A project is a JupyterLab development environment that runs on a Yandex Cloud VM. It includes the Jupyter Notebook editor and auxiliary tools.
A notebook is an
*.ipynb file that you are working with in the Jupyter Notebook editor. In this editor, you write code in cells and between them you can write explanations in Markdown. The code is run for each cell separately. Cells can be run in any order.
Projects store the state of the interpreter, variables, installed packages, and much more. When you reopen your project, the notebook loads in the state you last saved it in.
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 that are available in early access mode.
DataSphere provides 10 GB of free storage for each project. If, when a cell is running, the amount of data exceeds the allocated storage, the cell is stopped. You can expand your primary storage. Additional space will have to be paid for separately. For more information about the main storage expansion costs, see Pricing for DataSphere.
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:.
The service automatically redirects you to the management console if you don't use the project for 20 minutes or close it. For more information about service limits, see Quotas and limits in DataSphere.