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
limexhublibrary 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')
Nasdaq100_constituents = client.constituents()
SP500_constituents = client.constituents(universe='Q500US')
candles = client.candles(symbols = ["AAPL", "NVDA"],
start="2024-01-01",
end="2025-01-01",
interval = "1d",
pivot=False)
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.iloc[0]['id'],
symbol="AAPL",
from_date="2023-01-01")
congress = client.congress_trading(ticker="AAPL", limit=100)
congress = client.congress_trading(member_name="Pelosi", limit=100)
1 maintainer
Metadata
1 maintainer
Release files for limexhub 1.16.28
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| limexhub-1.16.28.tar.gz | 8.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| limexhub-1.16.28-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.3 kB
Release files / limexhub-1.16.28.tar.gz
| Download URL | limexhub-1.16.28.tar.gz |
|---|---|
| Size | 8.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.7
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Release files / limexhub-1.16.28-py3-none-any.whl
| Download URL | limexhub-1.16.28-py3-none-any.whl |
|---|---|
| Size | 8.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.7
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Security for limexhub 1.16.28
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