List out BigQuery tables metadata, sizes in GB, row_count, creation and last modified datetime and save into a csv using pandas dataframe

check_bqtables_metadata.py

from google.cloud import bigquery
import os
import pandas as pd

os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "YOURGCPSERVICEACCOUNTKEY.json"
GCP_PROJECT_ID = "YOURGCPPROJECT"

client = bigquery.Client(project=GCP_PROJECT_ID)
datasets = list(client.list_datasets())
project = client.project

if datasets:
    print(f"Datasets in project {project}:")
    for iter, dataset in enumerate(datasets):
        print(f'Dataset: {dataset.dataset_id}')
        query_job = client.query(
            f"""
            SELECT
            project_id, dataset_id, table_id,
            size_bytes/pow(1024,3) AS size_GB,
            TIMESTAMP_MILLIS(creation_time) AS creation_time,
            TIMESTAMP_MILLIS(last_modified_time) AS last_modified_time,
            row_count
            FROM `{GCP_PROJECT_ID}.{dataset.dataset_id}`.__TABLES__
            """
        )
        if iter == 0:
            df = query_job.to_dataframe()
        else:
            df = df.append(query_job.to_dataframe())
    df.to_csv("bqtables.csv",index=False)
else:
    print(f"{project} does not contain any datasets.")