Manage Projects
Set up a Project for your evaluation or monitoring use case.
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Set up a Project for your evaluation or monitoring use case.
Last updated
Before creating a Project, you need a Workspace.
In Evidently Cloud, your account is your Workspace. .
In self-hosted deployments, a Workspace is a remote or local directory. .
You can create a Project using the Python API or directly in the user interface.
To create a Project inside a workspace ws and Organization () with an org_id, assign a name and description, and save the changes:
In self-hosted open-source installation, you do not need to pass the Team ID. To create a Project:
Click on the “plus” sign on the home page, type your Project name and description.
After creating a Project, you can click to open a Dashboard. Since there's no data yet, it will be empty.
Project ID. Once you run create_project, you will see the Project ID. You can later use it to reference the Project. You can also copy the Project ID directly from the UI: it appears above the monitoring Dashboard.
To connect to an existing Project from Python, use the get_project method.
After making changes to the Project (such as editing description or adding monitoring Panels), always use the save() command:
You can see all available Projects on the monitoring homepage, or request a list programmatically. To get a list of all Projects in a workspace ws, use:
To find a specific Project by its name, use the search_project method:
You are deleting the data in a Project. If you delete a Project, you will delete all the snapshots stored inside it.
To delete the Project and all the data inside it:
Each Project has the following parameters.
name: str
Project name.
id: UUID4 = Field(default_factory=uuid.uuid4)
Unique identifier of the Project. Assigned automatically.
description: Optional[str] = None
Optional description. Visible when you browse Projects.
dashboard: DashboardConfig
date_from: Optional[datetime.datetime] = None
Start DateTime of the monitoring Dashboard. By default, Evidently shows data for all available periods based on the snapshot timestamps.
You can set a different DateTime. E.g., to refer to the last 30 days:
from datetime import datetime, timedelta
datetime.now() + timedelta(-30)
date_to: Optional[datetime.datetime] = None
End DateTime of the monitoring Dashboard. Works the same as above.
Once you create or connect to a Project, you can:
Dashboard configuration that describes the composition of the monitoring Panels.
Note: See for details. You don't need to explicitly pass DashboardConfig if you use the .dashboard.add_panel method to add Panels.
using the add_report or add_test_suite methods.
Configure the monitoring Dashboard in the or via the .
