test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyspark\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from influxdb_client import InfluxDBClient\n",
    "from influxdb_client.client.write_api import SYNCHRONOUS\n",
    "\n",
    "from math import sin, cos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/YOnkTt4znlZbV1QUwic/USceG8Se9Hxe+UEd0X7+pqFM7de1Ux8/NtSft+4ZY19CvmRHRqc+vugYSXCMJDgK5r6vdio99KU64dAAUnNK+euKIwA8dXUil3XySUZz+9g4rh4SQ41N4Zcf7aG4olqXOIRwmPXPqx2KfUPgjqUQENb5MXj5wM3vqlvNnN0Nq57q/BhaUF5Vy+Mf76XWpnDtsFhuHtVdlzgGxobw61n9AXj260Ok5pTqEodoP0lwjCZuLFz5vHp97TNwpu0l885Wa1P49Sd7qayxMblPBPdM7KlbLCaTib/cOIRuoWqPnN99fkCGjIXrytwHmxap16/7t9qrRi+hcfXzcba/oW4vo7PnvjtMak4p0SF+/Om6wbrGct/kBCb0Cqe8upYFS5Opru3chnXi0kiCY0Sj74PBN6mrG75ZALU1uoXy3uY0dp7KJ9DHwvM3DdF9nxarvzcv3zECi9nE13vP8snO07rGI8Qlqa2Brx4GpRYGXgcDr9U7IuiXVL+X3lePQNFZ3ULZcOw8/91yCoC/3TIUa4C+G/CazSZevHUYIX7qRsEvf2/MhSCiMUlwjMhkgtnPg58VMvfC9v/oEkZaTil/XamWpn53dSLduwToEkdTI+O78KukfgD831cHOVsg2zkIF7PlFfVv2y8Urvyb3tHUu/wP0G20uthh1R90CaGwrJonP1Ubx909oQdT+upTEm8qNtSf/3eDurnkK9+nsOtUvs4RiQuRBMeogiJhxjPq9R/+DIWdO1Jhsyk8uWwfFdU2JvYO544ObMHgDA9O7c3oHl0or67lue+O6B2OEBcv9wSse069Pusv6tw7o7B4wZyX1EaDB5bByfWdHsJTXx4gq6iCXhGBLLwysdMfvy3XDovl+uGx2BT41cfJVNYYv0GiJ5MEx8hG3gNx49Tlo9/9plMf+v2tp9iemkeAj4UXbhqqe2mqKbPZxDPXDcJsgq/3nmWr7BsjXIHNppZ/aiqg1+Uw/A69I2ouZpja7Rhg+RPqSq9Osiklh6/2nsViNvHS3OH4+zi4i7MDPHPdYCKDfUnLLWPxj2l6hyPaIAmOkZnNMGcRmL3gyDed1ojrXFEFL9Stmlp4VSJxYcYoTTU1KNbK7XUjS09/dZAamfgnjG73e3BqE3gHwDWLjLv33OW/h4AIyDmm7lnVCWptCv/v20OAujv48E7qd9NeVn9vnpw9AICXvz8uW8gYmCQ4Rhc1UG2jDrD8Sah0/r4oi9Yco6yqlpHxodxpsNJUU08k9cfq782RrGL+tz39wj8ghF7K8mD1/6nXr3gKuvTUNZw2+YdC0p/U6+v/2ikl8k93ZXAkq5gQPy8WzOjr9MfriBtHdGNINysllTW8tPqY3uGIVkiC4wqmPgmhPaDotNo3w4mOZxeztK6Z1e+uSsRsNugnzDpdAn14om7C8Yurjkk7dWFcm16CykKIGgzjfqZ3NBc27Ha1u3p1Kaz8vVMfqqSyhr+vUhOFR6b3JTTA2PvNmc0m/njNQACW7kjn0NkinSPqHDabjRdeeIE+ffrg6+tLfHw8f/7znwHYv38/V1xxBf7+/oSHh/PAAw9QUlL/gXzdunWMHTuWwMBAQkNDmTRpEqdOnXJqvJLguAKfAHXzPYBt/4HCM057qOe/O4pNgaSBUYzuqUPTsUtwx7geJMaEUFhezd9XHdU7HCGaKzyj/u2C2jnY0TuEO4PJpJ53TBY49AUcX+u0h3pj/QnOF1fSMzyAuyf0dNrjONKYnmFcPTQGmwJ/+uZQx3pyKQpUlXb+pZ0xL1y4kBdeeIGnnnqKQ4cO8b///Y+oqCjKysqYPXs2Xbp0YceOHXzyySesWbOGhx9+GICamhquv/56LrvsMvbt28eWLVt44IEHnD6307k7JQrH6TsTekyCUz/Chr+p9XsH256ax5rD57CYTfYasyuwmE08c+0gbn1jCx9tT+eOsfEM7mbVOywh6q17Dmor1b/hPjP0jubiRQ9WNwLe9ppaXut1uTo30IHOFpTz5kZ1f7nfXpmIj5frfO7+7ewBrD50ji0nc1l96BxJg6Iv7Y6qy+AvsY4N7mL87iz4BF7UocXFxfzzn//klVde4Z577gGgd+/eTJ48mTfffJPy8nL++9//Ehio3t8rr7zCNddcwwsvvIC3tzeFhYXMmTOH3r17A5CY6PwVcq7zm+TpTCa4oq4vxZ73IS/VoXevKAp/WX4YgLlj4ugT6dzdeh1tbEIY1w6LRVGwT5AWwhDOH4PkD9XrM5427sTi1lz2JPgEw7n96mIHB/v7yqNUVNsYmxDGrEEGWjJ/EeLCApg/JQGAPy8/7NbLxg8fPkxlZSXTp09v8XvDhg2zJzcAkyZNwmazcfToUcLCwrj33nuZNWsW11xzDf/85z/JzMx0eswyguNKekyE3tPhxFpY9zzc+IbD7vq7A1kkZxTg721hwXRjT/Brza9n9Wf5/kw2puSwOz2fkfFd9A5JCPj+WbUref+r1a1YXE1AGIx/UB05Xvc8DJjjsFGcfacL+GyPWnL/w9WJhmtHcTF+Pq0PH+88zancMj7Yms59kxPafyfeAepoSmfzvvgVsv7+/q1+T1GUVv/vtNvfffddHnnkEVasWMHSpUv5wx/+wOrVqxk/fnz7Ym4HGcFxNdoozr6lkO2YkYrqWpt9M835U3sRGeLnkPvtbHFhAdw4shsA/1qbonM0QgCnd8Lhr9XGedONsYnlJZnwC3VD0OyDcPhLh93t31aqc+ZuHNGNod1DHXa/nSnI14vHZqgLHd5Yf4KK6ksYxTGZ1FJRZ1/akVD27dsXf39/1q5tPhdr4MCBJCcnU1pavxHpjz/+iNlspl+/fvbbRowYwcKFC9m8eTODBw/mf//7X/tfq3aQBMfVdBupfoJCgXV/cchdLtmeTlpuGRFBPjwwtZdD7lMvv7i8DxaziXVHz5OcUaB3OMKTKQqseVq9Pux2iDRWV9528e8C43+uXl/3gtqwsIP2ZhSwMSUHi9nEYzP7XfgHDOzmUd2JsfqRXVzJJ7vcc388Pz8/fvOb3/Dkk0/y3//+lxMnTrB161befvtt7rzzTvz8/Ljnnns4cOAAP/zwA7/85S+ZN28eUVFRpKamsnDhQrZs2cKpU6dYtWoVx44dc/o8HElwXNHlvwdMcOhLdT+bDqiutfH6enWC38OX9yHI17Wrlj3CA7l+uIziCAM48T2kbQSLD0xbqHc0HTf+IfC1wvnDcKjju42/uk7dsPK64bGGbSZ6sXy8zPys7sPh6+tOuO1u40899RS/+tWv+OMf/0hiYiJz584lOzubgIAAVq5cSV5eHmPGjOHmm29m+vTpvPLKKwAEBARw5MgRbrrpJvr168cDDzzAww8/zM9+5tx2CSalQ2vbXFNRURFWq5XCwkJCQkL0DufSLLsf9n8CfZPgzk8u+W4+232axz/eS0SQD5t+cwV+3i6wfPUCUnNKmf7iOmwKfPXwJJcd+hYu7p0rIX2zmhjMfk7vaBxj3QvqyHFEP3ho6yUvd085V8zMf2zAZILVj02lT2SwgwPtfBXVtUx+4XtySqr4281DuWV0XMvHVVSQmppKQkICfn6uOR3A2dp6jdrz/i0jOK5q2kK1P0XKKrXOfwkUReGNutGbn0xKcIvkBiAhQkZxhM5O71STG7N3fSdydzD+QfCzqls4HPjsku/m1XUnAJg9KNotkhsAP28L86eoozivrTtBrc3jxg4MRxIcVxXeG4bOVa9vfvmS7uKHo9kcPVdMkK8Xd43v4cDg9PfwFX0wm2DN4WwOnCnUOxzhaX78p/p16K0QokN/E2fxs8KEuoRt/fNQW9Puu0jPLeOrveqKoYem9XFkdLq7c3wPrP7enMwpZfl+5y+DFm2TBMeVTfiF+vXwV5Cf1u4ff63uU9Qd4+Kx+ns7MDD99eoaxLXD1DcWGcURnSr3hLpyCtxr9EYz7mfqpOPc45fUF+eNDeroxtR+XRnS3b0acgb5evHTSeoy8X//cBybjOLoShIcVxY9WO0sqthg6+vt+tFdp/LYkZaPt8Vk/4N0Nw9f0QeTCVYdOsexc8V6hyM8xZZXAAX6znLtlVOt8QuBMfer17e+1q4fzS6q4JOd6iqjX0zr7ejIDOHeiT0J8vXiSFYxa49k6x2OR5MEx9VNVPf6YM/7UF5w0T/22jp17s2NI7oTbXXPiW59IoNJGqh2Rl28OU3fYIRnKDkPe+q6Fk96RN9YnGn0fer8ooytcGbXRf/YmxtPUlVrY3SPLoxNcI297trLGuDNvAlqyf+V71M6tkeV6BBJcFxd7+kQORCqSmD3exf1I8fOFbPm8DlMJnjgMtfue3MhP6kbnfps92kKy6p1jka4ve3/Ufecih2p7jvlrkJiYPCN6vWLHD0uKKviw23pAPziij4u2bX4Yt03OQE/bzN7Txey81R+i8dI4tM6R702kuC4OpOpfi7Otjeg9sJv4trKqVkDo+nd1bX2nGqvcQlhJMaEUFFtY8mOdL3DEe6sqhR2vKlen/So6+051V5a47+Dn0HRhbcZWLojg7KqWhJjQpjWr6uTg9NXRJCvfSVn09Fjb291vmNZWVlnh+UyqqqqALBYOray17W7ugnVkFtgzTNQdAYOfq6u3GhFVmEFXyare7886KY18IZMJhM/mdiTJ5ft479bTnHf5AS8LJLXCyfY8wGU50OXBEi8Ru9onC92BMRPVJfD73gLpv+x1UNrbQofbDsFwL0Te7j16I3m7gk9WbIjg5UHssgqrLBPBbBYLISGhpKdrc7PCQgI8IjX42LZbDbOnz9PQEAAXl4dS1EkwXEHXr4w9gH44f+pExyH3NLqp8ePtqdTY1MY07MLw+NCOzdOnVw7PJbnVxzhTEE5aw6fY/bgGL1DEu6mtqZucjHqiOolNsBzOeN/riY4O9+FKU+AT8sdidcfyyYjrxyrvzfXDuvWyUHqY2BsCGN7hrE9LY//bU/n8QbbUURHRwPYkxzRmNlsJj4+vsOJX6ckOK+++ip/+9vfyMzMZNCgQSxatIgpU6a0eOy9997Le+81n0sycOBADh48CMDixYv5yU9+0uyY8vJyz+0MOeY+2PiiunVD2iZIaP76VtfWl2nmTejZyQHqx8/bwu1j4/j3Dyd458c0SXCE4x1fDQXp6vLp4XfqHU3nGXA1hMarz33/xzDq3hYP++8WdfTm1tHd8ffxkOQPuHtiDzXB2ZbOw5f3wcdLHT02mUzExMQQGRlJdbXMDWzKx8cHswN2rHd6grN06VIWLFjAq6++yqRJk3jjjTe48sorOXToEPHx8c2O/+c//8nzzz9v/3dNTQ3Dhg3jlltuaXRcSEgIR48ebXSbxyY3AAFhMPwO2Pk2bPl3iwnOmkPnOFdUSUSQD7MHResQpH7mje/J6+tPsj01j4NnCxkU6179N4TOdr6jfh1xV6ujGG7JbIFxD8LK36lLxkfe02z0OC2nlHVHz2My4XYNRS9k1qBookJ8OVdUyXcHMrlueOPRK4vF0uF5JqJ1Tp+M8NJLL3Hfffdx//33k5iYyKJFi4iLi+O111run2C1WomOjrZfdu7cSX5+frMRG5PJ1Og4bcjPo41/SP2ashIKm+9oq9XAbx0dZ/8k4SmirX5cOVj9HVn8Y5q+wQj3kn8KUlar10c1H1l2eyPuAp8gOH9E3WC0iQ+2quedy/p1pUd4YGdHpytvi5k7x6lJ3XvSqqLTOfVdrqqqil27dpGUlNTo9qSkJDZv3nxR9/H2228zY8YMevRonPmXlJTQo0cPunfvzpw5c9izZ0+r91FZWUlRUVGji1uK6AM9p6iN//Z80OhbJ8+X8OPxXEwmuH1s85EzT6AtGf9y71lySyp1jka4jd3vAQr0mqZuoeJp/KxqkgOwrfGS8fKqWj7emQHA3RM8a/RGc9vYOLwtJnanF7D/tGwb05mcmuDk5ORQW1tLVFRUo9ujoqLIysq64M9nZmby3Xffcf/99ze6fcCAASxevJivvvqKjz76CD8/PyZNmkRKSsst+Z977jmsVqv9EhfX8i6vbkGrge/+L9hq7Tdr/Scu7x9JXJgHDaE3MDI+lKHdrVTV2PhouywZFw5QWw2731eve+LojWbsA+rX42sajR5/tfcMRRU1xIcFcFm/SJ2C01dksB9XD1Hn/b23JU3fYDxMp9Qpms6EVhTlomZHL168mNDQUK6//vpGt48fP5677rqLYcOGMWXKFD7++GP69evHyy+3vOnkwoULKSwstF8yMjIu+bkY3oA54B+mLhk/vgaAiupaPt2lnnTmeVgNvCGTycS9E3sCsGRHhuwTIzruyLdQmg1BUeqEW08V3ht6TFZHj5P/B6jn+fc2q+Wpu8bHYzF77lLou+vOO1/tPUteaZW+wXgQpyY4ERERWCyWZqM12dnZzUZ1mlIUhXfeeYd58+bh4+PT5rFms5kxY8a0OoLj6+tLSEhIo4vb8vZTJxsD7FoMwNd7z1JYXk33Lv5MdfMGWxdy1ZAYgv28OJ1fzuYTuXqHI1ydfXLxPLC414a17TbybvXr7vfBZmN3ej6HMovw9TJz62g3HjW/CCPiQhnSTR09XrrDjT9gG4xTExwfHx9GjRrF6tWrG92+evVqJk6c2ObPrl+/nuPHj3Pfffdd8HEURSE5OZmYGFn+C6grGQCOrYCis/ZJfneM8+xPUaAuGb9uuLrL+NKdcqIRHZB7AlLXAyYYdY/e0ehv4LXqfJzCdEhdx/t1S8OvGx5LaEDbH1Ldnclksu9PtXRHumzT0EmcXqJ6/PHHeeutt3jnnXc4fPgwjz32GOnp6Tz44IOAWj66++67m/3c22+/zbhx4xg8eHCz7z3zzDOsXLmSkydPkpyczH333UdycrL9Pj1e137qPjiKjXPr32Lv6UK8LSaP/xSlmTtanWS98mAWBWUyXCwu0a531a99Z6q9YDydtz8MnQtA1Y7FfHdAHbn3tKXhrbl6SAwBPhbScsta3Z9KOJbTE5y5c+eyaNEinn32WYYPH86GDRtYvny5fVVUZmYm6emNJ3wWFhaybNmyVkdvCgoKeOCBB0hMTCQpKYkzZ86wYcMGxo4d6+yn4zrqRnF89n2AGRtXDo4hIshX56CMYXC3EBJjQqiqsfFl8oX30BGimeqK+l3DR/9U31iMpK5MZTn6LQE1BfSPCmZIN+k5BRDo68WcoWqV4WMpU3UKk+KBY2VFRUVYrVYKCwvddz5OdTnKiwMwVRRwb9WTPHj/g4zvFa53VIax+MdUnv76EANjQlj+aMtdtYVo1b6P4bP5ENIdFuzznK0ZLsZ/psHZPfyp+i5iZv+K+6f00jsiw9iRlsctr28hwMfCjt/PINBXdktqr/a8f3tWtzdP4u3PyVh1w7+f+K9nbM8wnQMylutHdMPHy8yhzCIOnJHeFKKddv9X/Trybklumsjuq5ap5lp+4LphsTpHYyyje3QhISKQsqpalu/P1DsctycJjht7s0wdmZhSuxNz6TmdozGW0AAfZtVtVyGrGkS7FKRD2kb1+vDb9Y3FgD4oGUOZ4ks/8xm6Fu7TOxxDMZlM3DyqOwCf7GrebV44liQ4biqrsIKlp4LYaeuHmVrY+5HeIRnOraPVE80XyWeoqK69wNFC1Nn3sfq15xSZXNxETa2NJfsK+LZ2nHrD7uYbJ3u6G0d2w2yC7al5nMot1TsctyYJjpv6fM8ZFAV2hs5Wb9j3ib4BGdCk3hF0C/WnuKKGlQcv3FlbCBQF9i5Rrw+7Td9YDGjj8RyyiytZ7lO3Pc+Bz6DCTbfGuUQxVn8m91X7kX0qozhOJQmOG1IUhWW71T+cruNuBYsPZB+ErP06R2YsZrOJW+pGcaRMJS7K2d2QmwJe/pB4rd7RGM6nO9XzTs/hl0NEP6gug0Nf6hyV8Wijx5/uOk2tdFR3Gklw3NC+04Uczy7B18vMzFEDoJ82irNU38AM6JbRcZhMsPlELhl5ZXqHI4xOG71JnAN+broC8xIVlFWx+pA61+/m0XH1I1z7P9YxKmOakRiF1d+bzMIKfjyeo3c4bksSHDekjd7MGhRNiJ+3vfkW+z9ttAGngG6h/kzqHQHAl8lndI5GGFpNlfo3BFKeasHXe89SVWtjYEwIg2KtMOQW9RupG6FI+k011LCjukw2dh5JcNxMZU0tX+1VTyY31c3Wp+9M8AuF4kxI3aBfcAalnWi+SD4rLdRF646vhvI8CIqGhGl6R2M42hu1tkqI0HiInwAo9YmhsLtllNpZfuXBLArLqnWOxj1JguNmfjiSTUFZNVEhvkzuo45M4OULg29Ur++T4eKmZg2OxsfLzPHsEg5nFusdjjAqbSXikJvBIg3aGjp2rph9dVvCXD+iW/03tFEcKVM1M7hbCP2jgqmqsbHioPTEcQZJcNzMp7vUMsv1I7o13lhTK1Md/gqqZK5JQyF+3kwfEAlImUq0oiwPjq1Urw+T3jdNfbFH/buZ1j+SsMAGG2sOugHMXuoCh+wjOkVnTCaTiWvrRo+1UXfhWJLguJHckkrWHc0G4KaR3Rt/M24chPaAqhI4ulyH6IztugYnGpusahBNHfwcaqsgaghEN98A2JMpisLX+9Q3aO3vyC4gDPrMVK/LKE4z19Z1et5yIpfs4gqdo3E/kuC4keX7M6mxKQzuFkK/qODG3zSZ6kdxZDVVM9P6RxLs50VmYQU70vL0DkcYjfS+adXe04Vk5JUT4GNh+oCo5gcM1cpUn6h9hIRdXFgAI+JDsSnw7T4pUzmaJDhu5Ou6P5BrW9v/RUtwjq+FkuxOiso1+HlbuHKwunXDlzJcLBrKPQGnt4PJXD+nRNh9laz+vcwcGIW/Twv7cvW7EnyC1C0uMrZ1cnTGp52vpUzleJLguImsBiMPVw9tJcGJ6APdRoFSq3YYFY1cN1ydHLl8fyZVNTadoxGGcfBz9WuvaRDcwgiFB6u1KXxTV566prXzjk9AfVNEWeTQzNVDYjCbYE96gfTicjBJcNzEt/szURQY1aML3UL9Wz/QXqZa0jmBuZDxvcLpGuxLQVk1G46d1zscYRRagjPoRn3jMKAdaXlkF1cS4ufFlH4RrR+olakOfq72ExJ2kSF+jO8VDmCfyyQcQxIcN6F9ipozNKbtAwfdqA61n90DeamdEJnrsJhN9k+hUqYSAJw/BucOqCuBBlytdzSGo5VVrhwcg69XC+UpTcJlEBSl9hE6sbaTonMd9jJVspx3HEkSHDdwOr+MPekFmExw1ZALJDhBXdVdkAEOfeH02FyNtgpk9aEsSitrdI5G6E4bvel9hboiSNhV19r4br867++a1ub9acwWGHyTel3KVM1cOTgGb4uJI1nFpJyTXlyOIgmOG9Bm349LCCMqxO/CPzDoevXrwS+cFpOrGtrdSkJEIBXVNvu+OsKD2ctTN+gbhwH9eDyH/LJqIoJ8GN/rIpI/bYL2sRXSi6sJa4A3l/VTdxiXycaOIwmOG/jaXp66wKcoTeK1apkqM1nKVE2YTCb7cPEX0vTPs2UfhvOHweID/a/SOxrD0d6IrxoSg5flIt5KYkeo2zdUl6nbXohGrmmwmkq2jHEMSXBcXFpOKQfOFGExm+zLnC8oMELKVG3QTjQ/Hs+hsFz2iPFY9vLUdPAP1TUUo6mormXVQXWEs9W2FE2ZTDDwevW6jB43M3NgFP7eFk7llrHvdKHe4bgFSXBcnDa5eGLvcMKDfC/+B7UhdznRNNMnMoh+UUFU1yqsPSxlKo+kKFKeasO6o9mUVNYQa/VjZHyXi/9BLcE5thKqy50Sm6sK8PFixkC1DYGUqRxDEhwX903d/JtWe1C0JvEaMFmkTNWKKwerk7WX78/SORKhi3MHIecYWHyh/5V6R2M4X+9VzztzhsVibrjn3YV0GwnWOKguVRuOikauqVsF+93+TClTOYAkOC4s5VwxR7KK8baYmDXoIstTmsAI6DlZvS5lqmauHKK+nhtSzlMiq6k8jzZ603cm+IXoG4vBlFfVsvaIOrLZ7g9WJhMMvE69LuedZqb260qgj4WzhRXslTJVh0mC48K0rRmm9O2KNcC7/XcgZapW9Y8KpldEIFU1Nr4/IttaeBRFgYN1nb6lPNXM+mPnqai20b2LP4O7XULypyU4R1dAtWww2ZCft4XLB0QCsOKAjB53lCQ4Lmx5XQ+KCzb3a42UqVplMpmYXTdpW+v1ITxE1j7IOwleftBvtt7RGM6KA+rfw+xB0ZhM7ShPabqNhuBYqCqGE987ODrXp513VhyQMlVHSYLjoo5nl3A8uwRvi8k+Ma3dAiMgQVZTtUZrmrju6HnKqqRM5THs5akk8A3SNxaDqaqxsfawOqI5+2JXbTZlNjcoU33poMjcx+X9I/H1MpOWW8aRLGn61xGS4LiolQfV4cuJvSMI8buE8pRGlm22alBsCHFh/pRX17L+qOxN5REUpf5NV8pTzWw+kUNxZQ1dg33bt3qqKXuZ6juoqXRMcG4i0NeLqXVN/76TMlWHSILjorQEp92Ti5uSMlWrTCZT/WoqOdF4huzDannK4quO4IhGtHkhswZFtW/1VFNx4yAoGioL4eQ6xwTnRmYPqi9TiUsnCY4LOlNQzr7ThZhManOoDmlUppLh4qa05onfHz5HRXWtztEIpzvyjfq19+VSnmqi1qawqm77ktmDLnHen8ZshoHXqtflvNPMjMQovMwmjp0r4cT5Er3DcVmS4LigVXWjN6N7dKFrcDua+7Umse5Ec+Tbjt+XmxkeF0qs1Y/Sqlo2puToHY5wtsNfq18HzNE3DgPakZZHXmkVoQHejLuYvacuRCtTHfkGaqo6fn9uxBrgzcQ+EYCspuoISXBckMPKUxptn53TO6BY/pgaMplMzNJWU8lwsXvLP6WuoDKZpblfC7Q32hmJUXhfzN5TFxI/AQIjoaIQUtd3/P7czJX21VRyTr5UnZLgvPrqqyQkJODn58eoUaPYuHFjq8euW7cOk8nU7HLkyJFGxy1btoyBAwfi6+vLwIED+fzzz539NAwhr7SK7al5gAMTnJAYdekmijrpTzSiraZafegcVTU2naMRTnN0ufo1foJauhV2Nptif6Od7ajzjtkCiXUjZVppUNjNHBiF2QT7zxSSkSe7r18Kpyc4S5cuZcGCBfz+979nz549TJkyhSuvvJL09PQ2f+7o0aNkZmbaL3379rV/b8uWLcydO5d58+axd+9e5s2bx6233sq2bduc/XR0t+bQOWyKtsInwHF3POBq9auUqZoZFa+WAosrath8QspUbutw3ZuslKea2XemkKyiCgJ9LEzu68DkTzvvHP0ObPLhoaGIIF/G9FRLgdqovWgfpyc4L730Evfddx/3338/iYmJLFq0iLi4OF577bU2fy4yMpLo6Gj7xWKx2L+3aNEiZs6cycKFCxkwYAALFy5k+vTpLFq0yMnPRn8OL09ptJN66nqoKHLsfbs4s9lEUt1kbm2SpXAzpTmQvlm9rr3pCjutPHv5gEj8vC0XOLodek4Bn2AoOQdndzvuft2ElKk6xqkJTlVVFbt27SIpqfFyy6SkJDZv3tzmz44YMYKYmBimT5/ODz/80Oh7W7ZsaXafs2bNavU+KysrKSoqanRxRSWVNfaJrpfcZKs1XftBeF+orYLjaxx7325AW6225tA5bDbpLup2jn4Hig2ih0KXHnpHYyiKorBSK085+rzj5Qt9Z6jXpUzVjDb/b1d6PtlFsq1Fezk1wcnJyaG2tpaoqMZLmaOiosjKajkjjYmJ4T//+Q/Lli3js88+o3///kyfPp0NGzbYj8nKymrXfT733HNYrVb7JS4uroPPTB/rjmZTVWsjISKQvpFOWMIqZapWTegdTpCvF9nFlew/I5vguR3tzTXxGn3jMKCj54pJyy3Dx8vM5f0jHf8A2ujxkeWOv28XF2P1Z3hcKIoCqw/L6HF7dcok46b7lSiK0uoeJv3792f+/PmMHDmSCRMm8Oqrr3L11Vfz97///ZLvc+HChRQWFtovGRkZHXg2+ll5UP0Fn3Wpe8BciHaiSVklyzab8PWycFldd9HVUqZyL5XFcKJulFjKU82sPKD+vk/tG0Ggr5fjH6DPDDB7Qc5RyD3h+Pt3cQ1Hj0X7ODXBiYiIwGKxNBtZyc7ObjYC05bx48eTkpJi/3d0dHS77tPX15eQkJBGF1dTWVPLD3W7Ws8a1MHmfq3pNgqCoqCyCNI2XPh4D6OdaCTBcTPH10JtJXRJgMiBekdjOGvqRg6SBjq4PKXxD4Wek9XrMnrcjHbe+fFELqWVsideezg1wfHx8WHUqFGsXr260e2rV69m4sSJF30/e/bsISamvnPmhAkTmt3nqlWr2nWfrmbz8VxKKmuICvFlWPdQ5zyI2VzfE0dONM1M698Vi9nE0XPFpOfKsk23YS9PzQFnjIy6sKzCCvafUbumXz7ACeUpTX8pj7emb2QQ8WEBVNXYpNloOzm9RPX444/z1ltv8c4773D48GEee+wx0tPTefDBBwG1fHT33Xfbj1+0aBFffPEFKSkpHDx4kIULF7Js2TIefvhh+zGPPvooq1at4oUXXuDIkSO88MILrFmzhgULFjj76ehGq7/OHNjBPWAupGE9XJZtNhIa4MPYumWbqw7Jqga3UFMFx1ap1wfI/Jum1h5Rzzsj4kId0zW9NQPqPlhlbIMS2di2IZPJxIzEujKVzMNpF6cnOHPnzmXRokU8++yzDB8+nA0bNrB8+XJ69FBXKmRmZjbqiVNVVcUTTzzB0KFDmTJlCps2beLbb7/lxhtvtB8zceJElixZwrvvvsvQoUNZvHgxS5cuZdy4cc5+OrpQFIXvD6vlKe0X3WkStGWbWbJsswX2ericaNxD2kZ1w8fASOg+Ru9oDEeb9zGjo3veXYi1O8QMAxQ4tsK5j+WCZgxUR8++P5JNrazivGhOmDHW3EMPPcRDDz3U4vcWL17c6N9PPvkkTz755AXv8+abb+bmm292RHiGd/BsEVlFFQT4WBjfK9y5D+blC31nwsHP1KH77qOd+3guZubAKJ795hA70vIpKKsiNMBH75BER2hvpv1nqyVaYVdWVcOPJ3KBTvhgBWqZKnOv2lF65DznP54LGdMzjBA/L/JKq9iTns/ong7YC8wDyF+0C9BGC6b0jXBsk63WaCtJDktfiqbiwgIYEB1MrU3h+7pJ38JFKQocrUtw+sneU01tTMmhqsZGfFiAc9pSNKWVqU58D1Wlzn88F+JtMXNF3RwoWS5+8STBcQFr68pT0zvjUxSoIzhmb8hNgZzjnfOYLkRWU7mJ7ENQmA5eftBrmt7RGI69PJUY5Zy2FE1FDYbQeKipqF+2L+xmyHLxdpMEx+AarmK4wpmrGBrys0KPuhVpKSs75zFdiJbgrD92norqWp2jEZdMK08lXAY+DtzXzQ00HKHU5n84nclUv5rqqDT9a2pqv654W0ycOF/KyfMleofjEiTBMThtFcPwuFAigpy4iqGpfrPVrzLhr5kh3axEhfhSVlXLlro5CsIF2ctTs/SNw4CSM/LJLa0i2M/LvuFjp9DKVEe/A5t8eGgoxM/bPgdTG9UXbZMEx+DWdtbqqaa0k/6pzVAhWxM01HDZptTDXVRpDpzeoV7Xknlht6buvHN5/0i8LZ34NhE/UR1BLs+D0zs773FdhJx32kcSHAMrr6rlx+NqY6fpiZ00TKwJ761uvmmrUSf9iUYatk9XFFm26XJSVgGKurmmtZve0RhOpy0Pb8ripW7dAFIeb4H2PrAzLY/8UtlO50IkwTGwTcdzqKyx0b2LP/2jgjs/gP5amUpONE1N6B1OgI+F7OJKDp51zd3pPdrR79SvMnrTTFpOKSnZJXiZTfb91zpV37rRYznvNNO9SwCJMSHYFPjhqJSpLkQSHANbe7iTVzE0pZ38U1ZJPbwJXy8Lk/pEAMhycVdTU1U/KtlfEpymtLYUYxPCsPp7d34AfWaAyQznDkCBa26M7Ewz60ZxZBXnhUmCY1A2m8LaI9ry8E4uT2nixqn18LJcOLNLnxgMTFvVJgmOizm1CapK1I1lY0boHY3h6DbvTxMYXt9VOmWVPjEYmFY21PoUidZJgmNQ+88Ucr64kiBfL8YlOLl7cWss3vX1cFlN1czl/dUEZ+/pAnJLKnWORlw0bfVU3yTpXtxEYXk129PyAB0THKhf5CBlqmYGx1qJCPKlpLKGHXX/V6Jl8tdtUFp5amq/CHy8dPxv6ifzcFoTbfVjYEwIigLrjsoGgS5BabDXUX/pXtzUxpTz1NoU+kQGER+uY28gbR5O6nqoKtMvDgMym01M66/OjfpBRo/bJAmOQWnLNKcP0PFTFEg9/AK08uH3MuHPNZw/AgWnwOIr3Ytb8MMRNVHvtKairYkaBCHd1a7GaRv1jcWA7OVxOe+0SRIcA8oqrOBQZhEmE/ZMXTcBYepcHJBlmy24vO5Es+HYeaprpR5ueNrqqYSp4BOobywGY7MprD+mvmHqft4xmaBfknpdRo+bmdw3Ai+ziZPnSzmVK/t2tUYSHANaV5eVD48LJbwzuxe3RquHH5V5OE0N6x5KWKAPxRU17DqVr3c44kK0N0tZPdXM/jOF5JRUEeTrxegeBtitumF5XHpNNRLi583onl0AKVO1RRIcA9L6G2iTWHWnnWhSN8guv01YzCam9ZN6uEsoy4PT29XrfWV7hqa0886UvjrP+9P0nKJuhFp0Wt0YVTRSX6aS+X+tMcBvsWioqsbGphS1e7FhEpyuA9Rdfmsr4eR6vaMxHK1MtVYSHGM78T0oNogcCKFxekdjOFqCbpjzjk+AuhEqyCrOFmj/T1tP5lJWVaNzNMYkCY7B7EzLo7SqloggXwbFhugdjspkks032zC1X1csZhPHs0vIyJMVH4aVslr9qrU+EHbniyvZe1rdc073+TcN2efhSD+cpvpEBtG9iz9VNTY2H5dNf1siCY7BrDumDjdO698Vs1mH7sWt6Vt3ojm+RurhTVj9vRnVQ62HS9M/g7LZ1N9dqP9dFnYb6s47g7uFEBnip3M0DWilxNPb1RKjsDOZTPZRHFlN1TJJcAxGGyY21KcogJ6T6+rhZyD7sN7RGI50NTa4zD1QlgM+wRA/Xu9oDOd7o83704TGQeQgtbSojcAJO+28s+5Itmz62wJJcAwkI6+MlOwSLGYTU/oYLMHx9lcn/QEclxNNU9qJZovUw41Je3PsPU3t0C3sampt9hGcaUZLcKC+TCXnnWYm9A7H18vM2cIKjp4r1jscw5EEx0C08tSo+C5YAwx4Eu47U/0qn6Sa6Sv1cGPTfmelPNXMrlP5FFfU0CXAm+FxoXqH01yfuvPO8bWy6W8Tft4WJvZWt/KR0ePmJMExkHVaeWqAwUZvNNrkzPStUFGkbywGYzKZ6oeLj8mJxlBKc+o3i5UJxs38ULfM+LK6yfKGEzcWfEOgPA/O7tE7GsOpL1PJcvGmJMExiIrqWn48YbDl4U2F94awXmCrVveIEY1cVtcPZ93R81IPN5IT3wMKRA2BkFi9ozEcrbHo5Xpvz9Aai3f9thoyetyMVlbclZ5PYVm1ztEYiyQ4BrEtNY+KahvRIX4MiA7WO5zW9ZEyVWsm9A7Hx2LmdH45J3OkIaJhpNQtMdZKrMLuTEE5R7KKMZtgal+DjhxD/f+dthJO2MWFBdA3Moham8L6FBnFaUgSHIOwN9ka0BWTyYDDxBpZLt6qAB8vxiaoLe5ld3GDsNU2WB4uCU5T2ujNiPgudAn00TmaNmilxTO7oFTmuDXVcE88UU8SHIPQTjSGXMXQUM9Jsly8Ddry/vVyojGGM7uhPB98rdB9rN7RGI6WiF9utLYUTYXEqsvFUepKjqIhrTy+/th5bDb54KmRBMcAUnNKScstw9tiYlKfCL3DaZssF2+TdqLZejKX8ipZ8aE7rTzV5wqweOkbi8GoK/7UeX+X9TP4ByuAvnWjOFKmamZ0zy74e1s4X1zJ4SxZAKKRBMcAtPLU2IQwgnxd4CQsy8Vb1ScyiG6h6nLxrakylK47LQnvI+Wppnadyqe0qpbwQB/jbAvTlj4N5uHYbPrGYjC+XvXLxWX0uJ4kOAag/UJqn/4Nz75cfIssF2/CZDIxVRsulnk4+irJrl9WLMvDm9HOO1P7GWxbmNbEj1c7UZflQGay3tEYzmX95bzTlCQ4OquormVb3Sd9lxgmhrrl4r3BViPLxVsg83AM4vha9WvMMAiO0jcWA3K5D1YWb+hVt7u4lKma0f4f1caNslwcJMHR3fYGy8P7RQXpHc7FkzJVqyb2DsfLbCI1p5RTubJcXDfam6CUp5o5V1TB4cwiTCaY0tfg8/4a6iPzcFrTIzyQhIhAamwKm09IeRw6KcF59dVXSUhIwM/Pj1GjRrFx48ZWj/3ss8+YOXMmXbt2JSQkhAkTJrBy5cpGxyxevBiTydTsUlFR4eyn4nANP0UZenl4Uw3r4bJcvJFgv/rdxWUURye22vrVNn2m6xuLAWnLiYd0sxIe5KtzNO2gfbA6vUN2F29Bw9VUohMSnKVLl7JgwQJ+//vfs2fPHqZMmcKVV15Jenp6i8dv2LCBmTNnsnz5cnbt2sXll1/ONddcw549jVt0h4SEkJmZ2eji5+fn7KfjcBsa1MFdSs9J4OUvy8VboS33l344OslMVlv7+4ZA9zF6R2M4Llee0li7Q9dEdXfxkz/oHY3hXNZg/p90U++EBOell17ivvvu4/777ycxMZFFixYRFxfHa6+91uLxixYt4sknn2TMmDH07duXv/zlL/Tt25evv/660XEmk4no6OhGF1dztqCclOwSzCaYbPTl4U15+6tJDsCJtfrGYkDaiWbLiVwqqmW5eKc7Xjd6kzBVdg9votamsMm+PNzFEhyoXy6eImWqpsb1CsPHy8yZgnJOnJfyuFMTnKqqKnbt2kVSUuMdfJOSkti8efNF3YfNZqO4uJiwsLBGt5eUlNCjRw+6d+/OnDlzmo3wNFRZWUlRUVGjixFoozcjjLp7+IX0rhv6Py4JTlOJMcFEBvtSXl3LjjQZSu909vk3snqqqX2nCygoqybYz8uYu4dfiCwXb1WAjxfj6rqpS5nKyQlOTk4OtbW1REU1XsEQFRVFVlbWRd3Hiy++SGlpKbfeeqv9tgEDBrB48WK++uorPvroI/z8/Jg0aRIpKSkt3sdzzz2H1Wq1X+Li4i79STmQfZmmkfeAaYs2t+HUZqgq0zcWgzGZTI2Gi0UnKi9Q52iAzL9pgXbemdI3Ai+LC64ziR8P3oFQmg3nDugdjeHUb/qbrXMk+uuU3+6mk2cVRbmoCbUfffQRTz/9NEuXLiUysn4J9fjx47nrrrsYNmwYU6ZM4eOPP6Zfv368/PLLLd7PwoULKSwstF8yMjI69oQcoKbWVj9MbPQ26a2J6Ach3aG2Uk1yRCP2eTjySapzpa4HpRbC+0JovN7RGI7Lzr/RePlCQl03dSmPN6P9v25LzfP4bupOTXAiIiKwWCzNRmuys7Objeo0tXTpUu677z4+/vhjZsxoe5jZbDYzZsyYVkdwfH19CQkJaXTRW3JGAcUVNXQJ8GZIN6ve4Vwak6n+E7Is22xmcp8IzCY4nl3CmYJyvcPxHFrJVMpTzeSXVrE3owBwwYUNDUl5vFV9IoOItfpJN3WcnOD4+PgwatQoVq9u3Ctl9erVTJw4sdWf++ijj7j33nv53//+x9VXX33Bx1EUheTkZGJiYjocc2epHybuisUVuoi2Rktw5JNUM9YAb/sch40yitM5FEWWh7dh0/EcbAr0jwomxuqvdziXTvu/Td8KlSX6xmIwJpNJuhrXcXqJ6vHHH+ett97inXfe4fDhwzz22GOkp6fz4IMPAmr56O6777Yf/9FHH3H33Xfz4osvMn78eLKyssjKyqKwsNB+zDPPPMPKlSs5efIkycnJ3HfffSQnJ9vv0xWsd9Xl4U0lXAYmC+QcgwL9S39Go/3/bkjx7BNNp8k5BoUZYPGFHpP0jsZw7OUpVy2La8J6QWgPsFVD2ia9ozEcrSu+p080dnqCM3fuXBYtWsSzzz7L8OHD2bBhA8uXL6dHjx4AZGZmNuqJ88Ybb1BTU8MvfvELYmJi7JdHH33UfkxBQQEPPPAAiYmJJCUlcebMGTZs2MDYsWOd/XQcIrekkv1n1IRtqit1EW2Jfyh0H61el1GcZqbUTSDflJJDTa2s+HA6rWTRYyL4BOgbi8EoiuL68280Dcvjct5pZmKfcCx13dQz8jx3AUinbF390EMP8dBDD7X4vcWLFzf697p16y54f//4xz/4xz/+4YDI9LHpeA6KAgNjQogMcb3mhM30ng4Z29Q3l1H36h2NoQzrbiXEz4uiihr2nSlkZHwXvUNyb/bl4VKeaupwZjHniyvx97Ywuqcb/B72ng4735F5OC0I8fNmZHwoO9Ly2ZBynjvH9dA7JF244BpB16fVRV2+PKXR3kxOrofaGn1jMRgvi5nJdaN0Gzx8uNjpqsvh1I/qdZlg3MzGujLp+F5h+HpZdI7GARKmqOXxvBOQn6Z3NIajjR5vPJajcyT6kQSnk9lsChtSXLiLaEtiR4B/F6gshDO79I7GcLQ+R5LgONmpzVBTAcGx0HWA3tEYzsa6847bfLDys0Jc3bQEGcVpRvt//vGE55bHJcHpZIezisgpqSTQx2LfkNHlmS3Qa5p6XZaLNzOl7kSTnFFAYVm1ztG4Mfvy8OnqHA1hV15Vy/a6jtpTXLWxaEu05eLayjlhN6SbldAAb4orath7ukDvcHQhCU4n0z5FTegdjo+XG738vWXCX2u6hfrTu2sgNgU2n/Dc4WKnO9EgwRGNbEvNparGRqzVj95dA/UOx3H6XKF+PbkeauXDQ0MWs4lJdXscrvfQMpUbvcO6Bq0O7lafoqD+TeXMbiiTvZeakuXiTlZ4Gs4fAZO5fjRR2G04Vl+eupgu8i4jZjj4h0FVMZzeqXc0hqOt0t3ooecdSXA6UVlVDTtS8wF1Hxi3EhILkQMBBU7+oHc0hmNPcI7loCiKztG4oRN1v3PdRqnzwUQjbvvBymyB3per12X0uBnt/3uvh5bHJcHpRNtS86iqtdEt1J+ECDcaJtb0rhsuPi718KbGJYThYzFzpqCckzmleofjfrQ5GNrvoLA7W1BOSnYJZhNM6hOudziOJ9s2tCo21J8+kUHYFHWysaeRBKcTbXTXYWJNnwYT/mSUopEAHy/GJKgjC7KaysFstfWjhpLgNLOpbt7f0O6hhAb46ByNE2gjOGf3QKln773UEk9exSkJTifSholdvntxa+IngJcfFJ+F80f1jsZwPPlE41SZe6E8H3xD1BKVaGR9ipv13WpKyuNtmtKvvg+Xp5XHJcHpJA2HiSf2dtMEx9tfbZEPsmyzBdobzNaTeVTW1OocjRvRftcSpoLFW99YDKbWpvDj8bqRY3f9YAX1I3dy3mlmfEI4PhYzZwsrOHHes8rjkuB0Em2YeFhcKNYANz4Jy4mmVQOig+ka7Et5dS270vL1Dsd9aBOMtVKFsDtwppCCsmqCfb0YVrezvVuyl8d/kPJ4E/4+Fo8tj0uC00k2uOsqhqa0BCdtE9RU6huLwZhMJvvqufUeumzT4SqL1X3QQObftEB7Q5vYJxxvixuf7qU83iatPO5py8Xd+DfeOGptCps8YZgY1Fp4UBTUlEP6Vr2jMRxtew5tRE90UNqPYKuGLj0hrJfe0RiO1ljU7T9YSXm8Tdr/v6eVxyXB6QQNh4mHu/MwMagt8qVM1Sqts+jBs+qWHaKD7MvDpXtxU8UV1exOV0uhbrPvXVt6af1w5LzTVGJMMBFBnlcelwSnE2jDghP7hOPlzsPEGklwWhUR5MvAmBAA++RP0QHS/6ZVW07kUmNT6BkeQFxYgN7hOJ+Ux1tlMpns1QNPKo97wLut/jZ4yjCxRmuVn7UPSjznj+liacs2N0qZqmMK0iE3BUwWSJiidzSG4zHlKU3UIAiMlPJ4K7TzjieVxyXBcbKSyhp2n1KHBKd6yokmKBKih6jXT67TNRQjajjhz9P6UjiUtnqq+xjws+obiwHVb8/g5vP+NA3L49IPpxlPLI9LguNk2jBxj/AA4sM9YJhYI2WqVo3q0QVfLzPniipJyS7ROxzXpe09JOWpZjLyykjLLcNiNjGhtxtuz9AaOe+0KjLYj0QPK49LguNkHvcpStNwwp+MUjTi521hXC/1TcfT+lI4jK22fnRQEpxmtPLUyPhQgv3cuO9WU1p5PHMvlHrGm3h7TOnrWeVxSXCczOPq4BqtL0VJFmQf1jsaw9Em/G3ykE9SDnd2D1QUqqWp2BF6R2M42geryX087LwTHAVRg9XrUh5vpj7B8YzyuCQ4TpSRV0ZqTqnnDRMDePtBj0nqdRkubmZy3Ylm68lcj+pL4TD27RkuA4uXvrEYTMPtGbSJpR6ltywXb82YnmH28vhxDyiPS4LjRNqn8+FxoYR40jCxRurhreofpW7bUFFt86i+FA4j2zO0at/pAooqagjx82JoNw+cfG0/78i2DU35eVsYmxAG1K/udWeS4DjRJnt5ygM/RUH9iebUj1BdoW8sBtNw24aNUqZqn8piOL1dvS7zb5rRyuITe0d4Rt+tpmTbhjY1LFO5Ow/87e8cDbdn8NgEJzIRgmOgpgLSt+gdjeF46v4wHZa2CWw16tYMXXrqHY3h2D9YeWJ5CmTbhgvQ5oNu84BtGyTBcZIDZwopLK/bxbd7qN7h6MNkql9NJX0pmtH6Uhw4U0Suh/SlcAjtTauXlKeaarg9wxRPm2DckGzb0KoB0Q22bTjl3uVxSXCcRPtUPqG3h2zP0BqZ8NeqrsG+9r4UspqqHezzb6Q81dTWk3me2XerKdm2oVUNy+Pu3tXYg995ncu+PNwTNrlri33bhv2ybUMLpnrIicZhCjJke4Y2bPLUvltNRQ2CoCjZtqEVntIPRxIcJyitrGkwTOzhJ5qgSIiSbRtaM8U+DyfHI/pSdJhW6uw+WrZnaIH2huVx/W+aMpnqP1xJebyZyVp5/GwheaVVOkfjPJLgOMG21FyqaxXiwvzp4cnDxJre09SvcqJpZnRPdduGrKIKj+hL0WEy/6ZVp/PLOOmpfbda0nC5uGgkMsSPAdHBKIp7b9sgCY4TbDhW/ynKZDLpHI0BSF+KVjXsS+Huw8UdJtsztEkrcw7rbsXq74F9t5pqtG1Drq6hGJEnLBeXBMcJtAmjUz29Dq6JnwAWX+lL0QpPONE4ROZeKM8H3xDoNkrvaAxn43EP3RamNcHREDkIUCB1nd7RGM5kDyiPd0qC8+qrr5KQkICfnx+jRo1i48aNbR6/fv16Ro0ahZ+fH7169eL1119vdsyyZcsYOHAgvr6+DBw4kM8//9xZ4bdLZmE5x7NLMJvURluCxn0ppEzVjPaGtNUD+lJ0iPa7kzBVtmdoouH2DFM9tf9NS2QVZ6vG9gzDx8tMZmEFJ867Z3nc6QnO0qVLWbBgAb///e/Zs2cPU6ZM4corryQ9Pb3F41NTU7nqqquYMmUKe/bs4Xe/+x2PPPIIy5Ytsx+zZcsW5s6dy7x589i7dy/z5s3j1ltvZdu2bc5+OheklRmGdg/FGiDDxHZyomlVw74Uu08V6B2OcWlzKbTSg7A7cKaQgjIP77vVEvt5Z52Ux5vw97EwpmcXwH3L405PcF566SXuu+8+7r//fhITE1m0aBFxcXG89tprLR7/+uuvEx8fz6JFi0hMTOT+++/npz/9KX//+9/txyxatIiZM2eycOFCBgwYwMKFC5k+fTqLFi1y9tO5oI2evj1Da6QvRatMJhOT+6iTQjcdlzJVi6pK65f7yvybZrSyuMf33WoqfiJYfKDoNOQe1zsaw9FGj921TYVT/xKqqqrYtWsXSUlJjW5PSkpi8+bNLf7Mli1bmh0/a9Ysdu7cSXV1dZvHtHaflZWVFBUVNbo4g63hLr5SB28schAEdoXqMsjYrnc0huPuJ5oOS/sRbNUQGq9u0SAa2XBM+t+0yCcA4ser12X0uBltufiWk7lU1dh0jsbxnJrg5OTkUFtbS1RUVKPbo6KiyMrKavFnsrKyWjy+pqaGnJycNo9p7T6fe+45rFar/RIXF3epT6lNhzKLyCutItDHwoj4UKc8hssym2XbhjZMrntj2nemkHw37ktxyU426F4sKxMbadR3Sz5YNSfLxVs1MCaE8EAfyqpq2ZPufts2dMpYZtOl0oqitLl8uqXjm97envtcuHAhhYWF9ktGRka74r9YkcG+/O6qAdw/pRfeMkzcnMzDaVVUiB/9o9S+FJtPyJLWZqT/Tau0vlvdu0jfrRZpvzNpG6G2Wt9YDMZsNtn3xHPH7WKc+i4cERGBxWJpNrKSnZ3dbARGEx0d3eLxXl5ehIeHt3lMa/fp6+tLSEhIo4szRIb48cDU3jw2s59T7t/laZNDzyZDWZ6ekRjSZFku3rKis3D+CJjM6goq0UjDeX/Sd6sF0UMhIByqSuD0Dr2jMRztvLPBDcvjTk1wfHx8GDVqFKtXr250++rVq5k4cWKLPzNhwoRmx69atYrRo0fj7e3d5jGt3acwiJBY6JqI2pdivd7RGE7D/WHctS/FJdFKC7EjICBM31gMqD7BkfJUi8zm+g9XUqZqRjvv7D9dQEGZe5XHnV5Hefzxx3nrrbd45513OHz4MI899hjp6ek8+OCDgFo+uvvuu+3HP/jgg5w6dYrHH3+cw4cP88477/D222/zxBNP2I959NFHWbVqFS+88AJHjhzhhRdeYM2aNSxYsMDZT0d0lJSpWjUuIRwfi5kzBeWk5pTqHY5xnJTdw1uj9d0ymWCibM/QOvs8HDnvNBVj9adPZBA2NyyPOz3BmTt3LosWLeLZZ59l+PDhbNiwgeXLl9OjRw8AMjMzG/XESUhIYPny5axbt47hw4fzpz/9iX/961/cdNNN9mMmTpzIkiVLePfddxk6dCiLFy9m6dKljBs3ztlPR3SUbNvQKn8fC6N6qH0p3LEefklstgb9b2T+TVObGvTdCg3w0TkaA9N+d87uVrthi0bcdXfxTmkH+tBDD/HQQw+1+L3Fixc3u+2yyy5j9+7dbd7nzTffzM033+yI8ERn6lHXl6IwA3JPQEQfvSMylCn9IthyMpeNKTncPaGn3uHo79wBKMsBnyDoPkbvaAzHXp7qI8vD22TtBhH9IOcYpG6AgdfpHZGhTOkbwbs/prEx5fwFFwG5ElnqIzqXTyDE1Y20yXBxM1P6qPMotpzIpbrW/fpStJv2O9JzMnjJCEVDjftuSYJzQVKmatW4hHC8LSZO55dzKrdM73AcRhIc0fm0E430w2lmUGwIXQK8KamsYW9Ggd7h6E97M5L5N80cyiwit7SKAB8LI+K76B2O8WllKplo3Eygrxcj47VtG9xnFackOKLzaRONUzdIX4omGvalcMdlm+1SVSbbM7TBvj1Dr3B8vORUfkE9J4PZGwpOQd5JvaMxnKn96ncXdxfyVyE6X/Qw8A+TvhStmNpXO9G4zyepS5K+GWorIaQ7hMtcraa034/JUp66OL5BUh5vg33bhhO51LhJeVwSHNH5zOYGy8VluLgp7Q1rb0YBheUePMKl/W70vly2Z2iivKqWHWmyPUO7yXmnVYO7WbH6e1NcWcPe0wV6h+MQkuAIffSSfjitiQ31p3fXQGwKbDnhPsPF7dYwwRGNbE/Lo6rGRozVj95dA/UOx3U0Ko/X6BuLwVjMJvsozoZj7nHekQRH6KO39KVoi/ap3GPn4RRnQfZBwAQJ03QOxng2pdTvHu4uS3o7Rcxw8O8ClUVwZpfe0RiOthrPXfpwSYIj9GHtDhH9QbGpn6ZEI1P7efi+VCfXqV9jhkGgdOhtSpsIOlnKU+1jtjTYtkFGj5vSyuPJblIelwRH6Ee2bWiV1pciI6+cU7keuG2DLA9vVXZRBUeyijGZ6ieGinaQfjit6t4lgF5dA6m1KWxxg20bJMER+ml4opFtGxoJ9PWyb9vgcWUqRWkw/0YSnKa00ZvBsVbCAqX5Ybtp8//O7ITyAl1DMSJ3WsUpCY7QT49JdX0p0qUvRQu0eTgbj7n+iaZdzh2E0mzwDoC4sXpHYzgbG8y/EZcgNA7C+0p5vBXaqKA79MORBEfoR/pStEn7JOVx2zZoHa57TgYvX31jMRibTbFPAJXl4R0g3dRbNb53OF5mE+l5ZS5fHpcER+hL+lK0Stu2odjTtm3Qkl3ZPbyZw1lF5JSo2zOM7BGqdziuS+bhtCrI14uRblIelwRH6Es70aRtlG0bmvDIbRuqy+HUZvV6n+n6xmJAWtlgfK9wfL0sOkfjwnpOArMX5KdJebwFU7Xl4i4+D0cSHKGvmGH1fSlO79Q7GsNxpwl/F+XUZqipgJBuENFP72gMR+bfOIhvsJTH26CVPzcfd+1tGyTBEfpq2JdC6uHNeNy2Dfbl4bI9Q1PlVbXsSJXtGRxGyuOtGtzNSmiA62/bIAmO0J9Wpjq+Vt84DCg21J8+kUGes22DPcGR8lRT21Jzqaq1ESvbMziGdt6RbRuasTQsj7vwtg2S4Aj9aSeas7uhLE/fWAxIK0e4/TycokzIPgSY6kf1hJ02/2Zqv66yPYMjxAwHv9C6bRukPN6UNg/HlcvjkuAI/TXatmG93tEYjj3BOXYexZ0bImolytgREBCmbywGVD//RspTDiHbNrRJ2wbElbdtkARHGIO2YkZONM1o2zaczi8nLbdM73CcRytRyuqpZrIKKzh2rgSTCSb1kb25HEb7XZPyeDPdQv3p3TXQpcvjkuAIY9DmXByXbRuaarhtgysPF7fJZqsfwZHtGZrR/t+Hdg8lNEC2Z3AY7bwj5fEWaaOFrloelwRHGEOPiWDxhaLTkJOidzSGM7Vf3YnGXbdtyNoLZbngEwzdx+gdjeHY59/I8nDHsnaDrgOkPN6Kqf1cuzwuCY4wBp8A6DFBvX5ChoubarhtQ1WN6/alaJVWmkyYChZvfWMxGNmewclkFWerXL08LgmOMA5pn96qgTEhRAT5UFpVy65T+XqH43j23cNle4amDmUWkVdaRaCPhRHxoXqH4356N5j/54KjFM7k6uVxSXCEcWgnmrRNUFOpbywGYzabGtTDXe9E06bKEkjfql6X+TfNrK8rS07oHY63RU7ZDmcvj5+BnGN6R2M4Wnl8/VHXO+/IX4swjqhBEBQF1WX1b3jCrmE93K2kbQJbNXTpCeG99Y7GcLT/78v6SXnKKXwC1CQHpEzVAu33bstJ1yuPS4IjjMNkalCmkhNNU5P7qCeag2eLOF/sRiNc9u7FMnrTVHFFtb0kOVUSHOext6mQ805TidEhRAT5UlZVy85TrrXSTBIcYSwyD6dVXYN9GRgTAsCm4240iqO9qUiC08yWE7nU2BR6hgfQI1y2Z3Aa7Xcv7UeortA3FoMxm0321Xuutm2DJDjCWHrVTTLN2g8l2frGYkD1y8Vd60TTqvxTkHscTBZ1BZVoRJtvJaM3ThY5EIJjoKYc0rfoHY3h2OfhuFh5XBIcYSxBXSFmmHpdRnGa0ebhbEw5j83mBis+tNGb7mPAz6pvLAajKIr9DUXm3ziZlMfbNKVvBCYTHM4sIrvYdUa4JMERxiNlqlaN7hFGgI+FnJIqDmUW6R1Ox9m3Z5ihbxwGlJZbRkZeOd4WE+N7yfYMTmfvhyPnnabCg3wZHKt+ANnoQqPHTk1w8vPzmTdvHlarFavVyrx58ygoKGj1+Orqan7zm98wZMgQAgMDiY2N5e677+bs2bONjps2bRomk6nR5bbbbnPmUxGdqWFfCptrzdp3Nh8vMxPq3uxcfrl4bTWcrOseK/tPNbP+qFqiHdMzjEBfL52j8QC9LgdMkH0QirP0jsZw7Ks4Xei849QE54477iA5OZkVK1awYsUKkpOTmTdvXqvHl5WVsXv3bp566il2797NZ599xrFjx7j22mubHTt//nwyMzPtlzfeeMOZT0V0prhx4BMEpecha5/e0RiO22zbkLEdqoohIBxihusdjeFo+//I/JtOEhgOscPV6zJ63Mxl/SIBddsQVymPO+1jweHDh1mxYgVbt25l3LhxALz55ptMmDCBo0eP0r9//2Y/Y7VaWb16daPbXn75ZcaOHUt6ejrx8fH22wMCAoiOjnZW+EJPXj6QcBkc/RaOr6k/6Qig/g1v16l8SitrXPfT/fE16tfe08Es1fKGKmtq2XIiF6jfpkN0gt7T4ewetXQ6/A69ozGUEfGhBPl6kVdaxYGzhQztHqp3SBfktLPKli1bsFqt9uQGYPz48VitVjZv3nzR91NYWIjJZCI0NLTR7R9++CEREREMGjSIJ554guLi4lbvo7KykqKiokYXYXBayUIabzXTMzyAuDB/qmsV+5ugS9ISHJl/08zOtHzKq2vpGuxLYkyw3uF4jj4Ny+O1+sZiMN4WMxN715XHXWT02GkJTlZWFpGRkc1uj4yMJCvr4uqbFRUV/Pa3v+WOO+4gJCTEfvudd97JRx99xLp163jqqadYtmwZN954Y6v389xzz9nnAVmtVuLi4tr/hETn0k40GdugvEDXUIzGZDLZP9W7Uj28keJz9eVH6X/TjPYGMrVvV0wmk87ReJDuY8A3BMrz4Gyy3tEYjqu1qWh3gvP00083m+Db9LJz506AFv8wFUW5qD/Y6upqbrvtNmw2G6+++mqj782fP58ZM2YwePBgbrvtNj799FPWrFnD7t27W7yvhQsXUlhYaL9kZGS092mLztalJ4T3BaUWUtfrHY3huGpfCjttjkPMcLU1gGjEvjy8v7w2ncriDb2mqdePr27zUE+ktSvYlZ5PUUW1ztFcWLsTnIcffpjDhw+3eRk8eDDR0dGcO3eu2c+fP3+eqKioNh+jurqaW2+9ldTUVFavXt1o9KYlI0eOxNvbm5SUlBa/7+vrS0hISKOLcAF9Z6pftVKGsJvYOxwvs4lTuWWk5ZTqHU77SXmqVeeKKjiSVYzJBFP6ROgdjueR806r4sIC6BURSK1NYfNx45fH2z07MSIigoiIC//RTZgwgcLCQrZv387YsWMB2LZtG4WFhUycOLHVn9OSm5SUFH744QfCwy/c/+HgwYNUV1cTExNz8U9EGF+f6bD1VXUejqKozbgEAMF+3ozu2YWtJ/NYdzSbeyMS9A7p4tlq60dwJMFpRitPDe1mpUugj87ReCCtTcXpnVCWBwFh+sZjMFP7deVkTinrj51n9mBjL/Rx2hycxMREZs+ezfz589m6dStbt25l/vz5zJkzp9EKqgEDBvD5558DUFNTw80338zOnTv58MMPqa2tJSsri6ysLKqqqgA4ceIEzz77LDt37iQtLY3ly5dzyy23MGLECCZNmuSspyP00GMSePlB0RnIPqx3NIYzrb86x22dq5WpMpPVOQ6+VnXOg2hEuhfrzNoNIgcBiiwXb8FlDdpUKIqxl4s7dW3mhx9+yJAhQ0hKSiIpKYmhQ4fy/vvvNzrm6NGjFBYWAnD69Gm++uorTp8+zfDhw4mJibFftJVXPj4+rF27llmzZtG/f38eeeQRkpKSWLNmDRaLxZlPR3Q2b3/oOVm9LsPFzUyrm5+x5UQuFdUutOJDWxnX6zKwuOgSdyeptSlsOi79b3RnX8Up552mxvcKx8fLzJmCco5nl+gdTpucenYJCwvjgw8+aPOYhhlgz549L5gRxsXFsX69TDr1GH1mqieZ42tg0iN6R2Mo/aOCiQ7xI6uogq0nc+0jOoYn829alZxRQEFZNSF+XgyPC9U7HM/VdyZs/pf6u2qzSZ+mBvx9LIzvFc6GY+dZd/Q8faOM28ZA/teEsWlvgulboNLYnxY6m8lkso/iuMxqqvJ8OL1DvS7bMzSzrm57hqn9uuJlkdOzbuLGSzf1NkyrG138oe731ajkL0gYW3hvCO0BtVWQtlHvaAzHnuAcdZEE5+Q6UGzQNRGs3fWOxnDW1f0/usxonLvSuqmDLBdvgXbe2ZGWR0lljc7RtE4SHGFsJlP9KI7Uw5uZ1CcCL7OJkzmlpOeW6R3OhdnLUzJ601R2cQX7z6jzEWWCsQFov6Mpct5pKiEikB7hAVTXKmw+btymf5LgCOPT+lKkrFaXiwu7YD9vRvXoAsC6Y8YeLkZR6t8sJMFpRusOO6Sbla7BvjpHI+znndPb1dKqsDOZTPYylZFXcUqCI4yv5xQwe0PBKcg9oXc0hmNfLm70MlXWPijJAu9AtQWAaESbzzBNuhcbQ2g8RPRXS6on1+kdjeHYzztHsg27XFwSHGF8vkHQY4J6XerhzWjljM0ncoy9XDxllfq11zTwkhGKhmpqbWw8JvNvDEfK463SloufLawgxaDLxSXBEa6hj1amWqVvHAaUGBNMVIgvFdU2tqfm6R1O61LqklNt6F/Y7ckooKiihtAAb1kebiR9tQRnrZTHm/D3sTChl7rTwDqDrqaSBEe4hn6z1K9pm6DKBfdeciKTyWQfxTHscvGyvPrl4ZLgNGNfHt63KxazbEliGPETwTsAijPh3AG9ozEcrZxq1PK4JDjCNUT0q18uflIaPTZVPw/HmJ+k1E/ANogaLMvDW1C/PFzm3xiKt586BxBk9LgF2nnHqMvFJcERrsFkgr5J6vWUlfrGYkCT+kRgMZs4cb6UjDwDLhfX3hxk9KaZ7KIKDp4tAmR7BkPSfmePSYLTVMPl4j8acLm4JDjCdWhlKlku3ozV35tR8XXLxY02imOrrZ+kqSWpwk5bZjusu5WIIJl8bTjaeef0drXUKhq53MCrOCXBEa6j52Tw8ld3Fz93UO9oDOfyAeqJ5vsjBktwzuxqsHv4WL2jMRwtIb1MVk8ZU2g8RA5US6zaRrHC7jJ7N3XjLReXBEe4Dm9/dQdqkDJVC6Ynqm+QP57IpazKQPVwrTzV5wrZPbyJ6lobG1PUof3LZf6NcUl5vFUTeoXjW7dc/Ng5Yy0XlwRHuBaph7eqb2QQ3bv4U1VjY/PxXL3DqWeffzNL3zgMaPepfIoraugS4M3Q7qF6hyNa07A8XmugDw8G4OdtYUJvdbm40UaPJcERrqWv1MNbYzKZuEIrUxllHk5xFmTuVa9rTdOE3fcNdg+X5eEG1n0s+IVCRUF9uwNhN91eHj+ncySNSYIjXEtoXH09/MT3ekdjOPYE57BB6uFac7/YkRAkJZimvj+sJjjTE6N0jkS0yeJVn6BLmaoZbf7frlP55JdW6RxNPUlwhOvR6uHH5ETT1Phe4fh7W8gqquBQZpHe4TQoT8nqqabSc8tIyS7BYjZxWV9J/gxPK1NJebyZ7l0CGBAdjE0x1qa/kuAI16O9WR5foy5BFnZ+3hYm9YkA4Ae96+E1VXDiB/W6JDjNrK0bzh/TswvWAG+doxEX1GcGmMyQfRAKMvSOxnC0RQ5rD0uCI8SlixsHflZ16fGZXXpHYzj2E43eCU7GVqgqhoAIiB2hbywGpL0RTB8g5SmXEBBW3+ZAylTNXFH3e7z+2Hmqa206R6OSBEe4HosX9J6uXpcyVTNa463kjAJySyr1C+ToCvVr35lgllNNQ8UV1WxLVVe6aQmpcAH9tPK4lKmaGh4XSnigD8UVNexMy9c7HEASHOGqpC9Fq6KtfgyKDUFRdOwuqihwdLl6vf9V+sRgYBtTcqiuVUiICKRX1yC9wxEXS1vFmboeqgy4JYqOLGaTfW8qo6ymkgRHuKa+MwETZO2HwjN6R2M40/Xuanz+KOSngsUHel+hTwwGVl+ektEblxI1CEK6Q00FpG3UOxrDMdo8HElwhGsKjIC4unr4se/0jcWAtGWbG/Sqh2v/JwlTwVdGKBqqtSn8UNf/5gopT7kWk6lBmUpGj5ua0jcCb4uJkzmlnDyvf1djSXCE6+p/pfr1qCQ4TQ3rXlcPr6xhR5oODRG1/5N+szv/sQ0uOaOAvNIqgv28GNMzTO9wRHtpZaqUVbLpbxPBft6MSzBOV2NJcITr6n+1+jV1A1QW6xuLwZjNpvrNNzt7uLg0BzK2q9e1JFTYrT2szk+4rF9XvC1yCnY5CVPVTX8LM9QSuWjkCr3L4w3IX5dwXRF9Iaw31FbJLr8t0E40nb5c/NhKQIHoIWDt3rmP7QK0E/8M6V7smnwCoPfl6nVtIr2w0+bhbE/No6iiWtdYJMERrstkkjJVG7R6eGpOKcezO7Eers2/kdVTzZzOL+NIVjFmkzqCI1yU9rstCU4zPcID6d01kBqbwoZjOq3irCMJjnBt2okmZaXs8ttEsJ83E3urXY1XHcrqnAetroDjdXuESXmqGW30ZnSPMLoE+ugcjbhk/WYDJnUj2cLTekdjONroZKeXx5uQBEe4trhx4B8G5flq51zRyMyB6olm9aFO6kuRthGqSyE4BmKGd85jupA1h2X1lFsI6qqee0BGj1uglcd/OJpNrU2/idiS4AjXZvGq3wRPTjTNaAnOnvQCsosqnP+ADVdPmUzOfzwXUlJZw9YTdd2Lpf+N6xtQN3p85Ft94zCgUT268Msr+vDm3aPR8ywgCY5wfVop5Mi3smyziagQP4bFhQL1owdOoyhwrG57BilPNbPuaDZVtTYSIgLpEym9gVyetoozbRNUFOobi8F4Wcz8Kqk/o3uGYTbrl+I4NcHJz89n3rx5WK1WrFYr8+bNo6CgoM2fuffeezGZTI0u48ePb3RMZWUlv/zlL4mIiCAwMJBrr72W06elDuqxel+hdszNT4WcY3pHYzhJdaM4Tp+Hk7UPis6Ad4C6lFY0svKgWiZMGhiFSUa3XF9EH4joB7ZqSFmtdzSiBU5NcO644w6Sk5NZsWIFK1asIDk5mXnz5l3w52bPnk1mZqb9snx545nqCxYs4PPPP2fJkiVs2rSJkpIS5syZQ21trbOeijAy32BIuEy9LsPFzWgJzubjuZRUOnEitlae6nU5ePs773FcUGVNLT/UTTBOGhStczTCYWQ1laE5LcE5fPgwK1as4K233mLChAlMmDCBN998k2+++YajR4+2+bO+vr5ER0fbL2Fh9d0+CwsLefvtt3nxxReZMWMGI0aM4IMPPmD//v2sWbPGWU9HGJ0sF29Vn8ggEiICqaq1OXfZpn1zTSlPNbXlhJpcRgb7MqKuZCjcwIC6MlXKaqip0jcW0YzTEpwtW7ZgtVoZN26c/bbx48djtVrZvHlzmz+7bt06IiMj6devH/Pnzyc7u37uwK5du6iuriYpKcl+W2xsLIMHD271fisrKykqKmp0EW5G2xLg9A4o0b+DppGYTCb7ZONVB51UpipIV5fMYpLtGVqwqm4V28yBUbrOSRAO1m0UBHaFyiI4tUnvaEQTTktwsrKyiIxsvlIgMjKSrKzWT7JXXnklH374Id9//z0vvvgiO3bs4IorrqCystJ+vz4+PnTp0qXRz0VFRbV6v88995x9HpDVaiUuLq4Dz0wYkrVb3bLkBhNdhZ1Wpvr+SLZzNt88/I36tcdEdQmtsLPZFPsyfSlPuRmzpT6hPyJlKqNpd4Lz9NNPN5sE3PSyc+dOgBYn0imK0uYEu7lz53L11VczePBgrrnmGr777juOHTvGt9+2PbeirftduHAhhYWF9ktGRkY7nrFwGdpwsczDaWZEfBfCA30oqqhhe6oTNt88/LX6NfFax9+3i9uTkc/54kqC/byY0Ctc73CEo2nnnaPfySpOg/Fq7w88/PDD3HbbbW0e07NnT/bt28e5c82bi50/f56oqIvfgyUmJoYePXqQkpICQHR0NFVVVeTn5zcaxcnOzmbixIkt3oevry++vr4X/ZjCRSVeAz/8GU58DxVF4Beid0SGYTGbmJEYxdKdGaw+dI5JfSIcd+cl2ZC+Rb2eOMdx9+smVtWtnrpiQCQ+XtKZw+30mqauHCw6rZZpY4frHZGo0+6/toiICAYMGNDmxc/PjwkTJlBYWMj27dvtP7tt2zYKCwtbTURakpubS0ZGBjExMQCMGjUKb29vVq+uX5aXmZnJgQMH2nW/wg11HQDhfdTNN1NW6R2N4TSch6M48pPmkW8BBWJHyuaaTSiKwsq6eU9JA6U85Za8/dVWFSCjxwbjtI8TiYmJzJ49m/nz57N161a2bt3K/PnzmTNnDv3797cfN2DAAD7//HMASkpKeOKJJ9iyZQtpaWmsW7eOa665hoiICG644QYArFYr9913H7/61a9Yu3Yte/bs4a677mLIkCHMmDHDWU9HuAKTqb5EcuhLfWMxoMl9I/D3tnC2sIKDZx040d5enrrGcffpJo6dKyEttwwfLzPT+svcJLel/e4f/krfOEQjTh0v/fDDDxkyZAhJSUkkJSUxdOhQ3n///UbHHD16lMJCtQukxWJh//79XHfddfTr14977rmHfv36sWXLFoKDg+0/849//IPrr7+eW2+9lUmTJhEQEMDXX3+NxWJx5tMRrmBgXYJzfA1Ulekbi8H4eVuY2k8tTa101Gqq8gJIXa9el/k3zWir1qb0iSDQt90zAoSr6DcbzN5w/gicb7sNiug8Tv2LCwsL44MPPmjzmIZD5f7+/qxcufKC9+vn58fLL7/Myy+/3OEYhZuJGQ6h8eqy5eNr6hMeAcCVg2NYefAc3+7P5PGZ/TreUffYSrDVQNdEtbOraGRlXffopEEXP+9QuCD/UOh9uVoaP/QVXPZrvSMSyF5Uwt00LFPJcHEz0xMj8bGYOXm+lGPnSjp+h9prLOWpZk7nl3HgTBFmE8xIlATH7Q28Tv0q5XHDkARHuB8twTm2Emoq9Y3FYIL9vO1lquX7Mzt2Z1WlcHytel0SnGa01VOje4YRHiSrON1e/6vAZIFz+yH3hN7RCCTBEe6o+xgIjlG7i55cp3c0hnPVEHVFYocTnONroaYcQntA9BAHROZevjugvr6zpLmfZwgIq99kVkZxDEESHOF+zGYYUNeP5ZCUqZqaMTAKb4uJlOwSUs4VX/odNSxPye7YjWQVVrAjLR+Aq+sSSuEBpExlKJLgCPekTS4++i3UVusbi8GE+Hkzpa+6ZHn5/ktcTVVTqZYAof6kLuy00bExPbsQbfXTORrRaQbMAZMZMpMhP03vaDyeJDjCPcVPhIBwKM+HNNkEr6kOl6lSN6glwKBo6DbagZG5h2/2nQVk9MbjBHWFHpPU6zJ6rDtJcIR7snjV7xEjq6mamZmolqmOnivmePYlrKY6qDbnJHGOWhIUdmcKytmdXoDJBFdKguN5pExlGHJmEu4rse5Ec/gbsNXqG4vBWAO87ftRfdfeUZyayvruxYNvcnBkru87e3kqjKgQKU95nMRrABOc2QmFp/WOxqNJgiPcV8JU8LVCaTac2qx3NIajlam+bW+Cc3yNWp4K6QZx450QmWv7Zp/6es4ZKqM3Hik4GuInqNe1DwJCF5LgCPfl5QMD6/qzHPhU31gMKGlgFF5mE0eyijl5vh1lqgPL1K+DbpDyVBMZeWUkZxRgNsHswbI83GNJmcoQ5Owk3Nvgm9Wvh76Emip9YzGY0AAfJmplqgMXuZqqqhSOfqdel/JUM1rvm3EJ4UQGS3nKY2mNL9O3QuEZfWPxYJLgCPeWMBUCI9XVVCd/0Dsaw7l6iDrK8O2+iyxTHf0OqsugSwLEjnBiZK5Jex2vlvKUZ7N2qytTKXDwM72j8ViS4Aj3ZrbA4BvV6/ulTNVU0sBovMwmDmUWceJiylQH6k7Wg2+S5n5NZOSVsfd0oZSnhGpI3ejxvo/1jcODSYIj3J9WpjryLVSV6RuLwXQJ9GFqP7Xp35d7LjCUXl4Ax1er16U81Yw2uXhC73AiZO8pMfAGMHtB1j44f1TvaDySJDjC/XUfre6XVF0Kx77TOxrDuW54LABfJJ9FUZTWDzzyLdRWQddEiBrYSdG5jm/3a839YnWORBhCYDj0nq5e3/+JvrF4KElwhPszmepHHPYv0zcWA0oaGE2gj4X0vDJ2pxe0fqC2ekpGb5o5eb6EA2eKsJhNzBoUpXc4wiiG3qp+3f8JtPXhQTiFJDjCMwy5Rf16fLU64VjY+ftY7Dtef9Famao0p35ndm1Ok7D7vO51m9I3gnApTwlN/yvBO1Ddl+r0Tr2j8TiS4AjPEDUQIgeqJRZpvtXMdSO6AeoeStW1tuYHHPoSlFqIGQ7hvTs3OIOz2RR7gnPjyO46RyMMxSewfssYKVN1OklwhOewl6lkNVVTk+omxuaXVbPh2PnmBzRcPSUa2ZGWx+n8coJ8vUgaKOUp0YQ2enzwM6it0TcWDyMJjvAc2ptz2kYoPqdvLAbjZTFzzTC1d8sXyWcbf7MgHU79qF4fdEMnR2Z82ujNVUOi8fO26ByNMJzel0NAOJSeh9R1ekfjUSTBEZ4jLAG6jwHFVr8btrC7oa5MtfpQFiWVDT5p7l0KKGrTxNA4fYIzqIrqWvteXjeMkPKUaIHFu/6DwT4pU3UmSXCEZ9F64uz9SN84DGhINyu9IgKpqLaxUtu6QVEg+UP1+vA79QvOoNYcPkdxRQ3dQv0ZlxCmdzjCqLQy1ZFvpBdXJ5IER3iWITerzbcyk+HcQb2jMRSTycR1w9VRnC+S61ZTpW+F/FTwCarfX0fYfb5bfZ2uHxGL2SydnUUr4sZBaDxUlUgvrk4kCY7wLIER6tJNgD0f6huLAV0/Qm1S9+PxHLKLK+pHbwZdr64IEXY5JZWsq5uQLeUp0SaTqcHo8RJ9Y/EgkuAIzzNinvp13xLZYbyJHuGBjIgPxabA8l0n4OAX6jekPNXM13vPUmtTGNbdSp/IIL3DEUY3/A716/E1UHS27WOFQ0iCIzxP7+kQFA1luZCyUu9oDOfGusnG57Z9ClXF0KVn3c7IoiFt9ZQ2OVuINkX0hfiJ6iKHZBk97gyS4AjPY/GCYbep1/d8oG8sBnTt8G74eZuZVFKX/A2/U3YOb+J4djH7ThfiZTZxzTDZe0pcpJF1o8d7PgBbCw01hUNJgiM804i71K8pq6A4S99YDMbq782d/U1MNB9Sb9CSQWG3rG5y8bT+XWVrBnHxBl4HPsHq1g2nNukdjduTBEd4poi+6soGxSaT/lrwk6BtmE0KW5XBlPjLCEVD1bU2Pt11GpCtGUQ7+QTCkLqGo7vf1zcWDyAJjvBc2sTZPR/ITr8NKQrdTqmNEJdWT+HrvTIhsqE1h85xvriSiCBfZsrWDKK9Rt6tfj30pWz862SS4AjPNegG8A6A3BTI2K53NMaRvhVTfipVlgBW2MawZHu63hEZyofb1Ndj7pjueFvkFCraKXYkRA6C2krZF8/JnPrXmZ+fz7x587BarVitVubNm0dBQUGbP2MymVq8/O1vf7MfM23atGbfv+02mScg2skvBAZer15PlsnGdrsWA2BLvI4aiz97Txdy6GyRvjEZRFpOKZuO52AywW1j4vUOR7gik6l+svHu/+obi5tzaoJzxx13kJyczIoVK1ixYgXJycnMmzevzZ/JzMxsdHnnnXcwmUzcdFPjXYznz5/f6Lg33njDmU9FuKsRdWWqA59BVam+sRhBaa666zHgN36+vQSzdIeM4gB8VPc6TO3blbiwAJ2jES5r6Fyw+EDWPsjcq3c0bstpCc7hw4dZsWIFb731FhMmTGDChAm8+eabfPPNNxw9erTVn4uOjm50+fLLL7n88svp1atXo+MCAgIaHWe1Wp31VIQ76zEJuiSoLdRluBj2/BdqqyBmOHQbaR+l+HzPGSqqa/WNTWdVNTY+3alOLr5jnIzeiA4ICIMBc9TrMtnYaZyW4GzZsgWr1cq4cePst40fPx6r1crmzZsv6j7OnTvHt99+y3333dfsex9++CEREREMGjSIJ554guLi4lbvp7KykqKiokYXIQB1uHj0T9Xr2//j2ZONbbWw4x31+tj5YDIxuU8E3UL9Kaqo4bsDmfrGp7OVB7PILa0iKsSX6QMi9Q5HuDqtTLX/Y6gu1zcWN+W0BCcrK4vIyOYngcjISLKyLq7vyHvvvUdwcDA33nhjo9vvvPNOPvroI9atW8dTTz3FsmXLmh3T0HPPPWefB2S1WomLi2vfkxHubcRd4OUP5w7AqYtLvt1SyiooTAe/UBisloTNZhNzx6h/L0u2Z+gYnP4+3HYKgLlj4vGSycWioxKmqRtwVhTK6LGTtPuv9Omnn251IrB22blzJ6BOGG5KUZQWb2/JO++8w5133omfn1+j2+fPn8+MGTMYPHgwt912G59++ilr1qxh9+7dLd7PwoULKSwstF8yMjz7RC2aCAiDobeq17d78FyuHW+pX0fcBd7+9ptvGd0dswm2peaRcq71kVJ3duJ8CVtP5mE2wW1j5AOScACzGcbMV69ve92zR4+dpN0JzsMPP8zhw4fbvAwePJjo6GjOnTvX7OfPnz9PVNSFe0ds3LiRo0ePcv/991/w2JEjR+Lt7U1KSkqL3/f19SUkJKTRRYhGxv1M/Xr4Gyg8rW8sesg9oW4CiAnGNC4Jx1j97ZON3/kxrfNjM4CP6paGXzEgkthQ/wscLcRFGjlPbVVx7gCkbdQ7GrfT7gQnIiKCAQMGtHnx8/NjwoQJFBYWsn17fX+Rbdu2UVhYyMSJEy/4OG+//TajRo1i2LBhFzz24MGDVFdXExMT096nI4QqahD0mAxKLex8R+9oOp/2nPvMgLBezb5932T1ts92nyav1LN2YK+oruXT3TK5WDiBfxcYdrt6fevr+sbihpxWSE5MTGT27NnMnz+frVu3snXrVubPn8+cOXPo37+//bgBAwbw+eefN/rZoqIiPvnkkxZHb06cOMGzzz7Lzp07SUtLY/ny5dxyyy2MGDGCSZMmOevpCE8w7gH1667FUF2hayidqqqsftPRMS2PmI7p2YUh3axU1tj4X91cFE/xxZ4zFJRV0y3Un8v6yeRi4WDjHlS/Hl0Oean6xuJmnDpT7sMPP2TIkCEkJSWRlJTE0KFDef/9xkvijh49SmFhYaPblixZgqIo3H777c3u08fHh7Vr1zJr1iz69+/PI488QlJSEmvWrMFisTjz6Qh31/9qCOkGZblw8PMLH+8uDiyDigJ1wmPfmS0eYjKZuG9yAgD/3XKKqhrP2AnZZlN4c+NJAH4yqScWs+yqLhysaz/oPR1QYPubekfjVkyK4nkzm4qKirBarRQWFsp8HNHYhr/D93+C2BEw/wd1Gbk7UxT4z2Vqs7EZz8DkBa0eWlVjY/IL35NdXMlLtw7ziI0m1xw6x/3/3UmwnxdbFk4nyNdL75CEO0pZAx/eBL4h8Pgh8A3WOyLDas/7t6x1FKKhUfeCxRfO7oHTO/WOxvnSNqnJjcUXRrTdZdzHy8w9E3sC8PamVDzhs9F/NqijN3eMi5fkRjhP7ysgvC9UFkHyR3pH4zYkwRGiocAIew8YtnnApL9NL6lfR9wFgeEXPPyOsfH4eZs5eLaIbal5Tg5OX3vS89meloe3xcRPJiboHY5wZ2Zz/UrOba+DzTNKwM4mCY4QTWknmoOfQ95JfWNxprN74MT3YLLApEcu6ke6BPrYS1Nvb3LvCZHa3Jtrh3Uj2up3gaOF6KBht4OvFfJOwPHVekfjFiTBEaKp2OHqcmmlFjb9Q+9onGdj3ejNkJuhS8+L/rGfTlJHM9YcPkdajntuUHoqt5QVB9SO6w9Mbb5sXgiH8w2q375h88v6xuImJMERoiVTn1S/Jn8EBW7Y+fr8MTj8tXp98mPt+tE+kUFM698VRYF3fnTPUZy3N6ViU2Ba/670j5YJn6KTjP85mL3Vpn+evG2Mg0iCI0RL4sdBzylgq4Yf/6l3NI734yJAUZfGRya2+8cfmKKOaizZkUFmoXttFJhXWsXHO9WkVnueQnQKa3d1PhzAuuf1jcUNSIIjRGsuqxvF2f1fKL64DWJdQkEG7FuqXp/y+CXdxYTe4YxNCKOqxsarP5xwYHD6e3/LKSqqbQzuFsKE3heeeC2EQ015XB3FSV0vozgdJAmOEK3pOQXixkFtpXvVxDe/DLYaSJgK3Udf0l2YTCYen9kPgCU70jmdX+bICHVTWFbN25vUycUPTO190RsDC+EwofEyiuMgkuAI0RqTqX4uzs53oDRH33gcoeS8OiIFMPnSRm8043uFM7F3ONW1Cv/+4bgDgtPfGxtOUFRRQ7+oIK4eInvbCZ00GsXZonc0LksSHCHa0me62tW4ugy2/FvvaDpuyytQUw6xI6HXtA7fnTaK88nO06TnuvYoTnZRhX3S9K9nDZBtGYR+QuNhxJ3q9fUyinOpJMERoi0mE0z9tXp9+5tQnq9vPB1ReLq+eeHUXztkG4rRPcOY2q8rNTaFl79P6fD96enl749TUW1jZHwoMxJlU02hs8mPg9kLTq6TUZxLJAmOEBfS70qIHARVxbDxRb2juXRr/wQ1FdBjEvS/0mF3+9iMvgB8tucMqS7aF+dUbikfbU8H4MnZA2TujdBflx4wXEZxOkISHCEuxGyGGU+r17e+DrkuuGro7B7Yt0S9nvT/HLqJ6Ij4LlwxIJJam8K/1rrmKM4/Vh+jxqZwWb+ujO8lK6eEQUz5Vf0oTupGvaNxOZLgCHEx+iWp3Y1t1bDqD3pH0z6KAqueUq8PuRW6jXT4Qzw2Q52L80XyGY5kFTn8/p3p0Nkivtx7FoBfz+qvczRCNNClB4y8R73+3W+gtkbfeFyMJDhCXKxZf1E/TR1dru7h5CqOfqd2RvXyg+l/dMpDDOlu5aoh0SgK/PGLgy610/jfVx1FUWDO0BgGd7PqHY4QjV3xB/DvAtkHYefbekfjUiTBEeJide0PY+ar11f8zjU+TdVWw+q60ZvxD0FonNMe6vdXD8Tf28L2tDw+233GaY/jSJtP5PD9kWwsZhO/SpLRG2FAAWFwRd3f8Pd/Vls9uILD30Blia4hSIIjRHtM+w34h8H5w7DrXb2jubBdiyH3OAREtHvPqfbqFurPo3UTjv+y/DCFZdVOfbyOqqiu5fefHwDgjrHxJEQE6hyREK0YdS9ED4XKQlj7tN7RXFjGDvh4Hrw2QdeVp5LgCNEe/l3g8t+p13/4M5Tl6RtPW8ryYN1z6vXLF4JfiNMf8qeTEugTGURuaRV/W3XE6Y/XEf9am0JqTilRIb78eraM3ggDM1vgqr+r1/d8AKd36RtPW2oq4ctfgGKD+AnqOVMnkuAI0V6jfgKRA9VPJkZupb7811CWCxH96ycqOpmPl5k/XTcYgA+3pbPvdEGnPG57HTpbxBsb1C0Znr1uMCF+3jpHJMQFxI+DYXeo15f/Cmw2feNpzfoXIOcoBEbCbH3Pj5LgCNFeFi91wjHA9v9A2iZ942nJwc/hwKdgssD1r4Gl897AJ/QO54YR3VAU+MMXB6i1GWvCca1N4bef7aPWpnDl4GhmDYrWOyQhLs6Mp8E3RG37sOe/ekfT3Nlk2LRIvX71i+r8IR1JgiPEpeh9OYyYByjw2c+M1eG4+Bx8U7fP1JTHofuoTg9h4VUDCPb1Yt/pQv5X10DPKN79MZV9pwsJ9vPimWsH6R2OEBcvOAqmLVSvr/oj5KfpGk4jNVV1palaGHg9DLxW74gkwRHiks1+HsJ6QdFp+OYxtd+M3hQFvn4UyvPUSYnaZqGdLDLYjyfqesr85dvDHDtXrEscTWXklfHiqmMA/P6qRCJD/HSOSIh2Gjsfuo9VJxx/+lM1sTCCTf+AcwfURRjafCGdSYIjxKXyDYIb31LLQAc/h71L9I4Ikj+EY9+BxQdueB28fHQL5a7xPZjSN4Ly6loe/GAXJZX6LquvqbXx5Kf7KK+uZXyvMOaOcd6SeSGcxuINN78NflY4swu+f1bviODcQdjwN/X6VX+DoK76xlNHEhwhOqL7KHWFEsDyJyAvVb9YCtLhu9+q1y//HUTpW36xmE0smjuc6BA/Tp4vZeFn+3VtAPjcd0fYcjIXf28Lf7lhiOw3JVxXaDxc96p6ffPLcGyVfrFUFsOy+WqX9/5XweCb9IulCUlwhOioyY+ryyGrSuCzB/RpAFhVpg5XVxVD3DiY+Ejnx9CC8CBf/n3nCLzMJr7ee5b3t57SJY6Pd2bw9iY1+Xzp1mH06hqkSxxCOEziHBj7M/X65z+DQh2aa9bWqOed7IPqqqmrX3LoPncdJQmOEB1ltsCN/1FXN5zeDt/9unPn42gnmdM7wC9UXTVltnTe41/AqB5h/PbKAQD86ZtDJGcUdOrj7zqVxx/qGvo9Or0vVw6J6dTHF8Jpkv4EMcPUOXefze/8D1erfg8pq9RtYG5fAiHG+tuSBEcIRwiNh+teAUyw8x1Y83TnPK6iwLePq/NuvPzgjqUQ3rtzHrsd7pucwOxB0VTXKvziw92cL67slMc9W1DOz97fTVWtjdmDonl0et9OeVwhOoWXL9z8LvgEwakf4etHwFbbOY+9/U3Y9rp6/YbXdVmteSGS4AjhKAOvgzn/UK//uAg2vuj8x1z/Aux+D0xmuOltiB/v/Me8BCaTib/eMpSe4QGcKShn7n+2kFVY4dTHLK+q5Wfv7yKnpJIB0cG8eOswzGbjDJ8L4RDhvdUEw2RRFxl89UvnJzkpa+C7uhWaVzwFg25w7uNdIklwhHCk0T+BmX9Sr699Frb9x3mPteu9+q0Yrvq7WpM3sBA/bxb/ZCzdQv05eb6UW97YTEZemVMeK6ekktve3Mr+M4WEBfrw5t2jCfT1cspjCaG7xGvgprc6J8lJ3wqf3KtuxTDsDpjyK+c8jgNIgiOEo016pL7/zHe/VveOcSRFUVdOfLNA/feUJ2DMfY59DCfpGRHI0p+Np2d4ABl55dzy+hZOnHfsjsPHs0u44dUf2ZtRQGiAN2/ePZq4sACHPoYQhjP4RucnObvfh8Vz1MUMPSbBNYsMNam4KUlwhHCGy38H4x5Ur3/5C/h6AVSVdvx+ywtg6V2w6g/qJ6hR98IVf+j4/Xai7l0C+PhnE+gbGURWUQVz39jCobNFDrnvbSdzuem1zWTklRMfFsCyn09kVA/9NvsTolM1TXKW3a+eMzqqtgZWLISvHlaXgydeC3d+os4BMjCnJjh//vOfmThxIgEBAYSGhl7UzyiKwtNPP01sbCz+/v5MmzaNgwcPNjqmsrKSX/7yl0RERBAYGMi1117L6dOnnfAMhLhEJhPMeg4mPar+e9e78PoUtTHXpcrcC/+5DI58ozbyu+rvMGeRoT9BtSYyxI8lD4xnUGwIOSVVXP/vH/n7yqOUV13aJ06bTWHpjnTmvb2dwvJqRsSH8vlDE+kty8GFp2mY5Bz8DP49Dg5/fen3V54P/7sFttb13Zm2EG55D3wCHROvEzk1wamqquKWW27h5z//+UX/zF//+ldeeuklXnnlFXbs2EF0dDQzZ86kuLi+1fuCBQv4/PPPWbJkCZs2baKkpIQ5c+ZQW9tJs8eFuBhmM8x8Fu7+EoJjIe8EvDUT1v8VatqxiqjkvNol9K2Z6t4zofHw05Vqy3YXTG404UG+/G/+eKb170pVrY1XfjjOjJfW893+zItuCGizKSzfn8nsf27gN8v2U1Vr48rB0Xw0fzzhQcb+dCmE0wy+Ee79BsL7QEmWOuq79C4oyrz4+yjPhw1/h1fGwInvwTtATWym/VY9t7kAk9IJrUUXL17MggULKCgoaPM4RVGIjY1lwYIF/OY3vwHU0ZqoqCheeOEFfvazn1FYWEjXrl15//33mTt3LgBnz54lLi6O5cuXM2vWrAvGU1RUhNVqpbCwkJCQkA4/PyEuqDxf3QDz4Gfqv31DYMDV6uqDXpc331LBZoPU9bBrMRz5Vh0WBug3W10x4e8+ZRdFUVh58Bx/+uYQZwrKAZjUJ5xrhsYyumcXekUENVv9VFhWzZaTOSxak8KRLPXDT7CfFz+f1psHp/aW1VJCAFRXqB+OflwEthr1vJN4LfS5Qj3vtLTbd0EGbH1NPfdU15XVu/SEW9+HmKGdGHzL2vP+bagE5+TJk/Tu3Zvdu3czYsQI++3XXXcdoaGhvPfee3z//fdMnz6dvLw8unSpP8kPGzaM66+/nmeeeabZ/VZWVlJZWf+JuaioiLi4OElwROdSFNj/Caz+Pyg+W3+7nxW6jYLaanVkp6YCSs9DcYNPW91GwZj7YehtLvPpqb3Kq2p5bd1xXt9wkqoam/320ABvRsZ3IdDXi1O5pZzKLaOwvNr+/WBfL34yOYH7Jidg9ffWI3QhjC3rgDrp+OzuBjeaIHaEmryUnoeSc+qlorD+kKjBapl90A3qHlgG0J4Ex1DrJrOysgCIiopqdHtUVBSnTp2yH+Pj49MoudGO0X6+qeeee67FxEeITmUywdBbYfDNkLFN3aDz0BfqSeXE982P9w1Rjx95jyE+OTmbv4+Fx5P6c9Oo7ny8M4OdafnsPV1AQVk13x/JbnZ8dIgfN4/qzv1TEggN0G9TUSEML3ow3L9GHRU+vlY932QfUhOeRklPnZ5TYPIC6D3dpcvg7U5wnn766QsmCzt27GD06NGXHFTTTfAURbngxnhtHbNw4UIef/xx+7+1ERwhdGE2Q48J6mX2c2pfifw0dUWCl5968faH2OEuMZHP0XqEB/LrWerWDlU1Ng5lFrH7VD41Nhs9wgPpER5AfFgAAT6G+nwmhLGZLdD7CvUCUHQWTq5Ty+dBURAUqe4nFRzlNiXwdp8hHn74YW677bY2j+nZs+clBRMdHQ2oozQxMfV7WmRnZ9tHdaKjo6mqqiI/P7/RKE52djYTJ05s8X59fX3x9ZUJh8KAzBboOUm9iGZ8vMwMjwtleFyo3qEI4V5CYmH4HXpH4VTtTnAiIiKIiIhwRiwkJCQQHR3N6tWr7XNwqqqqWL9+PS+88AIAo0aNwtvbm9WrV3PrrbcCkJmZyYEDB/jrX//qlLiEEEII4VqcOsabnp5OXl4e6enp1NbWkpycDECfPn0IClL7UwwYMIDnnnuOG264AZPJxIIFC/jLX/5C37596du3L3/5y18ICAjgjjvUTNNqtXLffffxq1/9ivDwcMLCwnjiiScYMmQIM2bMcObTEUIIIYSLcGqC88c//pH33nvP/m9tVOaHH35g2rRpABw9epTCwvpZ208++STl5eU89NBD5OfnM27cOFatWkVwcLD9mH/84x94eXlx6623Ul5ezvTp01m8eDEWi8WZT0cIIYQQLqJTlokbjfTBEUIIIVxPe96/3bOhhhBCCCE8miQ4QgghhHA7kuAIIYQQwu1IgiOEEEIItyMJjhBCCCHcjiQ4QgghhHA7kuAIIYQQwu1IgiOEEEIItyMJjhBCCCHcjlO3ajAqrXlzUVGRzpEIIYQQ4mJp79sXswmDRyY4xcXFAMTFxekciRBCCCHaq7i4GKvV2uYxHrkXlc1m4+zZswQHB2MymRx630VFRcTFxZGRkSH7XDmZvNadR17rziOvdeeR17rzOOq1VhSF4uJiYmNjMZvbnmXjkSM4ZrOZ7t27O/UxQkJC5A+mk8hr3Xnkte488lp3HnmtO48jXusLjdxoZJKxEEIIIdyOJDhCCCGEcDuS4DiYr68v//d//4evr6/eobg9ea07j7zWnUde684jr3Xn0eO19shJxkIIIYRwbzKCI4QQQgi3IwmOEEIIIdyOJDhCCCGEcDuS4AghhBDC7UiC40CvvvoqCQkJ+Pn5MWrUKDZu3Kh3SC7vueeeY8yYMQQHBxMZGcn111/P0aNHGx2jKApPP/00sbGx+Pv7M23aNA4ePKhTxO7jueeew2QysWDBAvtt8lo7zpkzZ7jrrrsIDw8nICCA4cOHs2vXLvv35bV2jJqaGv7whz+QkJCAv78/vXr14tlnn8Vms9mPkdf60m3YsIFrrrmG2NhYTCYTX3zxRaPvX8xrW1lZyS9/+UsiIiIIDAzk2muv5fTp0x0PThEOsWTJEsXb21t58803lUOHDimPPvqoEhgYqJw6dUrv0FzarFmzlHfffVc5cOCAkpycrFx99dVKfHy8UlJSYj/m+eefV4KDg5Vly5Yp+/fvV+bOnavExMQoRUVFOkbu2rZv36707NlTGTp0qPLoo4/ab5fX2jHy8vKUHj16KPfee6+ybds2JTU1VVmzZo1y/Phx+zHyWjvG//t//08JDw9XvvnmGyU1NVX55JNPlKCgIGXRokX2Y+S1vnTLly9Xfv/73yvLli1TAOXzzz9v9P2LeW0ffPBBpVu3bsrq1auV3bt3K5dffrkybNgwpaampkOxSYLjIGPHjlUefPDBRrcNGDBA+e1vf6tTRO4pOztbAZT169criqIoNptNiY6OVp5//nn7MRUVFYrValVef/11vcJ0acXFxUrfvn2V1atXK5dddpk9wZHX2nF+85vfKJMnT271+/JaO87VV1+t/PSnP21024033qjcddddiqLIa+1ITROci3ltCwoKFG9vb2XJkiX2Y86cOaOYzWZlxYoVHYpHSlQOUFVVxa5du0hKSmp0e1JSEps3b9YpKvdUWFgIQFhYGACpqalkZWU1eu19fX257LLL5LW/RL/4xS+4+uqrmTFjRqPb5bV2nK+++orRo0dzyy23EBkZyYgRI3jzzTft35fX2nEmT57M2rVrOXbsGAB79+5l06ZNXHXVVYC81s50Ma/trl27qK6ubnRMbGwsgwcP7vDr75GbbTpaTk4OtbW1REVFNbo9KiqKrKwsnaJyP4qi8PjjjzN58mQGDx4MYH99W3rtT5061ekxurolS5awe/duduzY0ex78lo7zsmTJ3nttdd4/PHH+d3vfsf27dt55JFH8PX15e6775bX2oF+85vfUFhYyIABA7BYLNTW1vLnP/+Z22+/HZDfa2e6mNc2KysLHx8funTp0uyYjr5/SoLjQCaTqdG/FUVpdpu4dA8//DD79u1j06ZNzb4nr33HZWRk8Oijj7Jq1Sr8/PxaPU5e646z2WyMHj2av/zlLwCMGDGCgwcP8tprr3H33Xfbj5PXuuOWLl3KBx98wP/+9z8GDRpEcnIyCxYsIDY2lnvuucd+nLzWznMpr60jXn8pUTlAREQEFoulWbaZnZ3dLHMVl+aXv/wlX331FT/88APdu3e33x4dHQ0gr70D7Nq1i+zsbEaNGoWXlxdeXl6sX7+ef/3rX3h5edlfT3mtOy4mJoaBAwc2ui0xMZH09HRAfq8d6de//jW//e1vue222xgyZAjz5s3jscce47nnngPktXami3lto6OjqaqqIj8/v9VjLpUkOA7g4+PDqFGjWL16daPbV69ezcSJE3WKyj0oisLDDz/MZ599xvfff09CQkKj7yckJBAdHd3ota+qqmL9+vXy2rfT9OnT2b9/P8nJyfbL6NGjufPOO0lOTqZXr17yWjvIpEmTmrU7OHbsGD169ADk99qRysrKMJsbv9VZLBb7MnF5rZ3nYl7bUaNG4e3t3eiYzMxMDhw40PHXv0NTlIWdtkz87bffVg4dOqQsWLBACQwMVNLS0vQOzaX9/Oc/V6xWq7Ju3TolMzPTfikrK7Mf8/zzzytWq1X57LPPlP379yu33367LPF0kIarqBRFXmtH2b59u+Ll5aX8+c9/VlJSUpQPP/xQCQgIUD744AP7MfJaO8Y999yjdOvWzb5M/LPPPlMiIiKUJ5980n6MvNaXrri4WNmzZ4+yZ88eBVBeeuklZc+ePfYWKRfz2j744INK9+7dlTVr1ii7d+9WrrjiClkmbjT//ve/lR49eig+Pj7KyJEj7UuZxaUDWry8++679mNsNpvyf//3f0p0dLTi6+urTJ06Vdm/f79+QbuRpgmOvNaO8/XXXyuDBw9WfH19lQEDBij/+c9/Gn1fXmvHKCoqUh599FElPj5e8fPzU3r16qX8/ve/VyorK+3HyGt96X744YcWz9H33HOPoigX99qWl5crDz/8sBIWFqb4+/src+bMUdLT0zscm0lRFKVjY0BCCCGEEMYic3CEEEII4XYkwRFCCCGE25EERwghhBBuRxIcIYQQQrgdSXCEEEII4XYkwRFCCCGE25EERwghhBBuRxIcIYQQQrgdSXCEEEII4XYkwRFCCCGE25EERwghhBBuRxIcIYQQQrid/w8boyl0XY11MwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate dataframe to test with\n",
    "\n",
    "time = []\n",
    "sin_x = []\n",
    "cos_x = []\n",
    "\n",
    "for i in range(0,1000000):\n",
    "    time.append(i)\n",
    "    sin_x.append(sin(i /10))\n",
    "    cos_x.append(cos(i /10))\n",
    "\n",
    "\n",
    "plt.plot(time, sin_x, label=\"sin\")\n",
    "plt.plot(time, cos_x, label=\"cos\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>sin_x</th>\n",
       "      <th>cos_x</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1970-01-01 00:00:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1970-01-01 00:00:01</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.99995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1970-01-01 00:00:02</td>\n",
       "      <td>0.019999</td>\n",
       "      <td>0.99980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1970-01-01 00:00:03</td>\n",
       "      <td>0.029996</td>\n",
       "      <td>0.99955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1970-01-01 00:00:04</td>\n",
       "      <td>0.039989</td>\n",
       "      <td>0.99920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 time     sin_x    cos_x\n",
       "0 1970-01-01 00:00:00  0.000000  1.00000\n",
       "1 1970-01-01 00:00:01  0.010000  0.99995\n",
       "2 1970-01-01 00:00:02  0.019999  0.99980\n",
       "3 1970-01-01 00:00:03  0.029996  0.99955\n",
       "4 1970-01-01 00:00:04  0.039989  0.99920"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert data to dataframe\n",
    "df = pd.DataFrame(list(zip(time, sin_x)), columns=[\"time\", \"sin_x\"])\n",
    "df['time'] = pd.to_datetime(df['time'], unit='s')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "NewConnectionError",
     "evalue": "<urllib3.connection.HTTPConnection object at 0x7fb7fac2f610>: Failed to establish a new connection: [Errno 61] Connection refused",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mConnectionRefusedError\u001b[0m                    Traceback (most recent call last)",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connection.py:174\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    173\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 174\u001b[0m     conn \u001b[39m=\u001b[39m connection\u001b[39m.\u001b[39;49mcreate_connection(\n\u001b[1;32m    175\u001b[0m         (\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_dns_host, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mport), \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtimeout, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mextra_kw\n\u001b[1;32m    176\u001b[0m     )\n\u001b[1;32m    178\u001b[0m \u001b[39mexcept\u001b[39;00m SocketTimeout:\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/util/connection.py:95\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[39mif\u001b[39;00m err \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m---> 95\u001b[0m     \u001b[39mraise\u001b[39;00m err\n\u001b[1;32m     97\u001b[0m \u001b[39mraise\u001b[39;00m socket\u001b[39m.\u001b[39merror(\u001b[39m\"\u001b[39m\u001b[39mgetaddrinfo returns an empty list\u001b[39m\u001b[39m\"\u001b[39m)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/util/connection.py:85\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     84\u001b[0m     sock\u001b[39m.\u001b[39mbind(source_address)\n\u001b[0;32m---> 85\u001b[0m sock\u001b[39m.\u001b[39;49mconnect(sa)\n\u001b[1;32m     86\u001b[0m \u001b[39mreturn\u001b[39;00m sock\n",
      "\u001b[0;31mConnectionRefusedError\u001b[0m: [Errno 61] Connection refused",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mNewConnectionError\u001b[0m                        Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[5], line 8\u001b[0m\n\u001b[1;32m      5\u001b[0m token\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mL9aO2ZCpKWUV-jZncfsXB0CauuwrChRbOwC5PtcjzWFXGkE75lh24NTpIanN-aYXMCMgOTsJpcM8sUrJWL0tCw==\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m InfluxDBClient(url\u001b[38;5;241m=\u001b[39murl, token\u001b[38;5;241m=\u001b[39mtoken, org\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mteco\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m client:\n\u001b[0;32m----> 8\u001b[0m    res \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_api\u001b[49m\u001b[43m(\u001b[49m\u001b[43mwrite_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mSYNCHRONOUS\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbucket\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbucket\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrecord\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_frame_measurement_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mweather\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_frame_timestamp_column\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtime\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      9\u001b[0m    \u001b[38;5;28mprint\u001b[39m(res)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/client/write_api.py:374\u001b[0m, in \u001b[0;36mWriteApi.write\u001b[0;34m(self, bucket, org, record, write_precision, **kwargs)\u001b[0m\n\u001b[1;32m    371\u001b[0m     final_string \u001b[39m=\u001b[39m \u001b[39mb\u001b[39m\u001b[39m'\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m.\u001b[39mjoin(payload[\u001b[39m1\u001b[39m])\n\u001b[1;32m    372\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_post_write(_async_req, bucket, org, final_string, payload[\u001b[39m0\u001b[39m])\n\u001b[0;32m--> 374\u001b[0m results \u001b[39m=\u001b[39m \u001b[39mlist\u001b[39;49m(\u001b[39mmap\u001b[39;49m(write_payload, payloads\u001b[39m.\u001b[39;49mitems()))\n\u001b[1;32m    375\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m _async_req:\n\u001b[1;32m    376\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/client/write_api.py:372\u001b[0m, in \u001b[0;36mWriteApi.write.<locals>.write_payload\u001b[0;34m(payload)\u001b[0m\n\u001b[1;32m    370\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mwrite_payload\u001b[39m(payload):\n\u001b[1;32m    371\u001b[0m     final_string \u001b[39m=\u001b[39m \u001b[39mb\u001b[39m\u001b[39m'\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m.\u001b[39mjoin(payload[\u001b[39m1\u001b[39m])\n\u001b[0;32m--> 372\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_post_write(_async_req, bucket, org, final_string, payload[\u001b[39m0\u001b[39;49m])\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/client/write_api.py:483\u001b[0m, in \u001b[0;36mWriteApi._post_write\u001b[0;34m(self, _async_req, bucket, org, body, precision, **kwargs)\u001b[0m\n\u001b[1;32m    481\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_post_write\u001b[39m(\u001b[39mself\u001b[39m, _async_req, bucket, org, body, precision, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m--> 483\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_write_service\u001b[39m.\u001b[39;49mpost_write(org\u001b[39m=\u001b[39;49morg, bucket\u001b[39m=\u001b[39;49mbucket, body\u001b[39m=\u001b[39;49mbody, precision\u001b[39m=\u001b[39;49mprecision,\n\u001b[1;32m    484\u001b[0m                                           async_req\u001b[39m=\u001b[39;49m_async_req, content_encoding\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39midentity\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    485\u001b[0m                                           content_type\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mtext/plain; charset=utf-8\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    486\u001b[0m                                           \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/service/write_service.py:60\u001b[0m, in \u001b[0;36mWriteService.post_write\u001b[0;34m(self, org, bucket, body, **kwargs)\u001b[0m\n\u001b[1;32m     58\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpost_write_with_http_info(org, bucket, body, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)  \u001b[39m# noqa: E501\u001b[39;00m\n\u001b[1;32m     59\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m---> 60\u001b[0m     (data) \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpost_write_with_http_info(org, bucket, body, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)  \u001b[39m# noqa: E501\u001b[39;00m\n\u001b[1;32m     61\u001b[0m     \u001b[39mreturn\u001b[39;00m data\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/service/write_service.py:90\u001b[0m, in \u001b[0;36mWriteService.post_write_with_http_info\u001b[0;34m(self, org, bucket, body, **kwargs)\u001b[0m\n\u001b[1;32m     64\u001b[0m \u001b[39m\"\"\"Write data.\u001b[39;00m\n\u001b[1;32m     65\u001b[0m \n\u001b[1;32m     66\u001b[0m \u001b[39mWrites data to a bucket.  Use this endpoint to send data in [line protocol](https://docs.influxdata.com/influxdb/v2.2/reference/syntax/line-protocol/) format to InfluxDB.  #### InfluxDB Cloud  - Takes the following steps when you send a write request:    1. Validates the request and queues the write.   2. If the write is queued, responds with an HTTP `204` status code.   3. Handles the write asynchronously and reaches eventual consistency.    An HTTP `2xx` status code acknowledges that the write or delete is queued.   To ensure that InfluxDB Cloud handles writes and deletes in the order you request them,   wait for a response before you send the next request.    Because writes are asynchronous, data might not yet be written   when you receive the response.  #### InfluxDB OSS  - Validates the request, handles the write synchronously,   and then responds with success or failure. - If all points were written successfully, returns `204`,   otherwise returns the first line that failed.  #### Required permissions  - `write-buckets` or `write-bucket BUCKET_ID`.    `BUCKET_ID` is the ID of the destination bucket.  #### Rate limits (with InfluxDB Cloud)  `write` rate limits apply. For more information, see [limits and adjustable quotas](https://docs.influxdata.com/influxdb/cloud/account-management/limits/).  #### Related guides  - [Write data with the InfluxDB API](https://docs.influxdata.com/influxdb/v2.2/write-data/developer-tools/api). - [Optimize writes to InfluxDB](https://docs.influxdata.com/influxdb/v2.2/write-data/best-practices/optimize-writes/). - [Troubleshoot issues writing data](https://docs.influxdata.com/influxdb/v2.2/write-data/troubleshoot/)\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[39m         returns the request thread.\u001b[39;00m\n\u001b[1;32m     86\u001b[0m \u001b[39m\"\"\"\u001b[39;00m  \u001b[39m# noqa: E501\u001b[39;00m\n\u001b[1;32m     87\u001b[0m local_var_params, path_params, query_params, header_params, body_params \u001b[39m=\u001b[39m \\\n\u001b[1;32m     88\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_post_write_prepare(org, bucket, body, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m---> 90\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mapi_client\u001b[39m.\u001b[39;49mcall_api(\n\u001b[1;32m     91\u001b[0m     \u001b[39m'\u001b[39;49m\u001b[39m/api/v2/write\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39m'\u001b[39;49m\u001b[39mPOST\u001b[39;49m\u001b[39m'\u001b[39;49m,\n\u001b[1;32m     92\u001b[0m     path_params,\n\u001b[1;32m     93\u001b[0m     query_params,\n\u001b[1;32m     94\u001b[0m     header_params,\n\u001b[1;32m     95\u001b[0m     body\u001b[39m=\u001b[39;49mbody_params,\n\u001b[1;32m     96\u001b[0m     post_params\u001b[39m=\u001b[39;49m[],\n\u001b[1;32m     97\u001b[0m     files\u001b[39m=\u001b[39;49m{},\n\u001b[1;32m     98\u001b[0m     response_type\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m,  \u001b[39m# noqa: E501\u001b[39;49;00m\n\u001b[1;32m     99\u001b[0m     auth_settings\u001b[39m=\u001b[39;49m[],\n\u001b[1;32m    100\u001b[0m     async_req\u001b[39m=\u001b[39;49mlocal_var_params\u001b[39m.\u001b[39;49mget(\u001b[39m'\u001b[39;49m\u001b[39masync_req\u001b[39;49m\u001b[39m'\u001b[39;49m),\n\u001b[1;32m    101\u001b[0m     _return_http_data_only\u001b[39m=\u001b[39;49mlocal_var_params\u001b[39m.\u001b[39;49mget(\u001b[39m'\u001b[39;49m\u001b[39m_return_http_data_only\u001b[39;49m\u001b[39m'\u001b[39;49m),  \u001b[39m# noqa: E501\u001b[39;49;00m\n\u001b[1;32m    102\u001b[0m     _preload_content\u001b[39m=\u001b[39;49mlocal_var_params\u001b[39m.\u001b[39;49mget(\u001b[39m'\u001b[39;49m\u001b[39m_preload_content\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39mTrue\u001b[39;49;00m),\n\u001b[1;32m    103\u001b[0m     _request_timeout\u001b[39m=\u001b[39;49mlocal_var_params\u001b[39m.\u001b[39;49mget(\u001b[39m'\u001b[39;49m\u001b[39m_request_timeout\u001b[39;49m\u001b[39m'\u001b[39;49m),\n\u001b[1;32m    104\u001b[0m     collection_formats\u001b[39m=\u001b[39;49m{},\n\u001b[1;32m    105\u001b[0m     urlopen_kw\u001b[39m=\u001b[39;49mkwargs\u001b[39m.\u001b[39;49mget(\u001b[39m'\u001b[39;49m\u001b[39murlopen_kw\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m))\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/_sync/api_client.py:343\u001b[0m, in \u001b[0;36mApiClient.call_api\u001b[0;34m(self, resource_path, method, path_params, query_params, header_params, body, post_params, files, response_type, auth_settings, async_req, _return_http_data_only, collection_formats, _preload_content, _request_timeout, urlopen_kw)\u001b[0m\n\u001b[1;32m    304\u001b[0m \u001b[39m\"\"\"Make the HTTP request (synchronous) and Return deserialized data.\u001b[39;00m\n\u001b[1;32m    305\u001b[0m \n\u001b[1;32m    306\u001b[0m \u001b[39mTo make an async_req request, set the async_req parameter.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    340\u001b[0m \u001b[39m    then the method will return the response directly.\u001b[39;00m\n\u001b[1;32m    341\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    342\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m async_req:\n\u001b[0;32m--> 343\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m__call_api(resource_path, method,\n\u001b[1;32m    344\u001b[0m                            path_params, query_params, header_params,\n\u001b[1;32m    345\u001b[0m                            body, post_params, files,\n\u001b[1;32m    346\u001b[0m                            response_type, auth_settings,\n\u001b[1;32m    347\u001b[0m                            _return_http_data_only, collection_formats,\n\u001b[1;32m    348\u001b[0m                            _preload_content, _request_timeout, urlopen_kw)\n\u001b[1;32m    349\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    350\u001b[0m     thread \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpool\u001b[39m.\u001b[39mapply_async(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m__call_api, (resource_path,\n\u001b[1;32m    351\u001b[0m                                    method, path_params, query_params,\n\u001b[1;32m    352\u001b[0m                                    header_params, body,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    356\u001b[0m                                    collection_formats,\n\u001b[1;32m    357\u001b[0m                                    _preload_content, _request_timeout, urlopen_kw))\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/_sync/api_client.py:173\u001b[0m, in \u001b[0;36mApiClient.__call_api\u001b[0;34m(self, resource_path, method, path_params, query_params, header_params, body, post_params, files, response_type, auth_settings, _return_http_data_only, collection_formats, _preload_content, _request_timeout, urlopen_kw)\u001b[0m\n\u001b[1;32m    170\u001b[0m urlopen_kw \u001b[39m=\u001b[39m urlopen_kw \u001b[39mor\u001b[39;00m {}\n\u001b[1;32m    172\u001b[0m \u001b[39m# perform request and return response\u001b[39;00m\n\u001b[0;32m--> 173\u001b[0m response_data \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrequest(\n\u001b[1;32m    174\u001b[0m     method, url, query_params\u001b[39m=\u001b[39;49mquery_params, headers\u001b[39m=\u001b[39;49mheader_params,\n\u001b[1;32m    175\u001b[0m     post_params\u001b[39m=\u001b[39;49mpost_params, body\u001b[39m=\u001b[39;49mbody,\n\u001b[1;32m    176\u001b[0m     _preload_content\u001b[39m=\u001b[39;49m_preload_content,\n\u001b[1;32m    177\u001b[0m     _request_timeout\u001b[39m=\u001b[39;49m_request_timeout, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49murlopen_kw)\n\u001b[1;32m    179\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlast_response \u001b[39m=\u001b[39m response_data\n\u001b[1;32m    181\u001b[0m return_data \u001b[39m=\u001b[39m response_data\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/_sync/api_client.py:388\u001b[0m, in \u001b[0;36mApiClient.request\u001b[0;34m(self, method, url, query_params, headers, post_params, body, _preload_content, _request_timeout, **urlopen_kw)\u001b[0m\n\u001b[1;32m    379\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrest_client\u001b[39m.\u001b[39mOPTIONS(url,\n\u001b[1;32m    380\u001b[0m                                     query_params\u001b[39m=\u001b[39mquery_params,\n\u001b[1;32m    381\u001b[0m                                     headers\u001b[39m=\u001b[39mheaders,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    385\u001b[0m                                     body\u001b[39m=\u001b[39mbody,\n\u001b[1;32m    386\u001b[0m                                     \u001b[39m*\u001b[39m\u001b[39m*\u001b[39murlopen_kw)\n\u001b[1;32m    387\u001b[0m \u001b[39melif\u001b[39;00m method \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mPOST\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m--> 388\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrest_client\u001b[39m.\u001b[39;49mPOST(url,\n\u001b[1;32m    389\u001b[0m                                  query_params\u001b[39m=\u001b[39;49mquery_params,\n\u001b[1;32m    390\u001b[0m                                  headers\u001b[39m=\u001b[39;49mheaders,\n\u001b[1;32m    391\u001b[0m                                  post_params\u001b[39m=\u001b[39;49mpost_params,\n\u001b[1;32m    392\u001b[0m                                  _preload_content\u001b[39m=\u001b[39;49m_preload_content,\n\u001b[1;32m    393\u001b[0m                                  _request_timeout\u001b[39m=\u001b[39;49m_request_timeout,\n\u001b[1;32m    394\u001b[0m                                  body\u001b[39m=\u001b[39;49mbody,\n\u001b[1;32m    395\u001b[0m                                  \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49murlopen_kw)\n\u001b[1;32m    396\u001b[0m \u001b[39melif\u001b[39;00m method \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mPUT\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m    397\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrest_client\u001b[39m.\u001b[39mPUT(url,\n\u001b[1;32m    398\u001b[0m                                 query_params\u001b[39m=\u001b[39mquery_params,\n\u001b[1;32m    399\u001b[0m                                 headers\u001b[39m=\u001b[39mheaders,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    403\u001b[0m                                 body\u001b[39m=\u001b[39mbody,\n\u001b[1;32m    404\u001b[0m                                 \u001b[39m*\u001b[39m\u001b[39m*\u001b[39murlopen_kw)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/_sync/rest.py:311\u001b[0m, in \u001b[0;36mRESTClientObject.POST\u001b[0;34m(self, url, headers, query_params, post_params, body, _preload_content, _request_timeout, **urlopen_kw)\u001b[0m\n\u001b[1;32m    308\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mPOST\u001b[39m(\u001b[39mself\u001b[39m, url, headers\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, query_params\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, post_params\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m,\n\u001b[1;32m    309\u001b[0m          body\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, _preload_content\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m, _request_timeout\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39murlopen_kw):\n\u001b[1;32m    310\u001b[0m     \u001b[39m\"\"\"Perform POST HTTP request.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 311\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrequest(\u001b[39m\"\u001b[39;49m\u001b[39mPOST\u001b[39;49m\u001b[39m\"\u001b[39;49m, url,\n\u001b[1;32m    312\u001b[0m                         headers\u001b[39m=\u001b[39;49mheaders,\n\u001b[1;32m    313\u001b[0m                         query_params\u001b[39m=\u001b[39;49mquery_params,\n\u001b[1;32m    314\u001b[0m                         post_params\u001b[39m=\u001b[39;49mpost_params,\n\u001b[1;32m    315\u001b[0m                         _preload_content\u001b[39m=\u001b[39;49m_preload_content,\n\u001b[1;32m    316\u001b[0m                         _request_timeout\u001b[39m=\u001b[39;49m_request_timeout,\n\u001b[1;32m    317\u001b[0m                         body\u001b[39m=\u001b[39;49mbody,\n\u001b[1;32m    318\u001b[0m                         \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49murlopen_kw)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/influxdb_client/_sync/rest.py:220\u001b[0m, in \u001b[0;36mRESTClientObject.request\u001b[0;34m(self, method, url, query_params, headers, body, post_params, _preload_content, _request_timeout, **urlopen_kw)\u001b[0m\n\u001b[1;32m    218\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(body, \u001b[39mstr\u001b[39m) \u001b[39mor\u001b[39;00m \u001b[39misinstance\u001b[39m(body, \u001b[39mbytes\u001b[39m):\n\u001b[1;32m    219\u001b[0m     request_body \u001b[39m=\u001b[39m body\n\u001b[0;32m--> 220\u001b[0m     r \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpool_manager\u001b[39m.\u001b[39;49mrequest(\n\u001b[1;32m    221\u001b[0m         method, url,\n\u001b[1;32m    222\u001b[0m         body\u001b[39m=\u001b[39;49mrequest_body,\n\u001b[1;32m    223\u001b[0m         preload_content\u001b[39m=\u001b[39;49m_preload_content,\n\u001b[1;32m    224\u001b[0m         timeout\u001b[39m=\u001b[39;49mtimeout,\n\u001b[1;32m    225\u001b[0m         headers\u001b[39m=\u001b[39;49mheaders,\n\u001b[1;32m    226\u001b[0m         \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49murlopen_kw)\n\u001b[1;32m    227\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    228\u001b[0m     \u001b[39m# Cannot generate the request from given parameters\u001b[39;00m\n\u001b[1;32m    229\u001b[0m     msg \u001b[39m=\u001b[39m \u001b[39m\"\"\"\u001b[39m\u001b[39mCannot prepare a request message for provided\u001b[39m\n\u001b[1;32m    230\u001b[0m \u001b[39m             arguments. Please check that your arguments match\u001b[39m\n\u001b[1;32m    231\u001b[0m \u001b[39m             declared content type.\u001b[39m\u001b[39m\"\"\"\u001b[39m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/request.py:78\u001b[0m, in \u001b[0;36mRequestMethods.request\u001b[0;34m(self, method, url, fields, headers, **urlopen_kw)\u001b[0m\n\u001b[1;32m     74\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrequest_encode_url(\n\u001b[1;32m     75\u001b[0m         method, url, fields\u001b[39m=\u001b[39mfields, headers\u001b[39m=\u001b[39mheaders, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39murlopen_kw\n\u001b[1;32m     76\u001b[0m     )\n\u001b[1;32m     77\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m---> 78\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrequest_encode_body(\n\u001b[1;32m     79\u001b[0m         method, url, fields\u001b[39m=\u001b[39;49mfields, headers\u001b[39m=\u001b[39;49mheaders, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49murlopen_kw\n\u001b[1;32m     80\u001b[0m     )\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/request.py:170\u001b[0m, in \u001b[0;36mRequestMethods.request_encode_body\u001b[0;34m(self, method, url, fields, headers, encode_multipart, multipart_boundary, **urlopen_kw)\u001b[0m\n\u001b[1;32m    167\u001b[0m extra_kw[\u001b[39m\"\u001b[39m\u001b[39mheaders\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m.\u001b[39mupdate(headers)\n\u001b[1;32m    168\u001b[0m extra_kw\u001b[39m.\u001b[39mupdate(urlopen_kw)\n\u001b[0;32m--> 170\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49murlopen(method, url, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mextra_kw)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/poolmanager.py:376\u001b[0m, in \u001b[0;36mPoolManager.urlopen\u001b[0;34m(self, method, url, redirect, **kw)\u001b[0m\n\u001b[1;32m    374\u001b[0m     response \u001b[39m=\u001b[39m conn\u001b[39m.\u001b[39murlopen(method, url, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkw)\n\u001b[1;32m    375\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 376\u001b[0m     response \u001b[39m=\u001b[39m conn\u001b[39m.\u001b[39;49murlopen(method, u\u001b[39m.\u001b[39;49mrequest_uri, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkw)\n\u001b[1;32m    378\u001b[0m redirect_location \u001b[39m=\u001b[39m redirect \u001b[39mand\u001b[39;00m response\u001b[39m.\u001b[39mget_redirect_location()\n\u001b[1;32m    379\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m redirect_location:\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connectionpool.py:787\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    784\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(e, (SocketError, HTTPException)):\n\u001b[1;32m    785\u001b[0m     e \u001b[39m=\u001b[39m ProtocolError(\u001b[39m\"\u001b[39m\u001b[39mConnection aborted.\u001b[39m\u001b[39m\"\u001b[39m, e)\n\u001b[0;32m--> 787\u001b[0m retries \u001b[39m=\u001b[39m retries\u001b[39m.\u001b[39;49mincrement(\n\u001b[1;32m    788\u001b[0m     method, url, error\u001b[39m=\u001b[39;49me, _pool\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m, _stacktrace\u001b[39m=\u001b[39;49msys\u001b[39m.\u001b[39;49mexc_info()[\u001b[39m2\u001b[39;49m]\n\u001b[1;32m    789\u001b[0m )\n\u001b[1;32m    790\u001b[0m retries\u001b[39m.\u001b[39msleep()\n\u001b[1;32m    792\u001b[0m \u001b[39m# Keep track of the error for the retry warning.\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/util/retry.py:525\u001b[0m, in \u001b[0;36mRetry.increment\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m    513\u001b[0m \u001b[39m\"\"\"Return a new Retry object with incremented retry counters.\u001b[39;00m\n\u001b[1;32m    514\u001b[0m \n\u001b[1;32m    515\u001b[0m \u001b[39m:param response: A response object, or None, if the server did not\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    521\u001b[0m \u001b[39m:return: A new ``Retry`` object.\u001b[39;00m\n\u001b[1;32m    522\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    523\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtotal \u001b[39mis\u001b[39;00m \u001b[39mFalse\u001b[39;00m \u001b[39mand\u001b[39;00m error:\n\u001b[1;32m    524\u001b[0m     \u001b[39m# Disabled, indicate to re-raise the error.\u001b[39;00m\n\u001b[0;32m--> 525\u001b[0m     \u001b[39mraise\u001b[39;00m six\u001b[39m.\u001b[39;49mreraise(\u001b[39mtype\u001b[39;49m(error), error, _stacktrace)\n\u001b[1;32m    527\u001b[0m total \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtotal\n\u001b[1;32m    528\u001b[0m \u001b[39mif\u001b[39;00m total \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/packages/six.py:770\u001b[0m, in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m    768\u001b[0m     \u001b[39mif\u001b[39;00m value\u001b[39m.\u001b[39m__traceback__ \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m tb:\n\u001b[1;32m    769\u001b[0m         \u001b[39mraise\u001b[39;00m value\u001b[39m.\u001b[39mwith_traceback(tb)\n\u001b[0;32m--> 770\u001b[0m     \u001b[39mraise\u001b[39;00m value\n\u001b[1;32m    771\u001b[0m \u001b[39mfinally\u001b[39;00m:\n\u001b[1;32m    772\u001b[0m     value \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connectionpool.py:703\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    700\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_prepare_proxy(conn)\n\u001b[1;32m    702\u001b[0m \u001b[39m# Make the request on the httplib connection object.\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m httplib_response \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_make_request(\n\u001b[1;32m    704\u001b[0m     conn,\n\u001b[1;32m    705\u001b[0m     method,\n\u001b[1;32m    706\u001b[0m     url,\n\u001b[1;32m    707\u001b[0m     timeout\u001b[39m=\u001b[39;49mtimeout_obj,\n\u001b[1;32m    708\u001b[0m     body\u001b[39m=\u001b[39;49mbody,\n\u001b[1;32m    709\u001b[0m     headers\u001b[39m=\u001b[39;49mheaders,\n\u001b[1;32m    710\u001b[0m     chunked\u001b[39m=\u001b[39;49mchunked,\n\u001b[1;32m    711\u001b[0m )\n\u001b[1;32m    713\u001b[0m \u001b[39m# If we're going to release the connection in ``finally:``, then\u001b[39;00m\n\u001b[1;32m    714\u001b[0m \u001b[39m# the response doesn't need to know about the connection. Otherwise\u001b[39;00m\n\u001b[1;32m    715\u001b[0m \u001b[39m# it will also try to release it and we'll have a double-release\u001b[39;00m\n\u001b[1;32m    716\u001b[0m \u001b[39m# mess.\u001b[39;00m\n\u001b[1;32m    717\u001b[0m response_conn \u001b[39m=\u001b[39m conn \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m release_conn \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connectionpool.py:398\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    396\u001b[0m         conn\u001b[39m.\u001b[39mrequest_chunked(method, url, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mhttplib_request_kw)\n\u001b[1;32m    397\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 398\u001b[0m         conn\u001b[39m.\u001b[39;49mrequest(method, url, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mhttplib_request_kw)\n\u001b[1;32m    400\u001b[0m \u001b[39m# We are swallowing BrokenPipeError (errno.EPIPE) since the server is\u001b[39;00m\n\u001b[1;32m    401\u001b[0m \u001b[39m# legitimately able to close the connection after sending a valid response.\u001b[39;00m\n\u001b[1;32m    402\u001b[0m \u001b[39m# With this behaviour, the received response is still readable.\u001b[39;00m\n\u001b[1;32m    403\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mBrokenPipeError\u001b[39;00m:\n\u001b[1;32m    404\u001b[0m     \u001b[39m# Python 3\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connection.py:239\u001b[0m, in \u001b[0;36mHTTPConnection.request\u001b[0;34m(self, method, url, body, headers)\u001b[0m\n\u001b[1;32m    237\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39muser-agent\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m (six\u001b[39m.\u001b[39mensure_str(k\u001b[39m.\u001b[39mlower()) \u001b[39mfor\u001b[39;00m k \u001b[39min\u001b[39;00m headers):\n\u001b[1;32m    238\u001b[0m     headers[\u001b[39m\"\u001b[39m\u001b[39mUser-Agent\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m _get_default_user_agent()\n\u001b[0;32m--> 239\u001b[0m \u001b[39msuper\u001b[39;49m(HTTPConnection, \u001b[39mself\u001b[39;49m)\u001b[39m.\u001b[39;49mrequest(method, url, body\u001b[39m=\u001b[39;49mbody, headers\u001b[39m=\u001b[39;49mheaders)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/http/client.py:1285\u001b[0m, in \u001b[0;36mHTTPConnection.request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1282\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mrequest\u001b[39m(\u001b[39mself\u001b[39m, method, url, body\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, headers\u001b[39m=\u001b[39m{}, \u001b[39m*\u001b[39m,\n\u001b[1;32m   1283\u001b[0m             encode_chunked\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m):\n\u001b[1;32m   1284\u001b[0m     \u001b[39m\"\"\"Send a complete request to the server.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1285\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_send_request(method, url, body, headers, encode_chunked)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/http/client.py:1331\u001b[0m, in \u001b[0;36mHTTPConnection._send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m   1327\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(body, \u001b[39mstr\u001b[39m):\n\u001b[1;32m   1328\u001b[0m     \u001b[39m# RFC 2616 Section 3.7.1 says that text default has a\u001b[39;00m\n\u001b[1;32m   1329\u001b[0m     \u001b[39m# default charset of iso-8859-1.\u001b[39;00m\n\u001b[1;32m   1330\u001b[0m     body \u001b[39m=\u001b[39m _encode(body, \u001b[39m'\u001b[39m\u001b[39mbody\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m-> 1331\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mendheaders(body, encode_chunked\u001b[39m=\u001b[39;49mencode_chunked)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/http/client.py:1280\u001b[0m, in \u001b[0;36mHTTPConnection.endheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1278\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   1279\u001b[0m     \u001b[39mraise\u001b[39;00m CannotSendHeader()\n\u001b[0;32m-> 1280\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_send_output(message_body, encode_chunked\u001b[39m=\u001b[39;49mencode_chunked)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/http/client.py:1040\u001b[0m, in \u001b[0;36mHTTPConnection._send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m   1038\u001b[0m msg \u001b[39m=\u001b[39m \u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m\\r\u001b[39;00m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mjoin(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_buffer)\n\u001b[1;32m   1039\u001b[0m \u001b[39mdel\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_buffer[:]\n\u001b[0;32m-> 1040\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msend(msg)\n\u001b[1;32m   1042\u001b[0m \u001b[39mif\u001b[39;00m message_body \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m   1043\u001b[0m \n\u001b[1;32m   1044\u001b[0m     \u001b[39m# create a consistent interface to message_body\u001b[39;00m\n\u001b[1;32m   1045\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mhasattr\u001b[39m(message_body, \u001b[39m'\u001b[39m\u001b[39mread\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[1;32m   1046\u001b[0m         \u001b[39m# Let file-like take precedence over byte-like.  This\u001b[39;00m\n\u001b[1;32m   1047\u001b[0m         \u001b[39m# is needed to allow the current position of mmap'ed\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m         \u001b[39m# files to be taken into account.\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/http/client.py:980\u001b[0m, in \u001b[0;36mHTTPConnection.send\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    978\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msock \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    979\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mauto_open:\n\u001b[0;32m--> 980\u001b[0m         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mconnect()\n\u001b[1;32m    981\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    982\u001b[0m         \u001b[39mraise\u001b[39;00m NotConnected()\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connection.py:205\u001b[0m, in \u001b[0;36mHTTPConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    204\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mconnect\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 205\u001b[0m     conn \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_new_conn()\n\u001b[1;32m    206\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_prepare_conn(conn)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/TSSTORE/lib/python3.9/site-packages/urllib3/connection.py:186\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    179\u001b[0m     \u001b[39mraise\u001b[39;00m ConnectTimeoutError(\n\u001b[1;32m    180\u001b[0m         \u001b[39mself\u001b[39m,\n\u001b[1;32m    181\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mConnection to \u001b[39m\u001b[39m%s\u001b[39;00m\u001b[39m timed out. (connect timeout=\u001b[39m\u001b[39m%s\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    182\u001b[0m         \u001b[39m%\u001b[39m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhost, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtimeout),\n\u001b[1;32m    183\u001b[0m     )\n\u001b[1;32m    185\u001b[0m \u001b[39mexcept\u001b[39;00m SocketError \u001b[39mas\u001b[39;00m e:\n\u001b[0;32m--> 186\u001b[0m     \u001b[39mraise\u001b[39;00m NewConnectionError(\n\u001b[1;32m    187\u001b[0m         \u001b[39mself\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39mFailed to establish a new connection: \u001b[39m\u001b[39m%s\u001b[39;00m\u001b[39m\"\u001b[39m \u001b[39m%\u001b[39m e\n\u001b[1;32m    188\u001b[0m     )\n\u001b[1;32m    190\u001b[0m \u001b[39mreturn\u001b[39;00m conn\n",
      "\u001b[0;31mNewConnectionError\u001b[0m: <urllib3.connection.HTTPConnection object at 0x7fb7fac2f610>: Failed to establish a new connection: [Errno 61] Connection refused"
     ]
    }
   ],
   "source": [
    "# Write data to database\n",
    "\n",
    "url = \"http://localhost:8086\"\n",
    "bucket = \"testBucket\"\n",
    "token=\"L9aO2ZCpKWUV-jZncfsXB0CauuwrChRbOwC5PtcjzWFXGkE75lh24NTpIanN-aYXMCMgOTsJpcM8sUrJWL0tCw==\"\n",
    "\n",
    "with InfluxDBClient(url=url, token=token, org=\"teco\") as client:\n",
    "   res = client.write_api(write_options=SYNCHRONOUS).write(bucket=bucket, record=df, data_frame_measurement_name=\"weather\", data_frame_timestamp_column=\"time\")\n",
    "   print(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'function' object has no attribute 'query'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[35], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m InfluxDBClient(url\u001b[38;5;241m=\u001b[39murl, token\u001b[38;5;241m=\u001b[39mtoken, org\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mteco\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m client:\n\u001b[1;32m      2\u001b[0m     \u001b[38;5;28mprint\u001b[39m(client\u001b[38;5;241m.\u001b[39mping())\n\u001b[0;32m----> 3\u001b[0m     \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquery_api\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquery\u001b[49m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfrom(bucket:\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtestBucket\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'function' object has no attribute 'query'"
     ]
    }
   ],
   "source": [
    "with InfluxDBClient(url=url, token=token, org=\"teco\") as client:\n",
    "    print(client.ping())\n",
    "    client.query_api().query('from(bucket:\"testBucket\")')"
   ]
  }
 ],
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   "file_extension": ".py",
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