Client Initialization (Start Here)
Learn how to install the Pachyderm SDK, import a client, and initialize it with your configuration settings.
December 4, 2023
The Pachyderm SDK enables you to interact with HPE ML Data Management’s API, client, and configuration directly in a powerful way.
1. Installation #
Before using the Pachyderm SDK, make sure you have it installed. You can install the SDK using pip:
pip install pachyderm_sdk
2. Import the Client #
To use the Client class, you need to import it from the Pachyderm SDK:
from pachyderm_sdk import Client
3. Creating a Client Instance #
To interact with a Pachyderm cluster, you need to create an instance of the
Client class. The
Client class provides multiple ways to create a client instance based on your requirements.
Default Settings #
client = Client()
This creates a client that connects to the local Pachyderm cluster running on
localhost:30650 with default authentication settings.
Custom Settings #
You can customize the client settings by providing the relevant parameters to the Client constructor. Here’s an example:
client = Client( host='localhost', port=8080, auth_token='your-auth-token', root_certs=None, transaction_id=None, tls=False )
In the above example, the client is configured to connect to the local Pachyderm cluster running on localhost:8080 without TLS encryption.
auth_tokenparameter allows you to specify an authentication token for accessing the cluster.
root_certsparameter can be used to provide custom root certificates for secure connections.
transaction_idparameter allows you to specify a transaction ID to run operations on.
By default, the client will attempt to read the authentication token from the AUTH_TOKEN_ENV environment variable. You can also set the authentication token after creating the client using the auth_token property:
4. Connect #
The Client class provides different methods to connect to a Pachyderm cluster based on your deployment configuration.
From Within a Cluster #
If you’re running the code within a Pachyderm cluster, you can use the
new_in_cluster method to create a client instance that operates within the cluster. This method reads the cluster configuration from the environment and creates a client based on the available configuration.
client = Client.new_in_cluster(auth_token='your-auth-token', transaction_id='your-transaction-id')
Via PachD Address #
If you have the Pachd address (host:port) of the HPE ML Data Management cluster, you can create a client instance using the
client = Client.from_pachd_address('pachd-address', auth_token='your-auth-token', root_certs='your-root-certs', transaction_id='your-transaction-id')
Referencing a Config File #
If you have a HPE ML Data Management configuration file, you can create a client instance using the from_config method:
client = Client.from_config('path-to-config-file')
Test Connection #
If you’d like to quickly test out working with the Pachyderm SDK on your local machine (e.g., using a locally deployed Docker Desktop instance), try out the following:
from pachyderm_sdk import Client client = Client(host="localhost", port="80") version = client.get_version() print(version)
Version(major=2, minor=6, micro=4, git_commit='358bd1229130eb262c22caf82ed87b3cc91ec81c', git_tree_modified='false', build_date='2023-06-22T14:49:32Z', go_version='go1.20.5', platform='arm64')
If you see this, you are ready to start working with the SDK.