breeze-historical 0.1.0

A library for fetching and caching historical market data from Breeze API using DynamoDB

breeze-historical

A Python library for fetching, caching, and analyzing historical market data from the Breeze API, with optional AWS DynamoDB integration for persistent storage.

Features

• Fetch historical options and futures data from the Breeze API
• Cache and retrieve data using AWS DynamoDB
• Utilities for working with NSE symbols, expiries, and strikes
• Modular, extensible, and production-ready

Installation

From PyPI (when published):

pip install breeze-historical

From source (GitHub):

git clone https://github.com/kunalAgarwal35/building_breeze_wrapper.git
cd building_breeze_wrapper
pip install .

Setup

1. Environment Variables

Create a .env file in your working directory (or wherever you run your scripts) with the following keys:

BREEZE_API_KEY=your_breeze_api_key
BREEZE_API_SECRET=your_breeze_api_secret
BREEZE_USER_ID=your_breeze_user_id
BREEZE_PASSWORD=your_breeze_password
BREEZE_TOTP_SECRET=your_breeze_totp_secret
AWS_ACCESS_KEY_ID=your_aws_access_key_id
AWS_SECRET_ACCESS_KEY=your_aws_secret_access_key
AWS_REGION=ap-south-1
DYNAMO_TABLE_NAME=historical_market_data

2. DynamoDB Table

If you want to use DynamoDB caching, create a table with the name specified in DYNAMO_TABLE_NAME and primary key:

• Partition key: c_id (String)
• Sort key: ts (String)

Example Usage

from breeze_historical import BreezeHistorical
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

breeze_creds = {
    "api_key": os.getenv("BREEZE_API_KEY"),
    "api_secret": os.getenv("BREEZE_API_SECRET"),
    "user_id": os.getenv("BREEZE_USER_ID"),
    "password": os.getenv("BREEZE_PASSWORD"),
    "totp_key": os.getenv("BREEZE_TOTP_SECRET")
}

aws_creds = {
    "access_key_id": os.getenv("AWS_ACCESS_KEY_ID"),
    "secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"),
    "region": os.getenv("AWS_REGION", "ap-south-1"),
    "table_name": os.getenv("DYNAMO_TABLE_NAME", "historical_market_data")
}

client = BreezeHistorical(breeze_creds=breeze_creds, aws_creds=aws_creds, verbose=True)

# Fetch available indices
indices = client.get_nse_indices()
print("Available indices:", indices)

# Fetch expiry dates for NIFTY
expiries = client.get_nse_expiry_dates("NIFTY", 2024)
print("NIFTY Expiries:", expiries)

# Fetch option chain timeseries for NIFTY
option_chain = client.fetch_option_chain_timeseries(
    symbol="NIFTY",
    start_date="2024-04-01",
    end_date="2024-04-30",
    expiry="2024-04-25",
    granularity="5minute"
)
print(option_chain)

API Overview

BreezeHistorical

• get_nse_indices() — List all available indices
• get_nse_stocks() — List all available stocks
• get_nse_expiry_dates(symbol, year, instrument) — Get expiry dates for a symbol
• get_nse_option_chain(...) — Get option chain data from NSE
• fetch_option_chain_timeseries(...) — Fetch and cache option chain timeseries
• _fetch_option_data(...) — (Advanced) Fetch option data for a specific strike/type
• _fetch_futures_data(...) — (Advanced) Fetch futures data

Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repo
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request

License

MIT License

Links

• GitHub Repository