6 RealTime Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "characteristic-baltimore",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import urllib.request\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "from datetime import datetime, timezone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "incomplete-check",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-04-22 09:15:00\n"
     ]
    }
   ],
   "source": [
    "ts = int(\"1619063100\")\n",
    "print(datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "recovered-manufacturer",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-04-22 19:02:20\n"
     ]
    }
   ],
   "source": [
    "ts = int(\"1619098340\")\n",
    "print(datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "intelligent-movie",
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import deque\n",
    "import random\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, Dropout, LSTM, BatchNormalization, Bidirectional\n",
    "from tensorflow.keras.callbacks import TensorBoard\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint, ModelCheckpoint\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "planned-capital",
   "metadata": {},
   "outputs": [],
   "source": [
    "SEQ_LEN = 60  # how long of a preceeding sequence to collect for RNN\n",
    "FUTURE_PERIOD_PREDICT = 3  # how far into the future are we trying to predict?\n",
    "RATIO_TO_PREDICT = \"c\"\n",
    "EPOCHS = 20  # how many passes through our data\n",
    "BATCH_SIZE = 64  # how many batches? Try smaller batch if you're getting OOM (out of memory) errors.\n",
    "NAME = f\"{SEQ_LEN}-SEQ-{FUTURE_PERIOD_PREDICT}-PRED-{int(time.time())}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "portable-attitude",
   "metadata": {},
   "outputs": [],
   "source": [
    "def classify(current, future):\n",
    "    if float(future) > float(current):  # if the future price is higher than the current, that's a buy, or a 1\n",
    "        return 1\n",
    "    else:  # otherwise... it's a 0!\n",
    "        return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cellular-elimination",
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_dataset(df):\n",
    "    assert isinstance(df, pd.DataFrame), \"df needs to be a pd.DataFrame\"\n",
    "    df.dropna(inplace=True)\n",
    "    indices_to_keep = ~df.isin([np.nan, np.inf, -np.inf]).any(1)\n",
    "    return df[indices_to_keep].astype(np.float64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "attempted-marketing",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_df(df):\n",
    "    for col in df.columns:  # go through all of the columns\n",
    "        df[col] = df[col].pct_change()  # pct change \"normalizes\" the different currencies (each crypto coin has vastly diff values, we're really more interested in the other coin's movements)\n",
    "        df=clean_dataset(df) # remove the nas created by pct_change\n",
    "#         df.dropna(inplace=True)\n",
    "        df[col] = preprocessing.scale(df[col].values)  # scale between 0 and 1.\n",
    "\n",
    "    df.dropna(inplace=True)  # cleanup again... jic.\n",
    "    return df  # return X and y...and make X a numpy array!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "earlier-music",
   "metadata": {},
   "source": [
    "# RealTime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "gross-chaos",
   "metadata": {},
   "outputs": [],
   "source": [
    "model=tf.keras.models.load_model(\"models/FINAL_20EPOCH_MODEL/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "convertible-mitchell",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_7\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_14 (LSTM)               (None, 60, 32)            4608      \n",
      "_________________________________________________________________\n",
      "dropout_21 (Dropout)         (None, 60, 32)            0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_14 (Batc (None, 60, 32)            128       \n",
      "_________________________________________________________________\n",
      "lstm_15 (LSTM)               (None, 64)                24832     \n",
      "_________________________________________________________________\n",
      "dropout_22 (Dropout)         (None, 64)                0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_15 (Batc (None, 64)                256       \n",
      "_________________________________________________________________\n",
      "dense_14 (Dense)             (None, 22)                1430      \n",
      "_________________________________________________________________\n",
      "dropout_23 (Dropout)         (None, 22)                0         \n",
      "_________________________________________________________________\n",
      "dense_15 (Dense)             (None, 2)                 46        \n",
      "=================================================================\n",
      "Total params: 31,300\n",
      "Trainable params: 31,108\n",
      "Non-trainable params: 192\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "welcome-chrome",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(None, 60, 3)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.input_shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "accomplished-longer",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = datetime(time.localtime().tm_year, time.localtime().tm_mon, time.localtime().tm_mday, 9, 15)\n",
    "timestart = int(dt.timestamp())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "deadly-upgrade",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14696.75 at 2021-04-06 10:31:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14706.650390625 at 2021-04-06 10:32:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14703.849609375 at 2021-04-06 10:33:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14708.0 at 2021-04-06 10:34:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14703.75 at 2021-04-06 10:35:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14707.599609375 at 2021-04-06 10:36:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14714.849609375 at 2021-04-06 10:37:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14713.0 at 2021-04-06 10:38:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14715.900390625 at 2021-04-06 10:39:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14712.849609375 at 2021-04-06 10:40:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14724.25 at 2021-04-06 10:41:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14727.299804688 at 2021-04-06 10:42:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14724.75 at 2021-04-06 10:43:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14730.599609375 at 2021-04-06 10:44:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14735.0 at 2021-04-06 10:45:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14733.049804688 at 2021-04-06 10:46:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14731.150390625 at 2021-04-06 10:47:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14725.950195312 at 2021-04-06 10:48:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14728.599609375 at 2021-04-06 10:49:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14730.099609375 at 2021-04-06 10:50:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14733.799804688 at 2021-04-06 10:52:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14729.150390625 at 2021-04-06 10:53:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14729.950195312 at 2021-04-06 10:54:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14731.5 at 2021-04-06 10:55:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14734.25 at 2021-04-06 10:56:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14736.650390625 at 2021-04-06 10:57:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14736.900390625 at 2021-04-06 10:58:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14736.900390625 at 2021-04-06 10:59:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14733.75 at 2021-04-06 11:00:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14734.299804688 at 2021-04-06 11:01:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14736.099609375 at 2021-04-06 11:02:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14741.950195312 at 2021-04-06 11:03:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14741.950195312 at 2021-04-06 11:04:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14739.650390625 at 2021-04-06 11:05:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14735.349609375 at 2021-04-06 11:06:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14725.450195312 at 2021-04-06 11:07:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14731.549804688 at 2021-04-06 11:08:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14735.299804688 at 2021-04-06 11:09:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14738.900390625 at 2021-04-06 11:10:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14758.599609375 at 2021-04-06 11:11:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14759.700195312 at 2021-04-06 11:13:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14752.950195312 at 2021-04-06 11:14:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14751.900390625 at 2021-04-06 11:15:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14756.75 at 2021-04-06 11:16:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14764.5 at 2021-04-06 11:17:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14769.5 at 2021-04-06 11:18:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14769.0 at 2021-04-06 11:19:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14767.549804688 at 2021-04-06 11:20:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14764.75 at 2021-04-06 11:21:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14765.849609375 at 2021-04-06 11:22:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14765.599609375 at 2021-04-06 11:23:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14765.400390625 at 2021-04-06 11:24:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14770.099609375 at 2021-04-06 11:25:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14767.599609375 at 2021-04-06 11:26:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14761.950195312 at 2021-04-06 11:27:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14756.299804688 at 2021-04-06 11:28:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14760.650390625 at 2021-04-06 11:29:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14757.0 at 2021-04-06 11:30:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14755.799804688 at 2021-04-06 11:31:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14755.450195312 at 2021-04-06 11:32:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14748.299804688 at 2021-04-06 11:34:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14747.200195312 at 2021-04-06 11:35:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14746.950195312 at 2021-04-06 11:36:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14738.700195312 at 2021-04-06 11:37:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14739.700195312 at 2021-04-06 11:38:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14743.0 at 2021-04-06 11:39:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14748.150390625 at 2021-04-06 11:40:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14743.799804688 at 2021-04-06 11:41:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14738.049804688 at 2021-04-06 11:42:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14739.700195312 at 2021-04-06 11:43:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14732.75 at 2021-04-06 11:44:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14733.299804688 at 2021-04-06 11:45:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14735.549804688 at 2021-04-06 11:46:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14733.950195312 at 2021-04-06 11:47:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14719.849609375 at 2021-04-06 11:48:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14721.950195312 at 2021-04-06 11:49:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14717.950195312 at 2021-04-06 11:50:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14719.450195312 at 2021-04-06 11:51:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14712.450195312 at 2021-04-06 11:52:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14713.200195312 at 2021-04-06 11:53:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14716.549804688 at 2021-04-06 11:55:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14718.849609375 at 2021-04-06 11:56:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14728.799804688 at 2021-04-06 11:57:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14728.799804688 at 2021-04-06 11:58:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14725.549804688 at 2021-04-06 11:59:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14722.950195312 at 2021-04-06 12:00:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14720.900390625 at 2021-04-06 12:01:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14713.099609375 at 2021-04-06 12:02:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14715.299804688 at 2021-04-06 12:03:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14718.950195312 at 2021-04-06 12:04:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14719.049804688 at 2021-04-06 12:05:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14713.049804688 at 2021-04-06 12:06:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14713.75 at 2021-04-06 12:07:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14715.700195312 at 2021-04-06 12:08:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14719.75 at 2021-04-06 12:09:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14716.049804688 at 2021-04-06 12:10:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will decrease! from 14713.75 at 2021-04-06 12:11:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14716.0 at 2021-04-06 12:12:00\n",
      "Predicting!\n",
      "The price of Nifty-50 will increase! from 14721.950195312 at 2021-04-06 12:13:00\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-22-4d4243860dcd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mrequest\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m     \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murlopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[1;32m    220\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    221\u001b[0m         \u001b[0mopener\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 222\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    223\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    224\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    523\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    524\u001b[0m         \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maudit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'urllib.Request'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 525\u001b[0;31m         \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    526\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    527\u001b[0m         \u001b[0;31m# post-process response\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_open\u001b[0;34m(self, req, data)\u001b[0m\n\u001b[1;32m    540\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    541\u001b[0m         \u001b[0mprotocol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 542\u001b[0;31m         result = self._call_chain(self.handle_open, protocol, protocol +\n\u001b[0m\u001b[1;32m    543\u001b[0m                                   '_open', req)\n\u001b[1;32m    544\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    500\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    501\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 502\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    503\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    504\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttps_open\u001b[0;34m(self, req)\u001b[0m\n\u001b[1;32m   1395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1396\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mhttps_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1397\u001b[0;31m             return self.do_open(http.client.HTTPSConnection, req,\n\u001b[0m\u001b[1;32m   1398\u001b[0m                 context=self._context, check_hostname=self._check_hostname)\n\u001b[1;32m   1399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mdo_open\u001b[0;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[1;32m   1352\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1353\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1354\u001b[0;31m                 h.request(req.get_method(), req.selector, req.data, headers,\n\u001b[0m\u001b[1;32m   1355\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n\u001b[1;32m   1356\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# timeout error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1253\u001b[0m                 encode_chunked=False):\n\u001b[1;32m   1254\u001b[0m         \u001b[0;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1255\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1257\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36m_send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1299\u001b[0m             \u001b[0;31m# default charset of iso-8859-1.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1300\u001b[0m             \u001b[0mbody\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'body'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1301\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1303\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mgetresponse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mendheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1248\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1249\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1250\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1251\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1252\u001b[0m     def request(self, method, url, body=None, headers={}, *,\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36m_send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1008\u001b[0m         \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mb\"\\r\\n\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1009\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1010\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1011\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1012\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmessage_body\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    948\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msock\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    949\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 950\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    951\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    952\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mNotConnected\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1415\u001b[0m             \u001b[0;34m\"Connect to a host on a given (SSL) port.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1416\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1417\u001b[0;31m             \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1418\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1419\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tunnel_host\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    919\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m         \u001b[0;34m\"\"\"Connect to the host and port specified in __init__.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m         self.sock = self._create_connection(\n\u001b[0m\u001b[1;32m    922\u001b[0m             (self.host,self.port), self.timeout, self.source_address)\n\u001b[1;32m    923\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetsockopt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIPPROTO_TCP\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTCP_NODELAY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/socket.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address)\u001b[0m\n\u001b[1;32m    785\u001b[0m     \u001b[0mhost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mport\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maddress\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    786\u001b[0m     \u001b[0merr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 787\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgetaddrinfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mport\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSOCK_STREAM\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    788\u001b[0m         \u001b[0maf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msocktype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcanonname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msa\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    789\u001b[0m         \u001b[0msock\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/socket.py\u001b[0m in \u001b[0;36mgetaddrinfo\u001b[0;34m(host, port, family, type, proto, flags)\u001b[0m\n\u001b[1;32m    916\u001b[0m     \u001b[0;31m# and socket type values to enum constants.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    917\u001b[0m     \u001b[0maddrlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 918\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32min\u001b[0m \u001b[0m_socket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetaddrinfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mport\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfamily\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    919\u001b[0m         \u001b[0maf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msocktype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcanonname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msa\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m         addrlist.append((_intenum_converter(af, AddressFamily),\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "starter=timestart\n",
    "ender=timestart+(75*60)\n",
    "# starter=int(time.time()-3600)\n",
    "# buffPd=pd.DataFrame(columns=['t', 'c', 'o', 'h', 'l', 'v', 'vo', 's'])\n",
    "Resolution=1\n",
    "main_df=pd.DataFrame()\n",
    "while(1):\n",
    "    url = \"https://tvc4.forexpros.com/9e947eed212d70ba03e313a75eb9a1f5/1616696634/56/56/23/history?symbol=17940&resolution=\"+str(Resolution)+\"&from=\"+str(starter)+\"&to=\"+str(ender)\n",
    "    user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n",
    "\n",
    "    headers={'User-Agent':user_agent,} \n",
    "\n",
    "    request=urllib.request.Request(url,None,headers)\n",
    "    response = urllib.request.urlopen(request)\n",
    "\n",
    "    data = response.read()\n",
    "#     print(data)\n",
    "#     print(len(pd.read_json(data)))\n",
    "#     print(data)\n",
    "    try:\n",
    "        main_df=pd.read_json(data)\n",
    "#         time.sleep(60)\n",
    "    except:\n",
    "        print(\"No data available yet!\")\n",
    "#         time.sleep(60) #This\n",
    "    \n",
    "    if len(main_df)>=75:\n",
    "#         main_df=main_df[(main_df.index < 63)]\n",
    "        \n",
    "        url = \"https://tvc4.forexpros.com/9e947eed212d70ba03e313a75eb9a1f5/1616696634/56/56/23/history?symbol=17940&resolution=\"+str(5)+\"&from=\"+str(starter)+\"&to=\"+str(int(time.time()))\n",
    "        user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n",
    "\n",
    "        headers={'User-Agent':user_agent,} \n",
    "\n",
    "        request=urllib.request.Request(url,None,headers)\n",
    "        response = urllib.request.urlopen(request)\n",
    "\n",
    "        data = response.read()\n",
    "        main_dfV=pd.read_json(data)\n",
    "        \n",
    "        main_dfV=main_dfV[(main_dfV.index < 16)]\n",
    "        \n",
    "        npDf=np.array(main_df)\n",
    "        npDfV=np.array(main_dfV)\n",
    "        \n",
    "        opti=0\n",
    "        for i in npDfV[1:,:]:\n",
    "            buff=i[0]\n",
    "\n",
    "            for j in range(opti,npDf.shape[0]):\n",
    "                if npDf[j][0]==buff:\n",
    "                    opti=j\n",
    "                    break\n",
    "\n",
    "            npDf[j-4:j+1,-3]=i[-3]/5\n",
    "        \n",
    "        main_df=pd.DataFrame(npDf,columns=['t','c','o','h','l','v','vo','s'])\n",
    "        \n",
    "        prevPrice=str(np.array(main_df['c'])[-1])\n",
    "        prevTime=int(np.array(main_df['t'])[-1])\n",
    "        \n",
    "        main_df['diff']=main_df.h-main_df.l\n",
    "        main_df=main_df.drop(labels=['t','o','h','l','s','vo'],axis=1)\n",
    "\n",
    "        validation_x = preprocess_df(main_df)\n",
    "        print(\"Predicting!\")\n",
    "        Result=np.argmax(model.predict(np.array(validation_x)[-60:,:].reshape(1,60,3)))\n",
    "        \n",
    "#         dt=datetime.fromtimestamp(time.time()+300).strftime('%Y-%m-%d %H:%M:%S') #This\n",
    "        \n",
    "        dt=datetime.fromtimestamp(prevTime+60).strftime('%Y-%m-%d %H:%M:%S')\n",
    "        \n",
    "        if Result==0:\n",
    "            print(\"The price of Nifty-50 will decrease! from \" +prevPrice+\" at \"+dt)\n",
    "        else:\n",
    "            print(\"The price of Nifty-50 will increase! from \" +prevPrice+\" at \"+dt)\n",
    "#         time.sleep(200) #This\n",
    "        \n",
    "        starter+=63\n",
    "        ender+=63\n",
    "        \n",
    "        main_df=pd.DataFrame()\n",
    "    else:\n",
    "#         time.sleep(60) #This\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3608b312-8b8e-4d11-8ac0-bc2605be654d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "536e2877-7d55-46be-bb12-1b8202609ead",
   "metadata": {},
   "source": [
    "# Below code was for testing whole day's data at one go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bridal-latino",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The price of Nifty-50 will decrease! from 14763.950195312 at 2021-03-30 12:55:10\n",
      "The price of Nifty-50 will decrease! from 14759.900390625 at 2021-03-30 13:00:33\n",
      "The price of Nifty-50 will decrease! from 14738.549804688 at 2021-03-30 13:06:01\n",
      "The price of Nifty-50 will increase! from 14742.599609375 at 2021-03-30 13:10:24\n",
      "The price of Nifty-50 will increase! from 14746.299804688 at 2021-03-30 13:15:47\n",
      "The price of Nifty-50 will increase! from 14759.099609375 at 2021-03-30 13:20:09\n",
      "The price of Nifty-50 will decrease! from 14764.75 at 2021-03-30 13:25:31\n",
      "The price of Nifty-50 will decrease! from 14792.549804688 at 2021-03-30 13:30:54\n",
      "The price of Nifty-50 will decrease! from 14782.400390625 at 2021-03-30 13:35:16\n",
      "The price of Nifty-50 will decrease! from 14795.0 at 2021-03-30 13:40:44\n",
      "The price of Nifty-50 will decrease! from 14798.549804688 at 2021-03-30 13:45:08\n"
     ]
    },
    {
     "ename": "URLError",
     "evalue": "<urlopen error [Errno -2] Name or service not known>",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mgaierror\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mdo_open\u001b[0;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[1;32m   1353\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1354\u001b[0;31m                 h.request(req.get_method(), req.selector, req.data, headers,\n\u001b[0m\u001b[1;32m   1355\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1254\u001b[0m         \u001b[0;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1255\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36m_send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1300\u001b[0m             \u001b[0mbody\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'body'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1301\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mendheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1249\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1250\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1251\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36m_send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1009\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1010\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1011\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    949\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 950\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    951\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1416\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1417\u001b[0;31m             \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1418\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/http/client.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    920\u001b[0m         \u001b[0;34m\"\"\"Connect to the host and port specified in __init__.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m         self.sock = self._create_connection(\n\u001b[0m\u001b[1;32m    922\u001b[0m             (self.host,self.port), self.timeout, self.source_address)\n",
      "\u001b[0;32m/usr/lib/python3.8/socket.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address)\u001b[0m\n\u001b[1;32m    786\u001b[0m     \u001b[0merr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 787\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgetaddrinfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mport\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSOCK_STREAM\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    788\u001b[0m         \u001b[0maf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msocktype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcanonname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msa\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/socket.py\u001b[0m in \u001b[0;36mgetaddrinfo\u001b[0;34m(host, port, family, type, proto, flags)\u001b[0m\n\u001b[1;32m    917\u001b[0m     \u001b[0maddrlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 918\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32min\u001b[0m \u001b[0m_socket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetaddrinfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhost\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mport\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfamily\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    919\u001b[0m         \u001b[0maf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msocktype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcanonname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msa\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mgaierror\u001b[0m: [Errno -2] Name or service not known",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mURLError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-38-ea97754be007>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0mrequest\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m     \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murlopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[1;32m    220\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    221\u001b[0m         \u001b[0mopener\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 222\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    223\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    224\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    523\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    524\u001b[0m         \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maudit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'urllib.Request'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 525\u001b[0;31m         \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    526\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    527\u001b[0m         \u001b[0;31m# post-process response\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_open\u001b[0;34m(self, req, data)\u001b[0m\n\u001b[1;32m    540\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    541\u001b[0m         \u001b[0mprotocol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 542\u001b[0;31m         result = self._call_chain(self.handle_open, protocol, protocol +\n\u001b[0m\u001b[1;32m    543\u001b[0m                                   '_open', req)\n\u001b[1;32m    544\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    500\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    501\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 502\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    503\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    504\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttps_open\u001b[0;34m(self, req)\u001b[0m\n\u001b[1;32m   1395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1396\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mhttps_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1397\u001b[0;31m             return self.do_open(http.client.HTTPSConnection, req,\n\u001b[0m\u001b[1;32m   1398\u001b[0m                 context=self._context, check_hostname=self._check_hostname)\n\u001b[1;32m   1399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mdo_open\u001b[0;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[1;32m   1355\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n\u001b[1;32m   1356\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# timeout error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1357\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mURLError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1358\u001b[0m             \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1359\u001b[0m         \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mURLError\u001b[0m: <urlopen error [Errno -2] Name or service not known>"
     ]
    }
   ],
   "source": [
    "# starter=timestart\n",
    "starter=int(time.time()-3600)\n",
    "# buffPd=pd.DataFrame(columns=['t', 'c', 'o', 'h', 'l', 'v', 'vo', 's'])\n",
    "Resolution=5\n",
    "main_df=pd.DataFrame()\n",
    "while(1):\n",
    "    url = \"https://tvc4.forexpros.com/9e947eed212d70ba03e313a75eb9a1f5/1616696634/56/56/23/history?symbol=17940&resolution=\"+str(Resolution)+\"&from=\"+str(starter)+\"&to=\"+str(int(time.time()))\n",
    "    user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n",
    "\n",
    "    headers={'User-Agent':user_agent,} \n",
    "\n",
    "    request=urllib.request.Request(url,None,headers)\n",
    "    response = urllib.request.urlopen(request)\n",
    "\n",
    "    data = response.read()\n",
    "#     print(data)\n",
    "#     print(len(pd.read_json(data)))\n",
    "#     print(data)\n",
    "    try:\n",
    "        main_df=pd.read_json(data)\n",
    "#         time.sleep(60)\n",
    "    except:\n",
    "        print(\"No data available yet!\")\n",
    "        time.sleep(60)\n",
    "    \n",
    "    if len(main_df)>=13:\n",
    "        main_df=main_df[(main_df.index < 13)]\n",
    "        prevPrice=str(np.array(main_df['c'])[-1])\n",
    "        main_df['diff']=main_df.h-main_df.l\n",
    "        main_df=main_df.drop(labels=['t','o','h','l','s','vo'],axis=1)\n",
    "        \n",
    "        validation_x = preprocess_df(main_df)\n",
    "        Result=np.argmax(model.predict(np.array(validation_x).reshape(1,12,3)))\n",
    "        \n",
    "        dt=datetime.fromtimestamp(time.time()+300).strftime('%Y-%m-%d %H:%M:%S')\n",
    "        \n",
    "        if Result==0:\n",
    "            print(\"The price of Nifty-50 will decrease! from \" +prevPrice+\" at \"+dt)\n",
    "        else:\n",
    "            print(\"The price of Nifty-50 will increase! from \" +prevPrice+\" at \"+dt)\n",
    "        time.sleep(200)\n",
    "        starter+=300\n",
    "    else:\n",
    "        time.sleep(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "infinite-berlin",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The price of Nifty-50 will decrease! from 14848.549804688 at 2021-03-30 14:55:55\n",
      "The price of Nifty-50 will increase! from 14865.849609375 at 2021-03-30 15:00:17\n",
      "The price of Nifty-50 will decrease! from 14855.950195312 at 2021-03-30 15:05:40\n",
      "The price of Nifty-50 will decrease! from 14838.349609375 at 2021-03-30 15:11:03\n",
      "The price of Nifty-50 will decrease! from 14848.25 at 2021-03-30 15:15:24\n",
      "The price of Nifty-50 will decrease! from 14841.400390625 at 2021-03-30 15:20:47\n",
      "The price of Nifty-50 will decrease! from 14844.450195312 at 2021-03-30 15:25:14\n",
      "The price of Nifty-50 will decrease! from 14834.599609375 at 2021-03-30 15:30:38\n",
      "The price of Nifty-50 will decrease! from 14845.099609375 at 2021-03-30 15:37:07\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-42-ea97754be007>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     42\u001b[0m         \u001b[0mstarter\u001b[0m\u001b[0;34m+=\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m         \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m60\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# starter=timestart\n",
    "starter=int(time.time()-3600)\n",
    "# buffPd=pd.DataFrame(columns=['t', 'c', 'o', 'h', 'l', 'v', 'vo', 's'])\n",
    "Resolution=5\n",
    "main_df=pd.DataFrame()\n",
    "while(1):\n",
    "    url = \"https://tvc4.forexpros.com/9e947eed212d70ba03e313a75eb9a1f5/1616696634/56/56/23/history?symbol=17940&resolution=\"+str(Resolution)+\"&from=\"+str(starter)+\"&to=\"+str(int(time.time()))\n",
    "    user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n",
    "\n",
    "    headers={'User-Agent':user_agent,} \n",
    "\n",
    "    request=urllib.request.Request(url,None,headers)\n",
    "    response = urllib.request.urlopen(request)\n",
    "\n",
    "    data = response.read()\n",
    "#     print(data)\n",
    "#     print(len(pd.read_json(data)))\n",
    "#     print(data)\n",
    "    try:\n",
    "        main_df=pd.read_json(data)\n",
    "#         time.sleep(60)\n",
    "    except:\n",
    "        print(\"No data available yet!\")\n",
    "        time.sleep(60)\n",
    "    \n",
    "    if len(main_df)>=13:\n",
    "        main_df=main_df[(main_df.index < 13)]\n",
    "        prevPrice=str(np.array(main_df['c'])[-1])\n",
    "        main_df['diff']=main_df.h-main_df.l\n",
    "        main_df=main_df.drop(labels=['t','o','h','l','s','vo'],axis=1)\n",
    "        \n",
    "        validation_x = preprocess_df(main_df)\n",
    "        Result=np.argmax(model.predict(np.array(validation_x).reshape(1,12,3)))\n",
    "        \n",
    "        dt=datetime.fromtimestamp(time.time()+300).strftime('%Y-%m-%d %H:%M:%S')\n",
    "        \n",
    "        if Result==0:\n",
    "            print(\"The price of Nifty-50 will decrease! from \" +prevPrice+\" at \"+dt)\n",
    "        else:\n",
    "            print(\"The price of Nifty-50 will increase! from \" +prevPrice+\" at \"+dt)\n",
    "        time.sleep(200)\n",
    "        starter+=300\n",
    "    else:\n",
    "        time.sleep(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "novel-thesis",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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