route1io_connectors.google.sa360 module

SA360 connectors

This module contains code for accessing data from Search Ads 360.

class BaseColumn(name: str)

Bases: abc.ABC

Abstract base class for column subclasses

abstract format_payload() → dict

Return an appropriately formatted dictionary expected by SA360 API

class Column(name: str)

Bases: route1io_connectors.google.sa360.BaseColumn

Column provided by SA360

format_payload() → Dict[str, str]

Return an appropriately formatted dictionary for a normal column as expected by SA360 API

class FloodlightColumn(name: str)

Bases: route1io_connectors.google.sa360.BaseColumn

Custom floodlight column defined by advertiser in SA360

format_payload() → Dict[str, str]

Return an appropriately formatted dictionary for a floodlight column as expected by SA360 API

class SearchAds360(access_token: str)

Bases: object

High level Python connection to Search Ads 360

download_report(fpath: str, file_urls: list) → None

Download report to a given local fpath given a list of file_urls

classmethod from_refresh_token(refresh_token: str, cid: str, csc: str) → route1io_connectors.google.sa360.SearchAds360

Returns an instance of SearchAds360 with a valid access token generated from a refresh token and client credentials

get_request_report(report_id: str) → dict

Return response from a given URL via GET request

n_days(days: int, agency_id: str, report_type: str, advertiser_id: Optional[str] = None, columns: Optional[list] = None, verify_single_timezone: Optional[bool] = None, statistics_currency: str = 'agency', include_removed_entities: Optional[bool] = None, download_format: str = 'csv', pause: int = 5, max_requests: int = 50, silent: bool = True, tmp_directory: Optional[str] = None) → None

Return a DataFrame with data going back n days

post_request_report(agency_id: str, report_type: str, advertiser_id: Optional[str] = None, columns: Optional[list] = None, start_date: Optional[str] = None, end_date: Optional[str] = None, verify_single_timezone: Optional[bool] = None, statistics_currency: str = 'agency', include_removed_entities: Optional[bool] = None, max_rows_per_file: int = 1000000, download_format: str = 'csv') → dict

Return response from a POST requested report

request_and_download_report(fpath: str, agency_id: str, report_type: str, advertiser_id: Optional[str] = None, columns: Optional[list] = None, start_date: Optional[str] = None, end_date: Optional[str] = None, verify_single_timezone: Optional[bool] = None, statistics_currency: str = 'agency', include_removed_entities: Optional[bool] = None, max_rows_per_file: int = 1000000, download_format: str = 'csv', pause: int = 5, max_requests: int = 50, silent: bool = True)

Make a POST request for a report, wait for it to be created and then download it.

wait_for_report(report_id: str, pause: int = 5, max_requests: int = 50, silent: bool = True) → None

Wait until report is finished being created and return response with file URLs

create_report_payload(agency_id: str, report_type: str, advertiser_id: Optional[str] = None, columns: Optional[list] = None, start_date: Optional[str] = None, end_date: Optional[str] = None, verify_single_time_zone: Optional[bool] = None, statistics_currency: str = 'agency', include_removed_entities: Optional[bool] = None, max_rows_per_file: int = 1000000, download_format: Optional[str] = None) → str

Return a serialized JSON string containing how we want an SA360 report formatted

filter_zero_rows(df: pandas.core.frame.DataFrame, columns: list) → pandas.core.frame.DataFrame

Return a DataFrame that has had rows with zero values specified by columns filtered out