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Abstract manifest generation from tasks
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kind: Under the Hood | ||
body: Abstract manifest generation | ||
time: 2023-01-10T11:57:25.193965-06:00 | ||
custom: | ||
Author: stu-k | ||
Issue: "6357" |
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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: 1ee31fc16e025fb98598189ba2cb5fcb | ||
config: e27d6c1c419f2f0af393858cdf674109 | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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dbt-core's API documentation | ||
============================ | ||
How to invoke dbt commands in python runtime | ||
-------------------------------------------- | ||
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Right now the best way to invoke a command from python runtime is to use the `dbtRunner` we exposed | ||
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.. code-block:: python | ||
from dbt.cli.main import dbtRunner | ||
cli_args = ['run', '--project-dir', 'jaffle_shop'] | ||
# initialize the dbt runner | ||
dbt = dbtRunner() | ||
# run the command | ||
res, success = dbt.invoke(args) | ||
You can also pass in pre constructed object into dbtRunner, and we will use those objects instead of loading up from the disk. | ||
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.. code-block:: python | ||
# preload profile and project | ||
profile = load_profile(project_dir, {}, 'testing-postgres') | ||
project = load_project(project_dir, False, profile, {}) | ||
# initialize the runner with pre-loaded profile and project | ||
dbt = dbtRunner(profile=profile, project=project) | ||
# run the command, this will use the pre-loaded profile and project instead of loading | ||
res, success = dbt.invoke(cli_args) | ||
For the full example code, you can refer to `core/dbt/cli/example.py` | ||
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API documentation | ||
----------------- | ||
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.. dbt_click:: dbt.cli.main:cli |
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