Warnings & Limitations

This documentation is for Dash Enterprise.
Dash Enterprise is the fastest way to write & deploy Dash apps and
Jupyter notebooks.
10% of the Fortune 500 uses Dash Enterprise to productionize AI and
data science apps. Find out if your company is using Dash Enterprise.

Usage Limitations

• Only the owner of the app has the ability to create and rebuild a workspace. Administrators—in addition to the app owner—can stop, restart, and delete the workspace. For more information, refer to Roles and Permissions.
• You can’t share the development site URL with anyone except administrators. This is
  by design: the development app frequently runs with
  app.run(debug=True) which is an insecure view for third
  parties. To share your app with others, deploy it.
• When developing your app with Workspaces, the minimum supported Dash version is dash==1.10 and the recommended version is dash==2.3.0 or later. If you are using a version of Dash prior to 2.3 and use the preview panel on an app running in a workspace, if you stop the app in the terminal, Dash’s front-end’s alert system prevents you from returning to the workspace.
• Custom VS Code plugins and Jupyter plugins are not supported.
• When previewing apps that use Snapshot Engine in the Preview panel, PDF downloads are blocked by Chrome. Open a new tab and go to the development site to preview PDF downloads in Chrome.
• When previewing apps in the Preview panel, the fullscreen
  capabilities of Dash Design Kit only work in Chrome.

General Warnings

• You are not automatically logged in to the Dash Enterprise CLI. Log in with de --host example.plotly.host login, replacing the example host name with your Dash Enterprise host name (without https).
• There are no CPU limits within a workspace. Performing CPU intensive tasks within a workspace could cause resource issues for other apps.
• If using gunicorn or dash < 1.13.0 inside a workspace, then
  note that gunicorn or flask will print out a message like Listening at: <a href="http://0.0.0.0:8050.”>http://0.0.0.0:8050.</a> The app is not available at this URL. Instead, the app is available athttps://<your-dash-enterprise-server>/workspace/view/workspace-<appname>`
• Apps need to run on port 8050 (the default) within the workspace
  in order to preview them.
• Databases are shared between the deployed app and the
  workspace, which means that it is possible to delete data from a
  production database while using a workspace.
• Workspaces consume memory on the server even when they aren’t open.
• Closing a workspace does not stop a running development app. The development app continues to run and consume
  memory in the background. If your server is memory constrained, we
  recommend stopping the development app before closing your workspace, or even deleting old workspaces. Remember, you can quickly recreate them as needed.
• If running your development app causes your workspace to exceed its memory limit, the developement app is stopped and a killed message is printed in the terminal.
• Packages installed with pip in the terminal are not persisted on workspace rebuild if your app contains a project.toml file that specifies a Python version.
• The URL address bar of the preview tab does not update when
  navigating across multi-page apps. However, page
  navigation does work.

Debugging

• If your workspace has a process currently running in the
  terminal and you refresh the page, the workspace sometimes gets
  caught in a loading state. The solution to this is to empty your
  cache/cookies.

App Won’t Run with python app.py

If you run your app with python app.py and close your
browser, the process may continue running in the background. When
you reopen your workspace and run python app.py, you may find
that this fails as the previous app is still running. You may not
be able to terminate the previous process with ctrl+C as the previous
terminal view may not be available. To terminate the previously running
Python process, either:

• Save your files, add your recently installed packages to requirements.txt, and restart your workspace.

• List the Python processes with $ ps aux | grep python. Then, run $ pkill <pid> on the process IDs. For example,
  you might see:
  shell $ ps aux | grep python root 5446 1.9 0.2 236604 30868 pts/0 Sl+ 22:53 0:34 python app.py root 5557 2.8 2.7 4223340 429068 ? SLl 22:54 0:51 /usr/lib/theia/plugins/vscode-python/extension/languageServer.0.5.45/Microsoft.Python.LanguageServer root 6564 4.5 0.5 1138496 90080 pts/0 Sl+ 22:59 1:06 /app/.heroku/python/bin/python /workspace/app.py root 11721 0.0 0.0 11464 1088 pts/1 S+ 23:23 0:00 grep --color=auto python

in this case, you would run:
shell root@c4b0ace22eb0:/workspace# pkill 5446 root@c4b0ace22eb0:/workspace# pkill 6564