An unaffiliated python interface for dbt Cloud APIs
Documentation: https://dbtc.dpguthrie.com
Interactive Demo: https://dpguthrie-dbtc-streamlit-home-yy7c0b.streamlit.app/
Source Code: https://github.com/dpguthrie/dbtc
V2 Docs: https://docs.getdbt.com/dbt-cloud/api-v2
V3 Docs: https://docs.getdbt.com/dbt-cloud/api-v3
Overview
dbtc is an unaffiliated python interface to various dbt Cloud API endpoints.
This library acts as a convenient interface to two different APIs that dbt Cloud offers:
- Cloud API: This is a REST API that exposes endpoints that allow users to programatically create, read, update, and delete resources within their dbt Cloud Account.
- Metadata API: This is a GraphQL API that exposes metadata generated from a job run within dbt Cloud.
Requirements
Python 3.7+
- Requests - The elegant and simple HTTP library for Python, built for human beings.
- sgqlc - Simple GraphQL Client
- Typer - Library for building CLI applications
Installation
pip install dbtc
Basic Usage
Python
The interface to both APIs are located in the dbtCloudClient class.
The example below shows how you use the cloud property on an instance of the dbtCloudClient class to to access a method, trigger_job_from_failure, that allows you to restart a job from its last point of failure.
from dbtc import dbtCloudClient
# Assumes that DBT_CLOUD_SERVICE_TOKEN env var is set
client = dbtCloudClient()
account_id = 1
job_id = 1
payload = {'cause': 'Restarting from failure'}
run = client.cloud.trigger_job_from_failure(
account_id,
job_id,
payload,
should_poll=False,
)
# This returns a dictionary containing two keys
run['data']
run['status']
Similarly, use the metadata property to retrieve information about certain resources within your project - the example below shows how to retrieve metadata from models related to the most recent run for a given job_id.
from dbtc import dbtCloudClient
client = dbtCloudClient()
job_id = 1
models = client.metadata.get_models(job_id)
# Models nested inside a couple keys
models['data']['models']
# This is a list
models['data']['models'][0]
CLI
The CLI example below will map to the python cloud example above:
dbtc trigger-job-from-failure \
--account-id 1 \
--job-id 1 \
--payload '{"cause": "Restarting from failure"}' \
--no-should-poll
Similarly, for the metadata example above:
dbtc get-models --job-id 1
If not setting your service token as an environment variable, do the following:
dbtc --token this_is_my_token get_models --job-id 1
License
This project is licensed under the terms of the MIT license.
1 maintainer
Release files for dbtc 0.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dbtc-0.5.3.tar.gz | 41.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dbtc-0.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 85.8 kB
Release files / dbtc-0.5.3.tar.gz
| Download URL | dbtc-0.5.3.tar.gz |
|---|---|
| Size | 41.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ed3f30af386e02eb331c78907899f20e089f4f46a1a4dda564cceab6b9f92598
|
|
BLAKE2b-256 checksum How to use checksums |
8f474e67cec3054a82a4f758ae8655c437e40d2d756c9beaf72d3442688fc5c8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.5.1 CPython/3.11.4 Linux/5.15.0-1042-azure
|
Release files / dbtc-0.5.3-py3-none-any.whl
| Download URL | dbtc-0.5.3-py3-none-any.whl |
|---|---|
| Size | 43.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
dab616190196e5df1c1165ecd147e066c9258151d5582cbaa21bda3ca6177fde
|
|
BLAKE2b-256 checksum How to use checksums |
6b6760f7beaaaa6c14a8b778f83f9405f1b7b39f585f0e32187e0644357ffb9d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.5.1 CPython/3.11.4 Linux/5.15.0-1042-azure
|
