async def process(client: SocketModeClient, req: SocketModeRequest):
db_session = SessionLocal()
background_tasks = BackgroundTasks()
if req.type == "events_api":
response = await handle_slack_event(
db_session=db_session,
client=client.web_client,
request=req.payload,
background_tasks=background_tasks,
)
if req.type == "slash_commands":
response = await handle_slack_command(
db_session=db_session,
client=client.web_client,
request=req.payload,
background_tasks=background_tasks,
)
if req.type == "interactive":
response = await handle_slack_action(
db_session=db_session,
client=client.web_client,
request=req.payload,
background_tasks=background_tasks,
)
response = SocketModeResponse(envelope_id=req.envelope_id, payload=response)
await client.send_socket_mode_response(response)
# run the background tasks
await background_tasks()
def test_send(session, bad_user, event):
background_task = BackgroundTasks()
assert not send(session=session,
event_used=1,
user_to_send=1,
title="Test",
background_tasks=background_task)
def __init__(self) -> None:
"""
Crud instances of the collections needed.
"""
self.crud = CRUD(organizations_collection)
self.users = CRUD(users_collection)
self.events = CRUD(events_collection)
self.backgroud_task = BackgroundTasks()
async def _predict_label(
data: Data,
job_id: str,
background_tasks: BackgroundTasks = BackgroundTasks()
) -> Dict[str, Dict[str, float]]:
label_proba = await __async_predict_label(data)
store_data_job._save_data_job(data, job_id, background_tasks, False)
return {'prediction': label_proba, 'job_id': job_id}
async def _predict_async_post(
data: Data,
job_id: str,
background_tasks: BackgroundTasks = BackgroundTasks()
) -> Dict[str, List[float]]:
image = base64.b64decode(str(data.image_data))
io_bytes = io.BytesIO(image)
data.image_data = Image.open(io_bytes)
store_data_job._save_data_job(data, job_id, background_tasks, True)
return {'job_id': job_id}
async def _handle_request(self, request: Request) -> Response:
# route GET requests to the IDE
if request.method == "GET" and "text/html" in request.headers.get("Accept", ""):
# read the GraphiQL playground html and serve it as content
graphiql = pathlib.Path(__file__).parent / "graphiql.html"
raw_html = None
with open(graphiql.absolute(), "r") as f:
raw_html = f.read()
return HTMLResponse(raw_html)
# route POST requests to the graphql executor
elif request.method == "POST":
content_type = request.headers.get("Content-Type", "")
# parse graphql according to content type
if "application/json" in content_type:
data = await request.json()
else:
return PlainTextResponse(
"Unsupported Media Type",
status_code=status.HTTP_415_UNSUPPORTED_MEDIA_TYPE,
)
else:
return PlainTextResponse(
"Method Not Allowed", status_code=status.HTTP_405_METHOD_NOT_ALLOWED
)
# attempt to pull final query and vars
try:
query = data["query"]
variables = data.get("variables")
except KeyError:
return PlainTextResponse(
"No GraphQL query found in the request",
status_code=status.HTTP_400_BAD_REQUEST,
)
# construct foundation fastapi context
background = BackgroundTasks()
context = {"request": request, "background": background}
result = await self._execute_graphql(query, variables, context)
# parse graphql result
response = {}
if not result.invalid:
response["data"] = result.data
if result.errors:
response["errors"] = [format_error(e) for e in result.errors]
status_code = (
status.HTTP_400_BAD_REQUEST if result.errors else status.HTTP_200_OK
)
return ORJSONResponse(response, status_code=status_code, background=background)
async def _predict_label(
data: Data,
job_id: str,
background_tasks: BackgroundTasks = BackgroundTasks()
) -> Dict[str, List[float]]:
image = base64.b64decode(str(data.image_data))
io_bytes = io.BytesIO(image)
data.image_data = Image.open(io_bytes)
label_proba = await __async_predict_label(data)
store_data_job._save_data_job(data, job_id, background_tasks, False)
return {'prediction': label_proba, 'job_id': job_id}
async def post_message_async(
content: ItemInParse,
# user: User = Depends(get_current_user_authorizer()),
):
if not content.message:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=f"Couldn't find the message: {content}",
)
backgroundtask = BackgroundTasks()
backgroundtask.add_task(dummy_background_task, content.message)
return JSONResponse(
{"status": "Starting dummy background task"},
background=backgroundtask,
)
async def upload_py(file: UploadFile = File(...),
message_format: str = None,
background_tasks: BackgroundTasks = BackgroundTasks()):
message = ''
msg_format = 'text'
if message_format.lower() == 'json':
msg_format = 'json'
log.info(
f'{datetime.datetime.now().strftime("%Y-%m-%d-%H:%M.%S")}: '
f'Запрос на выполнение статического анализа файла "{file.filename}" '
f'с выводом отчета в формате {msg_format}')
if file.filename[-3:] != '.py':
message = f'Получен файл "{file.filename}" с неправилным расширением. Необходим файл с расширением .py'
log.warning(
f'{datetime.datetime.now().strftime("%Y-%m-%d-%H:%M.%S")}: {message}'
)
else:
if not os.path.exists(today_folder):
os.mkdir(today_folder)
file_name = f'{file.filename[:-3]}_{datetime.datetime.now().strftime("%H-%M-%S")}'
file_path = os.path.join(today_folder, f'{file_name}.py')
try:
with open(file_path, 'wb') as buffer:
shutil.copyfileobj(file.file, buffer)
except Exception:
message = f'Ошибка сервера'
log.exception(
f'{datetime.datetime.now().strftime("%Y-%m-%d-%H:%M.%S")}: {message}: {Exception}'
)
else:
message = f'Файл "{file.filename}" успешно загружен, ' \
f'сохранен под названием "{file_name}.py" ' \
f'и начaлся статический анализ с использованием pylint'
log.info(
f'{datetime.datetime.now().strftime("%Y-%m-%d-%H:%M.%S")}: {message}'
)
background_tasks.add_task(pylint_analyse, file_path, file_name,
msg_format)
return {f'message': message}
async def process(client: SocketModeClient, req: SocketModeRequest):
background_tasks = BackgroundTasks()
if req.type == "events_api":
response = await handle_slack_event(
config=config,
client=client.web_client,
event=EventEnvelope(**req.payload),
background_tasks=background_tasks,
)
if req.type == "slash_commands":
response = await handle_slack_command(
config=config,
client=client.web_client,
request=req.payload,
background_tasks=background_tasks,
)
if req.type == "interactive":
if req.payload["type"] == "block_suggestion":
response = await handle_slack_menu(
config=config,
client=client.web_client,
request=req.payload,
)
else:
response = await handle_slack_action(
config=config,
client=client.web_client,
request=req.payload,
background_tasks=background_tasks,
)
response = SocketModeResponse(envelope_id=req.envelope_id,
payload=response)
await client.send_socket_mode_response(response)
# run the background tasks
await background_tasks()
async def run_ranking(ranker: Ranker):
background_tasks = BackgroundTasks()
background_tasks.add_task(rank_service.rank_by_session, ranker)
response = JSONResponse(status_code=200, content="Ranking is running", background=background_tasks)
return response
def startup_event():
background_tasks = BackgroundTasks()
background_tasks.add_task(self.end)
return True
async def predict_label(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
return await _predict._predict_label(data, job_id, background_tasks)
def background_tasks():
bg_tasks = BackgroundTasks()
return bg_tasks
import pytest
import json
from PIL import Image
from typing import List, Tuple, Any
from fastapi import BackgroundTasks
from src.constants import PLATFORM_ENUM, CONSTANTS
from src.jobs import store_data_job
import src.jobs
from src.app.ml.base_predictor import BaseData, BaseDataInterface
test_job_id = '550e8400-e29b-41d4-a716-446655440000_0'
test_uuid = '550e8400-e29b-41d4-a716-446655440000'
mock_image = Image.open('src/app/ml/data/good_cat.jpg')
labels = ['a', 'b', 'c']
mock_BackgroundTasks = BackgroundTasks()
class MockData(BaseData):
data: List[List[int]] = [[5.1, 3.5, 1.4, 0.2]]
test_data: List[List[int]] = [[5.1, 3.5, 1.4, 0.2]]
labels: List[str] = labels
class MockDataImage(BaseData):
image_data: Any = mock_image
data: List[List[int]] = [[5.1, 3.5, 1.4, 0.2]]
test_data: List[List[int]] = [[5.1, 3.5, 1.4, 0.2]]
labels: List[str] = labels
async def create_ihou(info: dict):
try:
await IHou.objects.get(title=info['title'])
except orm.exceptions.NoMatch as e:
document = await IHou.objects.create(**info)
BackgroundTasks().add_task(insert_values(document.__dict__))
async def predict(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
result = await _predict_image._predict(data, job_id, background_tasks)
return result
async def predict(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
return await _predict_ab_test._predict(data, job_id, background_tasks,
AB_TEST_GROUP)
def test_send_mail_bad_invitation_internal(client, configured_smtpd,
sender_name, recipient_name,
recipient_mail):
background_task = BackgroundTasks()
assert not send_email_invitation(sender_name, recipient_name,
recipient_mail, background_task)
def test_send_mail_good_file_internal(client, configured_smtpd):
background_task = BackgroundTasks()
assert send_email_file(__file__, "*****@*****.**", background_task)
def test_send_mail_bad_file_internal(client, configured_smtpd, recipient_mail,
file_path):
background_task = BackgroundTasks()
assert not send_email_file(file_path, recipient_mail, background_task)