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Getting started with CloudQuant Data Liberator for Python

This guide introduces the CloudQuant Data Liberator library, available across multiple programming languages via the CloudQuant API platform.

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Basic setup

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Quick start

For environments where CloudQuant Data Liberator is pre-installed, simply use: 
import liberator

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Installation steps

If adding CloudQuant Data Liberator to your own Python environment (local installation, Jupyter, or IDE):
  1. Download the required files from your Liberator Profile page
  2. Install dependencies:
conda create -n liberator python=3.7
conda activate liberator
conda install -c anaconda requests pyopenssl cryptography six pytz
conda install pandas
conda install -c conda-forge httpx async_generator pyarrow=8.0.0
  1. Place files in either:
    • The same folder as your code, or
    • A central Python location (liberator.py only — see note below)
Putting liberator.py in site-packages lets you import liberator from anywhere, but liberator.json is still read from your working directory unless you set liberator.auth = '/path/to/liberator.json'.
To find your Python’s site-packages directory: 
import site
print(site.getsitepackages())

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Required files

FilePurpose
liberator.pyThe Python library
liberator.jsonPre-populated credentials (username and token)
liberator.pfxSecurity certificate (only required for releases prior to 2.0)
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.

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Server configuration

Files downloaded from your Liberator Profile page include the correct server URL preconfigured in the client.

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Override server URL

To connect to a different instance, set the URL explicitly: 
liberator.url = 'https://mywidgets.cloudquant.ai/'
liberator.url = 'http://10.10.56.127:47753/'
Use https:// for domain names and http:// for direct IP addresses. Specify port numbers as shown above when required.
Once your client is configured, you are ready to begin pulling data.