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import csv
from tempfile import NamedTemporaryFile
from typing import TYPE_CHECKING, Any, List, Optional, Sequence, Union
from airflow.models import BaseOperator
from airflow.providers.google.cloud.hooks.gcs import GCSHook
from airflow.providers.google.suite.hooks.sheets import GSheetsHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class GoogleSheetsToGCSOperator(BaseOperator):
"""
Writes Google Sheet data into Google Cloud Storage.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:GoogleSheetsToGCSOperator`
:param spreadsheet_id: The Google Sheet ID to interact with.
:param sheet_filter: Default to None, if provided, Should be an array of the sheet
titles to pull from.
:param destination_bucket: The destination Google cloud storage bucket where the
report should be written to. (templated)
:param destination_path: The Google cloud storage URI array for the object created by the operator.
For example: ``path/to/my/files``.
:param gcp_conn_id: The connection ID to use when fetching connection info.
:param delegate_to: The account to impersonate using domain-wide delegation of authority,
if any. For this to work, the service account making the request must have
domain-wide delegation enabled.
: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).
"""
[docs] template_fields: Sequence[str] = (
"spreadsheet_id",
"destination_bucket",
"destination_path",
"sheet_filter",
"impersonation_chain",
)
def __init__(
self,
*,
spreadsheet_id: str,
destination_bucket: str,
sheet_filter: Optional[List[str]] = None,
destination_path: Optional[str] = None,
gcp_conn_id: str = "google_cloud_default",
delegate_to: Optional[str] = None,
impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.gcp_conn_id = gcp_conn_id
self.spreadsheet_id = spreadsheet_id
self.sheet_filter = sheet_filter
self.destination_bucket = destination_bucket
self.destination_path = destination_path
self.delegate_to = delegate_to
self.impersonation_chain = impersonation_chain
def _upload_data(
self,
gcs_hook: GCSHook,
hook: GSheetsHook,
sheet_range: str,
sheet_values: List[Any],
) -> str:
# Construct destination file path
sheet = hook.get_spreadsheet(self.spreadsheet_id)
file_name = f"{sheet['properties']['title']}_{sheet_range}.csv".replace(" ", "_")
dest_file_name = (
f"{self.destination_path.strip('/')}/{file_name}" if self.destination_path else file_name
)
with NamedTemporaryFile("w+") as temp_file:
# Write data
writer = csv.writer(temp_file)
writer.writerows(sheet_values)
temp_file.flush()
# Upload to GCS
gcs_hook.upload(
bucket_name=self.destination_bucket,
object_name=dest_file_name,
filename=temp_file.name,
)
return dest_file_name
[docs] def execute(self, context: 'Context'):
sheet_hook = GSheetsHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
impersonation_chain=self.impersonation_chain,
)
gcs_hook = GCSHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
impersonation_chain=self.impersonation_chain,
)
# Pull data and upload
destination_array: List[str] = []
sheet_titles = sheet_hook.get_sheet_titles(
spreadsheet_id=self.spreadsheet_id, sheet_filter=self.sheet_filter
)
for sheet_range in sheet_titles:
data = sheet_hook.get_values(spreadsheet_id=self.spreadsheet_id, range_=sheet_range)
gcs_path_to_file = self._upload_data(gcs_hook, sheet_hook, sheet_range, data)
destination_array.append(gcs_path_to_file)
self.xcom_push(context, "destination_objects", destination_array)
return destination_array