https://github.com/dbt-labs/dbt-init

A dbt-init script for consulting projects
https://github.com/dbt-labs/dbt-init

Last synced: about 1 month ago
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A dbt-init script for consulting projects

• Host: GitHub
• URL: https://github.com/dbt-labs/dbt-init
• Owner: dbt-labs
• License: apache-2.0
• Created: 2019-02-21T01:47:08.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-09-28T11:10:03.000Z (9 months ago)
• Last Synced: 2024-04-13T18:38:25.568Z (2 months ago)
• Language: Python
• Size: 73.2 KB
• Stars: 55
• Watchers: 10
• Forks: 116
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-dbt - dbt-init - Create a project and populate as much of the dbt project as possible. (Packages)
• awesome-dbt - dbt-init - Create a project and populate as much of the dbt project as possible. (Packages)
• awesome-dbt - dbt-init - Create a project and populate as much of the dbt project as possible. (Packages)

README

        
# dbt-init

A tool to create dbt projects for consulting.

dbt-init will create a project as a subdirectory within the target directory you

provide it, and populate as much of the dbt project as possible

## Installation & usage

1. Install using `pip install dbt-init`

2. To create a new client project run a command like following:

```bash

$ dbt-init --client jaffle-shop --warehouse snowflake --target-dir ~/clients/

```

You can also check the available arguments with `dbt-init --help`

## Once you've created your project

1. Update `sample.profile.yml` to contain the correct profile details for your

client, _excluding_ the actual credentials – e.g. username and password:

 * You can often pre-fill the host and database name.

 * You may want to use an alternate connection method (e.g. OAuth) and update

 the sample file to reflect this.

2. Ensure that the users/groups/roles within a warehouse match the grant

statements in the post-run hooks (defined in `dbt_project.yml`).

## Building out the starter project

If you're interested in helping build out the starter project, here is a list of

variables you can use – a lot of them have defaults based on the client name.

```

{{ project.name }}: The name of the project, as defined in `dbt_project.yml`, e.g. jaffle_shop.

{{ project.warehouse }}: The warehouse that a client is using.

{{ project.client_name }}: The name of the client, e.g. jaffle-shop.

{{ project.dir_name }}: The name of the directory this project is in, e.g. jaffle-shop-dbt.

{{ project.profile_name }}: The name of the profile used by this project, e.g. jaffle_shop.

```

## Testing out the changes

If you're just making simple changes to the starter project, testing out the

changes is optional. If you want to improve the script, or just get familiar

with virtual environments, this is a good idea!

1. Clone this repo and `cd` into it

2. Create a new virtual environment `dbt-init-dev` and activate it. Make sure

your virtual environment uses python 3.

3. Run `pip install -r requirements-dev.txt`

4. You should now have a development version of `dbt-init` installed. Test your

changes by creating a sample project and inspecting the results (I know, we

should build real tests), e.g.:

```

$ dbt-init --client test --target-dir ~/clrcrl/ --warehouse bigquery

New dbt project for test created at /Users/claire/clrcrl/test-dbt! 🎉

$ open /Users/claire/clrcrl/test-dbt

```

## To-do:

- [ ] Configure a new profile as part of init process