gtindo

from django.contrib.auth.mixins import AccessMixin
from django.shortcuts import redirect

class UserIsStaffRequired(AccessMixin):
    """Verify that the current user is staff member."""
    def dispatch(self, request, *args, **kwargs):
        if not request.user.is_authenticated :
            return self.handle_no_permission()
        else:
            if not request.user.is_staff :

gtindo

import mimetypes
from django import forms
from django.core import validators

class CsvFileField(forms.FileField):
  def validate(self, value):
    super().validate(value)
    
    file_mime = mimetypes.guess_type(value)
    if file_mime != 'text/csv':

gtindo

from api_v1.models import Notification

class NotificationMiddleware:
    def __init__(self, get_response):
        self.get_response = get_response
        # One-time configuration and initialization.

    def __call__(self, request):
        # Code to be executed for each request before
        # the view (and later middleware) are called.

gtindo

from flask import Flask, escape, url_for, request, redirect, session
from werkzeug.utils import secure_filename

#Instancier une application Flask
app = Flask(__name__)

# Set the secret key to some random bytes. Keep this really secret!
app.secret_key = b'_5#y2L"F4Q8z\n\xec]/'

##########################

gtindo

import logging
import pika
import configparser

LOG_FORMAT = ('%(levelname) -10s %(asctime)s %(name) -30s %(funcName) '
              '-35s %(lineno) -5d: %(message)s')
LOGGER = logging.getLogger(__name__)


class RabbitmqManager:

gtindo

from flask import Blueprint, request
from werkzeug.utils import secure_filename
from pandas import pandas as pd
from flask_cors import cross_origin
import os
import uuid

from .. import config

bp = Blueprint("process", __name__, url_prefix='/process') 

gtindo

from threading import Thread, Event


event = Event()


def worker(number, outputs, exit_code):
    msg = "=== Table de mulitiplication par {}".format(number)
    outputs.append(msg)

gtindo

class FileVideoStream:
    def __init__(self, path, workers=6, queue_size=128):
        # Get number of frame
        self.nb_frame = imutils.video.count_frames(path)

        # Compute number of frame per workers
        self.bias = math.ceil(self.nb_frame / workers)

        # self.stream = cv2.VideoCapture(path)
        self.streams = {}

gtindo

def validation_required(validator_function):

    def decorator(function):

        async def error(websocket, err):
            await websocket.send(err)

        async def wrapper(websocket, data):
            status, err = validator_function(data)
            if status:

gtindo

import pandas as pd
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D, Dropout, Flatten, Dense, Activation, BatchNormalization
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt

import os