Merge pull request bellanov#36 from bellanov/35-cicd-workflow

.github/workflows/python-package.yml

@@ -0,0 +1,44 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
+name: Python package
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.9", "3.10", "3.11"]
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        echo "Executing Unit Tests..."
+        coverage run -m pytest tests/
+
+        echo "Generating Report..."
+        coverage report -m

CONTRIBUTING.md

@@ -71,7 +71,7 @@ First, a local project environment needs to be created, then the project's modul
    scripts/lint.sh
    ```
 
-4. Tag and version code changes. This will trigger a build in **Google Cloud Platform (GCP)** that will be associated with the pull request.
+4. Tag and version code changes.
 
    ```sh
    git tag -a "1.2.3" -m "Version 1.2.3"

examples/hello_world.py

@@ -20,7 +20,7 @@ def quality_assurance(data):
     for col in data.columns:
         if data[col].dtype == 'object':
             data[col] = data[col].apply(lambda x: str(x) if isinstance(x, dict) else x)
-    
+
     data = data.drop_duplicates()
     return data
 
@@ -31,7 +31,7 @@ def quality_assurance(data):
 pipeline.configure({
     "data_source": "local",
     "data_source_path": "/path/to/directory",
-    "data_format" : "csv"
+    "data_format": "csv"
 })
 
 # Extract

examples/quickstart.py

@@ -1,6 +1,5 @@
 """Example SerenadeFlow Usage."""
 
-import pandas as pd
 from serenade_flow import pipeline
 
 
@@ -10,7 +9,7 @@
 pipeline.configure({
     "data_source": "local",
     "data_source_path": "/path/to/directory",
-    "data_format" : "csv"
+    "data_format": "csv"
 })
 
 # Extract

tests/test_pipeline.py

@@ -11,7 +11,7 @@ def test_extact_local():
     pipeline.configure({
         "data_source": "local",
         "data_source_path": "/path/to/local/directory",
-        "data_format" : "csv"
+        "data_format": "csv"
     })
     data = pipeline.extract()
     assert len(data) == 3
@@ -23,7 +23,7 @@ def test_extact_remote():
     pipeline.configure({
         "data_source": "remote",
         "data_source_path": "http://path/to/storage/bucket",
-        "data_format" : "csv"
+        "data_format": "csv"
     })
     data = pipeline.extract()
     assert data == {}
@@ -35,7 +35,7 @@ def test_load():
     pipeline.configure({
         "data_source": "local",
         "data_source_path": "http://path/to/storage/bucket",
-        "data_format" : "csv"
+        "data_format": "csv"
     })
     data = pipeline.extract()
     assert pipeline.load(data, "output") == "Data loaded successfully"