clear_cache[source]

clear_cache(project_dir=None)

Removes all existing nbdbt cache entries

config_dbt[source]

config_dbt(line)

::

%config_dbt [-d PROFILE] [-p PROJECT] [-n NOTEBOOK] [-l LIMIT]

optional arguments: -d PROFILE, --profile PROFILE If provided, override the dbt profiles directory (default: '~/.dbt') -p PROJECT, --project PROJECT Set the dbt project directory -n NOTEBOOK, --notebook NOTEBOOK Set the notebook path -l LIMIT, --limit LIMIT Set the default sql row limit

class DbtMagicObject[source]

DbtMagicObject(raw_sql:str, file:str, limit:int, project_dir:Union[str, Path, NoneType]=None, notebook_name:Optional[str]=None, profile_dir:Union[str, Path, NoneType]=None)

	Type	Default	Details
raw_sql	str		sql string
file	str		path to sql file (relative to dbt project dir)
limit	int		limit row default
project_dir	typing.Union[str, pathlib.Path, NoneType]	None	dbt project dir
notebook_name	typing.Union[str, NoneType]	None	name of notebook
profile_dir	typing.Union[str, pathlib.Path, NoneType]	None	dbt profiles dir

DbtMagicObject.ref[source]

DbtMagicObject.ref(limit=-1)

None[source]

write_dbt[source]

write_dbt(line, cell)

::

%write_dbt [-a ASSIGN] [-p PROJECT] [-n NOTEBOOK] [-l LIMIT] file

positional arguments: file file path to write to

optional arguments: -a ASSIGN, --assign ASSIGN If provided, save the output to this variable instead of displaying it. -p PROJECT, --project PROJECT dbt project directory -n NOTEBOOK, --notebook NOTEBOOK notebook source file -l LIMIT, --limit LIMIT sql limit default

%dbtconfig -p ../my_dbt_project -n notebooks/00_dbt_cellmagic.ipynb

%%dbt analyses/sample1.sql

select *
from {{ ref('my_first_dbt_model') }}
where id is not null

	id
0	1

if "sample2" in globals():
    del sample2

%%dbt -a sample2 analyses/sample2.sql 

select *
from {{ ref('my_second_dbt_model') }}
where id is not null

results = sample2.ref()

results

	id
0	1

%%dbt -a my_third_model -n notebooks/index.ipynb models/my_third_model.sql
select *
from {{ ref('my_second_dbt_model') }}

my_third_model

<__main__.DbtMagicObject at 0x7efe6b4cb190>

The ref method on DbtMagicObject allows us to run the query and save the results into a dataframe.

results = my_third_model.ref()
results  # dataframe

	id
0	1

faldbt = FalDbt(nbdbt_config["project_dir"], nbdbt_config["profiles_dir"])
model0 = faldbt.list_models()[0]
source0 = faldbt.list_sources()[0]

model0.schema

	table_catalog	table_schema	table_name	column_name	ordinal_position	is_nullable	data_type	is_generated	generation_expression	is_stored	is_hidden	is_updatable	is_system_defined	is_partitioning_column	clustering_ordinal_position	collation_name
0	sample-dbt-learn-project	jaffle_shop	my_third_model	id	1	YES	INT64	NEVER	None	None	NO	None	NO	NO	NaN	NULL

source0.schema

	table_catalog	table_schema	table_name	column_name	ordinal_position	is_nullable	data_type	is_generated	generation_expression	is_stored	is_hidden	is_updatable	is_system_defined	is_partitioning_column	clustering_ordinal_position	collation_name
0	bigquery-public-data	ml_datasets	iris	sepal_length	1	YES	FLOAT64	NEVER	None	None	NO	None	NO	NO	NaN	NULL
1	bigquery-public-data	ml_datasets	iris	sepal_width	2	YES	FLOAT64	NEVER	None	None	NO	None	NO	NO	NaN	NULL
2	bigquery-public-data	ml_datasets	iris	petal_length	3	YES	FLOAT64	NEVER	None	None	NO	None	NO	NO	NaN	NULL
3	bigquery-public-data	ml_datasets	iris	petal_width	4	YES	FLOAT64	NEVER	None	None	NO	None	NO	NO	NaN	NULL
4	bigquery-public-data	ml_datasets	iris	species	5	YES	STRING	NEVER	None	None	NO	None	NO	NO	NaN	NULL