feat: add work flow ci

.github/workflows/ci.yaml

@@ -0,0 +1,55 @@
+name: CI
+
+on:
+  push:
+    branches: [main, develop]
+  pull_request:
+    branches: [main]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.11, 3.12]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e ".[dev]"
+
+      - name: Lint with ruff
+        run: |
+          ruff check src/ tests/
+
+      - name: Check formatting with black
+        run: |
+          black --check src/ tests/
+
+      - name: Run tests
+        run: |
+          pytest --cov=src/quant_research_starter --cov-report=xml
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          name: codecov-umbrella
+
+  build-docker:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Build Docker image
+        run: |
+          docker build -t quant-research-starter:latest .

.gitignore

@@ -1 +1,3 @@
-node_modules
+node_modules
+.vscode
+.coverage

README.md

@@ -1,2 +1,52 @@
-# template
-A Template Repository for OpenSpringFest (OSF)
+# QuantResearchStarter
+
+A modular, open-source quantitative research and backtesting framework designed for clarity and extensibility. Perfect for researchers, students, and developers interested in quantitative finance.
+
+![Python Version](https://img.shields.io/badge/python-3.10%2B-blue)
+![License](https://img.shields.io/badge/license-MIT-green)
+[![CI](https://github.com/username/QuantResearchStarter/actions/workflows/ci.yml/badge.svg)](https://github.com/username/QuantResearchStarter/actions)
+
+## Features
+
+- **Data Management**: Download real data or generate synthetic data for testing
+- **Factor Library**: Implement momentum, value, size, and volatility factors
+- **Backtesting Engine**: Vectorized backtester with transaction costs and constraints
+- **Risk Metrics**: Comprehensive performance and risk analytics
+- **Modular Design**: Easy to extend with new factors and strategies
+- **Production Ready**: Type hints, tests, CI/CD, and documentation
+
+## Quick Start
+
+### Installation
+
+```bash
+# Clone the repository
+git clone https://github.com/username/QuantResearchStarter.git
+cd QuantResearchStarter
+
+# Install package in development mode
+pip install -e .
+
+# Install development dependencies
+pip install -e ".[dev]"
+
+# Optional UI
+pip install streamlit plotly
+```
+
+### Quick Demo
+
+```bash
+make demo
+```
+
+Or step-by-step:
+
+```bash
+qrs generate-data -o data_sample/sample_prices.csv -s 5 -d 365
+qrs compute-factors -d data_sample/sample_prices.csv -f momentum -f value -o output/factors.csv
+qrs backtest -d data_sample/sample_prices.csv -s output/factors.csv -o output/backtest_results.json
+
+# Streamlit dashboard (optional)
+streamlit run src/quant_research_starter/dashboard/streamlit_app.py
+```