PyToQlik is a library that allows you to integrate Qlik Desktop with Jupyter notebooks. With it you can:

• Open and edit a Qlik app inside a Jupyter notebook;
• Create a Qlik object with data from a pandas DataFrame data structure and/or;
• Import data from a Qlik object and create a pandas DataFrame to work with in Python.

For this library to work you must have a functioning Qlik Desktop App installed and running on your local machine. You will also need to have the pandas library and a Jupyter Notebook local server (read https://jupyter.readthedocs.io/en/latest/running.html).

You can then download and install PyToQlik using:

Installation

pip install pytoqlik 

Creating a Qlik app and feeding it data

from pytoqlik import Pytoqlik
import seaborn

df = seaborn.load_dataset('tips')  # df is just some example data provided by the seaborn library

p2q = Pytoqlik()
app = p2q.toQlik(df)

Importing data from a Qlik object to Python

from pytoqlik import Pytoqlik
import seaborn

df = seaborn.load_dataset('tips')  # df is just some example data provided by the seaborn library

p2q = Pytoqlik()
app = p2q.toQlik(df)
app.toPy('your ObjectID')

Current documentation can be found here.

PyToQlik is currently implemented for QlikSense Desktop versions. Cloud and Enterprise versions of Qlik are still in active development.

• Qlik Enterprise support
• Qlik Cloud support

• Data fetching based on dimensions and measures
• More robust embedding objects and sheets
• More robust script editing
• Object creation and manipulation via Python
• Auxiliary functions, app listing and object listing
• Task creation and managing
• ETL features in Python