# Sharpe - Financial Data & Analysis Library
A Python library for financial data access, market analysis, and options calculations.
Wrappers around Polygon and Financial Modeling Prep.
## Features
- **Market Data**: Stock prices, options data, and historical information
- **Alternative Data**: News, earnings, and company profiles
- **Options Calculations**: Black-Scholes pricing and Greeks
- **Database Integration**: PostgreSQL with async support
- **AWS Integration**: Cloud data retrieval
## Installation
```bash
# From source
git clone https://github.com/wang-sanity/sharpe.git
cd sharpe
pip install -e .
# Using conda
conda env create -f environment.yml
conda activate tensorfi-sharpe
```
## Quick Start
```python
from sharpe.data import mkt, alt
from sharpe.utils import options, time, universe
# Get market data using aggregates
data = mkt.aggregates(
ticker="AAPL",
multiplier=1,
timespan="day",
from="2024-01-01",
to="2024-01-31"
)
# Get options chain for a ticker
options_data = mkt.options_chain("SPY")
# Work with time utilities
trading_day = time.closest_trading_day_now()
is_trading = time.is_trading_day("2024-01-15")
# Get universe of stocks
top_stocks = universe.get_top_n_traded_stock(n=50)
```
## Package Structure
- `sharpe/data/` - Market and alternative data access, database operations
- `sharpe/utils/` - Options calculations, time utilities, universe management
## Requirements
- Python 3.11+
- Core: pandas, numpy, scipy, sqlalchemy
- Optional: PostgreSQL, AWS credentials
## Development
```bash
# Setup
conda env create -f environment.yml
conda activate tensorfi-sharpe
pip install -e .[dev]
# Test
pytest
```
## License
CC BY-NC 4.0 License - see [LICENSE](LICENSE) file for details.
---
**Disclaimer**: For educational and research purposes only. Consult qualified professionals before making investment decisions.
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