def _create_click_conversion(
client: GoogleAdsClient,
customer_id: str,
action_name: str,
gclid: str,
utc_dt: datetime,
) -> UploadClickConversionsResponse:
ca = get_conversion_action(client, customer_id, action_name)
if ca is None:
raise MissingResourceError(
f"Could not find conversion_action with name {action_name}")
cc = client.get_type("ClickConversion", version="v6")
cc.conversion_action = ca.resource_name
cc.gclid = gclid
cc.conversion_date_time = utc_dt.strftime("%Y-%m-%d %H:%M:%S+00:00")
conversion_upload_service = client.get_service("ConversionUploadService",
version="v6")
res = conversion_upload_service.upload_click_conversions(
customer_id, [cc], partial_failure=True)
if is_partial_failure_error_present(res):
print('Click conversion failed.')
print(res)
raise Exception(res)
return res
def map_language_to_string_value(
client: GoogleAdsClient,
language_id: str,
) -> Any:
# google.protobuf.StringValue
language = client.get_type("StringValue")
language.value = client.get_service(
"LanguageConstantService",
version="v3").language_constant_path(language_id)
return language
def map_locations_to_string_values(
client: GoogleAdsClient,
location_ids: List[str],
) -> List:
gtc_service = client.get_service("GeoTargetConstantService", version="v3")
locations = []
location_id: str
for location_id in location_ids:
# google.protobuf.StringValue
location = client.get_type("StringValue")
location.value = gtc_service.geo_target_constant_path(location_id)
locations.append(location)
return locations
def get_conversion_action(client: GoogleAdsClient, customer_id: str,
name: str) -> ConversionAction:
ga_service = client.get_service("GoogleAdsService", version="v6")
query = f"""
SELECT conversion_action.id, conversion_action.name
FROM conversion_action
WHERE conversion_action.name = '{name}'
"""
response = ga_service.search_stream(customer_id, query=query)
try:
row = next(row for batch in response for row in batch.results)
return row.conversion_action
except StopIteration:
return None
def create_conversion_action(client: GoogleAdsClient, customer_id: str,
name: str) -> MutateConversionActionsResponse:
conversion_action_service = client.get_service("ConversionActionService",
version="v6")
conversion_action_operation = client.get_type("ConversionActionOperation",
version="v6")
action = conversion_action_operation.create
action.name = name
action.type = client.get_type("ConversionActionTypeEnum").UPLOAD_CLICKS
action.category = client.get_type("ConversionActionCategoryEnum").DEFAULT
action.status = client.get_type("ConversionActionStatusEnum").ENABLED
res = conversion_action_service.mutate_conversion_actions(
customer_id, [conversion_action_operation])
return res
def query_ga_campaign(query: str, client: GoogleAdsClient, customer_id: str):
ga_service = client.get_service('GoogleAdsService', version='v4')
# Issues a search request using streaming.
customer_id = customer_id.replace('-', '')
response = ga_service.search_stream(customer_id, query=query)
select_section = re.search('(?<=SELECT )(.*)(?= FROM)', query)[0]
extract_values = select_section.split(', ')
campaigns = []
try:
for batch in response:
for row in batch.results:
campaign = {}
#for col_table_and_name in col_tables_and_names:
for extract_value in extract_values:
attr = get_nested_attr(row, extract_value)
col_name = extract_value.split('.')[-1]
if type(attr) in [int]:
campaign_attr = {
col_name: attr
}
else:
campaign_attr = {
col_name: getattr(attr, 'value')
}
campaign.update(campaign_attr)
campaigns.append(campaign)
except GoogleAdsException as ex:
print(f'Request with ID "{ex.request_id}" failed with status '
f'"{ex.error.code().name}" and includes the following errors:')
for error in ex.failure.errors:
print(f'\tError with message "{error.message}".')
if error.location:
for field_path_element in error.location.field_path_elements:
print(f'\t\tOn field: {field_path_element.field_name}')
sys.exit(1)
df_campaigns = pd.DataFrame.from_dict(campaigns)
return df_campaigns
def download_expansion(
city: str,
client: GoogleAdsClient,
customer_id: str,
only_expand_missing: bool,
folder_expansion_raw: str,
folder_expansion_parents: str,
folder_keywords_google: str,
list_source_priority_order: Tuple[str] = DEFAULT_SOURCE_PRIORITY_ORDER,
folder_keywords: str = FOLDER_SEEDWORDS,
language_id: str = DEFAULT_LANGUAGE_ID_ENGLISH,
) -> None:
location_id: str = DEFAULT_CITIES.get(city, {}).get(GOOGLE_GEO_CODE, "")
list_location_ids: List[str] = [location_id]
keyword_plan_idea_service = client.get_service("KeywordPlanIdeaService",
version="v3")
keyword_competition_level_enum = (client.get_type(
"KeywordPlanCompetitionLevelEnum",
version="v3").KeywordPlanCompetitionLevel)
keyword_plan_network = client.get_type("KeywordPlanNetworkEnum",
version="v3").GOOGLE_SEARCH
locations = map_locations_to_string_values(
client=client,
location_ids=list_location_ids,
)
language = map_language_to_string_value(
client=client,
language_id=language_id,
)
url_seed = None
keyword_url_seed = None
dict_keywords: dict = trends.generate_keywords(
folder_keywords=folder_keywords, )
source: str
for source in list_source_priority_order:
folder_expansion_raw_source: str = generate_source_folder(
source=source,
folder=folder_expansion_raw,
)
list_source_keywords: List[str] = dict_keywords[source]
list_already_expanded_filenames_in_raw_source: Generator[
str, None, List[str]] = import_paths_from_folder(
folder=folder_expansion_raw_source,
list_paths_filter_conditions=(city, ),
)
seed_keyword: str
for seed_keyword in list_source_keywords:
# noinspection PyArgumentList
nt_filename_expansion_raw: tuple = NT_filename_expansion_raw(
city=city,
keyword=seed_keyword,
)
filename_expansion_raw: str = generate_filename(
nt_filename=nt_filename_expansion_raw,
delimiter=HYPHEN,
extension=CSV,
)
if only_expand_missing and filename_expansion_raw in list_already_expanded_filenames_in_raw_source:
continue
print(f"expansion : {city} : {seed_keyword}")
keyword_seed = client.get_type("KeywordSeed", version="v3")
keyword_protos = map_keywords_to_string_values(
client=client,
keywords=[seed_keyword],
)
keyword_seed.keywords.extend(keyword_protos)
time.sleep(2)
try:
keyword_ideas = keyword_plan_idea_service.generate_keyword_ideas(
customer_id,
language,
locations,
keyword_plan_network,
url_seed=url_seed,
keyword_seed=keyword_seed,
keyword_and_url_seed=keyword_url_seed,
)
except GoogleAdsException as ex:
log_error(
error=f"{city}{HYPHEN}{seed_keyword}{HYPHEN}exception")
log_exception(exception=ex)
write_errors_to_disk(clear_task_origin=False, overwrite=False)
continue
list_expanded_keywords: List[str] = []
list_individual_keyword_ideas_results: List[pd.DataFrame] = []
for idea in keyword_ideas.results:
dict_keyword_ideas_result = {}
dict_keyword_ideas_result.update({CITY: city})
expanded_keyword = idea.text.value
dict_keyword_ideas_result.update({KEYWORD: expanded_keyword})
dict_keyword_ideas_result.update({SOURCE: source})
list_expanded_keywords.append(
f"{city}{HYPHEN}{expanded_keyword}")
dict_keyword_ideas_result.update({
AVG_MONTHLY_SEARCH:
idea.keyword_idea_metrics.avg_monthly_searches.value
})
competition_value = keyword_competition_level_enum.Name(
idea.keyword_idea_metrics.competition)
dict_keyword_ideas_result.update(
{COMPETITION_VALUE: competition_value})
list_individual_keyword_ideas_results.append(
pd.DataFrame(
dict_keyword_ideas_result,
index=[0],
))
# noinspection PyArgumentList
filename_expansion_parent: str = generate_filename(
nt_filename=NT_filename_expansion_parents(
expanded_keyword=expanded_keyword, ),
extension=TXT,
)
write_list_to_file(
filename=f"{filename_expansion_parent}",
folder=folder_expansion_parents,
list_strings=[f"{city}{HYPHEN}{seed_keyword}"],
)
# noinspection PyArgumentList
output_keywords_google_filename: str = generate_filename(
nt_filename=NT_filename_keywords_google(
seed_keyword=seed_keyword, ),
extension=TXT,
)
write_list_to_file(
filename=f"{output_keywords_google_filename}",
folder=generate_source_folder(
source=source,
folder=folder_keywords_google,
),
list_strings=list_expanded_keywords,
)
df_keyword_ideas_for_city: pd.DataFrame
if len(list_individual_keyword_ideas_results) > 0:
df_keyword_ideas_for_city = pd.concat(
list_individual_keyword_ideas_results,
ignore_index=True,
)
else:
df_keyword_ideas_for_city = pd.DataFrame()
log_error(
error=f"{city}{HYPHEN}{seed_keyword}{HYPHEN}{ERROR_EMPTY}")
df_keyword_ideas_for_city.to_csv(
f"{folder_expansion_raw_source}{filename_expansion_raw}",
index=False,
)