Skip to main content

Documentation Index

Fetch the complete documentation index at: https://knowledge.cloudquant.com/llms.txt

Use this file to discover all available pages before exploring further.

​
Python SDK Getting Started

The CloudQuant Data Liberator Python SDK provides the simplest way to query and work with CloudQuant datasets from any Python environment.

​
Prerequisites

  • Python 3

​
Installation

conda create -n liberator python=3.7
conda activate liberator
conda install -c anaconda requests
conda install pandas
conda install -c conda-forge httpx async_generator pyarrow=8.0.0

​
Required Security Files

You need the following files from your Downloads ZIP file, all placed in your working directory or Python environment:
  • liberator.py — The CloudQuant Data Liberator API for Python
  • liberator.json — Contains your Username and Token
  • liberator.pfx — Security certificate (only required for releases prior to 2.0)
These files must be in your working directory.
As of release version 2.0, liberator.pfx is no longer required. If you are on a release prior to 2.0, you must also include liberator.pfx in your working directory.
When using Jupyter Notebooks, set the working directory to the location containing liberator.json (and liberator.pfx if you are on a release prior to 2.0). See this reference for changing the Jupyter Notebook startup folder on Windows.

​
Optional: CloudQuant Charting

If using CloudQuant Charting (included with the API), install these additional packages:
  • plotly
  • TALib
  • numpy

​
Quick Start

import liberator

liberator.url = 'https://api.cloudquant.ai'

df = liberator.get_dataframe(
    liberator.query(
        name='daily_bars',
        as_of='2020-11-15',
        symbols=['AAPL']
    )
)

print(df)