Add unit tests to the "commentAnalysis.py" (#17)

* Add unit tests to the "commentAnalysis.py"

1.'unittest' framework of python is used to develop unit tests
2. adds the __init__.py to have standard packaging template

* Add documentation to run unit tests

update the README.md with the commands to run unit tests

README.md

@@ -20,6 +20,7 @@ inclusive pull requests to foster a healthier open source community.
     1. [Environment Setup](#environment-setup)
         - [Prerequisites](#prerequisites)
         - [Installation](#installation)
+        - [Testing](#testing)
     2. [Build Dataset](#build-dataset)
         - [Extract Raw Data from GitHub](#extract-raw-data-from-github)
         - [Annotate](#annotate)
@@ -36,6 +37,7 @@ inclusive pull requests to foster a healthier open source community.
 
 - [Prerequisites](#prerequisites)
 - [Installation](#installation)
+- [Testing](#testing)
 
 #### Prerequisites
 
@@ -53,7 +55,7 @@ create isolated Python environment is recommended for this project.
 
 2. Set up ML Conversational Analytic Tool in a virtualenv
    ```python
-   python3 -m venv virtualenv-ml-conversational
+   python -m venv virtualenv-ml-conversational
    ```
 
 3. Activate the virtualenv
@@ -70,6 +72,17 @@ create isolated Python environment is recommended for this project.
    ```python
    pip install -r requirements.txt
    ```
+#### Testing
+6. Run all unit tests
+   ```python
+   cd ml-conversational-analytic-tool
+   python -m unittest discover -s tests
+   ```
+7. Run an individual unit test
+   ```python
+   cd ml-conversational-analytic-tool
+   python -m unittest tests/<file_name>
+   ```
 
 The libraries used within the project are available in the [requirements.txt](./requirements.txt).
 
@@ -160,7 +173,6 @@ Both `BaseCNN` and `BaseLSTM` also have prediction explanation mechanisms that c
 
 If you have ideas on how to improve the framework to assess text conversation for constructive and inclusive
 communication, we welcome your contributions!
-
 ## Documentation
 
 Auto-generated API documentation can be found in

ml-conversational-analytic-tool/tests/test_commentAnalysis.py

@@ -0,0 +1,52 @@
+import unittest
+import unittest.mock
+
+import commentAnalysis
+
+class TestCommentAnalysis(unittest.TestCase):
+
+    def setUp(self) -> None:
+        self.sentiment_analyzer = commentAnalysis.vader.SentimentIntensityAnalyzer()
+        self.sentiment_analyzer.polarity_scores = unittest.mock.MagicMock(return_value={"compound": 1.0})
+
+    def test_CommentAnalyzer_init(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['test'])
+        self.assertEqual({'test': 0}, analyzer.word_count)
+
+    def test_analyzeComment(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['test'])
+        analyzer.vader_sentiment = self.sentiment_analyzer
+        result = analyzer.analyzeComment("This is a test PR")
+        self.assertEqual({'test': 1, 'Sentiment': 1.0, 'Code Blocks': 0}, result)
+
+    def test_analyzeComment_with_empty_comment(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['empty comment'])
+        analyzer.vader_sentiment = self.sentiment_analyzer
+        result = analyzer.analyzeComment("")
+        self.assertEqual({'empty comment': 0, 'Sentiment': 1.0, 'Code Blocks': 0}, result)
+
+    def test_analyzeComment_with_codeBlocks(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['code block test'])
+        analyzer.vader_sentiment = self.sentiment_analyzer
+        result = analyzer.analyzeComment("```This patch has blocks```, ```This is second block```")
+        self.assertEqual({'code block test': 0, 'Sentiment': 1.0, 'Code Blocks': 2}, result)
+
+    def test_preProcess(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['preProcess test'])
+        result = analyzer.preProcess("THIS is a TEST COMMENT")
+        self.assertEqual("this is a test comment", result)
+
+    def test_countWords(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['count words test'])
+        result = analyzer.countWords("This is a test comment")
+        self.assertEqual({'count words test': 0}, result)
+
+    def test_getSentiment(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['sentiment test'])
+        result = analyzer.getSentiment("This is a very good PR")
+        self.assertEqual(float, type(result))
+
+    def test_getCodeBlockCount(self):
+        analyzer = commentAnalysis.CommentAnalyzer(['test'])
+        result = analyzer.getCodeBlockCount("```This comment has code block``` ``` this is the 2nd code block```")
+        self.assertEqual(2, result)