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dbterd

Generate the ERD-as-a-code from dbt artifacts

1.20.0
PyPI
Maintainers
1

dbterd

Generate the ERD-as-a-code (DBML, Mermaid, PlantUML, GraphViz, D2, DrawDB) from dbt artifact files (dbt Core) or from dbt metadata (dbt Cloud)

Entity Relationships are configurably detected by (docs):

PyPI version python-cli License: MIT python codecov

pip install dbterd --upgrade

Verify installation:

dbterd --version

[!TIP] For dbt-core Users, it's highly recommended to upgrade dbt-artifacts-parser to the latest version in order to support the newer dbt-core version which would cause to have the new manifest / catalog json schema:
πŸ‘‰ pip install dbt-artifacts-parser --upgrade

Quick examine with existing samples

  • Play with CLIs:

    Click me
    # select all models in dbt_resto
    dbterd run -ad samples/dbtresto
    # select all models in dbt_resto, Select multiple dbt resources
    dbterd run -ad samples/dbtresto -rt model -rt source
    # select only models in dbt_resto excluding staging
    dbterd run -ad samples/dbtresto -s model.dbt_resto -ns model.dbt_resto.staging
    # select only models in schema name mart excluding staging
    dbterd run -ad samples/dbtresto -s schema:mart -ns model.dbt_resto.staging
    # select only models in schema full name dbt.mart excluding staging
    dbterd run -ad samples/dbtresto -s schema:dbt.mart -ns model.dbt_resto.staging
    
    # other samples
    dbterd run -ad samples/fivetranlog
    dbterd run -ad samples/fivetranlog -rt model -rt source
    
    dbterd run -ad samples/facebookad
    dbterd run -ad samples/facebookad -rt model -rt source
    
    dbterd run -ad samples/shopify -s wildcard:*shopify.shopify__*
    dbterd run -ad samples/shopify -rt model -rt source
    
    dbterd run -ad samples/dbt-constraints -a "test_relationship:(name:foreign_key|c_from:fk_column_name|c_to:pk_column_name)"
    
    # your own sample without committing to repo
    dbterd run -ad samples/local -rt model -rt source
    
  • Play with Python API (whole ERD):

    from dbterd.api import DbtErd
    
    erd = DbtErd().get_erd()
    print("erd (dbml):", erd)
    
    erd = DbtErd(target="mermaid").get_erd()
    print("erd (mermaid):", erd)
    
  • Play with Python API (1 model's ERD):

    from dbterd.api import DbtErd
    
    dim_prize_erd = DbtErd(target="mermaid").get_model_erd(
        node_unique_id="model.dbt_resto.dim_prize"
    )
    print("erd of dim_prize (mermaid):", dim_prize_erd)
    

    Here is the output:

    erDiagram
      "MODEL.DBT_RESTO.DIM_PRIZE" {
        varchar prize_key
        nvarchar prize_name
        int prize_order
      }
      "MODEL.DBT_RESTO.FACT_RESULT" {
        varchar fact_result_key
        varchar box_key
        varchar prize_key
        date date_key
        int no_of_won
        float prize_value
        float prize_paid
        int is_prize_taken
      }
      "MODEL.DBT_RESTO.FACT_RESULT" }|--|| "MODEL.DBT_RESTO.DIM_PRIZE": prize_key
    

πŸƒCheck out the Quick Demo with DBML!

Contributing ✨

If you've ever wanted to contribute to this tool, and a great cause, now is your chance!

See the contributing docs CONTRIBUTING for more information.

If you've found this tool to be very helpful, please consider giving the repository a star, sharing it on social media, or even writing a blog post about it πŸ’Œ

dbterd stars buy me a coffee

Finally, super thanks to our Contributors:


Keywords

dbt

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