mik-laj commented on a change in pull request #16548:
URL: https://github.com/apache/airflow/pull/16548#discussion_r654918088
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File path: docs/apache-airflow/tutorial.rst
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@@ -426,17 +407,16 @@ Let's break this down into 3 steps: get data, insert
data, merge data:
for row in response.text.split("\n"):
file.write(row)
-Here we are passing a``GET`` request to get the data from the URL and save it
in ``employees.csv`` file on our Airflow instance.
+Here we are passing a`GET` request to get the data from the URL and save it in
`employees.csv` file on our Airflow instance.
.. code-block:: python
@task
def insert_data():
- engine = create_engine(
- "postgresql+psycopg2://postgres:password@localhost:5432/postgres"
- )
+ postgres_hook = PostgresHook(postgres_conn_id="LOCAL")
+ conn = postgres_hook.get_conn()
df = pd.read_csv("/usr/local/airflow/dags/files/employees.csv")
- df.to_sql("Employees_temp", con=engine, if_exists="replace",
chunksize=1000)
+ df.to_sql("Employees_temp", conn, if_exists="replace", chunksize=1000)
Review comment:
Are you sure if it works? Based on Pandas documentation, Dataframe
supports [`sqlalchemy.engine.(Engine or Connection) or
sqlite3.Connection`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_sql.html)
only. Here, we have `psycopg2.extensions.connection`?
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