{{codeEnv.envName}}

Code environment

General info

{{codeEnv.deploymentMode}}
{{codeEnv.owner}}
{{codeEnv.path}}
{{codeEnv.pythonInterpreterFriendlyName }}
{{codeEnv.desc.externalCondaEnvName}}
{{codeEnv.desc.conda ? "Yes" : "No"}} Whether to use Conda to create and manage the packages. If not, use simply virtualenv and pip.

Spark

Python binary on the Yarn nodes for Pyspark (save, remove then re-install jupyter support to update in notebooks)

Extra options

One item per option (so "-i /stuff" must be two items)
One item per option (so "-i /stuff" must be two items)
One item per option (so "-i /stuff" must be two items)
One item per option (so "-i /stuff" must be two items)

Jupyter

{{codeEnv.desc.pythonInterpreter == 'CUSTOM' ? codeEnv.desc.customInterpreter : codeEnv.desc.pythonInterpreter}}
{{codeEnv.kernelSpecName || 'not installed'}} (needs ipykernel package to be in the env)
Unable to check status

Code env usages

Permissions

Packages to install

Install support for Jupyter notebooks
The following packages were previously "Requested" and are currently installed, but have been removed from the requested list. These packages may become unavailable. Check whether this is desired.
{{getPackagesThatWereRequiredAndInstalledButAreNotRequiredAnymore('conda').join(', ')}}
pyspark is {{ isPackageInstalled('conda', 'pyspark') ? 'installed in' : 'in the requested packages of' }} your code env. It is not recommended to install pyspark manually. Please refer to the documentation to find out how to interact with Spark in the recommended way.
Requested packages (Conda)

Add here the packages that you want to be available in the environment. Do not remove packages once they are installed. Only packages mentioned here are guaranteed to be installed.

For information: base packages (Conda)

These are the packages required for the selected core features. These packages cannot be removed nor reversioned

{{codeEnv.mandatoryCondaEnvironment}}
The following packages were previously "Requested" and are currently installed, but have been removed from the requested list. These packages may become unavailable. Check whether this is desired.
{{getPackagesThatWereRequiredAndInstalledButAreNotRequiredAnymore('pip').join(', ')}}
pyspark is {{ isPackageInstalled('pip', 'pyspark') ? 'installed in' : 'in the requested packages of' }} your code env. It is not recommended to install pyspark manually. Please refer to the documentation to find out how to interact with Spark in the recommended way.
Requested packages (Pip)

Add here the packages that you want to be available in the environment. Do not remove packages once they are installed. Only packages mentioned here are guaranteed to be installed.

  Do not put packages here that are installed as conda packages or available as conda packages (including on conda-forge). Doing so is very likely to cause issues with those packages.
For information: base packages (Pip)

These are the packages required for the selected core features. These packages cannot be removed nor reversioned

{{codeEnv.mandatoryPackageList}}

Currently installed packages

Installed packages (Conda)
These are the packages that are currently installed in the code env. Note that only the list in "Packages to install" is authoritative as to which packages will be installed.
Packages that are not in "Packages to install" may not be installed when rebuilding this env or in containers.
This list only reflects the "local" code env, not what is available in containers. 
{{codeEnv.actualCondaEnvironment}}
Installed packages (Pip)
These are the packages that are currently installed in the code env. Note that only the list in "Packages to install" is authoritative as to which packages will be installed.
Packages that are not in "Packages to install" may not be installed when rebuilding this env or in containers.
This list only reflects the "local" code env, not what is available in containers. 
{{codeEnv.actualPackageList}}

Packages

Packages (Conda) 
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Packages (Pip) 
{{nonManagedEnvDetails.nocondaEnvSpec}}

Code env logs

Containerized execution

Resources

Cannot use code-environment resources without the core packages.