nexusdata 1.0.10

Quantweb3 Data API for quants

NexusData

NexusData revolutionizes decentralized market analysis by transforming complex data workflows into a single line of code. Designed for traders and developers, our platform seamlessly aggregates high-fidelity coin spots/contracts bar data from top exchanges like Binance and OKX, delivering:

• Zero-Learning-Code: Extract, clean, and structure raw data with one intuitive function
• Turbocharged Security: Local data vaulting ensures enterprise-grade protection + sub-millisecond access
• Future-Proof Scalability: Modular architecture primed for expanding exchange integrations
• Trade smarter: build faster – where simplicity meets institutional-grade data resilience.

Quick Start 🚀

Installation

pip install nexusdata

Basic Usage

from nexusdata import auth, fetch_data

1. Authentication (Get credentials at https://quantweb3.ai/subscribe)

auth('your_username', 'your_token')

2. Fetch Data Store the data in a local specified directory (csv format)

fetch_data()

Advanced Usage

Fetch data with custom parameters

fetch_data(
    tickers=["BTCUSDT"],
    store_dir="./tmp/data",
    start_time=datetime.datetime(2021, 1, 1),
    end_time=datetime.datetime(2022, 1, 2),
    data_type="klines",
    data_frequency="1m",
    asset_class="um"
)

Function Parameters 📋

• tickers (list[str]):
  A list of trading pairs to fetch data for.
  Example: ["BTCUSDT"].

• store_dir (str):
  The directory path where the fetched data will be stored.
  Example: "./tmp/data".

• start_time (datetime.datetime):
  The starting timestamp for the data retrieval.
  Example: datetime.datetime(2021, 1, 1).

• end_time (datetime.datetime):
  The ending timestamp for the data retrieval.
  Example: datetime.datetime(2022, 1, 2).

• data_type (str):
  The type of data to fetch. Defaults to "klines", which represents candlestick (OHLCV) data.

• data_frequency (str):
  The frequency at which the data is sampled.
  Example: "1m" for one-minute intervals.

• asset_class (str):
  The asset class identifier. For instance, "um" might indicate a specific market type.
  Note: The accepted values should be defined by your application context.

Data Structure 📊

The returned DataFrame contains the following columns:

Column	Description
Open time	The moment when the candlestick period started.
Open	The opening price for the period.
High	The highest price reached during the period.
Low	The lowest price reached during the period.
Close	The closing price at the end of the period.
Volume	The total traded quantity during the period.
Close time	The moment when the candlestick period ended.
Quote asset volume	The traded volume in terms of the quote asset during the period.
Number of trades	The total number of trades executed during the period.
Taker buy base asset volume	The amount of the base asset bought by takers during the period.
Taker buy quote asset volume	The amount of the quote asset used for taker buy orders during the period.
Ignore	A field reserved for future use and typically disregarded.

Authentication 🔑

1. Visit Quantweb3.ai Subscription Page(Note: New users get a 7-day free trial)
2. Register and obtain authentication credentials
3. Use the auth() function to authenticate

How to get free data service?

Note: Open an account using one of the above links and provide a screenshot to get 1 year's of free data service(Anyone).

• Bison Bank: Sign up
• OKX: Sign up
• Bybit: Sign up
• ZFX: Sign up

Examples 📝

• You can view the demo on Google Colab by clicking here.
• You can also look at the example folder in the directory

Dependencies 📦

• python-snappy >= 0.7.2
• grpcio >= 1.64.1
• pandas >= 1.5.3
• protobuf >= 4.25.3
• tqdm >= 4.65.0

FAQ ❓

Q: How to handle authentication errors?
A: Ensure your username and token are correct, and check your network connection.

Q: What is the data update frequency?
A: Hstorical data is updated daily.

Contributing 🤝

Issues and Pull Requests are welcome!

License 📄

This project is licensed under the MIT License - see the LICENSE file for details

Contact 📧

• Website: quantweb3.ai
• Email: [e-mail]
• X: https://x.com/quantweb3_ai
• Telegram: https://t.me/+6e2MtXxoibM2Yzlk

Changelog 📝