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JS9 brings image display right into your browser:

- display URL-based FITS images and binary tables
- drag and drop FITS images and binary tables
- change the colormap and scale
- manipulate the contrast/bias with the mouse
- display pixel values and WCS position information
- create and manipulate geometric regions of interest
- add your own extensions using plugins and the Public API
- perform data analysis (local and server-side)
- display RGB composite images
- control JS9 from the command line
- print images
- much more ...

See: for more information about JS9. connects Python and JS9 via the js9Helper.js back-end server:

- The JS9 class constructor connects to a single JS9 instance in a Web page.
- The JS9 object supports the JS9 Public API and a shorter command-line syntax.
- See: for info about the public api
- Send/retrieve numpy arrays and astropy (or pyfits) hdulists to/from JS9.

Requirements: Python 3.5 or higher is required. Beyond that, pyjs9 communicates with a JS9 back-end Node server (which communicates with the browser itself). By default, pyjs9 utilizes the requests <> module to communicate with the JS9 back-end server. However, if you install python-socketio <>`, pyjs9 will use the faster, persistent protocol.

Install from the repository using pip, as usual:

> pip install git+

or from a local copy:

> pip install /path/to/local/copy

Mandatory dependencies:


Optional dependencies:

numpy               # support for GetNumpy and SetNumpy methods
astropy             # support for GetFITS and SetFITS methods
python-socketio     # fast, persistent protocol, instead of html

To run:

> # ensure JS9 node-server is running ...
> # visit your local JS9 Web page in your browser ...
> python
... (startup messages) ...
>>> import pyjs9
>>> j = pyjs9.JS9()        # default: connect to 'http://localhost'
>>> j.GetColormap()
{'bias': 0.5, 'colormap': 'grey', 'contrast': 1}
>>> j.SetColormap('red')
>>> j.cmap()
'red 1 0.5'
>>> hdul = j.GetFITS()
Filename: (No file associated with this HDUList)
No.    Name         Type      Cards   Dimensions   Format
0    PRIMARY     PrimaryHDU       6   (1024, 1024)   int32
>>> narr = j.GetNumpy()
>>> narr.shape
(1024, 1024)

If you have internet connectivity, visit the JS9 Web page at with your browser and:

> python
... (startup messages) ...
>>> import pyjs9
>>> j = pyjs9.JS9('')        # connect to JS9 Web site
>>> j.GetColormap()
{'bias': 0.5, 'colormap': 'grey', 'contrast': 1}
>>> # etc ...
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