dtocean-qt

PySide6 (Qt for Python) utilities for use within the DTOcean software suite. Currently, only widgets and models for pandas (the data analysis / manipulation library for Python) are available.

Part of the DTOcean suite of tools.

Installation

pip install dtocean-qt

Usage

An example of a basic PySide6 widget for a pandas DataFrame. Begin by importing the required functions and classes:

>>> import pandas
>>> import numpy
>>> import sys
>>> from PySide6 import QtWidgets
>>> from dtocean_qt.pandas.excepthook import excepthook
>>> from dtocean_qt.pandas.models.DataFrameModel import DataFrameModel
>>> from dtocean_qt.pandas.views.DataTableView import DataTableWidget
>>> from dtocean_qt.pandas.views._ui import icons_rc

Redirect exceptions:

>>> sys.excepthook = excepthook

Now set up a new empty DataFrame model:

>>> model = DataFrameModel()
>>> model.freeze_first = True

Setup an application and create a data table widget:

>>> app = QtWidgets.QApplication([])
>>> widget = DataTableWidget()
>>> widget.resize(800, 600)
>>> widget.hideVerticalHeader(True)

Assign the created model to the widget:

>>> widget.setViewModel(model)

Now create some test data:

>>> data = {
...    'A': [10, 11, 12], 
...    'B': [20, 21, 22], 
...    'C': ['Peter Pan', 'Cpt. Hook', 'Tinkerbell'],
...    'D': [True, True, False]}
>>> df = pandas.DataFrame(data)
>>> df
    A   B           C      D
0  10  20   Peter Pan   True
1  11  21   Cpt. Hook   True
2  12  22  Tinkerbell  False

Convert the column to the numpy.int8 data type to test the delegates in the table. int8 is limited to -128-127:

>>> df['A'] = df['A'].astype(numpy.int8)
>>> df['B'] = df['B'].astype(numpy.float16)
>>> df
    A     B           C      D
0  10  20.0   Peter Pan   True
1  11  21.0   Cpt. Hook   True
2  12  22.0  Tinkerbell  False

Fill the model with data:

>>> model.setDataFrame(df)

Finally, start the app:

>>> widget.show()
>>> app.exec() # doctest: +SKIP

You can find other examples in the examples folder of the source.

cd examples
python TestApp.py

Development

Development of dtocean-qt uses the Poetry dependency manager. Poetry must be installed and available on the command line.

If installing from the git repository, the image files must first be retrieved using git-lfs (ensure that git-lfs is installed first):

git lfs fetch --all
git lfs pull

To install:

poetry install

Tests

A test suite is provided with the source code that uses pytest.

Install the testing dependencies:

poetry install --with test

Run the tests:

poetry run pytest

Code quality can also be audited using the ruff and pyright tools. Install the dependencies:

poetry install --with audit

Run the audit:

poetry run ruff
poetry run pyright src

The above tests can be run across all compatible Python versions using tox and tox-uv. To install and run:

poetry install --with tox
poetry run tox

Contributing

Please see the dtocean GitHub repository for contributing guidelines.

Credits

This package is a fork of the pandas-qt project by Matthias Ludwig at Datalyze Solutions. It was adapted for use in the EU DTOcean project by Mathew Topper at TECNALIA.

It is now maintained by Mathew Topper at Data Only Greater.

License

MIT