![]() Exercise 1 - Datasetsīoth the extract_historical_weather_data and transform_historical_weather_data DAG currently have their schedule set to None. You can find example solutions in the solutions_exercises folder.īefore you get started, go to include/global_variables/user_input_variables.py and enter your own info for HOT_DAY and BIRTHYEAR. The two DAGs tagged with part_2 are part of a partially built Airflow pipeline that handles historical weather data. View the Streamlit app now showing global climate data and the current weather for your city. If you are running locally go to localhost:8501. If you are using codespaces go to the Ports tab and open the URL of the forwarded port 8501. Watch the DAGs run according to their dependencies which have been set using Datasets. You can also run this DAG manually to trigger further pipeline runs by clicking on the play button on the right side of the DAG. Once the start DAG is unpaused it will run once, starting the pipeline. Unpause all DAGs that are tagged with part_1 by clicking on the toggle on their left hand side. Go to include/global_variables/user_input_variables.py and enter your own info for MY_NAME and MY_CITY. NOTE: The streamlit container can take a few minutes to start up.Īll DAGs tagged with part_1 are part of a pre-built, fully functional Airflow pipeline.
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