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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 operations
  • sharpe/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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