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Gold robot Ga1

MQL5 Эксперты Скрипты Forex Отладка робота/индикатора Оптимизация стратегий Статистика и математика C++ Модули стратегий Python Stocks (акции) Пользовательская графика Futures (фьючерсы) Дизайн продуктов Сбор данных из интернета Создание текстов RegExp

Техническое задание

mport pandas as pd
import numpy as np

def detecter_tendance(data):
    # Code pour détecter la tendance
    pass

def identifier_niveaux(data):
    # Code pour identifier les niveaux de support et de résistance
    pass

def calculer_stop_loss(tendance, support, resistance):
    # Code pour calculer les stop loss
    pass

def calculer_profils(tendance, support, resistance):
    # Code pour calculer les profils mport pandas as pd
import numpy as np

def detecter_tendance(data):
    # Code pour détecter la tendance
    pass

def identifier_niveaux(data):
    # Code pour identifier les niveaux de support et de résistance
    pass

def calculer_stop_loss(tendance, support, resistance):
    # Code pour calculer les stop loss
    pass

def calculer_profils(tendance, support, resistance):
    # Code pour calculer les profils import pandas as pd
import numpy as np

def detecter_tendance(data):
    # Code pour détecter la tendance
    pass

def identifier_niveaux(data):
    # Code pour identifier les niveaux de support et de résistance
    pass

def calculer_stop_loss(tendance, support, resistance):
    # Code pour calculer les stop loss
    pass

def calculer_profils(tendance, support, resistance):
    # Code pour calculer les profils from flask import Flask, render_template, request
from .models import detecter_tendance, identifier_niveaux, calculer_stop_loss, calculer_profils

app = Flask(__name__)

@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        data = request.files['data']
        data = pd.read_csv(data)
        tendance = detecter_tendance(data)
        support, resistance = identifier_niveaux(data)
        stop_loss = calculer_stop_loss(tendance, support, resistance)
        profils = calculer_profils(tendance, support, resistance)
        return render_template('index.html', tendance=tendance, support=support, resistance=resistance, stop_loss=stop_loss, profils=profils)
    return render_template('index.html
    pass

Файлы:

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