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XNO API Library for Financial Data

Project description

XNO API Library

XNO API is a Python package for retrieving financial data from multiple sources with a simple and intuitive interface.

Contents

Installation

You can install the XNO API package using pip:

pip install xnoapi

Alternatively, you can clone this repository and install the package manually:

$ git clone git@github.com:yourusername/xnoapi.git
$ pip install ./xnoapi

After installation, you can import and start using XNO API:

from xnoapi import client
from xnoapi.vn.data import stocks, derivatives
from xnoapi.vn.metrics import Metrics, Backtest_Derivates

client(apikey="your_api_key")

Documentation

Full documentation is available online:

Documentation Status

A PDF version of the documentation is available here.

Usage

XNO API provides a structured interface for retrieving financial data:

from xnoapi import client
from xnoapi.vn.data import stocks, derivatives

client(apikey="your_api_key")

# Retrieve list of liquid assets
stocks.list_liquid_asset()

# Get historical stock data
stocks.get_hist("VIC", "1D")

#Get historical derivatives
derivatives.get_hist("VN30F1M", "1m")

Available Modules

XNO API includes the following modules:

Financial Data

  • xnoapi.vn.data.stocks
    • list_liquid_asset(): Retrieve a list of liquid stocks.
    • get_hist(asset_name, frequency): Get historical data for a given asset.
  • xnoapi.vn.data.derivatives
    • get_hist(): Get historical derivative data.

Metrics and Analytics

  • xnoapi.vn.metrics
    • Metrics: Various financial metrics calculation.
    • Backtest_Derivates: Backtesting tools for derivatives.

Examples

Retrieving Stock Data

from xnoapi import client
from xnoapi.vn.data import stocks

client(apikey="your_api_key")

# Get list of liquid assets
liquid_assets = stocks.list_liquid_asset()

# Get historical data for VIC stock
vic_history = stocks.get_hist("VIC", "1D")

Using Metrics

from xnoapi.vn.metrics import Metrics, Backtest_Derivates
from xnoapi.vn.data import derivatives

def gen_position(df):
    """
    Position generation strategy: Volume change detection
    """
    return df.assign(
        position=np.sign(df["Close"] - df["Close"].rolling(window=20).median())
    )

# Initialize metrics instance
historical = derivatives.get_hist("VN30F1M", "1m")
position = gen_position(historical)
backtest = Backtest_Derivates(position, "raw") # raw or after_fees
metrics = Metrics(backtest)

# Example usage
result = metrics.avg_loss()

Credits

This library is developed and maintained by the XNO API team. Special thanks to contributors and financial data providers for their support.

License

This library is licensed under the MIT License. See LICENSE for more details.

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