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63 lines
1.6 KiB
Python
63 lines
1.6 KiB
Python
"""
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Helper functions used for ingestion of sample data into docker by calling airflow dags
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"""
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import time
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from pprint import pprint
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from typing import Tuple
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import requests
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from metadata.utils.logger import log_ansi_encoded_string
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from metadata.cli.docker import REQUESTS_TIMEOUT
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from requests.auth import HTTPBasicAuth
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HEADER_JSON = {"Content-Type": "application/json"}
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BASIC_AUTH = HTTPBasicAuth("admin", "admin")
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def get_last_run_info() -> Tuple[str, str]:
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"""
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Make sure we can pick up the latest run info
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"""
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dag_runs = None
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while not dag_runs:
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log_ansi_encoded_string(message="Waiting for DAG Run data...")
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time.sleep(5)
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runs = requests.get(
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"http://localhost:8080/api/v1/dags/sample_data/dagRuns", auth=BASIC_AUTH, timeout=REQUESTS_TIMEOUT
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).json()
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dag_runs = runs.get("dag_runs")
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return dag_runs[0].get("dag_run_id"), dag_runs[0].get("state")
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def print_last_run_logs() -> None:
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"""
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Show the logs
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"""
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logs = requests.get(
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"http://localhost:8080/api/v1/openmetadata/last_dag_logs?dag_id=sample_data",
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auth=BASIC_AUTH,
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timeout=REQUESTS_TIMEOUT
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).text
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pprint(logs)
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def main():
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state = None
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while state != "success":
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log_ansi_encoded_string(
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message="Waiting for sample data ingestion to be a success. We'll show some logs along the way.",
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)
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dag_run_id, state = get_last_run_info()
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log_ansi_encoded_string(message=f"DAG run: [{dag_run_id}, {state}]")
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print_last_run_logs()
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time.sleep(10)
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if __name__ == "__main__":
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main()
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