# Altair data server
[](https://travis-ci.org/altair-viz/altair_data_server)
[](https://github.com/altair-viz/altair_data_server/actions?query=workflow%3Abuild)
[](https://github.com/altair-viz/altair_data_server/actions?query=workflow%3Alint)
[](https://github.com/psf/black)
[](https://mybinder.org/v2/gh/altair-viz/altair_data_server/master?urlpath=lab/tree/AltairDataServer.ipynb)
[](https://colab.research.google.com/github/altair-viz/altair_data_server/blob/master/AltairDataServer.ipynb)
This is a data transformer plugin for [Altair](http://altair-viz.github.io)
that transparently serves data for Altair charts via a background WSGI server.
Note that charts will only render as long as your Python session is active.
The data server is a good option when you'll be **generating multiple charts as
part of an exploration of data**.
## Usage
First install the package and its dependencies:
```
$ pip install altair_data_server
```
Next import altair and enable the data server:
```python
import altair as alt
alt.data_transformers.enable('data_server')
```
Now when you create an Altair chart, the data will be served in the background
rather than embedded in the chart specification.
Once you are finished with exploration and want to generate charts that
will have their data fully embedded in the notebook, you can restore the
default data transformer:
```python
alt.data_transformers.enable('default')
```
and carry on from there.
## Remote Systems
Remotely-hosted notebooks (like JupyterHub or Binder) usually do not allow the end
user to access arbitrary ports. To enable users to work on that setup, make sure
[jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) is
installed on the jupyter server, and use the proxied data server transformer:
```python
alt.data_transformers.enable('data_server_proxied')
```
## Example
[](https://mybinder.org/v2/gh/altair-viz/altair_data_server/master?urlpath=lab/tree/AltairDataServer.ipynb)
[](https://colab.research.google.com/github/altair-viz/altair_data_server/blob/master/AltairDataServer.ipynb)
You can see this in action, as well as read some of the motivation for this
plugin, in the example notebook: [AltairDataServer.ipynb](AltairDataServer.ipynb).
Click the Binder or Colab links above to try it out in your browser.
## Known Issues
Because [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy)
requires at least Python 3.5, the methods described in
[Remote Systems](#remote-systems) do not work do not work for older versions of Python.
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"description": "# Altair data server\n\n[](https://travis-ci.org/altair-viz/altair_data_server)\n[](https://github.com/altair-viz/altair_data_server/actions?query=workflow%3Abuild)\n[](https://github.com/altair-viz/altair_data_server/actions?query=workflow%3Alint)\n[](https://github.com/psf/black)\n[](https://mybinder.org/v2/gh/altair-viz/altair_data_server/master?urlpath=lab/tree/AltairDataServer.ipynb)\n[](https://colab.research.google.com/github/altair-viz/altair_data_server/blob/master/AltairDataServer.ipynb)\n\n\nThis is a data transformer plugin for [Altair](http://altair-viz.github.io)\nthat transparently serves data for Altair charts via a background WSGI server.\n\nNote that charts will only render as long as your Python session is active.\n\nThe data server is a good option when you'll be **generating multiple charts as\npart of an exploration of data**.\n\n## Usage\n\nFirst install the package and its dependencies:\n\n```\n$ pip install altair_data_server\n```\n\nNext import altair and enable the data server:\n\n```python\nimport altair as alt\nalt.data_transformers.enable('data_server')\n```\nNow when you create an Altair chart, the data will be served in the background\nrather than embedded in the chart specification.\n\nOnce you are finished with exploration and want to generate charts that\nwill have their data fully embedded in the notebook, you can restore the\ndefault data transformer:\n\n```python\nalt.data_transformers.enable('default')\n```\n\nand carry on from there.\n\n## Remote Systems\nRemotely-hosted notebooks (like JupyterHub or Binder) usually do not allow the end\nuser to access arbitrary ports. To enable users to work on that setup, make sure\n[jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) is\ninstalled on the jupyter server, and use the proxied data server transformer:\n\n```python\nalt.data_transformers.enable('data_server_proxied')\n```\n\n## Example\n\n[](https://mybinder.org/v2/gh/altair-viz/altair_data_server/master?urlpath=lab/tree/AltairDataServer.ipynb)\n[](https://colab.research.google.com/github/altair-viz/altair_data_server/blob/master/AltairDataServer.ipynb)\n\nYou can see this in action, as well as read some of the motivation for this\nplugin, in the example notebook: [AltairDataServer.ipynb](AltairDataServer.ipynb).\nClick the Binder or Colab links above to try it out in your browser.\n\n## Known Issues\n\nBecause [jupyter-server-proxy](https://github.com/jupyterhub/jupyter-server-proxy)\nrequires at least Python 3.5, the methods described in\n[Remote Systems](#remote-systems) do not work do not work for older versions of Python.\n\n\n",
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