Metadata-Version: 2.1
Name: pytoqlik
Version: 0.0.9
Summary: This lib allows you to integrate qlik with jupyter notebook.
Home-page: https://github.com/bixtecnologia/pytoqlik
Author: Angelo Baruffi Nogueira
Author-email: angelo.baruffi@bixtecnologia.com.br
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/bixtecnologia/pytoqlik/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

![PTQ](https://i.imgur.com/0D4Qvkt.png)

# PyToQlik

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.

## Getting Started

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 
```

## Usage

### Example 1

**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)
```

### Example 2

**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
<img src="toPy.gif" />

---

### Documentation

Current documentation can be found [here](docs/documentation.md).

---

### Current limitations

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

---

### Features in development

#### Connectivity
- Qlik Enterprise support
- Qlik Cloud support

#### Functionality
- 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


