Merge pull request #51 from stephenhky/aws_s3

Word-embedding model in Unit Test stored in Amazon S3 Bucket

.travis.yml

@@ -15,6 +15,8 @@ before_install:
   - sudo apt-get update
   - sudo apt-get install libc6
   - conda install --yes libgcc
+  - sudo apt-get install python-dev
+  - sudo apt-get install python3-dev
 install:
   - conda create --yes -n shorttext-test python=$TRAVIS_PYTHON_VERSION
   - source activate shorttext-test

README.md

@@ -114,6 +114,7 @@ If you would like to contribute, feel free to submit the pull requests. You can
 
 ## Possible Future Updates
 
+- [x] Moving the testing word2vec model to AWS S3;
 - [ ] More scalability;
 - [ ] Including BERT models;
 - [ ] Dividing components to other packages;

test/test_var_nn_embedded_vec_classifier.py

@@ -11,7 +11,7 @@
 class TestVarNNEmbeddedVecClassifier(unittest.TestCase):
     def setUp(self):
         print("Downloading word-embedding model....")
-        link = "https://github.com/stephenhky/PyShortTextCategorization/blob/master/data/test_w2v_model.bin?raw=true"
+        link = "https://s3.amazonaws.com/shorttext-data-northernvirginia/trainingdata/test_w2v_model.bin"
         filename = "test_w2v_model.bin"
         if not os.path.isfile("test_w2v_model.bin"):
             if sys.version_info[0]==2: