def submit(self, request_data):
# secondary data pipeline using new internal data format
reports = self.prepare_reports(request_data)
for i in range(0, len(reports), 100):
batch = reports[i:i + 100]
# insert reports, expire the task if it wasn't processed
# after six hours to avoid queue overload
queue_reports.apply_async(kwargs={
'api_key': self.api_key.valid_key,
'email': self.email,
'nickname': self.nickname,
'reports': batch,
},
expires=21600)
def submit(self, api_key):
# may raise HTTP error
request_data = self.preprocess()
# data pipeline using new internal data format
reports = request_data["items"]
batch_size = 50
for i in range(0, len(reports), batch_size):
batch = reports[i : i + batch_size]
# insert reports, expire the task if it wasn't processed
# after six hours to avoid queue overload
queue_reports.apply_async(
kwargs={"api_key": api_key.valid_key, "nickname": self.nickname, "reports": batch}, expires=21600
)
self.emit_upload_metrics(len(reports), api_key)
def submit(self, api_key):
# may raise HTTP error
request_data = self.preprocess(api_key)
# data pipeline using new internal data format
transform = self.transform()
reports = transform.transform_many(request_data['items'])
for i in range(0, len(reports), 100):
batch = reports[i:i + 100]
# insert reports, expire the task if it wasn't processed
# after six hours to avoid queue overload
queue_reports.apply_async(
kwargs={
'api_key': api_key.valid_key,
'email': self.email,
'ip': self.request.client_addr,
'nickname': self.nickname,
'reports': batch,
},
expires=21600)
def submit(self, api_key):
# may raise HTTP error
request_data = self.preprocess()
# data pipeline using new internal data format
reports = request_data['items']
batch_size = 50
for i in range(0, len(reports), batch_size):
batch = reports[i:i + batch_size]
# insert reports, expire the task if it wasn't processed
# after six hours to avoid queue overload
queue_reports.apply_async(
kwargs={
'api_key': api_key.valid_key,
'nickname': self.nickname,
'reports': batch,
},
expires=21600)
self.emit_upload_metrics(len(reports), api_key)
def submit(self, api_key):
# may raise HTTP error
request_data = self.preprocess()
# data pipeline using new internal data format
reports = request_data['items']
batch_size = 50
for i in range(0, len(reports), batch_size):
batch = reports[i:i + batch_size]
# insert reports, expire the task if it wasn't processed
# after six hours to avoid queue overload
queue_reports.apply_async(
kwargs={
'api_key': api_key.valid_key,
'email': self.email,
'ip': self.request.client_addr,
'nickname': self.nickname,
'reports': batch,
},
expires=21600)
self.emit_upload_metrics(len(reports), api_key)