# Code generation
The code generation feature in the learning module allows users to generate Python code for their experiments with a simple click. This feature enables users to make in-depth changes to the experiment code, share it with other computer scientists, and navigate seamlessly between the user interface and the code base.
After running one or multiple experiment pipelines, follow the instructions below to generate the code for a given pipeline.
* Open the results panel:
* Click the *Generate* button to select your pipelines for code generation:
* Select the pipelines
* Click generation:
Consequently, a[ *juypter notebook*](https://jupyter.org/) will automatically open with the generated code:
{% hint style="danger" %}
In most cases, you need to select the appropriate kernel before running the Jupyter notebook. Follow the instructions below to do so.
{% endhint %}
### Selecting the kernel for your generated code
* Click kernel
* Change kernel
* Select: *med\_conda\_env*
* The selected kernel's name must appear on the top right
{% hint style="warning" %}
If *med\_conda\_env* kernel is missing from your kernel's list. Follow the instructions below to add it.
{% endhint %}
Add your *med\_conda\_env* to your kernel's list by running the following two commands:
```
conda activate med_conda_env
python -m ipykernel install --user --name=med_conda_env
```
Please feel free to [contact us](https://medomicslab.gitbook.io/mediml-app-docs/forms/contact-us) if you need any further assistance :innocent:.
