Why does my airflow dag run twice when I dockerize it?

I have dockerized by airflow dag that basically copies one csv file to gcp, then loads it to BigQuery and do simple transformation. When I run docker-compose run, my dag is executed twice. I am not able to understand due to which part of code is this happening. When I trigger dag manually from UI it runs once.

My Dag:

from scripts import extract_and_gcpload, load_to_BQ

default_args = {
    'owner': 'shweta',
    'start_date': datetime(2025, 4, 24),
    'retries': 0
}

with DAG(
    'spacex_etl_dag',
    default_args=default_args,
    schedule_interval=None,
    schedule=None,
    catchup=False              #prevents Airflow from running missed periods
) as dag:

    extract_and_upload = PythonOperator(
        task_id="extract_and_upload_to_gcs",
        python_callable=extract_and_gcpload.load_to_gcp_pipeline,
    )

    load_to_bq = PythonOperator(
        task_id="load_to_BQ",
        python_callable=load_to_BQ.load_csv_to_bigquery
    )

    run_dbt = BashOperator(
        task_id="run_dbt",
        bash_command="cd '/opt/airflow/dbt/my_dbt' && dbt run --profiles-dir /opt/airflow/dbt"
    )

    extract_and_upload >> load_to_bq >> run_dbt

My entrypoint file startscript.sh:

#!/bin/bash
set -euo pipefail

log() {
  echo "[$(date +'%Y-%m-%d %H:%M:%S')] $1"
}

# Optional: Run DB init & parse DAGs
log "Initializing Airflow DB..."
airflow db upgrade

log "Parsing DAGs..."
airflow scheduler --num-runs 1

DAG_ID="spacex_etl_dag"
log "Unpausing DAG: $DAG_ID"
airflow dags unpause "$DAG_ID" || true

log "Triggering DAG: $DAG_ID"
airflow dags trigger "$DAG_ID" || true

log "Creating admin user (if not exists)..."
airflow users create \
    --username admin \
    --firstname Admin \
    --lastname User \
    --role Admin \
    --email admin@example.com \
    --password admin || true

if [[ "$1" == "webserver" || "$1" == "scheduler" ]]; then
  log "Starting Airflow: $1"
  exec airflow "$@"
else
  log "Executing: $@"
  exec "$@"
fi

My docker-compose.yaml file:

services:

  airflow-webserver:
    build:
      context: .
      dockerfile: Dockerfile
    container_name: airflow-webserver
    env_file: .env
    restart: always
    environment:
      AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'false'
      AIRFLOW__LOGGING__REMOTE_LOGGING: 'False'
      AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
      AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
      GOOGLE_APPLICATION_CREDENTIALS: /opt/airflow/secrets/llms-395417-c18ea70a3f54.json
    volumes:
      - ./dags:/opt/airflow/dags
      - ./scripts:/opt/airflow/scripts
      - ./dbt:/opt/airflow/dbt
      - ./secrets:/opt/airflow/secrets
    ports:
      - 8080:8080
    command: webserver

  airflow-scheduler:
    build:
      context: .
      dockerfile: Dockerfile
    container_name: airflow-scheduler
    env_file: .env
    restart: always
    environment:
      AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'false'
      AIRFLOW__LOGGING__REMOTE_LOGGING: 'False'
      AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
      AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
      GOOGLE_APPLICATION_CREDENTIALS: /opt/airflow/secrets/llms-395417-c18ea70a3f54.json
    volumes:
      - ./dags:/opt/airflow/dags
      - ./dbt:/opt/airflow/dbt
      - ./secrets:/opt/airflow/secrets
      - ./scripts:/opt/airflow/scripts
    depends_on:
      - postgres
    command: scheduler

  postgres:
    image: postgres:13
    environment:
      POSTGRES_USER: airflow
      POSTGRES_PASSWORD: airflow
      POSTGRES_DB: airflow
    volumes:
      - postgres-db-volume:/var/lib/postgresql/data

volumes:
  postgres-db-volume:

You have two containers, each packaging the same Dockerfile and entrypoint script. That script is identical except for the last command to run airflow scheduler or airflow webserver. All of the preceding commands are being run in both containers, including:

# Optional: Run DB init & parse DAGs
log "Initializing Airflow DB..."
airflow db upgrade

log "Parsing DAGs..."
airflow scheduler --num-runs 1

DAG_ID="spacex_etl_dag"
log "Unpausing DAG: $DAG_ID"
airflow dags unpause "$DAG_ID" || true

log "Triggering DAG: $DAG_ID"
airflow dags trigger "$DAG_ID" || true

log "Creating admin user (if not exists)..."
airflow users create \
    --username admin \
    --firstname Admin \
    --lastname User \
    --role Admin \
    --email admin@example.com \
    --password admin || true

You should avoid repeating unnecessary commands in both images if possible. That can be done with multiple entrypoints, or a check in the entrypoint to only run the necessary steps in the relevant container. E.g. to only run some of the commands in the scheduler container (I'm unfamiliar with airflow to know if this is the correct design), you could configure the script with:

log() {
  echo "[$(date +'%Y-%m-%d %H:%M:%S')] $1"
}

if "$1" == "scheduler" ]]; then
  # Optional: Run DB init & parse DAGs
  log "Initializing Airflow DB..."
  airflow db upgrade

  log "Parsing DAGs..."
  airflow scheduler --num-runs 1

  DAG_ID="spacex_etl_dag"
  log "Unpausing DAG: $DAG_ID"
  airflow dags unpause "$DAG_ID" || true

  log "Triggering DAG: $DAG_ID"
  airflow dags trigger "$DAG_ID" || true
fi

log "Creating admin user (if not exists)..."
airflow users create \
    --username admin \
    --firstname Admin \
    --lastname User \
    --role Admin \
    --email admin@example.com \
    --password admin || true

if [[ "$1" == "webserver" || "$1" == "scheduler" ]]; then
  log "Starting Airflow: $1"
  exec airflow "$@"
else
  log "Executing: $@"
  exec "$@"
fi