Adding a customization

As Admin or Editor of a project, you can change the name, the description, and the hardware configuration of an environment definition that you created. You cannot change the language of an existing environment definition.

You can customize the software configuration of Jupyter notebook environment definitions through conda channels or by using pip. This can be done by providing a list of conda packages, a list of pip packages, or a combination of both. When using conda packages, it is also possible to provide a list of additional conda channel locations through which the packages can be obtained.

Remember: If you customized the software configuration of an environment or plan to install additional libraries within a notebook, but do not change the configuration of conda and pip (see Customization options for conda and pip), the runtimes that are started with a customization must have public network access.

The default environment runtimes use the time zone where they were created, which is UTC time. If you want to use your local time in notebook functions, you need to download and modify the environment runtime configuration file to use your time zone. See Notebook returns UTC time and not local time for the details about how to access and change the file.

Watch the following video see how to create a custom environment for a Jupyter notebook.

This video provides a visual method as an alternative to following the written steps in this documentation.

To customize an environment definition you created:

Click your project’s Environments tab and check that no runtime is active for the environment definition you want to change.
Select the environment definition you want to customize and add your changes.

For a Juypter notebook environment definition, you can create a customization and specify the libraries to add to the standard packages that are available by default. You can also use the customization to upgrade or downgrade packages that are part of the standard software configuration.

The libraries that are added to an environment definition through the customization aren’t persisted; however, they are automatically installed each time the environment runtime is started. Note that if you add a library using pip install through a notebook cell and not through the customization, only you will be able to use this library; the library is not available to someone else using the same environment definition.

If you want you can use the provided templates to add custom libraries. There is a different template for Python and for R. The following example shows you the Python template:
```
# Modify the following content to add a software customization to an environment.
# To remove an existing customization, delete the entire content and click Apply.

# Add conda channels below defaults, indented by two spaces and a hyphen.
channels:
  - defaults

# To add packages through conda or pip, remove the comment on the following line.
# dependencies:

# Add conda packages here, indented by two spaces and a hyphen.
# Remove the comment on the following line and replace sample package name with your package name:
#  - a_conda_package=1.0

# Add pip packages here, indented by four spaces and a hyphen.
# Remove the comments on the following lines and replace sample package name with your package name.
#  - pip:
#    - a_pip_package==1.0
```
Important when customizing:
- Before you customize a package, verify that the changes you are planning have the intended effect.
  - conda can report the changes required for installing a given package, without actually installing it. You can verify the changes from your notebook. For example, for the library spaCy:
    - In a Python notebook, enter: !conda install --dry-run spacy=2.0.16
    - In an R notebook, enter: print(system2("conda", args="install --dry-run spacy=2.0.16", stdout=TRUE))
  - pip does install the package. However, restarting the environment again after verification will remove the package. Here too, you can verify the changes from your notebook. For example, for the library spaCy:
    - In a Python notebook, enter: !pip install spacy
    - In an R notebook, enter: print(system2("pip", args="install spacy", stdout=TRUE))
- If you can get a package through conda from the default channels and through pip from PyPI, the preferred method is through conda from the default channels.
- Conda does dependency checking when installing packages which can be memory intensive if you add many packages to the customization. Ensure that you select an environment with sufficient RAM to enable dependency checking at the time the runtime is started.
- To prevent unnecessary dependency checking if you only want packages from one Conda channel, exclude the default channels by removing defaults from the channels list in the template and adding nodefaults.
- For R notebook environments on POWER: If you add a software customization to an environment definition, be mindful that the conda-forge channel is registered as a default channel and will be used for libraries that are not available on other conda channels for R environmments on POWER.
- If you only add packages through pip to the customization template, you must make sure that the dependencies key is not commented out in the template. A customization with a pip package that does not start with the dependencies key will generate an error.
- Wherever possible, provide a package version number even if the version that you want to use is the latest and might well be picked up by the package manager. Providing a version number reduces time and memory consumption significantly during package installation.
- When you specify a package version, use a single = for conda packages and == for pip packages. If the version you specify causes a dependency conflict that the package manage can resolve, a different or newer version might be installed. If you don’t specify a version, the package manager might pick the latest version available, or keep the version that is in the package.
- You cannot add arbitrary notebook extensions as a customization because notebook extensions must be pre-installed.
Apply your changes.

Adding a customization

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