class_docstr: Fetch daily results from the Google Ads API for 1-n clients.
  
  Converts and saves the data as a temporary CSV file Uploads the CSV to
  Google Cloud Storage.
  
  .. seealso::
      For more information on the Google Ads API, take a look at the API docs:
      https://developers.google.com/google-ads/api/docs/start
  
  .. seealso::
      For more information on how to use this operator, take a look at the guide:
      :ref:`howto/operator:GoogleAdsToGcsOperator`
  
  :param client_ids: Google Ads client IDs to query
  :param query: Google Ads Query Language API query
  :param attributes: List of Google Ads Row attributes to extract
  :param bucket: The GCS bucket to upload to
  :param obj: GCS path to save the object. Must be the full file path (ex. `path/to/file.txt`)
  :param gcp_conn_id: Airflow Google Cloud connection ID
  :param google_ads_conn_id: Airflow Google Ads connection ID
  :param page_size: The number of results per API page request. Max 10,000
  :param gzip: Option to compress local file or file data for upload
  :param impersonation_chain: Optional service account to impersonate using short-term
      credentials, or chained list of accounts required to get the access_token
      of the last account in the list, which will be impersonated in the request.
      If set as a string, the account must grant the originating account
      the Service Account Token Creator IAM role.
      If set as a sequence, the identities from the list must grant
      Service Account Token Creator IAM role to the directly preceding identity, with first
      account from the list granting this role to the originating account (templated).
  :param api_version: Optional Google Ads API version to use.
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code: def __init__(
      self,
      *,
      client_ids: list[str],
      query: str,
      attributes: list[str],
      bucket: str,
      obj: str,
      gcp_conn_id: str = "google_cloud_default",
      google_ads_conn_id: str = "google_ads_default",
      page_size: int = 10000,
      gzip: bool = False,
      impersonation_chain: str | Sequence[str] | None = None,
      api_version: str | None = None,
      **kwargs,
  ) -> None:
      super().__init__(**kwargs)
      self.client_ids = client_ids
      self.query = query
      self.attributes = attributes
      self.bucket = bucket
      self.obj = obj
      self.gcp_conn_id = gcp_conn_id
      self.google_ads_conn_id = google_ads_conn_id
      self.page_size = page_size
      self.gzip = gzip
      self.impersonation_chain = impersonation_chain
      self.api_version = api_version
  
file_path: airflow/airflow/providers/google/ads/transfers/ads_to_gcs.py
imports: from __future__ import annotations
  import csv
  from operator import attrgetter
  from tempfile import NamedTemporaryFile
  from typing import TYPE_CHECKING, Sequence
  from airflow.models import BaseOperator
  from airflow.providers.google.ads.hooks.ads import GoogleAdsHook
  from airflow.providers.google.cloud.hooks.gcs import GCSHook
label_desc: Use image node_id 1 to create a new GoogleAdsToGcsOperator object from inherited base classes: BaseOperator with example: obj = GoogleAdsToGcsOperator()