Wrap an arbitrary webapp so it can be used in place of jupyter-singleuser in a JupyterHub setting.
Within JupyterHub this allows similar operation to jupyter-server-proxy except it also removes the Jupyter notebook itself, so is working directly with the arbitrary web service.
OAuth authentication is enforced based on JUPYTERHUB_* environment variables.
This project is used in ContainDS Dashboards, which is a user-friendly way to launch Jupyter notebooks as shareable dashboards inside JupyterHub. Also works with Streamlit and other visualization frameworks.
Install using pip.
pip install jhsingle-native-proxy
The process to start is specified on the command line, for example a streamlit web app:
jhsingle-native-proxy streamlit hello
By default the jhsingle-native-proxy server will listen on port 8888, forwarding to port 8500.
But you will normally need to tell jhsingle-native-proxy which port the end process will run in, and maybe tell the end process which port you want it to use (which you can do with the substitution variable {port}).
Note the use of -- to signal the end of command line options to jhsingle-native-proxy. Then the third party command line itself can contain options starting with dashes. An alternative is to use the substitution {--}
jhsingle-native-proxy -- streamlit hello --server.port {port} --server.headless True --server.enableCORS False
To run jhsingle-native-proxy itself listening on a different port use:
jhsingle-native-proxy --port 8000 streamlit hello
To run jhsingle-native-proxy on port 8000, and the end process on 8505:
jhsingle-native-proxy --port 8000 --destport 8505 -- streamlit hello --server.port {port} --server.headless True --server.enableCORS False
Use the JUPYTERHUB_SERVICE_PREFIX env var to specify the first part of the URL to listen to (and then strip before forwarding). E.g. JUPYTERHUB_SERVICE_PREFIX=/user/dan will mean requests on http://localhost:8888/user/dan/something will forward to http://localhost:8500/something
You can also specify --ip 0.0.0.0 for the address to listen on.
Below we use the substitution {--} for the command to run, allowing us to specify --ip to jhsingle-native-proxy instead of the command being run.
jhsingle-native-proxy --port 8000 --destport 8505 streamlit hello {--}server.port {port} {--}server.headless True {--}server.enableCORS False --ip 0.0.0.0
Similarly, use e.g. {-}m to represent -m in the final command.
Running voila at the subfolder URL e.g. /user/dan/:
python -m jhsingle_native_proxy.main --destport 0 voila ./Presentation.ipynb {--}port={port} {--}no-browser {--}Voila.server_url=/ {--}Voila.base_url={base_url}/ {--}debug
'destport 0' above instructs jhsingle-native-proxy to choose a random free port on which to run the sub-process (Voila), and of course substitutes that as {port} in the Voila command line so it knows which port to listen on. destport 0 is the default anyway.
Or specify presentation_path as a substitution instead of hard-coding, which is sometimes easier in your wrapper code:
python -m jhsingle_native_proxy.main --destport 0 voila {presentation_path} {--}port={port} {--}no-browser {--}Voila.server_url=/ {--}Voila.base_url={base_url}/ {--}debug --presentation_path=./Presentation.ipynb
In addition, if presentation_path is provided, two further substitution variables are available: presentation_dirname and presentation_basename. These are computed using Python's os.path.dirname and os.path.basename functions on presentation_path.
The above examples all assume OAuth will be enforced, as per the JUPYTERHUB_* env vars.
Alternatives can be specified via the authtype flag:
Same as default:
jhsingle-native-proxy --authtype=oauth streamlit hello
No auth required at all:
jhsingle-native-proxy --authtype=none streamlit hello
The env vars JUPYTERHUB_USER and JUPYTERHUB_GROUP can be used, as typical for any JupyterHub single server, to specify user/groups of JupyterHub that should be allowed access via OAuth. There is an additional bespoke env var called JUPYTERHUB_ANYONE which can be set to 1 to allow any authenticated user access. (i.e. anyone who has an account on the JupyterHub)
--request-timeout=300 specifies the timeout in seconds that it waits for the underlying subprocess to return when proxying normal requests. Default is 300.
{origin_host} in the command argument will be replaced with the first 'host' seen in any request to the jhsingle-native-proxy server.
--last-activity-interval=300 specifies how often in seconds to update the hub to provide the last time any traffic passed through the proxy (default 300). Specify 0 to never update. --force-keep-alive or --no-force-keep-alive: the former (default) ensures that the hub is notified of recent activity even if there wasn't any - only works if last-activity-interval is not 0.
--ready-check-path (default /) to change the URL on the subprocess used to poll with an HTTP request to check for readiness.
--repo - use git to check out a repo before running the sub process
--repofolder - the path of a folder (to be created if necessary) to contain the git repo contents
--forward-user-info - forward to the underlying process an X-CDSDASHBOARDS-JH-USER HTTP header containing JupyterHub user info as JSON-encoded string
--query-user-info - add a GET query param named CDSDASHBOARDS_JH_USER when calling underlying process containing JupyterHub user info as JSON-encoded string
--ready-timeout - integer timeout for period of checking the process is running at startup (default 10). Increase if your process is not able to return anything at --ready-check-path until a longer time after it first starts up. Be aware that the process must (once ready) return its HTTP response within 1 second. Note this argument is different from --request-timeout which applies to individual HTTP proxy calls during normal operation (not just at startup).
--websocket-max-message-size - message size in bytes allowed by websocket connections made to the underlying process (default is to rely on the tornado library defaults).
--progressive - flush buffer from underlying service whenever chunks appear (this is useful to see results from Voila sooner)
- Pin simpervisor version to avoid conflict with version 1.0. Thanks to dangercrow.
- Change to work with JupyterHub 2 (detects port from JUPYTERHUB_SERVICE_URL env var if no --port set)
- New command-line options --ready-timeout and --websocket-max-message-size
- New command-line option --progressive to flush buffer from underlying service whenever chunks appear (this is useful to see results from Voila sooner)
- oauth_callback URL now accessible when running with JUPYTERHUB_BASE_URL of /
- New command-line option --query-user-info to add a CDSDASHBOARDS_JH_USER GET query param to the http request to the underlying service.
- New command-line option --forward-user-info to add a X-CDSDASHBOARDS-JH-USER header to the http request to the underlying service. The header value is a JSON-encoded dict containing kind, name, admin, groups fields from the logged-in JupyterHub user if available.
- Require simpervisor >= 0.4 to ensure Python 3.9 compat.
- Displays INFO level logs by default, which includes output of the subprocess (turn off with --no-logs) Issue #7
- Logs from subprocess written out at different level depending on source (stderr -> error, stdout -> info)
- Long subprocess logs are handled and truncated instead of throwing an error cdsdashboards issue #44
- Different handling of branch checkout when using git repo source, when switching brances compared to what was checked out before
- Always convert presentation_path to an absolute path (based on CWD) before passing to the sub-command.
- Also accept URLs at the URL-encoded equivalent of the prefix and redirect to the regular version of the URL.
- Change working folder to repofolder when specified
- Require tornado 6.0.4+
- Fix to ensure both websockets are opened at the same time, to avoid writing to a websocket that's not yet open.
- Open up underlying process' websocket before connecting our own with the client. This ensures any other GET headers can be passed back to the client. (Fix for Streamlit XSRF problems.)
- Added --allow-root option (currently ignored) to avoid errors if this flag is usually passed to jupyter-singleuser
- Switch to a Conda env before running subprocess by specifying --conda-env option
- fix because subprocess sometimes blocked if too much output generated
- repo and repofolder optional arguments added
- Defaults presentation_path to empty str ('') if not supplied, avoiding error
- presentation_path can be provided as a command line argument to become a substitution variable.
- presentation_basename and presentation_dirname are also available when presentation_path is supplied.
- Better websocket handling (subprotocols)
- {origin_host} variable added
- request-timeout added to the proxy call, and the default set to 300 (20 seconds was the httpclient's default previously)
- Now allows single-dash placeholder, e.g. {-}m translates to -m in the final subprocess command.
git clone https://github.com/ideonate/jhsingle-native-proxy.git
cd jhsingle-native-proxy
pip install -e .
To run directly in python: python -m jhsingle_native_proxy.main <rest of command line>
Testing git puller:
python -m jhsingle_native_proxy.main --authtype=none --destport=0 --port=8888 voila ./sincosfolder/Presentation.ipynb {--}port={port} {--}no-browser {--}Voila.server_url=/ {--}Voila.base_url={base_url}/ --repo=https://github.com/danlester/binder-sincos --repofolder=sincosfolder