Financial data access and analysis library with market data, options calculations, and database integration
Project description
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
# 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
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 operationssharpe/utils/- Options calculations, time utilities, universe management
Requirements
- Python 3.11+
- Core: pandas, numpy, scipy, sqlalchemy
- Optional: PostgreSQL, AWS credentials
Development
# 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 file for details.
Disclaimer: For educational and research purposes only. Consult qualified professionals before making investment decisions.
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