dtocean-qt

Utilities to use pandas (the data analysis / manipulation library for Python) with Qt within the DTOcean software suite. This package is a dependency of dtocean-app.

* For python 2.7 only.

Installation

Installation and development of dtocean-qt uses the Anaconda Distribution (Python 2.7)

Conda Package

To install:

$ conda install -c dataonlygreater dtocean-qt

Source Code

Conda can be used to install dependencies into a dedicated environment from the source code root directory:

$ conda create -n _dtocean_qt python=2.7 pip pyyaml

Activate the environment, then copy the .condrc file to store installation
channels:

$ conda activate _dtocean_qt
$ copy .condarc %CONDA_PREFIX%

Install dtocean-qt and its dependencies using conda and pip:

$ conda install --file requirements-conda-dev.txt
$ pip install -e .

To deactivate the conda environment:

$ conda deactivate

Tests

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

If not already active, activate the conda environment set up in the Source Code section:

$ conda activate _dtocean_qt

Install packages required for testing to the environment (one time only):

$ conda install -y -c conda-forge "pytest<4" pytest-qt

Run the tests:

$ py.test tests

Uninstall

To uninstall the conda package:

$ conda remove dtocean-qt

To uninstall the source code and its conda environment:

$ conda remove --name _dtocean_qt --all

Usage

An example of a basic PyQt4 widget for a pandas DataFrame.

Import the required modules. Redirect exceptions and use QtGui from the compat module to take care if correct sip version, etc:

>>> import pandas
>>> import numpy
>>> import sys
>>> from dtocean_qt.excepthook import excepthook
>>> sys.excepthook = excepthook

>>> from dtocean_qt.compat import QtGui
>>> from dtocean_qt.models.DataFrameModel import DataFrameModel
>>> from dtocean_qt.views.DataTableView import DataTableWidget
>>> from dtocean_qt.views._ui import icons_rc

Now set up a new empty DataFrame model:

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

Setup an application and create a data table widget:

>>> app = QtGui.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)

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)

Fill the model with data:

>>> model.setDataFrame(df)

Finally, start the app:

>>> widget.show(); app.exec_()

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

$ cd examples
$ python TestApp.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

See this blog post for information regarding development of the DTOcean ecosystem.

Please make sure to update tests as appropriate.

Credits

This package is a fork of the (now superseded) 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