chart.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NJEQbNwYX+ZYW2rlBr8J+nLybyP/gB+X/8yPyV19NPe2A8E5eF3m3htfJk+lO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10438cd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import time\n",
    "import pylab as pl\n",
    "from IPython import display\n",
    "for i in range(10):\n",
    "    pl.clf()\n",
    "    pl.plot(pl.randn(100))\n",
    "    display.display(pl.gcf())\n",
    "    display.clear_output(wait=True)\n",
    "    time.sleep(1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import clawler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import urllib3\n",
    "import certifi\n",
    "http = urllib3.PoolManager(cert_reqs='CERT_REQUIRED', ca_certs=certifi.where())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'timestamp': '2016/06/26 20:43:13', 'ask': '68693', 'bid': '66464'}\n",
      "{'timestamp': '2016/06/26 20:43:16', 'ask': '68693', 'bid': '66464'}\n",
      "{'timestamp': '2016/06/26 20:43:18', 'ask': '68693', 'bid': '66464'}\n",
      "{'timestamp': '2016/06/26 20:43:20', 'ask': '68693', 'bid': '66415'}\n",
      "{'timestamp': '2016/06/26 20:43:22', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:24', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:27', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:29', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:31', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:33', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:35', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:38', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:40', 'ask': '68693', 'bid': '66469'}\n",
      "{'timestamp': '2016/06/26 20:43:42', 'ask': '68693', 'bid': '66473'}\n",
      "{'timestamp': '2016/06/26 20:43:44', 'ask': '68693', 'bid': '66519'}\n",
      "{'timestamp': '2016/06/26 20:43:46', 'ask': '68693', 'bid': '66519'}\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-17-3f1018523ca6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mclawler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_bitcoin_price\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import time\n",
    "while True:\n",
    "    print(clawler.get_bitcoin_price(http))\n",
    "    time.sleep(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}