Platform Environments

Datalayer supports a range of predefined environments to help you quickly leverage powerful GPU and CPU capabilities, enabling you to focus on your Data Science projects without unnecessary setup time.

Platform Environments come equipped with popular Data Science libraries such as PyTorch, HuggingFace, Langchain and more.

If you need a specific library that is not included in the Platform Environments, you can install it directly within your Kernel using the !pip install command.

SaaS

You can see the list of available environments in the SaaS under the Environments tab.

JupyterLab

CLI

You can list the available environments using the following CLI command:

datalayer envs list

                                               Environments                                           
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ID        ┃ Cost p… ┃ Name              ┃ Description                    ┃  ┃                Resources ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ python-s… │    0.01 │ Python Simple En… │ A Python environment for simp… │  │ {"cpu": "250m", "memory… │
└───────────┴─────────┴───────────────────┴────────────────────────────────┴──┴──────────────────────────┘