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:
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')
Step by step guide
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.
Features in 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