-transform-object-rest-spread": "^6.26.0",
     "babel-polyfill": "^6.23.0",
     "babel-preset-env": "^1.6.0",

src/index.js

@@ -1,5 +1,3 @@
-import Properties from './properties';
-import Pipeline from './pipeline';
 import Document from './simple/document';
 import Sentence from './simple/sentence';
 import Token from './simple/token';
@@ -14,24 +12,23 @@ import ParserAnnotator from './simple/annotator/parse';
 import DependencyParseAnnotator from './simple/annotator/depparse';
 import RelationExtractorAnnotator from './simple/annotator/relation';
 import RegexNERAnnotator from './simple/annotator/regexner';
-import Service from './service';
-import ConnectorServer from './connector/connector-server';
-import ConnectorCli from './connector/connector-cli';
 import Tree from './util/tree';
+import _Properties from './properties';
+import _Pipeline from './pipeline';
+import _Service from './service';
+import _ConnectorCli from './connector/connector-cli';
+import _ConnectorServer from './connector/connector-server';
+
+export const Properties = _Properties;
+export const Pipeline = _Pipeline;
+export const Service = _Service;
+export const ConnectorCli = _ConnectorCli;
+export const ConnectorServer = _ConnectorServer;
 
 /**
  * CoreNLP NodeJS Interface
  */
 export default {
-  connector: {
-    ConnectorServer,
-    ConnectorCli,
-  },
-
-  Properties,
-  Pipeline,
-  Service,
-
   /**
    * https://stanfordnlp.github.io/CoreNLP/simple.html
    */

src/index.spec.js

@@ -1,4 +1,9 @@
-import CoreNLP from '.';
+import CoreNLP, {
+  Properties,
+  Pipeline,
+  ConnectorServer,
+  ConnectorCli,
+} from '.';
 import Document from './simple/document';
 import Sentence from './simple/sentence';
 import Token from './simple/token';
@@ -13,8 +18,6 @@ import ParserAnnotator from './simple/annotator/parse';
 import DependencyParseAnnotator from './simple/annotator/depparse';
 import RelationExtractorAnnotator from './simple/annotator/relation';
 import RegexNERAnnotator from './simple/annotator/regexner';
-import ConnectorServer from './connector/connector-server';
-import ConnectorCli from './connector/connector-cli';
 import Tree from './util/tree';
 
 describe('CoreNLP Library entry point', () => {
@@ -27,11 +30,11 @@ describe('CoreNLP Library entry point', () => {
 
     describe('connector', () => {
       it('should have ConnectorServer', async () => {
-        expect(CoreNLP.connector).to.have.property('ConnectorServer').that.equals(ConnectorServer);
+        expect(ConnectorServer).to.be.a('function');
       });
 
       it('should have ConnectorCli', async () => {
-        expect(CoreNLP.connector).to.have.property('ConnectorCli').that.equals(ConnectorCli);
+        expect(ConnectorCli).to.be.a('function');
       });
     });
 
@@ -78,5 +81,79 @@ describe('CoreNLP Library entry point', () => {
         expect(CoreNLP.util).to.have.property('Tree').that.equals(Tree);
       });
     });
+
+    describe('Integration Test', () => {
+      context('Using ConnectorServer', async () => {
+        it('should allow to initialize a pipeline and run annotations', async () => {
+          const connector = new ConnectorServer({ dsn: 'http://localhost:9000' });
+          sinon.stub(connector, 'get').returns(Promise.resolve({
+            sentences: [{
+              tokens: [
+                {
+                  word: 'Hello',
+                  pos: 'UH',
+                  ner: 'O',
+                },
+                {
+                  word: 'world',
+                  pos: 'NN',
+                  ner: 'O',
+                },
+              ],
+            }],
+          }));
+          const props = new Properties({
+            annotators: 'tokenize,ssplit',
+          });
+          const pipeline = new Pipeline(props, 'English', connector);
+          const sent = new CoreNLP.simple.Sentence('Hello world');
+          await pipeline.annotate(sent);
+          expect(sent.word(0)).to.equal('Hello');
+          expect(sent.word(1)).to.equal('world');
+          expect(sent.token(0).pos()).to.equal('UH');
+          expect(sent.token(1).pos()).to.equal('NN');
+          expect(sent.token(0).ner()).to.equal('O');
+          expect(sent.token(1).ner()).to.equal('O');
+        });
+      });
+
+      context('Using ConnectorCli', async () => {
+        it('should allow to initialize a pipeline and run annotations', async () => {
+          const connector = new ConnectorCli({
+            classPath: 'corenlp/stanford-corenlp-full-2017-06-09/*',
+            mainClass: 'edu.stanford.nlp.pipeline.StanfordCoreNLP',
+            props: 'StanfordCoreNLP-spanish.properties',
+          });
+          sinon.stub(connector, 'get').returns(Promise.resolve({
+            sentences: [{
+              tokens: [
+                {
+                  word: 'Hello',
+                  pos: 'UH',
+                  ner: 'O',
+                },
+                {
+                  word: 'world',
+                  pos: 'NN',
+                  ner: 'O',
+                },
+              ],
+            }],
+          }));
+          const props = new Properties({
+            annotators: 'tokenize,ssplit',
+          });
+          const pipeline = new Pipeline(props, 'English', connector);
+          const sent = new CoreNLP.simple.Sentence('Hello world');
+          await pipeline.annotate(sent);
+          expect(sent.word(0)).to.equal('Hello');
+          expect(sent.word(1)).to.equal('world');
+          expect(sent.token(0).pos()).to.equal('UH');
+          expect(sent.token(1).pos()).to.equal('NN');
+          expect(sent.token(0).ner()).to.equal('O');
+          expect(sent.token(1).ner()).to.equal('O');
+        });
+      });
+    });
   });
 });