Merge pull request #1 from JeremyBrent/jb/github-actions

added github action

.github/workflows/unittest.yml

@@ -0,0 +1,26 @@
+name: Unittests
+run-name: Automated Github action for Unittests - ${{ github.actor }}
+on:
+  pull_request
+jobs:
+  unittests:
+    runs-on: ubuntu-latest
+    steps:
+      - run: echo "🎉 The job was automatically triggered by a ${{ github.event_name }} event."
+      - run: echo "🐧 This job is now running on a ${{ runner.os }} server in ${{ runner.workspace}}!"
+
+      - name: Check out code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version-file: '.python-version'
+
+      - name: Install dependencies
+        run: |
+          pip install -r requirements.txt
+
+      - name: Run tests
+        run: |
+          python -m unittest discover -s tests

.python-version

@@ -0,0 +1 @@
+3.9.13

README.md

@@ -67,3 +67,14 @@ Any new models should be replicated based on existing research found
 
 We should also implement a more sophisticated metric for 
 measuring the performance of the FSA models. Currently, we are only using a raw accuracy. 
+
+# The Code Base
+Given the timeframe of the project, I put together a small, end-to-end project. Some of these end 
+to end features include unittests, CICD with Github actions, environment creation with Make and
+requirements.txt, and github branch protection rules found 
+[here](https://github.com/JeremyBrent/stock_market_analyzer/settings/branch_protection_rules/54816872)
+which require 1. PRs and 2. passing Github actions in order to update the main branch.
+
+With more time, some things I would build upon would be, 
+expanding unittest portfolio would need to build out, and further developing the Github actions
+if we were deploying this model as a service

src/utils.py

@@ -1,5 +1,6 @@
 import datetime as dt
 from src.consts import DATE_FORMAT
+from zoneinfo import ZoneInfo
 
 
 class Utils:
@@ -14,8 +15,8 @@ def convert_datetime(timestamp: int) -> tuple[str, str]:
         :param timestamp:
         :return:
         """
-        # Convert to datetime object
-        original_date = dt.datetime.fromtimestamp(timestamp)
+        # Ensure datetime is in NY Timezone bc that's were the NYSE is located
+        original_date = dt.datetime.fromtimestamp(timestamp, tz=ZoneInfo("America/New_York"))
         dt_object = original_date
 
         # Define 4 PM as the time to compare against

tests/test_utils.py

@@ -19,4 +19,4 @@ def test_convert_datetime(self):
 
         for input, expected_data in test_data.items():
             actual_output = self.utils.convert_datetime(input)
-            self.assertEqual(actual_output, expected_data)
+            self.assertEqual(actual_output, expected_data)