GitHub user assadali007 added a comment to the discussion: manual trigger dag
`from datetime import datetime
from pathlib import Path
import pandas as pd
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.operators.python import PythonOperator
dag = DAG(
dag_id="01_unscheduled",
start_date=datetime(2026, 1, 5),
schedule_interval='@daily'
)
fetch_events = BashOperator(
task_id="fetch_events",
bash_command= """
mkdir -p /Users/asadali/data/events && \
curl -o /Users/asadali/data/events/events.json \
'http://localhost:5000/events'
""",
dag=dag,
)
def _calculate_stats(input_path, output_path):
"""Calculates event statistics."""
print(input_path)
print(output_path)
Path(output_path).parent.mkdir(exist_ok=True)
events = pd.read_json(input_path)
stats = events.groupby(["date", "user"]).size().reset_index()
stats.to_csv(output_path, index=False)
calculate_stats = PythonOperator(
task_id="calculate_stats",
python_callable=_calculate_stats,
op_kwargs={"input_path": "/Users/asadali/data/events/events.json",
"output_path": "/Users/asadali/data/events/stats.csv"},
dag=dag,
)
fetch_events >> calculate_stats` this is code i got this example on book
GitHub link:
https://github.com/apache/airflow/discussions/60255#discussioncomment-15466475
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