pyqtgraph/pyqtgraph: Fast data visualization and GUI tools for scientific / engineering applications

PyQtGraph =========

A pure-python graphics library thatm uses the Qt framework.

PyQtGraph is intended for use in mathematics / scientific / engineering applications. Despite being written entirely in python, the library is fast due to its heavy leverage of numpy for number crunching, Qt's GraphicsView framework for 2D display, and OpenGL for 3D display.

Requirements ------------

PyQtGraph has adopted SPEC 0.

This project supports:

Python versions released within the last 3 years
NumPy, SciPy and matplotlib versions released within the last 2 years
Qt5 5.15 or Qt6 6.8+

Currently this means:

Python 3.12+
Qt 5.15 or 6.8+
PyQt5, or

PyQt6, or PySide6

numpy 2.2+

Optional Dependencies for Added Functionality ---------------------------------------------

Through 3rd party libraries, additional functionality may be added to PyQtGraph, see the table below for a summary.

| Library | Added functionality | | -------------- | - | | [scipy] |

Image processing through [ndimage]
Data array filtering through [signal]

h5py

Export in hdf5 format

colorcet

Add a collection of perceptually uniform colormaps

matplotlib

Export of PlotItem in matplotlib figure
Add matplotlib collection of colormaps

cupy

CUDA-enhanced image processing

numba

Faster image processing

jupyter_rfb

Jupyter Notebook support

[scipy]: https://github.com/scipy/scipy [ndimage]: https://docs.scipy.org/doc/scipy/reference/ndimage.html [signal]: https://docs.scipy.org/doc/scipy/reference/signal.html [h5py]: https://github.com/h5py/h5py [colorcet]: https://github.com/holoviz/colorcet [matplotlib]: https://github.com/matplotlib/matplotlib [numba]: https://github.com/numba/numba [cupy]: https://docs.cupy.dev/en/stable/install.html [jupyter_rfb]: https://github.com/vispy/jupyter_rfb

Support -------

Report issues on the GitHub issue tracker
Post questions to

Installation Methods --------------------

From PyPI

pip install pyqtgraph

pip install git+https://github.com/pyqtgraph/pyqtgraph@master

From conda

conda install -c conda-forge pyqtgraph

Many linux package repositories have release versions.

The official documentation lives at pyqtgraph.readthedocs.io

The easiest way to get familiar with PyQtGraph is to browse through the examples; run python -m pyqtgraph.examples to launch the examples application.

Benchmarking ------------

There is support for the asv benchmarking library. Should a user have cuda installed on their system, they should edit asv.conf.json file, and add the entry "cupy-cuda##x": [""] to the matrix.req section (where ## is the version of cuda is the version of cuda installed on your machine). It relavent section should look like the the following.

...
    "req": {
      "pyqt6": [""],
      "pyqt5": [""],
      "PySide6-Essentials": [""],
      "numba": [""],
      "cupy-cuda##x": [""]  // add this line, replace ## with cuda version
    }
...

As a variety of different versions of python and Qt bindings are tested, running the full benchmark suite can take a while!

Used By -------

Here is a partial listing of some of the applications that make use of PyQtGraph!

pyqtgraph/pyqtgraph: Fast data visualization and GUI tools for scientific / engineering applications

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