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Datazone Northstar Client Package

Project description

Datazone Northstar Client Library 👋

Installation

You can install package via pip

pip install datazone-northstar

Configuration & Login

Run the following command in your terminal

datazone auth configure

When prompted, enter the following information:

Host [app.datazone.co]: <DATAZONE_ADDRESS>
Username: <USERNAME>
Password: <PASSWORD>
Repeat for confirmation: <PASSWORD_CONFIRM>

Then you can run following command to login

datazone auth login

It will keep your tokens until refresh token expired. (Default 30min). Then you can re-run and login again.

Create first repository

datazone repository create hello-world
cd hello-world

It creates a new folder in your current directory. Thıs folder has two file initially. config.yaml and first_pipeline.py. After you modify your script you can deploy project via following command. (It takes about one minute).

datazone repository deploy

After the deployment is complete, you can check your repository status via following command.

datazone repository summary

If repository has deployed, you can run your first execution with following command.

datazone execution run <pipeline_id>

Commands

Also you can check all command with help sub command. datazone auth --help or datazone repository summary --help

# Auth
datazone auth configure
datazone auth login

# Repository
datazone repository list
datazone repository create
datazone repository deploy
datazone repository summary <file_name>
datazone repository clone <repository_id>
datazone repository pull

# Dataset
datazone dataset list
datazone dataset show <dataset_id> [<branch_name>] [<size>] [<transaction_id>]
datazone dataset transactions <dataset_id>

# View
datazone dataset view create
datazone dataset view list <dataset_id>
datazone dataset view delete <view_id>

# Source
datazone source create
datazone source list
datazone source update <source_id>
datazone source delete <source_id>

# Extract
datazone extract create
datazone extract list
datazone extract update <extract_id>
datazone extract delete <extract_id>
datazone extract execute <extract_id>

# Schedule
datazone schedule create
datazone schedule list
datazone schedule delete <source_id>

# Execution
datazone execution run [--extract-id] [--pipeline-id] [<execution_type>] [<transform_selection>]
datazone execution list [--extract-id] [--pipeline-id]
datazone execution log <execution_id>

# Pipeline
datazone pipeline create

# Common
datazone version
datazone info

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