Quickstart¶
Client configuration¶
Start by importing the Python Client and authentication provider:
from tamr_unify_client import Client
from tamr_unify_client.auth import UsernamePasswordAuth
Next, create an authentication provider and use that to create an authenticated client:
import os
username = os.environ['TAMR_USERNAME']
password = os.environ['TAMR_PASSWORD']
auth = UsernamePasswordAuth(username, password)
tamr = Client(auth)
Warning
For security, it’s best to read your credentials in from environment variables or secure files instead of hardcoding them directly into your code.
For more, see User Guide > Secure Credentials.
By default, the client tries to find the Tamr instance on localhost
. To point to a different host, set the host argument when instantiating the Client.
For example, to connect to 10.20.0.1
:
tamr = Client(auth, host='10.20.0.1')
Top-level collections¶
The Python Client exposes 2 top-level collections: Projects and Datasets.
You can access these collections through the client and loop over their members
with simple for
-loops.
E.g.:
for project in tamr.projects:
print(project.name)
for dataset in tamr.datasets:
print(dataset.name)
Fetch a specific resource¶
If you know the identifier for a specific resource, you can ask for it directly via the by_resource_id
methods exposed by collections.
E.g. To fetch the project with ID '1'
:
project = tamr.projects.by_resource_id('1')
Similarly, if you know the name of a specific resource, you can ask for it directly via the by_name
methods exposed by collections.
E.g. To fetch the project with name 'Number 1'
:
project = tamr.projects.by_name('Number 1')
Note
If working with projects across Tamr instances for migrations or promotions, use external IDs (via by_external_id
) instead of name (via by_name
).
Resource relationships¶
Related resources (like a project and its unified dataset) can be accessed through specific methods.
E.g. To access the Unified Dataset for a particular project:
ud = project.unified_dataset()
Kick-off Tamr Operations¶
Some methods on Model objects can kick-off long-running Tamr operations.
Here, kick-off a “Unified Dataset refresh” operation:
operation = project.unified_dataset().refresh()
assert op.succeeded()
By default, the API Clients expose a synchronous interface for Tamr operations.