Dockerised and added ui for all the models- added github actions/unit tests

.coveragerc

@@ -0,0 +1,5 @@
+[run]
+relative_files = True
+omit =
+    tests/*
+    */__init__.py

.github/workflows/ci-coverage.yml

@@ -0,0 +1,67 @@
+name: CI Coverage
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+
+permissions:
+  contents: write
+  pull-requests: write
+
+jobs:
+  test-and-coverage:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11"]  # Aligns with your project's requirement
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: 'pip'
+
+      # CRITICAL STEP: Install System Dependencies for TA-Lib & LightGBM
+      # This mimics the logic inside your Dockerfile but runs on the GitHub Action runner
+      - name: Install System Dependencies (TA-Lib & OpenMP)
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y libgomp1 build-essential wget
+          # Download and build TA-Lib from source
+          wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
+          tar -xzf ta-lib-0.4.0-src.tar.gz
+          cd ta-lib/
+          ./configure --prefix=/usr
+          make
+          sudo make install
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          # Install testing & security tools (from optionsauditor ci.yml)
+          pip install pytest pytest-cov bandit pip-audit pytest-rerunfailures
+          # Install project requirements
+          pip install -r requirements.txt
+
+      - name: Security Scan - Python Static Analysis (Bandit)
+        # Scans 'app' directory, skips B104 (binding to all interfaces)
+        run: bandit -r app -ll -s B104
+
+      - name: Security Scan - Python Dependencies (pip-audit)
+        run: pip-audit
+
+      - name: Run tests with Coverage
+        # Targets 'app' folder for coverage, runs tests in 'tests' folder
+        run: pytest --cov=app --cov-report=xml --cov-report=term tests/
+
+      - name: Coverage Badge
+        uses: py-cov-action/python-coverage-comment-action@v3
+        with:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/docker-build-test.yml

@@ -0,0 +1,76 @@
+name: Docker Build and Training Pipeline Test
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+  workflow_dispatch:
+
+jobs:
+  build-and-test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Build Docker image
+        run: docker build -t spy-backend .
+
+      - name: Run Docker container
+        run: |
+          docker run -d --name spy-backend -p 8000:8000 spy-backend
+          sleep 10  # Wait for the server to start
+
+      - name: Wait for API to be ready
+        run: |
+          # Retry loop to check if the API is responding
+          for i in {1..30}; do
+            if curl -s http://localhost:8000/docs > /dev/null; then
+              echo "API is up!"
+              exit 0
+            fi
+            echo "Waiting for API..."
+            sleep 2
+          done
+          echo "API failed to start."
+          docker logs spy-backend
+          exit 1
+
+      - name: Refresh Data
+        run: |
+          response=$(curl -s -w "%{http_code}" -X POST http://localhost:8000/data/refresh)
+          http_code=${response: -3}
+          echo "Response: $response"
+          if [ "$http_code" -ne 200 ]; then
+            echo "Data refresh failed with status $http_code"
+            docker logs spy-backend
+            exit 1
+          fi
+
+      - name: Generate Features
+        run: |
+          response=$(curl -s -w "%{http_code}" -X POST http://localhost:8000/features/generate)
+          http_code=${response: -3}
+          echo "Response: $response"
+          if [ "$http_code" -ne 200 ]; then
+            echo "Feature generation failed with status $http_code"
+            docker logs spy-backend
+            exit 1
+          fi
+
+      - name: Train LightGBM Model
+        run: |
+          response=$(curl -s -w "%{http_code}" -X POST http://localhost:8000/train/lightgbm)
+          http_code=${response: -3}
+          echo "Response: $response"
+          if [ "$http_code" -ne 200 ]; then
+            echo "LightGBM training failed with status $http_code"
+            docker logs spy-backend
+            exit 1
+          fi
+
+      - name: Stop Docker container
+        if: always()
+        run: docker stop spy-backend

.github/workflows/main.yml

@@ -0,0 +1,49 @@
+name: CI
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Set up Python 3.12
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.12'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        # Install TA-Lib
+        wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
+        tar -xzf ta-lib-0.4.0-src.tar.gz
+        cd ta-lib
+        ./configure --prefix=/usr
+        make
+        sudo make install
+        cd ..
+        pip install -r requirements.txt
+        pip install pytest httpx
+
+    - name: Run tests
+      run: |
+        pytest tests/
+
+    - name: Linting
+      run: |
+        pip install flake8
+        # 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: Security Scan
+      run: |
+        pip install bandit
+        bandit -r app/

Dockerfile

@@ -0,0 +1,45 @@
+# Use an official Python runtime as a parent image
+FROM python:3.12-slim
+
+# Set work directory
+WORKDIR /app
+
+# Install system dependencies (needed for TA-Lib and other libraries)
+# build-essential and python3-dev for compiling C extensions
+# curl for healthchecks
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    python3-dev \
+    curl \
+    libgomp1 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install TA-Lib C library
+# Download and install TA-Lib C library
+RUN curl -L http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz -o ta-lib-0.4.0-src.tar.gz && \
+    tar -xzf ta-lib-0.4.0-src.tar.gz && \
+    cd ta-lib && \
+    ./configure --prefix=/usr && \
+    make && \
+    make install && \
+    cd .. && \
+    rm -rf ta-lib ta-lib-0.4.0-src.tar.gz
+
+# Copy requirements file
+COPY requirements.txt .
+
+# Install Python dependencies
+# Update requirements to not use ta-lib-binary if it fails on linux, we use standard ta-lib since we installed C lib
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application
+COPY . .
+
+# Create output directory for persistence
+RUN mkdir -p output/models/lightgbm
+
+# Expose port
+EXPOSE 8000
+
+# Run the API
+CMD ["uvicorn", "app.api.main:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

@@ -84,11 +84,37 @@ pip install xgboost lightgbm catboost
 pip install scikit-learn matplotlib seaborn
 ```
 
-### 2. Download Data
+### 2. Docker Deployment
+
+The application works best when run as a full-stack Dockerized application using Docker Compose. This automatically builds and starts both the backend API and the frontend dashboard.
+
+```bash
+# Build and run the application
+docker-compose up --build
+```
+
+#### Accessing the Application
+
+Once the containers are running (you will see logs indicating the server started), open your web browser and navigate to:
+
+- **Frontend Dashboard**: http://localhost:3000
+  - This is the main interface where you can view predictions, charts, and trigger data updates.
+- **Backend API Documentation**: http://localhost:8000/docs
+  - Interactive Swagger UI to test API endpoints directly.
+
+> **Note**: If port 3000 or 8000 is already in use on your machine, you may need to modify the port mapping in `docker-compose.yml`.
+
+### 3. Download Data (Manual / Docker)
+
+You can trigger data download from the dashboard UI or manually:
 
 ```bash
 # Download OHLCV data for SPY, VIX, TLT, DXY, GLD (2015-present)
-python download_data.py
+# If running locally:
+python -m app.core.download_data
+
+# If running via API:
+curl -X POST http://localhost:8000/data/refresh
 ```
 
 See [download_data.md](download_data.md) for details.