users.md

title	Users
linkTitle	Users
weight	2

User provisioning allows you to create, update, or delete user profiles in your GoodData environment.

You can provision users using full or incremental load methods. Each of these methods requires a specific input type.

{{% alert color="info" %}} This section covers the usage with manual data validation. You can also take advantage of the generic provisioning function. You can read more about it on the Provisioning page. {{% /alert %}}

Usage

Start by importing and initializing the UserProvisioner.

from gooddata_pipelines import UserProvisioner

host = "http://localhost:3000"
token = "some_user_token"

# Initialize the provisioner with GoodData credentials
provisioner = UserProvisioner.create(host=host, token=token)

Then validate your data using an input model corresponding to the provisioned resource and selected workflow type, i.e., UserFullLoad if you intend to run the provisioning in full load mode, or UserIncrementalLoad if you want to provision incrementally.

The models expect the following fields:

• user_id: User ID.
• firstname: First name of the user.
• lastname: Last name of the user.
• email: Email of the user.
• auth_id: Authorization ID associated with the user.
• user_groups: List of user group IDs that the user should belong to.
• is_active: Deletion flag. Present only in the IncrementalLoad models.

{{% alert color="info" title="Note on IDs"%}} Each ID can only contain allowed characters. See Workspace Object Identification to learn more about object identifiers. {{% /alert %}}

Use the appropriate model to validate your data:

# Add the model to the imports
from gooddata_pipelines import UserIncrementalLoad, UserProvisioner

host = "http://localhost:3000"
token = "some_user_token"

# Initialize the provisioner with GoodData credentials
provisioner = UserProvisioner.create(host=host, token=token)

# Load your data
raw_data = [
    {
        "user_id": "user_id_1",
        "firstname": "Example",
        "lastname": "User",
        "email": "example.user@gooddata.com",
        "auth_id": "",
        "user_groups": ["user_group_1", "user_group_2"],
        "is_active": True,
    },
]

# Validate the data
validated_data = [
    UserIncrementalLoad(
        user_id=item["user_id"],
        firstname=item["firstname"],
        lastname=item["lastname"],
        email=item["email"],
        auth_id=item["auth_id"],
        user_groups=item["user_groups"],
        is_active=item["is_active"],
    )
    for item in raw_data
]

Now with the provisioner initialized and your data validated, you can run the provisioner:

# Import, initialize, validate...
...

# Run the provisioning method
provisioner.incremental_load(validated_data)

Examples

Here are full examples of a full load and incremental load user provisioning workflows:

Full Load

import logging

from gooddata_pipelines import UserFullLoad, UserProvisioner

host = "http://localhost:3000"
token = "some_user_token"

# Initialize the provisioner
provisioner = UserProvisioner.create(host=host, token=token)

# Optional: set up logging and subscribe to logs emitted by the provisioner
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

provisioner.logger.subscribe(logger)

# Prepare your data
raw_data = [
    {
        "user_id": "user_id_1",
        "firstname": "Example",
        "lastname": "User",
        "email": "example.user@gooddata.com",
        "auth_id": "",
        "user_groups": ["user_group_1", "user_group_2"],
    },
]

# Validate the data
validated_data = [
    UserFullLoad(
        user_id=item["user_id"],
        firstname=item["firstname"],
        lastname=item["lastname"],
        email=item["email"],
        auth_id=item["auth_id"],
        user_groups=item["user_groups"],
    )
    for item in raw_data
]

# Run the provisioning with the validated data
provisioner.full_load(validated_data)

Incremental Load

import logging

from gooddata_pipelines import UserIncrementalLoad, UserProvisioner

host = "http://localhost:3000"
token = "some_user_token"

# Initialize the provisioner
provisioner = UserProvisioner.create(host=host, token=token)

# Optional: set up logging and subscribe to logs emitted by the provisioner
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

provisioner.logger.subscribe(logger)

# Prepare your data
raw_data = [
    {
        "user_id": "user_id_1",
        "firstname": "Example",
        "lastname": "User",
        "email": "example.user@gooddata.com",
        "auth_id": "",
        "user_groups": ["user_group_1", "user_group_2"],
        "is_active": True,
    },
]

# Validate the data
validated_data = [
    UserIncrementalLoad(
        user_id=item["user_id"],
        firstname=item["firstname"],
        lastname=item["lastname"],
        email=item["email"],
        auth_id=item["auth_id"],
        user_groups=item["user_groups"],
        is_active=item["is_active"],
    )
    for item in raw_data
]

# Run the provisioning with the validated data
provisioner.incremental_load(validated_data)