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.
git clone
an app that you co-own over HTTPS in a workspace. To work around this~/.gitconfig
file, then run git clone
again and supply your Dash Enterprise credentials when prompted.app.run(debug=True)
which is an insecure view for thirdproject.toml
that uses environment variables to customize your app build (for example, the Python version used), these environment variables are not applied in workspaces.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.gcc
cannot be installed within workspaces (but can be installed during app deployment). Most package versions newer than 2020 include prebuilt package wheels that don’t need compilation.numpy
and statsmodels
packages, numpy==1.17.3
and statsmodels==0.10.2
or later will successfully install in workspaces.kubectl
commands below.To view a workspace’s build logs (correspond to what is available in the App Info), make sure your kubectl
context is set to the right cluster, and then run the following commands:
sh
kubectl get pods -l app=workspace-<app-name> -n dash-apps | awk '{print $1}' | tail +2
where <app-name>
is the name of the app whose workspace build logs you want to view. The output is the name of the pod the workspace is running on.
sh
kubectl logs <pod-name> dash-app-build -n dash-apps
where <pod-name>
is the name of the pod the workspace is running on.
To view a workspace’s debug logs (not available in the App Info), make sure your kubectl
context is set to the right cluster, and then run the following command:
sh
kubectl logs -l app=workspace-<app-name> -n dash-apps
<app-name>
is the name of the app whose workspace debug logs you want to view.pip
in a workspace terminal are not persisted with rebuilds.gunicorn
or dash < 1.13.0
inside a workspace, thengunicorn
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 at
https://<your-dash-enterprise-server>/workspace/view/workspace-<appname>`killed
message is printed in the terminal.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