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