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databricks-cli/acceptance/bundle/templates/default-python/output/my_default_python
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Lennart Kats (databricks) bc30d44097
Provide instructions for testing in the default-python template (#2355) 
## Changes
Adds instructions for testing to the default-python template.

## Tests
- Unit & acceptance tests.
 		2025-02-17 12:38:03 +00:00
..
.vscode Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
fixtures Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
resources acc: Use [VARNAME] instead of $VARNAME (#2282) 2025-02-03 14:10:19 +00:00
scratch Switch to using `[` from `<` in text replacements (#2224) 2025-01-28 10:54:23 +00:00
src Switch to using `[` from `<` in text replacements (#2224) 2025-01-28 10:54:23 +00:00
tests Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
README.md Provide instructions for testing in the default-python template (#2355) 2025-02-17 12:38:03 +00:00
databricks.yml acc: Use [VARNAME] instead of $VARNAME (#2282) 2025-02-03 14:10:19 +00:00
out.gitignore Do not gitignore .databricks and terraform (#2318) 2025-02-10 11:42:39 +01:00
pytest.ini Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
requirements-dev.txt Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
setup.py acc: Use [VARNAME] instead of $VARNAME (#2282) 2025-02-03 14:10:19 +00:00

README.md

my_default_python

The 'my_default_python' project was generated by using the default-python template.

Getting started

  1. Install the Databricks CLI from https://docs.databricks.com/dev-tools/cli/databricks-cli.html

  2. Authenticate to your Databricks workspace, if you have not done so already:

    $ databricks configure

  3. To deploy a development copy of this project, type:

    $ databricks bundle deploy --target dev

    (Note that "dev" is the default target, so the --target parameter is optional here.)

    This deploys everything that's defined for this project. For example, the default template would deploy a job called [dev yourname] my_default_python_job to your workspace. You can find that job by opening your workpace and clicking on Workflows.

  4. Similarly, to deploy a production copy, type:

    $ databricks bundle deploy --target prod

    Note that the default job from the template has a schedule that runs every day (defined in resources/my_default_python.job.yml). The schedule is paused when deploying in development mode (see https://docs.databricks.com/dev-tools/bundles/deployment-modes.html).

  5. To run a job or pipeline, use the "run" command:

    $ databricks bundle run

  6. Optionally, install the Databricks extension for Visual Studio code for local development from https://docs.databricks.com/dev-tools/vscode-ext.html. It can configure your virtual environment and setup Databricks Connect for running unit tests locally. When not using these tools, consult your development environment's documentation and/or the documentation for Databricks Connect for manually setting up your environment (https://docs.databricks.com/en/dev-tools/databricks-connect/python/index.html).

  7. For documentation on the Databricks asset bundles format used for this project, and for CI/CD configuration, see https://docs.databricks.com/dev-tools/bundles/index.html.