I installed Airflow by docker according to this video. (Windows+WSL+Ubuntu+Docker)

I have my_dag.py file (replaced APIKEY):

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime
import pandas as pd

def _read_api_data():
    x1 = requests.get('http://api.openweathermap.org/data/2.5/weather?q=London&appid=APIKEY')
    x2 = requests.get('http://api.openweathermap.org/data/2.5/weather?q=Moscow&appid=APIKEY')

    responses = [x1, x2]
    output_object = {"responses": []}
    for x in responses:
        json_object = x.json()
        output_object["responses"].append(json_object)
    json_str = json.dumps(output_object, indent=4)
    # Writing to weather_data.json
    with open("/tmp/weather_data.json", "w") as outfile:
        outfile.write(json_str)

def _download_data():
    with open('/tmp/weather_data.json') as f:
        d = json.load(f)
        responses = d["responses"]
        temps_K = [round(r["main"]["temp"] - 273.15, 2) for r in responses]
        names = [r["name"] for r in responses]
        df = pd.DataFrame({"names": names, "temps_K": temps_K})
        return df

def _process_data(ti):
    df = ti.xcom_pull(task_ids="download_data")
    df["temps_C"] = round(temps["temps_K"] - 273.15, 2)
    df.to_csv('/tmp/processed_weather_data.csv')
    return df

def _save_data(ti):
    df = ti.xcom_pull(task_ids="process_data")
    df.to_parquet('/tmp/weather.parquet')

with DAG("weather_data_pipeline_dag",
        schedule_interval="@once",
         start_date=datetime(2024,7,14)) as dag:
    taskPython0 = PythonOperator(
        task_id = "read_api_data",
        python_callable = _read_api_data
    )
    taskPython1 = PythonOperator(
        task_id = "download_data",
        python_callable = _download_data
    )
    taskPython2 = PythonOperator(
        task_id = "process_data",
        python_callable = _process_data
    )
    taskPython3 = PythonOperator(
        task_id = "save_data",
        python_callable = _save_data
    )
    taskPython0 >> taskPython1 >> taskPython2 >> taskPython3

But my dag failed. It read_api_data task failed. . How to solve that? where i can read LOG traceback of my DAG? it seems that airflow does not give details.