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Learn about kernels
Pages in Dolphyn are powered by "kernels" β€” this means that you can execute code and produce outputs.
Dolphyn's pages are powered by Jupyter kernels. This means that you can execute any commands in Dolphyn in the same way as a traditional Jupyter notebook. You can learn more about Jupyter kernels here.
By default, when you create a new page in Dolphyn, we automatically spin up a kernel enabling you to execute code and use our low-code building blocks.
This process usually happens on the order of milliseconds, but occasionally you may see the Connecting flag on the page header β€” indicating that the kernel is setting up, and code execution won't work until the flag disappears.
The Connecting flag in the header indicates that the kernel is starting up.

Running, restarting and interrupting kernels

Look to the top right of a page for everything to do with running, and managing your kernel.

Running a page

Blocks on a page are executed sequentially from top to bottom. During execution, if a block error's out, it will stop execution of all subsequent blocks on the page.
There are 2 main ways to run the whole page:
  1. 1.
    Click on the blue Run All button at the top right of the page. This will execute and any code or low-code block sequentially on the page.
  2. 2.
    Open the more menu ... and select Run all.

Restarting the kernel

Restarting the kernel will erase the stored value of any Python variables in memory. If you have data that is hard to reproduce, you may want to save it before restart.
You may need or want to occasionally clean up the variable state of the kernel, or there may be cases where the kernel is hung by some code that you've run. In either case, you can navigate to the more menu ... and click on Restart kernel to reset the kernel state and clear out any existing variables.

Interrupting kernels

There may be a case where a long running job has stalled or is unresponsive. To halt execution you can visit the more menu ... and select Interrupt kernel.

Some pages don't have kernels...

Depending on the type of page you're viewing on in Dolphyn β€” eg. model, data source, API, the kernel may not be available, because the type of page doesn't serve as a canvas from where you would execute code. In this case, you should see a banner under the header indicating that the page type doesn't support code execution.
The yellow banner indicates that the kernel is not available for this page type.