![]() This password will be used to access any Jupyter session running from this installation, so pick something sensible. You can edit this manually, but the easiest option is to set the password by running Jupyter with the password argument: jupyter notebook password ![]() ![]() This is stored in jupyter_notebook_config.py which by default lives in ~/.jupyter. First, connect to the remote server if you haven’t already ssh Jupyter takes browser security very seriously, so in order to access a remote session from a local browser we need to set up a password associated with the remote Jupyter session. The best part about this is that you can set up the Jupyter session once then connect to it from any browser on any machine once an ssh tunnel is created, without worrying about X11 forwarding.ġ. Fortunately, the solution is simple: we run Jupyter remotely, create an ssh tunnel connecting a local port to the one used by the Jupyter session, and connect directly to the Jupyter session using our local browser. There’s just one problem – since Jupyter notebook is browser-based and works by connecting to the Jupyter session running locally, you can’t just run Jupyter remotely and forward X11 like you would a traditional graphical IDE. You can’t copy the data to your local machine (well, you can, but you’re sensible so you won’t), but you can run your Jupyter session on the remote server. Suppose you have lots of data which lives on a remote server and you want to play with it in a Jupyter notebook. ![]() To celebrate the recent beta release of Jupyter Lab (try it out of you haven’t already), today we’re going to look at how to run a Jupyter session (Notebook or Lab) on a remote server. ![]()
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