A project is a user's main workspace run on a Yandex Cloud VM. Projects store the state of the interpreter, variables, installed packages, and much more. Operations with projects are performed in the JupyterLab development environment.
A notebook is an
*.ipynb file that you're working with in the code editor. In a notebook, you write code in cells and can add explanations in Markdown between them. The code is run for each cell separately. Cells can be run in any order.
DataSphere provides 10 GB of free storage for each project. You can increase the storage size if needed. Additional space will have to be paid for separately. For more information about the main storage expansion costs, see Pricing for DataSphere.
When you reopen your project, the notebook loads in the state you last saved it in.
Some variables aren't serialized and therefore can't be saved. For example, a variable with a file open for writing:
f = open("file.txt", "w").
A warning is shown for these variables during the assignment:
The following variables cannot be serialized:.
You can upload small amounts of data (up to 100 MB) to your DataSphere project over the interface. If you want to upload larger amounts of data, use your network storages or databases. For larger data volumes, it's also convenient to use datasets.
Configuring a project runtime environment
Projects are created with a preset development environment and pre-installed packages. For a list of all pre-installed packages, see List of pre-installed software. If you're missing a package, you can install it right from the notebook cell or build a Docker image.