8/6/2023 0 Comments Best airflow tutorial![]() ![]() Then start the web server with this command: airflow webserver Start the scheduler with this command: airflow scheduler With a dag_id named 'etl_twitter_pipeline', this dag is scheduled to run every two minutes, as defined by the schedule interval. Start by importing the different airflow operators like this: from airflow import DAGįrom import EmptyOperatorĭescription="A simple twitter ETL pipeline using Python,PostgreSQL and Apache Airflow", Install the provider package for the Postgres database like this: pip install apache-airflow-providers-postgres How to Set Up the DAG ScriptĬreate a file named etl_pipeline.py inside the dags folder. If this fails, try installing the binary version like this: pip install psycopg2-binary Install the libraries pip install psycopg2 You should have PostgreSQL installed and running on your machine. To store your data, you'll use PostgreSQL as a database. # perform data cleaning and transformationĬontents of transform.py file The DatabaseĪirflow comes with a SQLite3 database. Postgres_sql_upload.bulk_load('twitter_etl_table', data) Postgres_sql_upload = PostgresHook(postgres_conn_id="postgres_connection") Tweets_df = pd.DataFrame(tweets_list, columns=)įrom _hook import PostgresHookĭata = data.to_csv(index=None, header=None) Tweets_list.append([tweet.date,, tweet.rawContent, Inside the Airflow dags folder, create two files: extract.py and transform.py.Įxtract.py: import as sntwitterįor i,tweet in enumerate(sntwitter.TwitterSearchScraper('Chatham House since:').get_items()): Make sure your Airflow virtual environment is currently active. You will also need Pandas, a Python library for data exploration and transformation. Numerous libraries make it easy to connect to the Twitter API. To get data from Twitter, you need to connect to its API. Tons of data is generated daily through this platform. Twitter is a social media platform where users gather to share information and discuss trending world events/topics.
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