Airflow: How to load data from a REST API to BigQuery?

Question

I am new to Airflow here, and I am trying to write a Python method to insert data into BigQuery from a REST API, but I am having no luck.

So far, I have tried to read the documentation, but I have not found an example of what I am trying to accomplish; though, I have written the following code, but I am not sure if it is correct:

def insert_from_api_to_bq():
    
    request1 = Request(
        '[URL GOES GERE]', headers=headers)

    sale_list = urlopen(request1).read()
    dec_sale_list = json.loads(sale_list)
    for sale in dec_sale_list['SaleList']:
        print("sale ID: " + sale['SaleID'] + " Customer:" + sale['Customer'] + " Order Date: " + sale['OrderDate'])

with DAG("sales_data_pipeline", start_date=datetime(2021, 1 ,1),
    schedule_interval="@daily", default_args=default_args, catchup=False) as dag:

    downloading_sales = PythonOperator(
        task_id="downloading_sales",
        python_callable=download_sales

Answer 1

You are in the good direction.

In your Python method that retrieves data from the api, you can then transform and load the result to a BigQuery table with Python client:

from google.cloud import bigquery

def insert_from_api_to_bq():
    
    request1 = Request(
        '[URL GOES GERE]', headers=headers)

    sale_list = urlopen(request1).read()
    dec_sale_list = json.loads(sale_list)
    
    # you can transform and adapt dec_sale_list before writing to BQ
    client = bigquery.Client()
    client.insert_rows_json(f'{dataset}.{table}', dec_sale_list)

with DAG("sales_data_pipeline", start_date=datetime(2021, 1 ,1),
    schedule_interval="@daily", default_args=default_args, catchup=False) as dag:

    downloading_sales = PythonOperator(
        task_id="downloading_sales",
        python_callable=download_sales

The insert_rows_json method allows saving a Python list of Dict to BigQuery .