A simple API wrapper for Limex DataHub
Project description
Limexhub
limexhub
is a comprehensive Python library designed to simplify interactions with the financial data and services provided by Limex DataHub. It provides an easy-to-use interface for fetching various types of financial data, including instruments, candles, fundamentals, news, events, and predictive signals.
Features
- Ease of Use: The
limexhub
library has a straightforward, intuitive interface that enables quick access to Limex DataHub. - Comprehensive Data Coverage: Access a wide range of financial data, from market instruments and historical candlestick charts to company fundamentals and latest news.
- Predictive Signals: Leverage advanced machine learning models and signals to inform your financial decisions.
- Customization: Easily customize your data queries with flexible parameters suitable for different analysis and trading strategies.
- Efficiency: The library is designed for efficiency, minimizing the amount of code needed to make requests and handle responses.
Installation
Install limexhub
with pip:
pip install limexhub
Getting Started
The library needs to be configured with an API key from your account. Sign up for free and you will automatically receive a set of API keys to start with.
import limexhub
api_token = 'your_api_key'
client = limexhub.RestAPI(token=api_token)
instruments = client.instruments(assets='stocks')
DJI_constituents = client.constituents(index = 'DJI')
SP500_constituents = client.constituents()
candles = client.candles(symbol="AAPL",
to_date="2024-01-01",
from_date="2023-01-01",
timeframe=3)
fundamental = client.fundamental(symbol="AAPL",
from_date="2023-01-01",
to_date="2024-01-01",
fields='roa')
fundamental = client.fundamental(symbol="AAPL",
from_date="2010-01-01",
to_date="2024-01-01",
fields=None)
fundamental = client.fundamental(fields='roa',
quarter='Q2-2023')
events = client.events(symbol="AAPL",
from_date="2023-01-01",
to_date="2024-01-01",
event_type="dividends")
news = client.news(symbol="AAPL",
from_date="2023-03-01",
to_date="2024-03-03")
models = client.models(vendor = 'boosted')
signals = client.signals(vendor="boosted",
model=models[0]['id'],
symbol="AAPL",
from_date="2023-01-01")
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