dbt™️ generator

To use this feature, make sure to first install the dbt™️-codegen package in your dbt™️ project.

The dbt™️ generator integration allows you to generate based models from your sources and transform model at scale. This will help you save time generating base models from the Paradime Integrated Terminal.

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Generate base models

To generate base models, use the dbt-generator generate command. This is a wrapper around the codegen command that will generate the base models. This is especially useful when you have a lot of models, and you want to generate them all at once.

Usage: dbt-generator generate [OPTIONS]

  Generate base models based on a .yml source

Options:
  -s, --source-yml PATH   Source .yml file to be used
  -o, --output-path PATH  Path to write generated models
  -m, --model STRING      Model name
  -c, --custom_prefix.    Enter a Custom String Prefix for Model Filename
  --model-prefix BOOLEAN  optional prefix of source_name + "_" to the resulting modelname.sql to avoid model name collisions across sources 
  --source-index INTEGER  Index of the source to generate base models for
  --help                  Show this message and exit.

Example

$ dbt-generator generate -s ./models/source.yml -o ./models/staging/source_name/

This will read in the source.yml file and generate the base models in the staging/source_name folder. If you have multiple sources defined in your yml file, use the --source-index flag to specify which source you want to generate base models for.

Transform base models using a custom YAML file

Usage: dbt-generator transform [OPTIONS]

  Transform base models in a directory using a transforms.yml file

Options:
  -m, --model-path PATH       The path to models
  -t, --transforms-path PATH  Path to a .yml file containing transformations
  -o, --output-path PATH      Path to write transformed models to
  --drop-metadata BOOLEAN     (default=False) optionally drop source columns prefixed with "_" if that designates metadata columns not needed in target
  --case-sensitive BOOLEAN    (default=False) treat column names as case-sensitive - otherwise force all to lower
  --help                      Show this message and exit.

With this package, you can write a transforms.yml file that will be read in (the .yml file can be named anything). This file will contain the transforms that you want to apply to all the base models. You can just rename the fields in the base models or apply a custom SQL select to the transformed fields.

For the same source, you often have consistent naming conventions between tables. For example, the created_at and modified_at fields are often named the same for all tables. Changing all these fields to common values across different sources is a best practice. However, doing that for all the date columns in 10+ tables is a pain.

Transform base models using pre-built configs

Supported data warehouse:

• BigQuery: bq_transform

• Snowflake: sf_transform

Usage: dbt-generator bq-transform/sf-transform [OPTIONS]

  Transform base models in a directory for BigQuery source

Options:
  -m, --model-path PATH        The path to models
  -o, --output-path PATH       Path to write transformed models to
  --drop-metadata BOOLEAN      (default=False) optionally drop source columns prefixed with "_" if that designates metadata columns not needed in target
  --case-sensitive BOOLEAN     (default=False) treat column names as case-sensitive - otherwise force all to lower
  --split-columns BOOLEAN      Split column names. E.g. currencycode =>
                               currency_code
  --id-as-int BOOLEAN          Convert id to int
  --convert-timestamp BOOLEAN  Convert timestamp to datetime
  --help                       Show this message and exit.

Example

ID:
  name: ID
  sql: CAST(ID as INT64)
CREATED_TIME:
  name: CREATED_AT
UPDATED_TIME:
  name: MODIFIED_AT
DATE_START:
  name: START_AT
DATE_STOP:
  name: STOP_AT

This .yml file when applied to all models in the staging/source_name folder will cast all ID field to INT64 and rename all the date columns to a value in the name key. For example, CREATED_TIME will be renamed to CREATED_AT and DATE_START will be renamed to START_AT. If no sql is provided, the package will just rename the field. If a sql is provided, the package will execute the SQL and rename the field using the name key.

$ dbt-generator transform -m ./models/staging/source_name/ -t ./transforms.yml

This will transform all models in the staging/source_name folder using the transforms.yml file. You can also drop the metadata by setting the drop-metadata flag to true (dropping columns start with _). The --case-sensitive flag will determine if the transforms will use case-sensitive names or not.\