From 5c7047690dd0d2a024156ed56bd913be8e469367 Mon Sep 17 00:00:00 2001
From: Claire <clairegerson@gmail.com>
Date: Thu, 11 Oct 2018 11:11:38 -0400
Subject: [PATCH] adding sent analysis endpt and test

---
 dandelion/datatxt.py |  5 +++++
 docs/datatxt.rst     | 18 ++++++++++++++++++
 tests/datatxt.py     |  5 +++++
 3 files changed, 28 insertions(+)

diff --git a/dandelion/datatxt.py b/dandelion/datatxt.py
index be173dd..23194f7 100644
--- a/dandelion/datatxt.py
+++ b/dandelion/datatxt.py
@@ -23,5 +23,10 @@ def li(self, text, **params):
             dict(params, text=text), ('li', 'v1')
         )
 
+    def sent(self, text, **params):
+        return self.do_request(
+            dict(params, text=text), ('sent', 'v1')
+        )
+
     def _get_uri_tokens(self):
         return 'datatxt',
diff --git a/docs/datatxt.rst b/docs/datatxt.rst
index dcab68e..ac716bd 100644
--- a/docs/datatxt.rst
+++ b/docs/datatxt.rst
@@ -81,3 +81,21 @@ You can identify the language of a text with::
      'timestamp': '2042-01-01T01:02:03'}
 
 Check out the `dataTXT-LI documentation on dandelion.eu`_.
+
+
+SENT: Sentiment Analysis
+---------------------------
+dataTXT-SENT is a sentiment analysis API that analyses a text and tells whether the expressed opinion is positive, negative, or neutral. Given a short sentence, it returns a label representing the identified sentiment, along with a numeric score ranging from strongly positive (1.0) to extremely negative (-1.0).
+
+You can identify the sentiment of a text with::
+
+    >>> datatxt.sent('I really love your APIs')
+    {"sentiment": {
+        "type": "positive",
+        "score": 0.9
+    },
+    "lang": "en",
+    "time": 0,
+    "timestamp": "2018-10-11T14:45:15.529"}
+
+Check out the `dataTXT-SENT documentation on dandelion.eu`_.
\ No newline at end of file
diff --git a/tests/datatxt.py b/tests/datatxt.py
index c8f0091..443631b 100644
--- a/tests/datatxt.py
+++ b/tests/datatxt.py
@@ -43,6 +43,11 @@ def test_li(self):
 
         self.assertGreater(res.detectedLangs[0].confidence, 0.9999)
 
+    def test_sent(self):
+        res = self.datatxt.sent("I really love your APIs")
+
+        self.assertEqual(res.sentiment.score, 0.9)
+
     def test_raises_on_error(self):
         with self.assertRaises(DandelionException):
             self.datatxt.nex(text=None)