# dbterd
Generate the ERD-as-a-code ([DBML](https://dbdiagram.io/d), [Mermaid](https://mermaid-js.github.io/mermaid-live-editor/), [PlantUML](https://plantuml.com/ie-diagram), [GraphViz](https://graphviz.org/), [D2](https://d2lang.com/)) from dbt artifact files (`dbt Core`) or from dbt metadata (`dbt Cloud`)
[](https://pypi.org/project/dbterd/)
[](https://opensource.org/licenses/MIT)
[](https://www.python.org)
[](https://codecov.io/gh/datnguye/dbterd)
```bash
pip install dbterd --upgrade
```
Verify installation:
```bash
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](https://schemas.getdbt.com/):</br>
> 👉 `pip install dbt-artifacts-parser --upgrade`
## Quick examine with existing samples
- Play with CLIs:
<details>
<summary>Click me</summary>
```bash
# 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 commiting to repo
dbterd run -ad samples/local -rt model -rt source
```
</details>
- Play with Python API (whole ERD):
```python
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):
```python
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:
```mermaid
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
```
</details>
🏃Check out the [Quick Demo](https://dbterd.datnguyen.de/latest/nav/guide/targets/generate-dbml.html) 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](https://dbterd.datnguyen.de/latest/nav/development/contributing-guide.html) 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 💌
[](https://github.com/datnguye/dbterd)
[](https://www.buymeacoffee.com/datnguye)
Finally, super thanks to our *Contributors*:
<a href="https://github.com/datnguye/dbterd/graphs/contributors">
<img src="https://contrib.rocks/image?repo=datnguye/dbterd" />
</a>
</br>
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"description": "# dbterd\n\nGenerate the ERD-as-a-code ([DBML](https://dbdiagram.io/d), [Mermaid](https://mermaid-js.github.io/mermaid-live-editor/), [PlantUML](https://plantuml.com/ie-diagram), [GraphViz](https://graphviz.org/), [D2](https://d2lang.com/)) from dbt artifact files (`dbt Core`) or from dbt metadata (`dbt Cloud`)\n\n[](https://pypi.org/project/dbterd/)\n\n[](https://opensource.org/licenses/MIT)\n[](https://www.python.org)\n[](https://codecov.io/gh/datnguye/dbterd)\n\n```bash\npip install dbterd --upgrade\n```\n\nVerify installation:\n\n```bash\ndbterd --version\n```\n\n> [!TIP]\n> 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](https://schemas.getdbt.com/):</br>\n> \ud83d\udc49 `pip install dbt-artifacts-parser --upgrade`\n\n## Quick examine with existing samples\n\n- Play with CLIs:\n\n <details>\n <summary>Click me</summary>\n\n ```bash\n # select all models in dbt_resto\n dbterd run -ad samples/dbtresto\n # select all models in dbt_resto, Select multiple dbt resources\n dbterd run -ad samples/dbtresto -rt model -rt source\n # select only models in dbt_resto excluding staging\n dbterd run -ad samples/dbtresto -s model.dbt_resto -ns model.dbt_resto.staging\n # select only models in schema name mart excluding staging\n dbterd run -ad samples/dbtresto -s schema:mart -ns model.dbt_resto.staging\n # select only models in schema full name dbt.mart excluding staging\n dbterd run -ad samples/dbtresto -s schema:dbt.mart -ns model.dbt_resto.staging\n\n # other samples\n dbterd run -ad samples/fivetranlog\n dbterd run -ad samples/fivetranlog -rt model -rt source\n\n dbterd run -ad samples/facebookad\n dbterd run -ad samples/facebookad -rt model -rt source\n\n dbterd run -ad samples/shopify -s wildcard:*shopify.shopify__*\n dbterd run -ad samples/shopify -rt model -rt source\n\n dbterd run -ad samples/dbt-constraints -a \"test_relationship:(name:foreign_key|c_from:fk_column_name|c_to:pk_column_name)\"\n\n # your own sample without commiting to repo\n dbterd run -ad samples/local -rt model -rt source\n ```\n\n </details>\n\n- Play with Python API (whole ERD):\n\n ```python\n from dbterd.api import DbtErd\n\n erd = DbtErd().get_erd()\n print(\"erd (dbml):\", erd)\n\n erd = DbtErd(target=\"mermaid\").get_erd()\n print(\"erd (mermaid):\", erd)\n ```\n\n- Play with Python API (1 model's ERD):\n\n ```python\n from dbterd.api import DbtErd\n\n dim_prize_erd = DbtErd(target=\"mermaid\").get_model_erd(\n node_unique_id=\"model.dbt_resto.dim_prize\"\n )\n print(\"erd of dim_prize (mermaid):\", dim_prize_erd)\n ```\n\n Here is the output:\n\n ```mermaid\n erDiagram\n \"MODEL.DBT_RESTO.DIM_PRIZE\" {\n varchar prize_key\n nvarchar prize_name\n int prize_order\n }\n \"MODEL.DBT_RESTO.FACT_RESULT\" {\n varchar fact_result_key\n varchar box_key\n varchar prize_key\n date date_key\n int no_of_won\n float prize_value\n float prize_paid\n int is_prize_taken\n }\n \"MODEL.DBT_RESTO.FACT_RESULT\" }|--|| \"MODEL.DBT_RESTO.DIM_PRIZE\": prize_key\n ```\n\n</details>\n\n\ud83c\udfc3Check out the [Quick Demo](https://dbterd.datnguyen.de/latest/nav/guide/targets/generate-dbml.html) with DBML!\n\n## Contributing \u2728\n\nIf you've ever wanted to contribute to this tool, and a great cause, now is your chance!\n\nSee the contributing docs [CONTRIBUTING](https://dbterd.datnguyen.de/latest/nav/development/contributing-guide.html) for more information.\n\nIf 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 \ud83d\udc8c\n\n[](https://github.com/datnguye/dbterd)\n[](https://www.buymeacoffee.com/datnguye)\n\nFinally, super thanks to our *Contributors*:\n\n<a href=\"https://github.com/datnguye/dbterd/graphs/contributors\">\n <img src=\"https://contrib.rocks/image?repo=datnguye/dbterd\" />\n</a>\n\n</br>\n",
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