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(bigquery_plugin_example)=
# BigQuery plugin example

```{code-cell}

try:
    from typing import Annotated
except ImportError:
    from typing_extensions import Annotated

import pandas as pd
from flytekit import StructuredDataset, kwtypes, task, workflow
from flytekitplugins.bigquery import BigQueryConfig, BigQueryTask

# Note that in order for registration to work properly, you'll need to give your
# BigQuery task a name that's unique across your project/domain for your Flyte installation.
bigquery_task_no_io = BigQueryTask(
    name="sql.bigquery.no_io",
    inputs={},
    query_template="SELECT 1",
    task_config=BigQueryConfig(ProjectID="flyte"),
)


@workflow
def no_io_wf():
    return bigquery_task_no_io()


DogeCoinDataset = Annotated[StructuredDataset, kwtypes(hash=str, size=int, block_number=int)]

bigquery_task_templatized_query = BigQueryTask(
    name="sql.bigquery.w_io",
    # Define inputs as well as their types that can be used to customize the query.
    inputs=kwtypes(version=int),
    output_structured_dataset_type=DogeCoinDataset,
    task_config=BigQueryConfig(ProjectID="flyte"),
    query_template="SELECT * FROM `bigquery-public-data.crypto_dogecoin.transactions` WHERE version = @version LIMIT 10;",
)


@task
def convert_bq_table_to_pandas_dataframe(sd: DogeCoinDataset) -> pd.DataFrame:
    return sd.open(pd.DataFrame).all()


@workflow
def full_bigquery_wf(version: int) -> pd.DataFrame:
    sd = bigquery_task_templatized_query(version=version)
    return convert_bq_table_to_pandas_dataframe(sd=sd)


# Check query result on bigquery console: `https://console.cloud.google.com/bigquery`
```