hello_ape_infura.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 51,
      "id": "163d83d4",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "All packages installed\n"
          ]
        }
      ],
      "source": [
        "import pkg_resources\n",
        "from darkmode import darkmode_orange # pylint: disable=unused-import\n",
        "try:\n",
        "    pkg_resources.require(['eth-ape','ape-alchemy','ape-etherscan','mplfinance', 'pandas', 'numpy', 'python-dotenv'])\n",
        "    print('All packages installed')\n",
        "except:\n",
        "    !pip3 install eth-ape ape-alchemy ape-etherscan mplfinance pandas numpy python-dotenv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "id": "b407728b",
      "metadata": {
        "id": "b407728b"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import mplfinance as mpf\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import typing as tp\n",
        "import os\n",
        "from ape import accounts, chain, Contract, networks"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "id": "u22HsueI9E7Y",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u22HsueI9E7Y",
        "outputId": "2bd1cf8a-53be-47e6-f323-b70f0f11641c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 53,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# manually input your keys like this\n",
        "# %env WEB3_ALCHEMY_API_KEY = xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\n",
        "# %env ETHERSCAN_API = xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\n",
        "\n",
        "# or load from a separate \".env\" file, which is more secure!\n",
        "from dotenv import load_dotenv\n",
        "load_dotenv()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "id": "e0a51bfd",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e0a51bfd",
        "outputId": "5687888d-896e-4455-b53c-22b2002f42f3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "INFO: Connecting to existing Geth node at  https://mainnet.infura.io/v3/0adcd5893aa345109328472d2ddd0426.\n",
            "ape version: 0.6.8\n",
            "provider.config of type=<class 'ape_geth.provider.GethConfig'>\n",
            " extra = allow\n"
          ]
        }
      ],
      "source": [
        "context = networks.parse_network_choice(f\"ethereum:mainnet:https://mainnet.infura.io/v3/{os.getenv('INFURA_API_KEY')}\")\n",
        "context.__enter__()\n",
        "print(f\"ape version: {pkg_resources.get_distribution('eth-ape').version}\")\n",
        "print(f\"provider.config of type={type(context.provider.config)}\")\n",
        "for k,v in context.provider.config.Config.__dict__.items():\n",
        "    if not k.startswith('__'):\n",
        "        print(f\" {k} = {v}\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "id": "01fd094e",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "plugin_name=alchemy, ecosystem_class=('ethereum', 'mainnet', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('ethereum', 'goerli', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('ethereum', 'sepolia', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('arbitrum', 'mainnet', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('arbitrum', 'goerli', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('optimism', 'mainnet', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('optimism', 'goerli', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('polygon', 'mainnet', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=alchemy, ecosystem_class=('polygon', 'mumbai', <class 'ape_alchemy.provider.Alchemy'>)\n",
            "plugin_name=test, ecosystem_class=('ethereum', 'local', <class 'ape_test.provider.LocalProvider'>)\n",
            "plugin_name=geth, ecosystem_class=('ethereum', 'mainnet', <class 'ape_geth.provider.Geth'>)\n",
            "plugin_name=geth, ecosystem_class=('ethereum', 'goerli', <class 'ape_geth.provider.Geth'>)\n",
            "plugin_name=geth, ecosystem_class=('ethereum', 'sepolia', <class 'ape_geth.provider.Geth'>)\n",
            "plugin_name=geth, ecosystem_class=('ethereum', 'local', <class 'ape_geth.provider.GethDev'>)\n"
          ]
        }
      ],
      "source": [
        "# list plugins and available networks\n",
        "for plugin_name, ecosystem_class in context.plugin_manager.providers:\n",
        "    print(f\"plugin_name={plugin_name}, ecosystem_class={ecosystem_class}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "id": "069b902c",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "069b902c",
        "outputId": "0bda7f20-00da-4c3c-bcaa-c2ad348f8dd9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "dev.balance=0\n"
          ]
        }
      ],
      "source": [
        "# get an account that you can use\n",
        "dev = accounts.test_accounts[0]\n",
        "print(f\"{dev.balance=}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "id": "542dac5f",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "542dac5f",
        "outputId": "d735edfb-1e3b-4b7d-c574-0102e34c72b1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "current_block=17192524\n"
          ]
        }
      ],
      "source": [
        "current_block = chain.blocks[-1].number\n",
        "print(f\"{current_block=}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "id": "f558faa8",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f558faa8",
        "outputId": "cb48b02b-e8f8-4feb-86f9-51eae31b5551",
        "scrolled": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "starting block is 14,564,524 for 365 day lookback\n"
          ]
        }
      ],
      "source": [
        "# determine starting block for the query\n",
        "seconds_in_day = 86400\n",
        "seconds_in_block = 12\n",
        "last_number_of_days = 365\n",
        "dblocks = int(seconds_in_day*last_number_of_days/seconds_in_block)\n",
        "start_block = current_block - dblocks\n",
        "print(f\"starting block is {start_block:,.0f} for {last_number_of_days} day lookback\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "id": "5842fa52",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5842fa52",
        "outputId": "23b22b4a-8365-4ff5-be39-e8d6aab458ac"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "balance of curve_steth is 346,230 stETH\n"
          ]
        }
      ],
      "source": [
        "# set up contracts, ABIs come from Etherscan\n",
        "curve_steth = Contract(\"0xDC24316b9AE028F1497c275EB9192a3Ea0f67022\")\n",
        "steth = Contract(\"0xae7ab96520DE3A18E5e111B5EaAb095312D7fE84\")\n",
        "print(f\"balance of curve_steth is {steth.balanceOf(curve_steth)/1e18:,.0f} stETH\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "id": "7e281650",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7e281650",
        "outputId": "3d54375f-1834-42ce-84ca-c68ad75aea7f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "TokenExchange(address indexed buyer, int128 sold_id, uint256 tokens_sold, int128 bought_id, uint256 tokens_bought)"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "ape.contracts.base.ContractEvent"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# identify the event we want to query\n",
        "display(curve_steth.TokenExchange)\n",
        "display(type(curve_steth.TokenExchange))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "id": "629e5e2e",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 650
        },
        "id": "629e5e2e",
        "outputId": "6ca67714-d718-4393-c36a-dfee8329ce2a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 37.9 ms, sys: 3.48 ms, total: 41.4 ms\n",
            "Wall time: 201 ms\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0x1199193579d9e9c6f1293998bf3a8d0a65ae9d201237...</td>\n",
              "      <td>17189594</td>\n",
              "      <td>0x3014ab7656a231ffedebdce7305fbc4b1645407f233a...</td>\n",
              "      <td>221</td>\n",
              "      <td>92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x0000000000a84D1a9B0063A910315C7fF...</td>\n",
              "      <td>0x580bbebbc02181ad22db6a15d9a79e9e14af57b1712c...</td>\n",
              "      <td>17189597</td>\n",
              "      <td>0x001ccee0428ac670e7006943342de872e2d6ee6defd8...</td>\n",
              "      <td>23</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x1136B25047E142Fa3018184793aEc68fB...</td>\n",
              "      <td>0x1c7e2dbd76df5c7f1537d9d5377304e397be2b400c2b...</td>\n",
              "      <td>17189626</td>\n",
              "      <td>0xf22056cf429f214969a7d811a045aa31358aa29f1706...</td>\n",
              "      <td>245</td>\n",
              "      <td>76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xd669621C0F97B11f8E74Fa57bBF7e33dF...</td>\n",
              "      <td>0x4f45bca0a92453500d8a476063dbf2db7d801ed44571...</td>\n",
              "      <td>17189783</td>\n",
              "      <td>0x266aac769698dad8ae37c89cb887969904d7ade40c1b...</td>\n",
              "      <td>213</td>\n",
              "      <td>75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0xb7b47a182c22581aa0376771310db7d3f6ce0d74afb7...</td>\n",
              "      <td>17189816</td>\n",
              "      <td>0x862907da53a084381c2604e7b018cb510e154f8db511...</td>\n",
              "      <td>108</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      event_name                            contract_address  \\\n",
              "0  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "1  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "2  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "3  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "4  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                     event_arguments  \\\n",
              "0  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "1  {'buyer': '0x0000000000a84D1a9B0063A910315C7fF...   \n",
              "2  {'buyer': '0x1136B25047E142Fa3018184793aEc68fB...   \n",
              "3  {'buyer': '0xd669621C0F97B11f8E74Fa57bBF7e33dF...   \n",
              "4  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "\n",
              "                                    transaction_hash  block_number  \\\n",
              "0  0x1199193579d9e9c6f1293998bf3a8d0a65ae9d201237...      17189594   \n",
              "1  0x580bbebbc02181ad22db6a15d9a79e9e14af57b1712c...      17189597   \n",
              "2  0x1c7e2dbd76df5c7f1537d9d5377304e397be2b400c2b...      17189626   \n",
              "3  0x4f45bca0a92453500d8a476063dbf2db7d801ed44571...      17189783   \n",
              "4  0xb7b47a182c22581aa0376771310db7d3f6ce0d74afb7...      17189816   \n",
              "\n",
              "                                          block_hash  log_index  \\\n",
              "0  0x3014ab7656a231ffedebdce7305fbc4b1645407f233a...        221   \n",
              "1  0x001ccee0428ac670e7006943342de872e2d6ee6defd8...         23   \n",
              "2  0xf22056cf429f214969a7d811a045aa31358aa29f1706...        245   \n",
              "3  0x266aac769698dad8ae37c89cb887969904d7ade40c1b...        213   \n",
              "4  0x862907da53a084381c2604e7b018cb510e154f8db511...        108   \n",
              "\n",
              "   transaction_index  \n",
              "0                 92  \n",
              "1                  3  \n",
              "2                 76  \n",
              "3                 75  \n",
              "4                 16  "
            ]
          },
          "execution_count": 61,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# query it\n",
        "%time query_swaps_recent = curve_steth.TokenExchange.query(\"*\", start_block=current_block-3000) # last 10 hr\n",
        "query_swaps_recent.head(5) # it's a pandas dataframe 🙌"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "id": "61f9b0b8",
      "metadata": {
        "id": "61f9b0b8",
        "outputId": "4e0a4fd2-cb26-428b-f452-e5ba0c0b726c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85C178C18',\n",
              " 'sold_id': 0,\n",
              " 'tokens_sold': 1066757696656800,\n",
              " 'bought_id': 1,\n",
              " 'tokens_bought': 1066758029431578}"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# the event arguments field is a dict of the event arguments\n",
        "display(query_swaps_recent[\"event_arguments\"][0])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "id": "29580294",
      "metadata": {
        "id": "29580294",
        "outputId": "20c9ebf4-9c31-4c21-ed4c-fd3a93e887d6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 22.1 s, sys: 403 ms, total: 22.5 s\n",
            "Wall time: 19.6 s\n"
          ]
        },
        {
          "data": {
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              "    }\n",
              "\n",
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              "        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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...</td>\n",
              "      <td>0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...</td>\n",
              "      <td>14564536</td>\n",
              "      <td>0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...</td>\n",
              "      <td>486</td>\n",
              "      <td>288</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x8e764bE4288B842791989DB5b8ec06727...</td>\n",
              "      <td>0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...</td>\n",
              "      <td>14564686</td>\n",
              "      <td>0x6f365e20679769f1ede16e367b116c73a821da1c45cf...</td>\n",
              "      <td>143</td>\n",
              "      <td>55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...</td>\n",
              "      <td>14564717</td>\n",
              "      <td>0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...</td>\n",
              "      <td>237</td>\n",
              "      <td>139</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...</td>\n",
              "      <td>0x666c9ce15b870eab687fbda36866211e1e418294be2a...</td>\n",
              "      <td>14564751</td>\n",
              "      <td>0xd05bcdd6fab11f4433853397b401bcba774e74de5384...</td>\n",
              "      <td>214</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...</td>\n",
              "      <td>0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...</td>\n",
              "      <td>14564765</td>\n",
              "      <td>0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...</td>\n",
              "      <td>103</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      event_name                            contract_address  \\\n",
              "0  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "1  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "2  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "3  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "4  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                     event_arguments  \\\n",
              "0  {'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...   \n",
              "1  {'buyer': '0x8e764bE4288B842791989DB5b8ec06727...   \n",
              "2  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "3  {'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...   \n",
              "4  {'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...   \n",
              "\n",
              "                                    transaction_hash  block_number  \\\n",
              "0  0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...      14564536   \n",
              "1  0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...      14564686   \n",
              "2  0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...      14564717   \n",
              "3  0x666c9ce15b870eab687fbda36866211e1e418294be2a...      14564751   \n",
              "4  0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...      14564765   \n",
              "\n",
              "                                          block_hash  log_index  \\\n",
              "0  0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...        486   \n",
              "1  0x6f365e20679769f1ede16e367b116c73a821da1c45cf...        143   \n",
              "2  0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...        237   \n",
              "3  0xd05bcdd6fab11f4433853397b401bcba774e74de5384...        214   \n",
              "4  0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...        103   \n",
              "\n",
              "   transaction_index  \n",
              "0                288  \n",
              "1                 55  \n",
              "2                139  \n",
              "3                 90  \n",
              "4                 57  "
            ]
          },
          "execution_count": 63,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# ok great. let's look a bit further into the past to start_block from above. see how long it takes\n",
        "%time query_swaps_original = curve_steth.TokenExchange.query(\"*\", start_block=start_block)\n",
        "query_swaps_original.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "id": "a09591e3",
      "metadata": {
        "id": "a09591e3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "query_swaps shrunk from 67942 to 67938 rows by removing 4 rows with tokens_sold=0\n"
          ]
        }
      ],
      "source": [
        "query_swaps = query_swaps_original.copy()\n",
        "query_swaps[\"tokens_sold\"] = query_swaps[\"event_arguments\"].apply(lambda x: x[\"tokens_sold\"])\n",
        "query_swaps = query_swaps.loc[query_swaps['tokens_sold'] > 0,:]\n",
        "print(f\"query_swaps shrunk from {len(query_swaps_original)} to {len(query_swaps)} rows by removing {len(query_swaps_original)-len(query_swaps)} rows with tokens_sold=0\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "id": "11b8e5ca",
      "metadata": {
        "id": "11b8e5ca",
        "outputId": "c8ad66ce-4517-45af-e8fe-29d059cadbd2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "coin_indices=['0xEeeeeEeeeEeEeeEeEeEeeEEEeeeeEeeeeeeeEEeE', '0xae7ab96520DE3A18E5e111B5EaAb095312D7fE84']\n"
          ]
        }
      ],
      "source": [
        "# get coin indices:\n",
        "#  - 0 = ETH (native)\n",
        "#  - 1 = stETH\n",
        "coin_indices = [curve_steth.coins(i) for i in range(2)]\n",
        "print(f\"{coin_indices=}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "id": "65b54df5",
      "metadata": {
        "id": "65b54df5",
        "outputId": "7f11c1f7-98df-4038-a657-52045e22a692"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 66,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "steth.address == coin_indices[-1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "id": "a1801ec8",
      "metadata": {
        "id": "a1801ec8",
        "outputId": "f051e810-5af7-4479-c712-928141bbeba1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "curve_steth_fee=0.0004\n"
          ]
        }
      ],
      "source": [
        "# cache the fee to calculate associated price correctly (prior to fees applied)\n",
        "curve_steth_fee = curve_steth.fee() / 1e10  # fee denom is 1e10\n",
        "print(f\"{curve_steth_fee=}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "id": "9db01db2",
      "metadata": {
        "id": "9db01db2",
        "outputId": "6d115ba4-cd75-449d-e995-bec06e224a2f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "last swap event: {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF489b5788f', 'sold_id': 1, 'tokens_sold': 17000000000000000000, 'bought_id': 0, 'tokens_bought': 16984657814864192582}\n",
            "price: 0.9994971575288316\n"
          ]
        }
      ],
      "source": [
        "# if sold_id == 1, then selling stETH for ETH, which is price wanted\n",
        "#  i.e. quote = <ETH>, base = <stETH>\n",
        "last_swap = query_swaps[\"event_arguments\"].iloc[-1]\n",
        "print('last swap event:', last_swap)\n",
        "\n",
        "last_price = last_swap['tokens_bought'] * (1+curve_steth_fee) / last_swap['tokens_sold']\n",
        "if last_swap['sold_id'] == 0:\n",
        "    last_price = 1 / last_price\n",
        "print('price:', last_price)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "id": "05daceae",
      "metadata": {
        "id": "05daceae"
      },
      "outputs": [],
      "source": [
        "# write a function that iterates over event_arguments to calculate marginal price from last token swap\n",
        "def get_price(event_args: dict) -> float:\n",
        "    price = event_args['tokens_bought'] * (1+curve_steth_fee) / event_args['tokens_sold']\n",
        "    if event_args['sold_id'] == 0:\n",
        "        price = 1 / price\n",
        "    return price"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 70,
      "id": "8f06306a",
      "metadata": {
        "id": "8f06306a",
        "outputId": "3f5df51d-f7ca-40ec-9832-3127e7504d14"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 70,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# validate with logic in cell above for last price\n",
        "get_price(query_swaps[\"event_arguments\"].iloc[-1]) == last_price"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "id": "18eede99",
      "metadata": {
        "id": "18eede99",
        "outputId": "93da2148-fed2-4df1-9191-52902d44b568"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 54.4 ms, sys: 0 ns, total: 54.4 ms\n",
            "Wall time: 53.7 ms\n"
          ]
        },
        {
          "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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "      <th>tokens_sold</th>\n",
              "      <th>price (STETH/ETH)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...</td>\n",
              "      <td>0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...</td>\n",
              "      <td>14564536</td>\n",
              "      <td>0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...</td>\n",
              "      <td>486</td>\n",
              "      <td>288</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.998864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x8e764bE4288B842791989DB5b8ec06727...</td>\n",
              "      <td>0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...</td>\n",
              "      <td>14564686</td>\n",
              "      <td>0x6f365e20679769f1ede16e367b116c73a821da1c45cf...</td>\n",
              "      <td>143</td>\n",
              "      <td>55</td>\n",
              "      <td>4030795658071524182</td>\n",
              "      <td>0.998864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...</td>\n",
              "      <td>14564717</td>\n",
              "      <td>0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...</td>\n",
              "      <td>237</td>\n",
              "      <td>139</td>\n",
              "      <td>29027981991561935158</td>\n",
              "      <td>0.998863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...</td>\n",
              "      <td>0x666c9ce15b870eab687fbda36866211e1e418294be2a...</td>\n",
              "      <td>14564751</td>\n",
              "      <td>0xd05bcdd6fab11f4433853397b401bcba774e74de5384...</td>\n",
              "      <td>214</td>\n",
              "      <td>90</td>\n",
              "      <td>5579999000001067821</td>\n",
              "      <td>0.998862</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...</td>\n",
              "      <td>0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...</td>\n",
              "      <td>14564765</td>\n",
              "      <td>0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...</td>\n",
              "      <td>103</td>\n",
              "      <td>57</td>\n",
              "      <td>5249564484417209000</td>\n",
              "      <td>0.998862</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      event_name                            contract_address  \\\n",
              "0  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "1  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "2  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "3  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "4  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                     event_arguments  \\\n",
              "0  {'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...   \n",
              "1  {'buyer': '0x8e764bE4288B842791989DB5b8ec06727...   \n",
              "2  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "3  {'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...   \n",
              "4  {'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...   \n",
              "\n",
              "                                    transaction_hash  block_number  \\\n",
              "0  0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...      14564536   \n",
              "1  0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...      14564686   \n",
              "2  0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...      14564717   \n",
              "3  0x666c9ce15b870eab687fbda36866211e1e418294be2a...      14564751   \n",
              "4  0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...      14564765   \n",
              "\n",
              "                                          block_hash  log_index  \\\n",
              "0  0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...        486   \n",
              "1  0x6f365e20679769f1ede16e367b116c73a821da1c45cf...        143   \n",
              "2  0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...        237   \n",
              "3  0xd05bcdd6fab11f4433853397b401bcba774e74de5384...        214   \n",
              "4  0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...        103   \n",
              "\n",
              "   transaction_index           tokens_sold  price (STETH/ETH)  \n",
              "0                288  10000000000000000000           0.998864  \n",
              "1                 55   4030795658071524182           0.998864  \n",
              "2                139  29027981991561935158           0.998863  \n",
              "3                 90   5579999000001067821           0.998862  \n",
              "4                 57   5249564484417209000           0.998862  "
            ]
          },
          "execution_count": 71,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# create new column with marginal price (stETH as base and ETH as quote, so should be at a discount)\n",
        "%time query_swaps['price (STETH/ETH)'] = query_swaps['event_arguments'].apply(get_price)\n",
        "query_swaps.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 106,
      "id": "c7301a74",
      "metadata": {
        "id": "c7301a74",
        "outputId": "8d57508d-a764-499a-8ed5-1906b2221983"
      },
      "outputs": [
        {
          "ename": "TypeError",
          "evalue": "module() missing required argument 'name' (pos 1)",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[106], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mdarkmode\u001b[39;00m \u001b[39mimport\u001b[39;00m darkmode_orange \u001b[39mas\u001b[39;00m darkmode_orange \u001b[39m# pylint: disable=unused-import\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m darkmode_orange\u001b[39m.\u001b[39;49m\u001b[39m__init__\u001b[39;49m()\n\u001b[1;32m      3\u001b[0m query_swaps\u001b[39m.\u001b[39mplot(x\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mblock_number\u001b[39m\u001b[39m'\u001b[39m, y\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mprice (STETH/ETH)\u001b[39m\u001b[39m'\u001b[39m)\n",
            "\u001b[0;31mTypeError\u001b[0m: module() missing required argument 'name' (pos 1)"
          ]
        }
      ],
      "source": [
        "query_swaps.plot(x='block_number', y='price (STETH/ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "id": "d4ae9127",
      "metadata": {
        "id": "d4ae9127",
        "outputId": "4cf5cc6c-c872-4e4a-abac-4bcc2384eafd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: xlabel='block_number'>"
            ]
          },
          "execution_count": 73,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# well those are weird dips and spikes. look at smooth parts\n",
        "query_swaps[(query_swaps['block_number'] > 15100000) & (query_swaps['block_number'] < 15200000)].plot(x='block_number', y='price (STETH/ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "id": "0cdc144e",
      "metadata": {
        "id": "0cdc144e",
        "outputId": "1d89b980-e8a3-435a-935d-98deda4c1d4b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: xlabel='block_number'>"
            ]
          },
          "execution_count": 74,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# weird spike for swaps back to 1.000 exchange rate. should look at this in event df\n",
        "query_swaps[(query_swaps['block_number'] > 15131500) & (query_swaps['block_number'] < 15133000)].plot(x='block_number', y='price (STETH/ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "id": "fefbc986",
      "metadata": {
        "id": "fefbc986"
      },
      "outputs": [],
      "source": [
        "# first, unfold event arguments into separate columns\n",
        "def unfold_event_args(key: str, event_args: dict):\n",
        "    return event_args[key]\n",
        "\n",
        "for key in query_swaps.iloc[-1]['event_arguments'].keys():\n",
        "    query_swaps[key] = query_swaps['event_arguments'].apply(lambda ev: unfold_event_args(key, ev))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "id": "9dc5f51e",
      "metadata": {
        "id": "9dc5f51e",
        "outputId": "5b7bf676-d3a5-4cfa-a73c-e2dca0fea40f"
      },
      "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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "      <th>tokens_sold</th>\n",
              "      <th>price (STETH/ETH)</th>\n",
              "      <th>buyer</th>\n",
              "      <th>sold_id</th>\n",
              "      <th>bought_id</th>\n",
              "      <th>tokens_bought</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...</td>\n",
              "      <td>0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...</td>\n",
              "      <td>14564536</td>\n",
              "      <td>0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...</td>\n",
              "      <td>486</td>\n",
              "      <td>288</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.998864</td>\n",
              "      <td>0xDf1B1abA9E86bd0c3b264B689D8Cd5C4812f0cdd</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>9984648306739818054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x8e764bE4288B842791989DB5b8ec06727...</td>\n",
              "      <td>0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...</td>\n",
              "      <td>14564686</td>\n",
              "      <td>0x6f365e20679769f1ede16e367b116c73a821da1c45cf...</td>\n",
              "      <td>143</td>\n",
              "      <td>55</td>\n",
              "      <td>4030795658071524182</td>\n",
              "      <td>0.998864</td>\n",
              "      <td>0x8e764bE4288B842791989DB5b8ec067279829809</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4024606663873612212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...</td>\n",
              "      <td>14564717</td>\n",
              "      <td>0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...</td>\n",
              "      <td>237</td>\n",
              "      <td>139</td>\n",
              "      <td>29027981991561935158</td>\n",
              "      <td>0.998863</td>\n",
              "      <td>0x22F9dCF4647084d6C31b2765F6910cd85C178C18</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>28983388107398573857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...</td>\n",
              "      <td>0x666c9ce15b870eab687fbda36866211e1e418294be2a...</td>\n",
              "      <td>14564751</td>\n",
              "      <td>0xd05bcdd6fab11f4433853397b401bcba774e74de5384...</td>\n",
              "      <td>214</td>\n",
              "      <td>90</td>\n",
              "      <td>5579999000001067821</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0xDEF171Fe48CF0115B1d80b88dc8eAB59176FEe57</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5571422061111647197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...</td>\n",
              "      <td>0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...</td>\n",
              "      <td>14564765</td>\n",
              "      <td>0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...</td>\n",
              "      <td>103</td>\n",
              "      <td>57</td>\n",
              "      <td>5249564484417209000</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0x40011Fed885d26dDa406094f30dEA8f49Aa4cAc6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5241494058285726651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67937</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x3185Fd8f4578f746441Eff27CEbCE8948...</td>\n",
              "      <td>0x065d070e7997f5b6384805d0ca3991628f14e4449f83...</td>\n",
              "      <td>17192383</td>\n",
              "      <td>0xa4c7ca73b5e58a642c3e65f3be37e74fe6a1aeac28df...</td>\n",
              "      <td>144</td>\n",
              "      <td>52</td>\n",
              "      <td>4312914589013558420</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0x3185Fd8f4578f746441Eff27CEbCE89480904C20</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4309007710881342283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67938</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0xf86ca22a2c62ff87debfcc3fbabdd469efe232c48634...</td>\n",
              "      <td>17192471</td>\n",
              "      <td>0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...</td>\n",
              "      <td>122</td>\n",
              "      <td>38</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>10001055771217278855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67939</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x0982bb975F4eEeA52ce98E41f5dBAb6b1...</td>\n",
              "      <td>0xe596f987648ba1b2db561865d061ee01dfe325f4933a...</td>\n",
              "      <td>17192471</td>\n",
              "      <td>0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...</td>\n",
              "      <td>200</td>\n",
              "      <td>78</td>\n",
              "      <td>373852331500000000</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0x0982bb975F4eEeA52ce98E41f5dBAb6b15eDf59D</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>373514212681202490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67940</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0x3822fbf533b5d276cdbd9aced2daa6201f9f8ffa005a...</td>\n",
              "      <td>17192499</td>\n",
              "      <td>0xfe51dbc2d8595aac1f299ece2cc697070b55135dc076...</td>\n",
              "      <td>51</td>\n",
              "      <td>12</td>\n",
              "      <td>19000000000000000000</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>19001955528835282326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67941</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0x514fcf8754627c85788064c761b9566d13f9d5f0551f...</td>\n",
              "      <td>17192506</td>\n",
              "      <td>0xc4c3a3a6030817aec15979ba62f31ecdbde7ffb86448...</td>\n",
              "      <td>93</td>\n",
              "      <td>21</td>\n",
              "      <td>17000000000000000000</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>16984657814864192582</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>67938 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          event_name                            contract_address  \\\n",
              "0      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "1      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "2      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "3      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "4      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "...              ...                                         ...   \n",
              "67937  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67938  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67939  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67940  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67941  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                         event_arguments  \\\n",
              "0      {'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...   \n",
              "1      {'buyer': '0x8e764bE4288B842791989DB5b8ec06727...   \n",
              "2      {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "3      {'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...   \n",
              "4      {'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...   \n",
              "...                                                  ...   \n",
              "67937  {'buyer': '0x3185Fd8f4578f746441Eff27CEbCE8948...   \n",
              "67938  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "67939  {'buyer': '0x0982bb975F4eEeA52ce98E41f5dBAb6b1...   \n",
              "67940  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "67941  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "\n",
              "                                        transaction_hash  block_number  \\\n",
              "0      0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...      14564536   \n",
              "1      0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...      14564686   \n",
              "2      0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...      14564717   \n",
              "3      0x666c9ce15b870eab687fbda36866211e1e418294be2a...      14564751   \n",
              "4      0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...      14564765   \n",
              "...                                                  ...           ...   \n",
              "67937  0x065d070e7997f5b6384805d0ca3991628f14e4449f83...      17192383   \n",
              "67938  0xf86ca22a2c62ff87debfcc3fbabdd469efe232c48634...      17192471   \n",
              "67939  0xe596f987648ba1b2db561865d061ee01dfe325f4933a...      17192471   \n",
              "67940  0x3822fbf533b5d276cdbd9aced2daa6201f9f8ffa005a...      17192499   \n",
              "67941  0x514fcf8754627c85788064c761b9566d13f9d5f0551f...      17192506   \n",
              "\n",
              "                                              block_hash  log_index  \\\n",
              "0      0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...        486   \n",
              "1      0x6f365e20679769f1ede16e367b116c73a821da1c45cf...        143   \n",
              "2      0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...        237   \n",
              "3      0xd05bcdd6fab11f4433853397b401bcba774e74de5384...        214   \n",
              "4      0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...        103   \n",
              "...                                                  ...        ...   \n",
              "67937  0xa4c7ca73b5e58a642c3e65f3be37e74fe6a1aeac28df...        144   \n",
              "67938  0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...        122   \n",
              "67939  0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...        200   \n",
              "67940  0xfe51dbc2d8595aac1f299ece2cc697070b55135dc076...         51   \n",
              "67941  0xc4c3a3a6030817aec15979ba62f31ecdbde7ffb86448...         93   \n",
              "\n",
              "       transaction_index           tokens_sold  price (STETH/ETH)  \\\n",
              "0                    288  10000000000000000000           0.998864   \n",
              "1                     55   4030795658071524182           0.998864   \n",
              "2                    139  29027981991561935158           0.998863   \n",
              "3                     90   5579999000001067821           0.998862   \n",
              "4                     57   5249564484417209000           0.998862   \n",
              "...                  ...                   ...                ...   \n",
              "67937                 52   4312914589013558420           0.999494   \n",
              "67938                 38  10000000000000000000           0.999495   \n",
              "67939                 78    373852331500000000           0.999495   \n",
              "67940                 12  19000000000000000000           0.999497   \n",
              "67941                 21  17000000000000000000           0.999497   \n",
              "\n",
              "                                            buyer  sold_id  bought_id  \\\n",
              "0      0xDf1B1abA9E86bd0c3b264B689D8Cd5C4812f0cdd        1          0   \n",
              "1      0x8e764bE4288B842791989DB5b8ec067279829809        1          0   \n",
              "2      0x22F9dCF4647084d6C31b2765F6910cd85C178C18        1          0   \n",
              "3      0xDEF171Fe48CF0115B1d80b88dc8eAB59176FEe57        1          0   \n",
              "4      0x40011Fed885d26dDa406094f30dEA8f49Aa4cAc6        1          0   \n",
              "...                                           ...      ...        ...   \n",
              "67937  0x3185Fd8f4578f746441Eff27CEbCE89480904C20        1          0   \n",
              "67938  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        0          1   \n",
              "67939  0x0982bb975F4eEeA52ce98E41f5dBAb6b15eDf59D        1          0   \n",
              "67940  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        0          1   \n",
              "67941  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        1          0   \n",
              "\n",
              "              tokens_bought  \n",
              "0       9984648306739818054  \n",
              "1       4024606663873612212  \n",
              "2      28983388107398573857  \n",
              "3       5571422061111647197  \n",
              "4       5241494058285726651  \n",
              "...                     ...  \n",
              "67937   4309007710881342283  \n",
              "67938  10001055771217278855  \n",
              "67939    373514212681202490  \n",
              "67940  19001955528835282326  \n",
              "67941  16984657814864192582  \n",
              "\n",
              "[67938 rows x 14 columns]"
            ]
          },
          "execution_count": 76,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "query_swaps"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "id": "d175028b",
      "metadata": {
        "id": "d175028b",
        "outputId": "744a518b-52d4-47f9-8e91-c6223b467eb1"
      },
      "outputs": [
        {
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
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              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
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              "      <th>buyer</th>\n",
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              "      <th>bought_id</th>\n",
              "      <th>tokens_bought</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>18350</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
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              "      <th>18351</th>\n",
              "      <td>TokenExchange</td>\n",
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              "    <tr>\n",
              "      <th>18352</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
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              "      <td>0xed21e5dc1f4099e247b0e815eb3874a7ff1d837d3a8e...</td>\n",
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              "      <td>73</td>\n",
              "      <td>46</td>\n",
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              "      <td>0.962230</td>\n",
              "      <td>0x0031130c56162e00A7e9C01eE4147b11cbac8776</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2556919375120216623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18353</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
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              "      <td>0x7905d8a7692da709cb1f9deaed58d35b3e29fa956fae...</td>\n",
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              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>18354</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
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              "      <td>0</td>\n",
              "      <td>33670122355004768780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18355</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>18356</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x56804547a6d74ac0152564a250aff84cea33b85ed53f...</td>\n",
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              "      <td>0xc766211f83c2421824f805fd98f43bca867a03c63947...</td>\n",
              "      <td>62</td>\n",
              "      <td>8</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18357</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x3356a73accd1729384e364750411036472c2b9ff5327...</td>\n",
              "      <td>15132229</td>\n",
              "      <td>0x368ab30333621f418f1f6634d737d72adb2f77421518...</td>\n",
              "      <td>58</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18358</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0xd6978029b6bb52e8b4ffae55ce8f5a2de8b652ef0a1f...</td>\n",
              "      <td>15132280</td>\n",
              "      <td>0xd3893a3097aadadfa9fea3fadad6f7bdd48c54c03f80...</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18359</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x93751a459ccb0838f4cfe07960e6afff4eeaf33facbe...</td>\n",
              "      <td>15132283</td>\n",
              "      <td>0x74c38343de39bd403e4c49b068e389068b21be043ef0...</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18360</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x9965822080d9a2289c9ecb72e742deeba0e5df310be4...</td>\n",
              "      <td>15132285</td>\n",
              "      <td>0x18f73cfe64524b30f3ca5cedb4f6310b24e8a5f34be8...</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18361</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x9b50dac650f0091aff2d956cbcdde04702a4914a2f60...</td>\n",
              "      <td>15132287</td>\n",
              "      <td>0x0213b636029a48c67572e289fa294af9fb8df921bd2d...</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18362</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...</td>\n",
              "      <td>0x1485bca489d43349a141deebd2f3afc561d795aa04d4...</td>\n",
              "      <td>15132320</td>\n",
              "      <td>0xd63526030219fc21b0b53331027f8a2034313ee8769c...</td>\n",
              "      <td>16</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000400</td>\n",
              "      <td>0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18363</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xF2F400C138F9fb900576263af0BC7fCde...</td>\n",
              "      <td>0x67bfb48da3932454bc219404db6ceb77b649be938e78...</td>\n",
              "      <td>15132329</td>\n",
              "      <td>0x99b1cdd57e4c8cfe3598fa4ec19f0420c7fba33771e7...</td>\n",
              "      <td>32</td>\n",
              "      <td>2</td>\n",
              "      <td>400000000000000000000</td>\n",
              "      <td>0.962106</td>\n",
              "      <td>0xF2F400C138F9fb900576263af0BC7fCde2B1b8a8</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>384688609984980420741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18364</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xF2F400C138F9fb900576263af0BC7fCde...</td>\n",
              "      <td>0x8c5ab3a4c05c49e4931b1729aa80f75d747c9af93f3d...</td>\n",
              "      <td>15132367</td>\n",
              "      <td>0x6fe694dfa72cfebbe71617e59600d3cd6b6bd30993d9...</td>\n",
              "      <td>176</td>\n",
              "      <td>56</td>\n",
              "      <td>2749205000000000000</td>\n",
              "      <td>0.962001</td>\n",
              "      <td>0xF2F400C138F9fb900576263af0BC7fCde2B1b8a8</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2856655854053809321</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18365</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x198E5Fb1b9A8Cf0B7AAC03E0d55427d43...</td>\n",
              "      <td>0x10f4cfb0c9a6e32ee99f09f2eb8bd8be424d1443b216...</td>\n",
              "      <td>15132371</td>\n",
              "      <td>0x49d183944e6f13c328e83b6c1cb89fdfaa3060d9410e...</td>\n",
              "      <td>719</td>\n",
              "      <td>249</td>\n",
              "      <td>486794713448949200</td>\n",
              "      <td>0.962002</td>\n",
              "      <td>0x198E5Fb1b9A8Cf0B7AAC03E0d55427d431e4a111</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>505820290826336577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18366</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xFeDaa17AC2Bd92fc715e3B2706B9F10A0...</td>\n",
              "      <td>0x0dc7ec65cb7ee108208683a1fc22cb9db84fd37f414c...</td>\n",
              "      <td>15132376</td>\n",
              "      <td>0x1634de442d205feb779f8951263a54681ffa94e100c6...</td>\n",
              "      <td>330</td>\n",
              "      <td>145</td>\n",
              "      <td>1500000000000000000</td>\n",
              "      <td>0.962002</td>\n",
              "      <td>0xFeDaa17AC2Bd92fc715e3B2706B9F10A0514d225</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1558624162035676942</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          event_name                            contract_address  \\\n",
              "18350  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18351  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18352  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18353  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18354  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18355  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18356  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18357  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18358  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18359  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18360  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18361  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18362  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18363  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18364  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18365  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "18366  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                         event_arguments  \\\n",
              "18350  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18351  {'buyer': '0xfA9a30350048B2BF66865ee20363067c6...   \n",
              "18352  {'buyer': '0x0031130c56162e00A7e9C01eE4147b11c...   \n",
              "18353  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18354  {'buyer': '0xfA9a30350048B2BF66865ee20363067c6...   \n",
              "18355  {'buyer': '0x93Fa84f3102d45fC8e0721143c05b2c15...   \n",
              "18356  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18357  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18358  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18359  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18360  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18361  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18362  {'buyer': '0x6A0Af71516690d9e85c579a3a18C76ac8...   \n",
              "18363  {'buyer': '0xF2F400C138F9fb900576263af0BC7fCde...   \n",
              "18364  {'buyer': '0xF2F400C138F9fb900576263af0BC7fCde...   \n",
              "18365  {'buyer': '0x198E5Fb1b9A8Cf0B7AAC03E0d55427d43...   \n",
              "18366  {'buyer': '0xFeDaa17AC2Bd92fc715e3B2706B9F10A0...   \n",
              "\n",
              "                                        transaction_hash  block_number  \\\n",
              "18350  0xbaafb0dd80a49933313f5fae987331002fddd66ce398...      15132106   \n",
              "18351  0x38ecea57eecc869cc4a62d96555f15ffe3136f32e06d...      15132124   \n",
              "18352  0xed21e5dc1f4099e247b0e815eb3874a7ff1d837d3a8e...      15132156   \n",
              "18353  0x7438e5f555766a7f549d93c98022e0c6484729fa8d9f...      15132176   \n",
              "18354  0x722c4b153c4e33f1f5cbd0819d4847851d588d08184a...      15132179   \n",
              "18355  0x510b3876226e4bc81ae5afeedc3754dffcd5842bbe1d...      15132219   \n",
              "18356  0x56804547a6d74ac0152564a250aff84cea33b85ed53f...      15132225   \n",
              "18357  0x3356a73accd1729384e364750411036472c2b9ff5327...      15132229   \n",
              "18358  0xd6978029b6bb52e8b4ffae55ce8f5a2de8b652ef0a1f...      15132280   \n",
              "18359  0x93751a459ccb0838f4cfe07960e6afff4eeaf33facbe...      15132283   \n",
              "18360  0x9965822080d9a2289c9ecb72e742deeba0e5df310be4...      15132285   \n",
              "18361  0x9b50dac650f0091aff2d956cbcdde04702a4914a2f60...      15132287   \n",
              "18362  0x1485bca489d43349a141deebd2f3afc561d795aa04d4...      15132320   \n",
              "18363  0x67bfb48da3932454bc219404db6ceb77b649be938e78...      15132329   \n",
              "18364  0x8c5ab3a4c05c49e4931b1729aa80f75d747c9af93f3d...      15132367   \n",
              "18365  0x10f4cfb0c9a6e32ee99f09f2eb8bd8be424d1443b216...      15132371   \n",
              "18366  0x0dc7ec65cb7ee108208683a1fc22cb9db84fd37f414c...      15132376   \n",
              "\n",
              "                                              block_hash  log_index  \\\n",
              "18350  0x3f0dafa8c0bc1f75da4b77185df4b5e72f82367ce714...          6   \n",
              "18351  0x97431fe5b1b89ff7dd6dd8c340ca44707052bbdf729f...        291   \n",
              "18352  0x369ef5481d51a5d35c3e5fa176283314cdd284d829eb...         73   \n",
              "18353  0x7905d8a7692da709cb1f9deaed58d35b3e29fa956fae...         34   \n",
              "18354  0x8ec15d94c325e9e9552dc7f2c48e20f982ff5e694b3f...         40   \n",
              "18355  0x57d3a5987fce344172cc3549db379419aff5745c1ccc...        323   \n",
              "18356  0xc766211f83c2421824f805fd98f43bca867a03c63947...         62   \n",
              "18357  0x368ab30333621f418f1f6634d737d72adb2f77421518...         58   \n",
              "18358  0xd3893a3097aadadfa9fea3fadad6f7bdd48c54c03f80...          6   \n",
              "18359  0x74c38343de39bd403e4c49b068e389068b21be043ef0...          6   \n",
              "18360  0x18f73cfe64524b30f3ca5cedb4f6310b24e8a5f34be8...          6   \n",
              "18361  0x0213b636029a48c67572e289fa294af9fb8df921bd2d...          6   \n",
              "18362  0xd63526030219fc21b0b53331027f8a2034313ee8769c...         16   \n",
              "18363  0x99b1cdd57e4c8cfe3598fa4ec19f0420c7fba33771e7...         32   \n",
              "18364  0x6fe694dfa72cfebbe71617e59600d3cd6b6bd30993d9...        176   \n",
              "18365  0x49d183944e6f13c328e83b6c1cb89fdfaa3060d9410e...        719   \n",
              "18366  0x1634de442d205feb779f8951263a54681ffa94e100c6...        330   \n",
              "\n",
              "       transaction_index            tokens_sold  price (STETH/ETH)  \\\n",
              "18350                  1       9999999999999999           0.962210   \n",
              "18351                123   33697027127765331114           0.962220   \n",
              "18352                 46    2461328000000000000           0.962230   \n",
              "18353                 10                      1           1.000400   \n",
              "18354                 24   35006090866436268938           0.962221   \n",
              "18355                144    1300000000000000000           0.962212   \n",
              "18356                  8                      1           1.000400   \n",
              "18357                 12                      1           1.000400   \n",
              "18358                  1                      1           1.000400   \n",
              "18359                  1                      1           1.000400   \n",
              "18360                  1                      1           1.000400   \n",
              "18361                  1                      1           1.000400   \n",
              "18362                  2                      1           1.000400   \n",
              "18363                  2  400000000000000000000           0.962106   \n",
              "18364                 56    2749205000000000000           0.962001   \n",
              "18365                249     486794713448949200           0.962002   \n",
              "18366                145    1500000000000000000           0.962002   \n",
              "\n",
              "                                            buyer  sold_id  bought_id  \\\n",
              "18350  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18351  0xfA9a30350048B2BF66865ee20363067c66f67e58        0          1   \n",
              "18352  0x0031130c56162e00A7e9C01eE4147b11cbac8776        0          1   \n",
              "18353  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18354  0xfA9a30350048B2BF66865ee20363067c66f67e58        1          0   \n",
              "18355  0x93Fa84f3102d45fC8e0721143c05b2c156026025        0          1   \n",
              "18356  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18357  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18358  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18359  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18360  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18361  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18362  0x6A0Af71516690d9e85c579a3a18C76ac8E33efD1        1          0   \n",
              "18363  0xF2F400C138F9fb900576263af0BC7fCde2B1b8a8        1          0   \n",
              "18364  0xF2F400C138F9fb900576263af0BC7fCde2B1b8a8        0          1   \n",
              "18365  0x198E5Fb1b9A8Cf0B7AAC03E0d55427d431e4a111        0          1   \n",
              "18366  0xFeDaa17AC2Bd92fc715e3B2706B9F10A0514d225        0          1   \n",
              "\n",
              "               tokens_bought  \n",
              "18350       9618254969587698  \n",
              "18351   35006090866436268938  \n",
              "18352    2556919375120216623  \n",
              "18353                      1  \n",
              "18354   33670122355004768780  \n",
              "18355    1350513053366563254  \n",
              "18356                      1  \n",
              "18357                      1  \n",
              "18358                      1  \n",
              "18359                      1  \n",
              "18360                      1  \n",
              "18361                      1  \n",
              "18362                      1  \n",
              "18363  384688609984980420741  \n",
              "18364    2856655854053809321  \n",
              "18365     505820290826336577  \n",
              "18366    1558624162035676942  "
            ]
          },
          "execution_count": 77,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# now, check swaps where price spikes up to 1 between blocks 15132100 and 15132400\n",
        "query_swaps[(query_swaps['block_number'] > 15132100) & (query_swaps['block_number'] < 15132400)]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "id": "e4b90a3c",
      "metadata": {
        "id": "e4b90a3c"
      },
      "outputs": [],
      "source": [
        "# ahh, ok :) .. someones selling 1 wei into the pool (see e.g. block 15132225)\n",
        "# which is causing rounding issues for price calc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "id": "20aa3340",
      "metadata": {
        "id": "20aa3340",
        "outputId": "ed9d6d9b-552f-4b76-c450-6492c3a8f975"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: xlabel='block_number'>"
            ]
          },
          "execution_count": 79,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# are the dusting rounding issues also causing those spikes down to zero?\n",
        "# look at first spike down to 0\n",
        "query_swaps[(query_swaps['block_number'] > 14824600) & (query_swaps['block_number'] < 14825000)].plot(x='block_number', y='price (STETH/ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "id": "fb6fb625",
      "metadata": {
        "id": "fb6fb625",
        "outputId": "a18a8e86-6598-4d99-cada-5a74a56108b3"
      },
      "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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "      <th>tokens_sold</th>\n",
              "      <th>price (STETH/ETH)</th>\n",
              "      <th>buyer</th>\n",
              "      <th>sold_id</th>\n",
              "      <th>bought_id</th>\n",
              "      <th>tokens_bought</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7427</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x08CC4a936A24A278097FeB566Fccf71FF...</td>\n",
              "      <td>0xbefdc34be9f6d50dcf7d9692c834f2fcb750a7880a30...</td>\n",
              "      <td>14824621</td>\n",
              "      <td>0x10cf6cb3feb597dcaefdfa6fab3730491fea055a51b4...</td>\n",
              "      <td>236</td>\n",
              "      <td>204</td>\n",
              "      <td>2000000000000000000000</td>\n",
              "      <td>0.975627</td>\n",
              "      <td>0x08CC4a936A24A278097FeB566Fccf71FFe84A833</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2049143953945768280377</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7428</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...</td>\n",
              "      <td>0xe7a98e6b9dbdab7e4e169efbb8ba055a9f0a28da8587...</td>\n",
              "      <td>14824663</td>\n",
              "      <td>0xc07d6c8038fd4165fd07386037f0a63b56701b00e1d7...</td>\n",
              "      <td>66</td>\n",
              "      <td>60</td>\n",
              "      <td>9669640333791112375</td>\n",
              "      <td>0.975835</td>\n",
              "      <td>0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>9905129894611176792</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7429</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x27239549DD40E1D60F5B80B0C41969237...</td>\n",
              "      <td>0xebbe2cac6a8cea633f4ce13aecc6b3d402f0a53de0df...</td>\n",
              "      <td>14824714</td>\n",
              "      <td>0x090d8bfa4b34ab2e8670c488fdde86fa8c5caef4cbd4...</td>\n",
              "      <td>115</td>\n",
              "      <td>81</td>\n",
              "      <td>4393970000000000000</td>\n",
              "      <td>0.975836</td>\n",
              "      <td>0x27239549DD40E1D60F5B80B0C4196923745B1FD2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4286080251138498473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7430</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...</td>\n",
              "      <td>0x6a1a41032f086a90520761d6444937ff73b3aea580c2...</td>\n",
              "      <td>14824787</td>\n",
              "      <td>0x2749b488383fe28bb2abeab7d111d8472e406c445803...</td>\n",
              "      <td>150</td>\n",
              "      <td>92</td>\n",
              "      <td>1000730293446869257</td>\n",
              "      <td>0.975836</td>\n",
              "      <td>0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>976157742840268152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7431</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0xf97ecc3423d91b6f51e0f384518237b4c5439490f21f...</td>\n",
              "      <td>14824795</td>\n",
              "      <td>0x9038606c713de55bd5e65ed931117811e79820115ee7...</td>\n",
              "      <td>139</td>\n",
              "      <td>77</td>\n",
              "      <td>476594175496263493</td>\n",
              "      <td>0.975836</td>\n",
              "      <td>0x22F9dCF4647084d6C31b2765F6910cd85C178C18</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>488200580530122222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7432</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...</td>\n",
              "      <td>0xd3c3131024e6f4fb640f27a7a07513c44a4247ea663c...</td>\n",
              "      <td>14824820</td>\n",
              "      <td>0x0c7676c94dcc0bd3a33e55f1ae8bce51c723e1251f5d...</td>\n",
              "      <td>43</td>\n",
              "      <td>49</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.975835</td>\n",
              "      <td>0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>9754443750619738380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7433</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xEda584Ac4234113e977Bd172e6393F579...</td>\n",
              "      <td>0x953204aa910f21a8012789670728e410039a8f9840b6...</td>\n",
              "      <td>14824835</td>\n",
              "      <td>0xfdf144489b7e75244e22839ce1c8a398f7745a57a1c0...</td>\n",
              "      <td>397</td>\n",
              "      <td>246</td>\n",
              "      <td>47870179539630044007</td>\n",
              "      <td>0.975829</td>\n",
              "      <td>0xEda584Ac4234113e977Bd172e6393F579282b816</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>46694419191845003347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7434</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xEda584Ac4234113e977Bd172e6393F579...</td>\n",
              "      <td>0xb2c64c3e9722df4fbcd79662cd6746e069ae08f55242...</td>\n",
              "      <td>14824840</td>\n",
              "      <td>0xfc556897c82ced07979693ce76cd27b4565e78cb0959...</td>\n",
              "      <td>462</td>\n",
              "      <td>195</td>\n",
              "      <td>1</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0xEda584Ac4234113e977Bd172e6393F579282b816</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7435</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x27239549DD40E1D60F5B80B0C41969237...</td>\n",
              "      <td>0xc5de9e64196dff8dd176eece734d88b68e9f4e41cd1d...</td>\n",
              "      <td>14824850</td>\n",
              "      <td>0x1bc4068a1b8284a00ea135dc590d18744bf548a1c795...</td>\n",
              "      <td>84</td>\n",
              "      <td>43</td>\n",
              "      <td>1000000000000000000</td>\n",
              "      <td>0.975824</td>\n",
              "      <td>0x27239549DD40E1D60F5B80B0C4196923745B1FD2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1024364849804104284</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7436</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x11CE580B7D64Fb08F73161AA95835202a...</td>\n",
              "      <td>0xe0c2a35ae160788e8d1d73a5bf465279363581af043f...</td>\n",
              "      <td>14824871</td>\n",
              "      <td>0x0f6bf5cc06980ac2ef46f0a73831494c426c0c9b3336...</td>\n",
              "      <td>394</td>\n",
              "      <td>188</td>\n",
              "      <td>381485996253488127</td>\n",
              "      <td>0.975824</td>\n",
              "      <td>0x11CE580B7D64Fb08F73161AA95835202ae1C9417</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>372114382696495947</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7437</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...</td>\n",
              "      <td>0x168a27738d7c005056eb7066cabf72139c7117bd31e0...</td>\n",
              "      <td>14824881</td>\n",
              "      <td>0x0ac25353128ab0b234a46d69c52794d1dde3bd6159d6...</td>\n",
              "      <td>124</td>\n",
              "      <td>79</td>\n",
              "      <td>9988410555478815545</td>\n",
              "      <td>0.975825</td>\n",
              "      <td>0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>10231765617890507635</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7438</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0xb0883f89889bea5205ec2496464afd7902b0b2fc7f4d...</td>\n",
              "      <td>14824926</td>\n",
              "      <td>0xd2a11519ace15f0f8aaab66c95439db218d8f4bd54ad...</td>\n",
              "      <td>361</td>\n",
              "      <td>210</td>\n",
              "      <td>700000000000000000</td>\n",
              "      <td>0.975826</td>\n",
              "      <td>0x22F9dCF4647084d6C31b2765F6910cd85C178C18</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>682805110842010655</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7439</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x0ea37B047B4D2F37cEF7bE3E6671Bf9CB...</td>\n",
              "      <td>0x4b70b93af843d6c73386196fbf6494c55b7d81e77887...</td>\n",
              "      <td>14824952</td>\n",
              "      <td>0x7c4533e872e0b51cd7ed090ed1762ad30fae7bfc85b5...</td>\n",
              "      <td>183</td>\n",
              "      <td>226</td>\n",
              "      <td>4077890328278097871</td>\n",
              "      <td>0.975826</td>\n",
              "      <td>0x0ea37B047B4D2F37cEF7bE3E6671Bf9CB85e2e5b</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3977718553966826464</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         event_name                            contract_address  \\\n",
              "7427  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7428  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7429  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7430  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7431  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7432  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7433  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7434  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7435  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7436  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7437  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7438  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "7439  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                        event_arguments  \\\n",
              "7427  {'buyer': '0x08CC4a936A24A278097FeB566Fccf71FF...   \n",
              "7428  {'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...   \n",
              "7429  {'buyer': '0x27239549DD40E1D60F5B80B0C41969237...   \n",
              "7430  {'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...   \n",
              "7431  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "7432  {'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...   \n",
              "7433  {'buyer': '0xEda584Ac4234113e977Bd172e6393F579...   \n",
              "7434  {'buyer': '0xEda584Ac4234113e977Bd172e6393F579...   \n",
              "7435  {'buyer': '0x27239549DD40E1D60F5B80B0C41969237...   \n",
              "7436  {'buyer': '0x11CE580B7D64Fb08F73161AA95835202a...   \n",
              "7437  {'buyer': '0x220bdA5c8994804Ac96ebe4DF184d25e5...   \n",
              "7438  {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "7439  {'buyer': '0x0ea37B047B4D2F37cEF7bE3E6671Bf9CB...   \n",
              "\n",
              "                                       transaction_hash  block_number  \\\n",
              "7427  0xbefdc34be9f6d50dcf7d9692c834f2fcb750a7880a30...      14824621   \n",
              "7428  0xe7a98e6b9dbdab7e4e169efbb8ba055a9f0a28da8587...      14824663   \n",
              "7429  0xebbe2cac6a8cea633f4ce13aecc6b3d402f0a53de0df...      14824714   \n",
              "7430  0x6a1a41032f086a90520761d6444937ff73b3aea580c2...      14824787   \n",
              "7431  0xf97ecc3423d91b6f51e0f384518237b4c5439490f21f...      14824795   \n",
              "7432  0xd3c3131024e6f4fb640f27a7a07513c44a4247ea663c...      14824820   \n",
              "7433  0x953204aa910f21a8012789670728e410039a8f9840b6...      14824835   \n",
              "7434  0xb2c64c3e9722df4fbcd79662cd6746e069ae08f55242...      14824840   \n",
              "7435  0xc5de9e64196dff8dd176eece734d88b68e9f4e41cd1d...      14824850   \n",
              "7436  0xe0c2a35ae160788e8d1d73a5bf465279363581af043f...      14824871   \n",
              "7437  0x168a27738d7c005056eb7066cabf72139c7117bd31e0...      14824881   \n",
              "7438  0xb0883f89889bea5205ec2496464afd7902b0b2fc7f4d...      14824926   \n",
              "7439  0x4b70b93af843d6c73386196fbf6494c55b7d81e77887...      14824952   \n",
              "\n",
              "                                             block_hash  log_index  \\\n",
              "7427  0x10cf6cb3feb597dcaefdfa6fab3730491fea055a51b4...        236   \n",
              "7428  0xc07d6c8038fd4165fd07386037f0a63b56701b00e1d7...         66   \n",
              "7429  0x090d8bfa4b34ab2e8670c488fdde86fa8c5caef4cbd4...        115   \n",
              "7430  0x2749b488383fe28bb2abeab7d111d8472e406c445803...        150   \n",
              "7431  0x9038606c713de55bd5e65ed931117811e79820115ee7...        139   \n",
              "7432  0x0c7676c94dcc0bd3a33e55f1ae8bce51c723e1251f5d...         43   \n",
              "7433  0xfdf144489b7e75244e22839ce1c8a398f7745a57a1c0...        397   \n",
              "7434  0xfc556897c82ced07979693ce76cd27b4565e78cb0959...        462   \n",
              "7435  0x1bc4068a1b8284a00ea135dc590d18744bf548a1c795...         84   \n",
              "7436  0x0f6bf5cc06980ac2ef46f0a73831494c426c0c9b3336...        394   \n",
              "7437  0x0ac25353128ab0b234a46d69c52794d1dde3bd6159d6...        124   \n",
              "7438  0xd2a11519ace15f0f8aaab66c95439db218d8f4bd54ad...        361   \n",
              "7439  0x7c4533e872e0b51cd7ed090ed1762ad30fae7bfc85b5...        183   \n",
              "\n",
              "      transaction_index             tokens_sold  price (STETH/ETH)  \\\n",
              "7427                204  2000000000000000000000           0.975627   \n",
              "7428                 60     9669640333791112375           0.975835   \n",
              "7429                 81     4393970000000000000           0.975836   \n",
              "7430                 92     1000730293446869257           0.975836   \n",
              "7431                 77      476594175496263493           0.975836   \n",
              "7432                 49    10000000000000000000           0.975835   \n",
              "7433                246    47870179539630044007           0.975829   \n",
              "7434                195                       1           0.000000   \n",
              "7435                 43     1000000000000000000           0.975824   \n",
              "7436                188      381485996253488127           0.975824   \n",
              "7437                 79     9988410555478815545           0.975825   \n",
              "7438                210      700000000000000000           0.975826   \n",
              "7439                226     4077890328278097871           0.975826   \n",
              "\n",
              "                                           buyer  sold_id  bought_id  \\\n",
              "7427  0x08CC4a936A24A278097FeB566Fccf71FFe84A833        0          1   \n",
              "7428  0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4        0          1   \n",
              "7429  0x27239549DD40E1D60F5B80B0C4196923745B1FD2        1          0   \n",
              "7430  0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4        1          0   \n",
              "7431  0x22F9dCF4647084d6C31b2765F6910cd85C178C18        0          1   \n",
              "7432  0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4        1          0   \n",
              "7433  0xEda584Ac4234113e977Bd172e6393F579282b816        1          0   \n",
              "7434  0xEda584Ac4234113e977Bd172e6393F579282b816        1          0   \n",
              "7435  0x27239549DD40E1D60F5B80B0C4196923745B1FD2        0          1   \n",
              "7436  0x11CE580B7D64Fb08F73161AA95835202ae1C9417        1          0   \n",
              "7437  0x220bdA5c8994804Ac96ebe4DF184d25e5c2196D4        0          1   \n",
              "7438  0x22F9dCF4647084d6C31b2765F6910cd85C178C18        1          0   \n",
              "7439  0x0ea37B047B4D2F37cEF7bE3E6671Bf9CB85e2e5b        1          0   \n",
              "\n",
              "               tokens_bought  \n",
              "7427  2049143953945768280377  \n",
              "7428     9905129894611176792  \n",
              "7429     4286080251138498473  \n",
              "7430      976157742840268152  \n",
              "7431      488200580530122222  \n",
              "7432     9754443750619738380  \n",
              "7433    46694419191845003347  \n",
              "7434                       0  \n",
              "7435     1024364849804104284  \n",
              "7436      372114382696495947  \n",
              "7437    10231765617890507635  \n",
              "7438      682805110842010655  \n",
              "7439     3977718553966826464  "
            ]
          },
          "execution_count": 80,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# looks like it (see swap at block 14824840); similar rounding issues except rounded down to zero here\n",
        "query_swaps[(query_swaps['block_number'] > 14824600) & (query_swaps['block_number'] < 14825000)]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "id": "3bdb0eef",
      "metadata": {
        "id": "3bdb0eef"
      },
      "outputs": [],
      "source": [
        "# apply min size to swaps we care about to ignore the dustings\n",
        "min_bought = 0.0001 * 1e18  # trade size must be > 0.0001 ETH \n",
        "query_swaps = query_swaps[query_swaps['tokens_bought'] > min_bought]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "id": "2103c9da",
      "metadata": {
        "id": "2103c9da",
        "outputId": "c1f8b6bd-5c14-4d22-af0e-dd372d8fd429"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: xlabel='block_number'>"
            ]
          },
          "execution_count": 82,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# nice! way better\n",
        "query_swaps.plot(x='block_number', y='price (STETH/ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "id": "b7e9c553",
      "metadata": {
        "id": "b7e9c553"
      },
      "outputs": [],
      "source": [
        "# should smooth the price data out so not so jittery by averaging over 1h for hourly candles.\n",
        "# keep the volumes numbers as well, so make some slight changes to the (tokens_bought, tokens_sold)\n",
        "# columns to instead track (volume_coin0, volume_coin1) at each swap"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "id": "1e4b633a",
      "metadata": {
        "id": "1e4b633a"
      },
      "outputs": [],
      "source": [
        "# write a function that returns volume on coin indices for a swap (normalized by 1e18 for decimals)\n",
        "def get_volume(coin_index: int, x: pd.Series) -> (float, float):\n",
        "    volume = x['tokens_sold'] if x['sold_id'] == coin_index else x['tokens_bought']\n",
        "    volume = volume / 1e18\n",
        "    return volume"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "id": "22a96898",
      "metadata": {
        "id": "22a96898"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "for coin_index in range(2):\n",
        "    key = f'volume_coin{coin_index}'\n",
        "    query_swaps[key] = query_swaps.apply(lambda x: get_volume(coin_index, x), axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "id": "7420b5bb",
      "metadata": {
        "id": "7420b5bb",
        "outputId": "44b34021-0521-47f1-ad35-b410848ad3c1"
      },
      "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>event_name</th>\n",
              "      <th>contract_address</th>\n",
              "      <th>event_arguments</th>\n",
              "      <th>transaction_hash</th>\n",
              "      <th>block_number</th>\n",
              "      <th>block_hash</th>\n",
              "      <th>log_index</th>\n",
              "      <th>transaction_index</th>\n",
              "      <th>tokens_sold</th>\n",
              "      <th>price (STETH/ETH)</th>\n",
              "      <th>buyer</th>\n",
              "      <th>sold_id</th>\n",
              "      <th>bought_id</th>\n",
              "      <th>tokens_bought</th>\n",
              "      <th>volume_coin0</th>\n",
              "      <th>volume_coin1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...</td>\n",
              "      <td>0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...</td>\n",
              "      <td>14564536</td>\n",
              "      <td>0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...</td>\n",
              "      <td>486</td>\n",
              "      <td>288</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.998864</td>\n",
              "      <td>0xDf1B1abA9E86bd0c3b264B689D8Cd5C4812f0cdd</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>9984648306739818054</td>\n",
              "      <td>9.984648</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x8e764bE4288B842791989DB5b8ec06727...</td>\n",
              "      <td>0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...</td>\n",
              "      <td>14564686</td>\n",
              "      <td>0x6f365e20679769f1ede16e367b116c73a821da1c45cf...</td>\n",
              "      <td>143</td>\n",
              "      <td>55</td>\n",
              "      <td>4030795658071524182</td>\n",
              "      <td>0.998864</td>\n",
              "      <td>0x8e764bE4288B842791989DB5b8ec067279829809</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4024606663873612212</td>\n",
              "      <td>4.024607</td>\n",
              "      <td>4.030796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...</td>\n",
              "      <td>0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...</td>\n",
              "      <td>14564717</td>\n",
              "      <td>0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...</td>\n",
              "      <td>237</td>\n",
              "      <td>139</td>\n",
              "      <td>29027981991561935158</td>\n",
              "      <td>0.998863</td>\n",
              "      <td>0x22F9dCF4647084d6C31b2765F6910cd85C178C18</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>28983388107398573857</td>\n",
              "      <td>28.983388</td>\n",
              "      <td>29.027982</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...</td>\n",
              "      <td>0x666c9ce15b870eab687fbda36866211e1e418294be2a...</td>\n",
              "      <td>14564751</td>\n",
              "      <td>0xd05bcdd6fab11f4433853397b401bcba774e74de5384...</td>\n",
              "      <td>214</td>\n",
              "      <td>90</td>\n",
              "      <td>5579999000001067821</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0xDEF171Fe48CF0115B1d80b88dc8eAB59176FEe57</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5571422061111647197</td>\n",
              "      <td>5.571422</td>\n",
              "      <td>5.579999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...</td>\n",
              "      <td>0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...</td>\n",
              "      <td>14564765</td>\n",
              "      <td>0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...</td>\n",
              "      <td>103</td>\n",
              "      <td>57</td>\n",
              "      <td>5249564484417209000</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0x40011Fed885d26dDa406094f30dEA8f49Aa4cAc6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5241494058285726651</td>\n",
              "      <td>5.241494</td>\n",
              "      <td>5.249564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67937</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x3185Fd8f4578f746441Eff27CEbCE8948...</td>\n",
              "      <td>0x065d070e7997f5b6384805d0ca3991628f14e4449f83...</td>\n",
              "      <td>17192383</td>\n",
              "      <td>0xa4c7ca73b5e58a642c3e65f3be37e74fe6a1aeac28df...</td>\n",
              "      <td>144</td>\n",
              "      <td>52</td>\n",
              "      <td>4312914589013558420</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0x3185Fd8f4578f746441Eff27CEbCE89480904C20</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4309007710881342283</td>\n",
              "      <td>4.309008</td>\n",
              "      <td>4.312915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67938</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0xf86ca22a2c62ff87debfcc3fbabdd469efe232c48634...</td>\n",
              "      <td>17192471</td>\n",
              "      <td>0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...</td>\n",
              "      <td>122</td>\n",
              "      <td>38</td>\n",
              "      <td>10000000000000000000</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>10001055771217278855</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.001056</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67939</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x0982bb975F4eEeA52ce98E41f5dBAb6b1...</td>\n",
              "      <td>0xe596f987648ba1b2db561865d061ee01dfe325f4933a...</td>\n",
              "      <td>17192471</td>\n",
              "      <td>0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...</td>\n",
              "      <td>200</td>\n",
              "      <td>78</td>\n",
              "      <td>373852331500000000</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0x0982bb975F4eEeA52ce98E41f5dBAb6b15eDf59D</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>373514212681202490</td>\n",
              "      <td>0.373514</td>\n",
              "      <td>0.373852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67940</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0x3822fbf533b5d276cdbd9aced2daa6201f9f8ffa005a...</td>\n",
              "      <td>17192499</td>\n",
              "      <td>0xfe51dbc2d8595aac1f299ece2cc697070b55135dc076...</td>\n",
              "      <td>51</td>\n",
              "      <td>12</td>\n",
              "      <td>19000000000000000000</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>19001955528835282326</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>19.001956</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67941</th>\n",
              "      <td>TokenExchange</td>\n",
              "      <td>0xDC24316b9AE028F1497c275EB9192a3Ea0f67022</td>\n",
              "      <td>{'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...</td>\n",
              "      <td>0x514fcf8754627c85788064c761b9566d13f9d5f0551f...</td>\n",
              "      <td>17192506</td>\n",
              "      <td>0xc4c3a3a6030817aec15979ba62f31ecdbde7ffb86448...</td>\n",
              "      <td>93</td>\n",
              "      <td>21</td>\n",
              "      <td>17000000000000000000</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0x99a58482BD75cbab83b27EC03CA68fF489b5788f</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>16984657814864192582</td>\n",
              "      <td>16.984658</td>\n",
              "      <td>17.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>67569 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          event_name                            contract_address  \\\n",
              "0      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "1      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "2      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "3      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "4      TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "...              ...                                         ...   \n",
              "67937  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67938  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67939  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67940  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "67941  TokenExchange  0xDC24316b9AE028F1497c275EB9192a3Ea0f67022   \n",
              "\n",
              "                                         event_arguments  \\\n",
              "0      {'buyer': '0xDf1B1abA9E86bd0c3b264B689D8Cd5C48...   \n",
              "1      {'buyer': '0x8e764bE4288B842791989DB5b8ec06727...   \n",
              "2      {'buyer': '0x22F9dCF4647084d6C31b2765F6910cd85...   \n",
              "3      {'buyer': '0xDEF171Fe48CF0115B1d80b88dc8eAB591...   \n",
              "4      {'buyer': '0x40011Fed885d26dDa406094f30dEA8f49...   \n",
              "...                                                  ...   \n",
              "67937  {'buyer': '0x3185Fd8f4578f746441Eff27CEbCE8948...   \n",
              "67938  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "67939  {'buyer': '0x0982bb975F4eEeA52ce98E41f5dBAb6b1...   \n",
              "67940  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "67941  {'buyer': '0x99a58482BD75cbab83b27EC03CA68fF48...   \n",
              "\n",
              "                                        transaction_hash  block_number  \\\n",
              "0      0xe61861ceb9ce4c206429b8d0ce98fabe41797325ce33...      14564536   \n",
              "1      0xdab14f6d8f01f56e3c89cd5eeb25c144fba207ebe3b9...      14564686   \n",
              "2      0x7f53981e6ab18de95975bb65b4119c0a80ca2479663e...      14564717   \n",
              "3      0x666c9ce15b870eab687fbda36866211e1e418294be2a...      14564751   \n",
              "4      0xcc78ead1f4187bb27022a5bca2fec7154f77d907ea3b...      14564765   \n",
              "...                                                  ...           ...   \n",
              "67937  0x065d070e7997f5b6384805d0ca3991628f14e4449f83...      17192383   \n",
              "67938  0xf86ca22a2c62ff87debfcc3fbabdd469efe232c48634...      17192471   \n",
              "67939  0xe596f987648ba1b2db561865d061ee01dfe325f4933a...      17192471   \n",
              "67940  0x3822fbf533b5d276cdbd9aced2daa6201f9f8ffa005a...      17192499   \n",
              "67941  0x514fcf8754627c85788064c761b9566d13f9d5f0551f...      17192506   \n",
              "\n",
              "                                              block_hash  log_index  \\\n",
              "0      0xea7712f63c6a7faaa2b78a30c6f1a38592c097f5ff6f...        486   \n",
              "1      0x6f365e20679769f1ede16e367b116c73a821da1c45cf...        143   \n",
              "2      0xf624d7d14de17201a5588fd4e67842e26d13df9841ec...        237   \n",
              "3      0xd05bcdd6fab11f4433853397b401bcba774e74de5384...        214   \n",
              "4      0x618541384bf9ad30bb724baf979bbd0d12f16879caaf...        103   \n",
              "...                                                  ...        ...   \n",
              "67937  0xa4c7ca73b5e58a642c3e65f3be37e74fe6a1aeac28df...        144   \n",
              "67938  0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...        122   \n",
              "67939  0x0cd15f1aa081ff166bb6f45003edf07db7a26410f6a4...        200   \n",
              "67940  0xfe51dbc2d8595aac1f299ece2cc697070b55135dc076...         51   \n",
              "67941  0xc4c3a3a6030817aec15979ba62f31ecdbde7ffb86448...         93   \n",
              "\n",
              "       transaction_index           tokens_sold  price (STETH/ETH)  \\\n",
              "0                    288  10000000000000000000           0.998864   \n",
              "1                     55   4030795658071524182           0.998864   \n",
              "2                    139  29027981991561935158           0.998863   \n",
              "3                     90   5579999000001067821           0.998862   \n",
              "4                     57   5249564484417209000           0.998862   \n",
              "...                  ...                   ...                ...   \n",
              "67937                 52   4312914589013558420           0.999494   \n",
              "67938                 38  10000000000000000000           0.999495   \n",
              "67939                 78    373852331500000000           0.999495   \n",
              "67940                 12  19000000000000000000           0.999497   \n",
              "67941                 21  17000000000000000000           0.999497   \n",
              "\n",
              "                                            buyer  sold_id  bought_id  \\\n",
              "0      0xDf1B1abA9E86bd0c3b264B689D8Cd5C4812f0cdd        1          0   \n",
              "1      0x8e764bE4288B842791989DB5b8ec067279829809        1          0   \n",
              "2      0x22F9dCF4647084d6C31b2765F6910cd85C178C18        1          0   \n",
              "3      0xDEF171Fe48CF0115B1d80b88dc8eAB59176FEe57        1          0   \n",
              "4      0x40011Fed885d26dDa406094f30dEA8f49Aa4cAc6        1          0   \n",
              "...                                           ...      ...        ...   \n",
              "67937  0x3185Fd8f4578f746441Eff27CEbCE89480904C20        1          0   \n",
              "67938  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        0          1   \n",
              "67939  0x0982bb975F4eEeA52ce98E41f5dBAb6b15eDf59D        1          0   \n",
              "67940  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        0          1   \n",
              "67941  0x99a58482BD75cbab83b27EC03CA68fF489b5788f        1          0   \n",
              "\n",
              "              tokens_bought  volume_coin0  volume_coin1  \n",
              "0       9984648306739818054      9.984648     10.000000  \n",
              "1       4024606663873612212      4.024607      4.030796  \n",
              "2      28983388107398573857     28.983388     29.027982  \n",
              "3       5571422061111647197      5.571422      5.579999  \n",
              "4       5241494058285726651      5.241494      5.249564  \n",
              "...                     ...           ...           ...  \n",
              "67937   4309007710881342283      4.309008      4.312915  \n",
              "67938  10001055771217278855     10.000000     10.001056  \n",
              "67939    373514212681202490      0.373514      0.373852  \n",
              "67940  19001955528835282326     19.000000     19.001956  \n",
              "67941  16984657814864192582     16.984658     17.000000  \n",
              "\n",
              "[67569 rows x 16 columns]"
            ]
          },
          "execution_count": 86,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "query_swaps"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 87,
      "id": "8d21ac2c",
      "metadata": {
        "id": "8d21ac2c"
      },
      "outputs": [],
      "source": [
        "# prep for smoothing by setting index to block number (choose last swap in block to represent price at block)\n",
        "query_swaps_filtered = query_swaps.filter(['block_number', 'price (STETH/ETH)', 'volume_coin0', 'volume_coin1']).drop_duplicates('block_number', keep='last')\n",
        "query_swaps_filtered = query_swaps_filtered.set_index('block_number')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "id": "09a61518",
      "metadata": {
        "id": "09a61518"
      },
      "outputs": [],
      "source": [
        "# reindex by block number (1 block steps) and ffill price values \n",
        "new_index = range(query_swaps_filtered.index.min(), query_swaps_filtered.index.max()+1)\n",
        "query_swaps_filtered = query_swaps_filtered.reindex(new_index).ffill()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "id": "f175d460",
      "metadata": {
        "id": "f175d460"
      },
      "outputs": [],
      "source": [
        "# separate data into windows of 260 blocks (~ 1h)\n",
        "# remove first (last_block - first_block) % window rows so even candle windows\n",
        "window = 260\n",
        "first_index = (query_swaps_filtered.index[-1] - query_swaps_filtered.index[0]) % window\n",
        "query_swaps_filtered = query_swaps_filtered[first_index:]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 90,
      "id": "60225e2c",
      "metadata": {
        "id": "60225e2c",
        "outputId": "1b4f918d-03ce-439d-9b16-eb666e71e303"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"5\" halign=\"left\">price (STETH/ETH)</th>\n",
              "      <th>volume_coin0</th>\n",
              "      <th>volume_coin1</th>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
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              "    <tr>\n",
              "      <th>block_number</th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>14564686</th>\n",
              "      <td>0.998864</td>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998869</td>\n",
              "      <td>46992.268443</td>\n",
              "      <td>47027.021337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14564946</th>\n",
              "      <td>0.998932</td>\n",
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              "      <td>0.998928</td>\n",
              "      <td>0.998929</td>\n",
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              "      <td>4301.799461</td>\n",
              "      <td>4306.109799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14565206</th>\n",
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              "      <td>0.998937</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998931</td>\n",
              "      <td>11231.449626</td>\n",
              "      <td>11240.503320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14565466</th>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.998918</td>\n",
              "      <td>3095.994754</td>\n",
              "      <td>3100.584796</td>\n",
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              "    <tr>\n",
              "      <th>14565726</th>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.999017</td>\n",
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              "      <td>0.999015</td>\n",
              "      <td>0.998995</td>\n",
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              "      <td>139924.738127</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>17191466</th>\n",
              "      <td>0.999527</td>\n",
              "      <td>0.999527</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999521</td>\n",
              "      <td>14199.262423</td>\n",
              "      <td>14211.673507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17191726</th>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>407.116935</td>\n",
              "      <td>407.477323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17191986</th>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0.999501</td>\n",
              "      <td>10950.659521</td>\n",
              "      <td>10960.398701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17192246</th>\n",
              "      <td>0.999495</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>797.511410</td>\n",
              "      <td>798.192932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17192506</th>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>130.984658</td>\n",
              "      <td>131.011733</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10108 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             price (STETH/ETH)                                          \\\n",
              "                         first       max       min      last      mean   \n",
              "block_number                                                             \n",
              "14564686              0.998864  0.998932  0.998862  0.998932  0.998869   \n",
              "14564946              0.998932  0.998932  0.998928  0.998929  0.998930   \n",
              "14565206              0.998929  0.998937  0.998922  0.998922  0.998931   \n",
              "14565466              0.998922  0.998922  0.998917  0.998917  0.998918   \n",
              "14565726              0.998917  0.999017  0.998917  0.999015  0.998995   \n",
              "...                        ...       ...       ...       ...       ...   \n",
              "17191466              0.999527  0.999527  0.999514  0.999514  0.999521   \n",
              "17191726              0.999514  0.999514  0.999514  0.999514  0.999514   \n",
              "17191986              0.999514  0.999514  0.999494  0.999495  0.999501   \n",
              "17192246              0.999495  0.999497  0.999494  0.999497  0.999494   \n",
              "17192506              0.999497  0.999497  0.999497  0.999497  0.999497   \n",
              "\n",
              "               volume_coin0   volume_coin1  \n",
              "                        sum            sum  \n",
              "block_number                                \n",
              "14564686       46992.268443   47027.021337  \n",
              "14564946        4301.799461    4306.109799  \n",
              "14565206       11231.449626   11240.503320  \n",
              "14565466        3095.994754    3100.584796  \n",
              "14565726      139831.906439  139924.738127  \n",
              "...                     ...            ...  \n",
              "17191466       14199.262423   14211.673507  \n",
              "17191726         407.116935     407.477323  \n",
              "17191986       10950.659521   10960.398701  \n",
              "17192246         797.511410     798.192932  \n",
              "17192506         130.984658     131.011733  \n",
              "\n",
              "[10108 rows x 7 columns]"
            ]
          },
          "execution_count": 90,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# smooth data using mean over 260 blocks for ~ 1h candles\n",
        "s = (query_swaps_filtered.index.to_series() / window).astype(int)\n",
        "query_swaps_candled = query_swaps_filtered.groupby(s).agg({'price (STETH/ETH)': ['first', 'max', 'min', 'last', 'mean'], 'volume_coin0': 'sum', 'volume_coin1': 'sum'}).set_index(s.index[::window])\n",
        "query_swaps_candled"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "id": "4d2cba1d",
      "metadata": {
        "id": "4d2cba1d",
        "outputId": "4494b923-699f-47b3-9db0-0b49290b5109"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Axes: xlabel='block_number'>"
            ]
          },
          "execution_count": 91,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# make some fancy plots w subplots ...\n",
        "fig, ax = plt.subplots(2, 1)\n",
        "query_swaps.plot(x='block_number', y='price (STETH/ETH)', ax=ax[0])\n",
        "query_swaps_candled['price (STETH/ETH)'].plot(y='mean', ax=ax[0], label='price (STETH/ETH) - 1H mean')\n",
        "query_swaps_candled['volume_coin0'].plot(y='sum', color='g', ax=ax[1], label='volume (ETH)')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "id": "13db0817",
      "metadata": {
        "id": "13db0817"
      },
      "outputs": [],
      "source": [
        "# plot the candles since that's dope :o"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "id": "e0e2664d",
      "metadata": {
        "id": "e0e2664d"
      },
      "outputs": [],
      "source": [
        "# get the timestamps every 24 candles (~ 24h) and interpolate the rest (SEE banteg gist again)\n",
        "# NOTE: include last block in index for interp to work properly\n",
        "T = 24\n",
        "blocks = query_swaps_candled.index[::24].to_list() + [query_swaps_candled.index[-1]]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "id": "1fd0e66e",
      "metadata": {
        "id": "1fd0e66e",
        "outputId": "d3c8546f-847e-41c2-9543-5657bb955af3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 2.38 s, sys: 27.4 ms, total: 2.41 s\n",
            "Wall time: 17.3 s\n"
          ]
        }
      ],
      "source": [
        "%time timestamps = [ chain.blocks[i].timestamp for i in blocks ]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 95,
      "id": "002a577e",
      "metadata": {
        "id": "002a577e",
        "outputId": "71de742f-29cd-4d15-f2f8-699ba22cfff4"
      },
      "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 tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"5\" halign=\"left\">price (STETH/ETH)</th>\n",
              "      <th>volume_coin0</th>\n",
              "      <th>volume_coin1</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>first</th>\n",
              "      <th>max</th>\n",
              "      <th>min</th>\n",
              "      <th>last</th>\n",
              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>block_number</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>14564686</th>\n",
              "      <td>0.998864</td>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998862</td>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998869</td>\n",
              "      <td>46992.268443</td>\n",
              "      <td>47027.021337</td>\n",
              "      <td>2022-04-11 13:35:31.000000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14564946</th>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998932</td>\n",
              "      <td>0.998928</td>\n",
              "      <td>0.998929</td>\n",
              "      <td>0.998930</td>\n",
              "      <td>4301.799461</td>\n",
              "      <td>4306.109799</td>\n",
              "      <td>2022-04-11 14:34:55.624999936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14565206</th>\n",
              "      <td>0.998929</td>\n",
              "      <td>0.998937</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998931</td>\n",
              "      <td>11231.449626</td>\n",
              "      <td>11240.503320</td>\n",
              "      <td>2022-04-11 15:34:20.249999872</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14565466</th>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998922</td>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.998918</td>\n",
              "      <td>3095.994754</td>\n",
              "      <td>3100.584796</td>\n",
              "      <td>2022-04-11 16:33:44.875000064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14565726</th>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.999017</td>\n",
              "      <td>0.998917</td>\n",
              "      <td>0.999015</td>\n",
              "      <td>0.998995</td>\n",
              "      <td>139831.906439</td>\n",
              "      <td>139924.738127</td>\n",
              "      <td>2022-04-11 17:33:09.500000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17191466</th>\n",
              "      <td>0.999527</td>\n",
              "      <td>0.999527</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999521</td>\n",
              "      <td>14199.262423</td>\n",
              "      <td>14211.673507</td>\n",
              "      <td>2023-05-05 02:28:38.000000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17191726</th>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>407.116935</td>\n",
              "      <td>407.477323</td>\n",
              "      <td>2023-05-05 03:21:11.000000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17191986</th>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999514</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>0.999501</td>\n",
              "      <td>10950.659521</td>\n",
              "      <td>10960.398701</td>\n",
              "      <td>2023-05-05 04:13:55.000000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17192246</th>\n",
              "      <td>0.999495</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999494</td>\n",
              "      <td>797.511410</td>\n",
              "      <td>798.192932</td>\n",
              "      <td>2023-05-05 05:06:39.000000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17192506</th>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>0.999497</td>\n",
              "      <td>130.984658</td>\n",
              "      <td>131.011733</td>\n",
              "      <td>2023-05-05 05:59:23.000000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10108 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             price (STETH/ETH)                                          \\\n",
              "                         first       max       min      last      mean   \n",
              "block_number                                                             \n",
              "14564686              0.998864  0.998932  0.998862  0.998932  0.998869   \n",
              "14564946              0.998932  0.998932  0.998928  0.998929  0.998930   \n",
              "14565206              0.998929  0.998937  0.998922  0.998922  0.998931   \n",
              "14565466              0.998922  0.998922  0.998917  0.998917  0.998918   \n",
              "14565726              0.998917  0.999017  0.998917  0.999015  0.998995   \n",
              "...                        ...       ...       ...       ...       ...   \n",
              "17191466              0.999527  0.999527  0.999514  0.999514  0.999521   \n",
              "17191726              0.999514  0.999514  0.999514  0.999514  0.999514   \n",
              "17191986              0.999514  0.999514  0.999494  0.999495  0.999501   \n",
              "17192246              0.999495  0.999497  0.999494  0.999497  0.999494   \n",
              "17192506              0.999497  0.999497  0.999497  0.999497  0.999497   \n",
              "\n",
              "               volume_coin0   volume_coin1                     timestamp  \n",
              "                        sum            sum                                \n",
              "block_number                                                              \n",
              "14564686       46992.268443   47027.021337 2022-04-11 13:35:31.000000000  \n",
              "14564946        4301.799461    4306.109799 2022-04-11 14:34:55.624999936  \n",
              "14565206       11231.449626   11240.503320 2022-04-11 15:34:20.249999872  \n",
              "14565466        3095.994754    3100.584796 2022-04-11 16:33:44.875000064  \n",
              "14565726      139831.906439  139924.738127 2022-04-11 17:33:09.500000000  \n",
              "...                     ...            ...                           ...  \n",
              "17191466       14199.262423   14211.673507 2023-05-05 02:28:38.000000000  \n",
              "17191726         407.116935     407.477323 2023-05-05 03:21:11.000000000  \n",
              "17191986       10950.659521   10960.398701 2023-05-05 04:13:55.000000000  \n",
              "17192246         797.511410     798.192932 2023-05-05 05:06:39.000000000  \n",
              "17192506         130.984658     131.011733 2023-05-05 05:59:23.000000000  \n",
              "\n",
              "[10108 rows x 8 columns]"
            ]
          },
          "execution_count": 95,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "query_swaps_candled['timestamp'] = pd.to_datetime(np.interp(query_swaps_candled.index, blocks, timestamps) * 1e9)\n",
        "query_swaps_candled"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 96,
      "id": "48b85378",
      "metadata": {
        "id": "48b85378",
        "outputId": "ad0a638a-4be3-4b8d-c88e-85a572eacdc9"
      },
      "outputs": [
        {
          "data": {
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              "      <th>Open</th>\n",
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              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
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              "      <th>2023-05-05 04:13:55.000000000</th>\n",
              "      <td>0.999514</td>\n",
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              "      <td>0.999494</td>\n",
              "      <td>0.999495</td>\n",
              "      <td>10950.659521</td>\n",
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              "    <tr>\n",
              "      <th>2023-05-05 05:06:39.000000000</th>\n",
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              "      <th>2023-05-05 05:59:23.000000000</th>\n",
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            ],
            "text/plain": [
              "                                   Open      High       Low     Close  \\\n",
              "Date                                                                    \n",
              "2022-04-11 13:35:31.000000000  0.998864  0.998932  0.998862  0.998932   \n",
              "2022-04-11 14:34:55.624999936  0.998932  0.998932  0.998928  0.998929   \n",
              "2022-04-11 15:34:20.249999872  0.998929  0.998937  0.998922  0.998922   \n",
              "2022-04-11 16:33:44.875000064  0.998922  0.998922  0.998917  0.998917   \n",
              "2022-04-11 17:33:09.500000000  0.998917  0.999017  0.998917  0.999015   \n",
              "...                                 ...       ...       ...       ...   \n",
              "2023-05-05 02:28:38.000000000  0.999527  0.999527  0.999514  0.999514   \n",
              "2023-05-05 03:21:11.000000000  0.999514  0.999514  0.999514  0.999514   \n",
              "2023-05-05 04:13:55.000000000  0.999514  0.999514  0.999494  0.999495   \n",
              "2023-05-05 05:06:39.000000000  0.999495  0.999497  0.999494  0.999497   \n",
              "2023-05-05 05:59:23.000000000  0.999497  0.999497  0.999497  0.999497   \n",
              "\n",
              "                                      Volume  \n",
              "Date                                          \n",
              "2022-04-11 13:35:31.000000000   46992.268443  \n",
              "2022-04-11 14:34:55.624999936    4301.799461  \n",
              "2022-04-11 15:34:20.249999872   11231.449626  \n",
              "2022-04-11 16:33:44.875000064    3095.994754  \n",
              "2022-04-11 17:33:09.500000000  139831.906439  \n",
              "...                                      ...  \n",
              "2023-05-05 02:28:38.000000000   14199.262423  \n",
              "2023-05-05 03:21:11.000000000     407.116935  \n",
              "2023-05-05 04:13:55.000000000   10950.659521  \n",
              "2023-05-05 05:06:39.000000000     797.511410  \n",
              "2023-05-05 05:59:23.000000000     130.984658  \n",
              "\n",
              "[10108 rows x 5 columns]"
            ]
          },
          "execution_count": 96,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# put data into new df for ohlcv with 1h candles\n",
        "query_swaps_ohlcv = pd.DataFrame({\n",
        "    'Open': query_swaps_candled['price (STETH/ETH)']['first'],\n",
        "    'High': query_swaps_candled['price (STETH/ETH)']['max'],\n",
        "    'Low': query_swaps_candled['price (STETH/ETH)']['min'],\n",
        "    'Close': query_swaps_candled['price (STETH/ETH)']['last'],\n",
        "    'Volume': query_swaps_candled['volume_coin0']['sum'],\n",
        "    'Date': query_swaps_candled['timestamp']\n",
        "})\n",
        "query_swaps_ohlcv = query_swaps_ohlcv.set_index('Date')\n",
        "query_swaps_ohlcv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "id": "9e2027a5",
      "metadata": {
        "id": "9e2027a5",
        "outputId": "359efe65-c77f-4c41-bcc6-fd623ce28550"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/mihai/.pyenv/versions/3.10.11/lib/python3.10/site-packages/mplfinance/_arg_validators.py:83: UserWarning: \n",
            "\n",
            " ================================================================= \n",
            "\n",
            "   WARNING: YOU ARE PLOTTING SO MUCH DATA THAT IT MAY NOT BE\n",
            "            POSSIBLE TO SEE DETAILS (Candles, Ohlc-Bars, Etc.)\n",
            "   For more information see:\n",
            "   - https://github.com/matplotlib/mplfinance/wiki/Plotting-Too-Much-Data\n",
            "   \n",
            "   TO SILENCE THIS WARNING, set `type='line'` in `mpf.plot()`\n",
            "   OR set kwarg `warn_too_much_data=N` where N is an integer \n",
            "   LARGER than the number of data points you want to plot.\n",
            "\n",
            " ================================================================ \n",
            "  warnings.warn('\\n\\n ================================================================= '+\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x575 with 4 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# oooooo fancy :)\n",
        "def fancy_plot(\n",
        "    data,\n",
        "    mav=(10, 50),\n",
        "    plt_type='candle',\n",
        "    volume=True,\n",
        "    datetime_format='%b%d',\n",
        "    xrotation=0,\n",
        "    tight_layout=True,\n",
        "    style='mike', # mpf.available_styles() to pick your fav\n",
        "    **kwargs\n",
        "):\n",
        "    mpf.plot(\n",
        "        data,\n",
        "        warn_too_much_data=2500,\n",
        "        mav=mav,\n",
        "        type=plt_type,\n",
        "        volume=volume,\n",
        "        datetime_format=datetime_format,\n",
        "        xrotation=xrotation,\n",
        "        tight_layout=tight_layout,\n",
        "        style=style,\n",
        "        **kwargs\n",
        "    )\n",
        "\n",
        "title=\"STETH/ETH\"\n",
        "fancy_plot(query_swaps_ohlcv, mav=(10, 50, 200), title=title)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 98,
      "id": "2235e778",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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T2LBhQ5adT/nz59d9XqZMGYN603M+ffDBBwaOzOHDh3F0dMTFxYVy5crpbko//PADlStXJiEhwaQ26dsBiSOc//77r0GbbPG6t2/fPt1IwKtXrxg4cCBt2rQxepwKFSpk1BEYMmQIX3/9tUXblLzv2dvbM2LECN2N+sWLF4SEhPDq1Svu3r1Lz549dce4a9eu/Pnnn3Tq1EnXprNnzwKJ14jDhw9TpUoVqlatir29PbVqvYkiePny5Qz1PS8vrxT6AMyaNYuGDRsatOnrr782mrdQoUJMnjxZ97+57k8ajSbVvnfixAm2bdtGrly5AHj9+jV//fUXUVFRjB49Gnt7eypWrMjx48dp06aN0eME8O2339KtWzeDtK1btxIaGmqgY2xsLHPnzmX27NkAuhG0e/fu6bQpX758mm2qUKECoaGhhIaGcuHCBS5VTBxJ9yp0wOznU6NGjQyu8Vn5HJFkZ/v27dPVpmmhJXigBkcnR+LAoE0NGzakbdu2eHl5UX/CVcqGvGJg1EVcHkqEnbqHBwVwU7nw3BNOfiUjWhtn8b6XkeOUdL+1hee906dP6/4OCgoyqHfmzJnMmjXLIK1AgQLY29sTFhZmkB4WFmbQ1/Xx9/fHy8tLN+rSsmVLOnXqpHOcoqOjOXXqFBMmTODmzZuEhYXRs2dPGjRowN27dwG4desWwcHBTJs2jbFjx/L69Wu8vLzw8PDQPbuVKlUKgO+++47vv/+eK1eu0KdPH3bt2kW9evV0Zdkczs7OUlb9FCxYUEqicOHC0vDhw6U8efJICoVCAiSFQiE5Ojrqfuzt7SVAUiqVBul2dnYSIDk4OBiky+VyCTBISysdkORyebrSHRwcJECys7MzSFcqlRIg2dvbG6Rbsk158uSRBg8enKJsc7Vp4cKFuuN0584dydnZOUWbcufOLXXo0CHNNq1evVrSp3z58qm2SZ/Dhw9nuE3ly5c3KGP16tWpHqdZs2YZ5G3evLlOS19fX8nX11d6//33DfJMnz7d6HH67bffJEmSJO9dtxO1qdpN+t/SjSnK9/X1lSpRTAp1WCHlcnB+a5t+//13gzJKfntFYsQ5o21Krl3ScWpqV0m6w8/SZLuPpcOHDxvkS2/fmzJlSorvOTg4SIMHD5batm0r/fbbb9K5c+ekkJAQKSYmRoqNjZWCg4Olbdu2Se3btzd6/Nq3by/t2LFDevTokRQfHy+9fv1aCg4Olg4dOiTNnz9fKleunGRvb59CA2O8//77bz2ffHx8dPmfP39uYMuyZcsMynN3d09336tQoYK0ZcsWKTIyUoqOjpZOnjwpde3aNUXfad26ta7vValSRdq/f7907Ngx6f79+9LLly+l+Ph46enTp9LBgwel0aNH646rUqmUTp8+rSvn77//TnGc2rRpY1BXixYtJEdHR8nV1VWaMGGCdOrUKen58+eSWq2WIiMjpVu3bkl//vmn9M0336Ro065du3TlzJ8/P81rxK1bt3R59f+WJEnq3r270evevXv3dHl+//13qUqVKtKmTZuksLAwKSYmRjp//rw0aNCgFNcI/X5w//59ycvLS1qxYoX06NEjSa1WS9OnT5cA6fvvv5dat26d4jgNHDjQwL4tW7ak61r+7bffGnyvefPmGbqWJ78mqdVq3d/t2rXT5a9SpYqUkJCQIo8kSVLp0qV1+YoWLSrNnz9f2rdvnxQUFCS9ePFCUqlUUkREhHTixAlp/PjxUq5cuXT5//zzT105Fy9e1N07hg8fLjk7O0slS5Y0qGvgwIGSvb29NH36dF1aQkKCVKtWLV2bvLy8DL6T1LeNXcczes/V7+vffPONru/5+flJS5cuTbwHVe0m2VfumlhOpc6Somo3ydHRUVq6dKnk6+srLV68WFIoFJK8zzZJ3mdbYl+q1FmifAdJqVQapGfmOUKhUOieW8x5z03vc0TS/Sm9zxGyT89LTJUkRpwzbJODo7RlvK907CNf6V8mSU9lK6WzLr9La+RjpAn2XaTO1JXqyTylMg5FpZ2yCdJa+WeSs4OTSW3S73vmeDby9fW1mec9V1dXg3O2cOHCup+8efOmeBYuU6aMJEmJ12v9dG9vb+nMmTNGn59LlCgh7dixQ9JoNJJarZZu3bol/fLLL1JMTIwuT5UqVaQjR47oriVnz56VNmzYIN24cUOXp3HjxtLly5d1efbt2yf9888/0t69eyVnZ2epZcuWkiRJ0ty5cw3qv3r1qjRv3rws8xcy+mM1ZyZ//vzSb7/9putM4if9P46OjhbVTt+ZCQ8Pl8qWLZupclatWmVwcytZsmSqefU5ePBghutKfmNetWpVqnn1b9aSlPiQkvSZj4+P5OPjIzVv3twgz5QpU1KUI5fLpbCwMEmSJKlJkya69OQOQPPmzaXFixdL+z/xla5W9Mmcdv85MxnVrixFpHPMlh4dvGmQL726Jm+Lfv/76aefpLcxceJEg/L69Onz1u8MHDjQqAbG0D92qf189tlnuvwajUbq2LGjpFQqpVKlSknnz5/XfXbmzJl061KtWjXp2bNnRm3avn17qjZ27dr1rW3atWuXJJPJJED65JNPdOkqlUoqWrSogR3Lly/XfR4QEKBL37t371vr0S9HqVRKMTExus86duyYatubNm1qUE7Pnj2lGzdu6P7fvXu30e/pOzNnzpyRnj9/btSuyZMnp3ouhIWFpfiesXNT/ydXrlwG+Xfs2PHW46tQKKRHjx7pvnP06FGTr0l//fWXUY1WrFihS9+8ebPBd/SvmVWqVDGqlz7nzp3TPSw2bNjQ4LN69eoZ3DsmTJig+ywyMlL3ABcQEKBLv3LlikGbChQoYFDmkiVLUr0W3blzR4qPj5eioqKk8+fPS1OmTJFcXV1T1cvb21v33X379qW4JmdUf6M/I86leh0FpNw4SIsZLF1hrrSBsdK3dJHaUlPKg5PBtc9azy0Z1mLEOQNnpkP7DlJbakr+TJYe5VkhnWvsK3WjvlSg/6lUdXHFWTrO/6SZfGKS7ebWzmx9wgw/zs7Our5bsGDBtz4Lu7q6Smq1WurZs6dB+rp166SdO3em+d18+fJJnp6ekrOzs7RgwQLp2rVrRp+1y5QpIzk7O0ubN2+W9uzZkyJPkSJFpBIlSkjOzs7SmTNnpF9++UVydnaWKlWqJEmSJA0ZMsQg/+bNm6WNGzda3WlJ7UfEyBOk4MKFC7q/CxYsyK1bt7h69Srnzp3j4sWLHD16lCtXrlis/uLFi/PVV1+lSH/48CF//vmn2evr1asXdevWBaB69eoABlONUuO9996jUKFChIaGcuLEiTTLv3v3LvWKNSSoWBRftU9s26ZNm3QLX82FMe12Es3E4m5mrQcSp58cOXKEK1eu8OzZM2JiYnB1daV169bUq1cPgKlTp7JmzRpCQ0MBDKbe3Lx5k82bN6NSqfDw8KBSpUoG0zc2btxIQEAA3333nW6q2dmzZ9m0aZMuT3qGvFesWEGPHj147733sLOzY8eOHQafa7Va/v33X4YOHZrutq9Zs4Z8+fLp/vfz8+P8+fO0aNGCTp06pfo9jUZDZGQkO3bs4MmTJ0RFReHk5EStWrXo0KEDcrmcdu3a0a1bN7Zs2cJff/3FvHnz8PDwQKFQMHToUN00CTs7O4PF1L/++iuQOOXmgw8+0KVv3bqVc+fOkSdPHjw8PGjUqBFly5Y1sKtevXoGUzXOnDmTahv0dXr58iU7duygYsWKTJs2DYAPPviAYsWK8fjx41TLqFevHqGhofj6+uLg4MDgwYN16zOmTJnCzp07uXTpUorvJU29PHDgAEeOHCFfvnxp1gNQqVIlg//1p4SkxoABAyhWrJju/zlz5rz1O2/j6tWr5MmThw8++IAPP/yQihUrEhkZSb9+/YDE82HXrl18/PHHRr+v1Wq5ceMGZ86c4cmTJzx//hylUkmlSpX4+OOPUSgU1KlTh1GjRrFgwQJOnTrFmTNndHPwR44cyWeffaYr75NPPtH9vW7dOuLj41EqlQZTg5OfX5GRkURFReHq6gpgMLU3OUnhXpVKJbVr16Z27doMHjyYli1bcu/evRT59ftc48aNdetCsopqFGclI3nEM8bwG+UoSnVKMIlueFKYcwRxTHOLvHcl5JL1QuNnGEmi4rNY3ucDxl3pTBxR/Mwe6s/yQKuErSfOgFPqj4JRxPAJP/MP3/GQSH5hfxYanzNRq9VcvHiRFi1a4OeXGL1UJpPRokULfHx80vxuUlCTpFDXW7emDO4QExNDTEwMefPmpXXr1kyaNClFnpcvXwKJ52nt2rV16yUfPHhASEhIiqnp5cqVY9++fZlqb1YgnBlBCv744w9GjRqlm9ctl8upUaNGijUpEydOZPv27Wav39PT02BhXBKHDh2yiDMzatSoFGn6c9pTI2k+eFJUp/SWn/Soe+7cObM7M6lpZwlmzJhBXFwctWvXpnLlyuTLlw+NRsO2bdt0zoyDgwOtWrVi3bp1gOEC1KlTpxo4JpC4ziopz969e9m7dy+fffaZzpm5du0aCxYsyJCd8fHxtGrVigULFugiv+gTHBzMhg0b0n0s6tevb7CWYs2aNQbzqvfv30/r1q2Nfnf//v3s2LGDefPmUaVKFdzc3FCr1Rw5coTatWvj4eEBQNu2bdmyZQsajYZly5bp5lwPGzaMmTNnIkkSrVq10j3cx8fH6xaV62scFRXFJ598glqtNrAj+b4C+s6NSqXi6dOnRu3PnTu3QdSbbdu2ERcXx/r163XOjJ2dHYMGDdJF9zOGSqWiadOmuvnl27Zt4+DBg7rvDx8+nDFjxhj97rVr12jfvn2KxbDGcHFxwdfXV/d/aGgoy5cvT/M7MpnMYA3L1atX2bVr11vrSg8LFizggw8+QC6X8+WXXxIaGqo7XgsXLkzzOnLjxg0qV66Mu7s79erVw93dHScnJ86fP0/VqlWpVq0akNh3ks6RhQsXsn79eiDRefnuu++AxAcT/YADK1euBCBfvnwGi5eTHnj0efnypc6ZKViwYIrPAwICOHnyJMHBwRQsWJCePXvqQsOWLFmSP/74g8aNG6f4XnBwsO7vXLly4e7ubpBmKWTIGEErvqMr3vhR7ud29HP8EpVKlfjypddWisZoabHzd1prq9NwocSV+Dkc4joL2U0ADy1uY2bIgxNjzoXS5/ZGXGLjOEZ57jaX6LRuIvFoqKs0Ht3PGA+JpA+L2M7XBPGUfVjuZea7wuLFi/H19eXixYucO3eOMWPG4OzszNq1a4HEl3AhISG6SKp169bF3d2dK1eu4O7uzvfff49cLuenn37Sldm6dWtkMhmBgYF4enoyc+ZMAgMDdWVC4rrBiIgIHj58SJUqVZg3bx47d+7E399fl2fhwoV8//33XL16lStXrtC3b1/Kly9P3759s0idjGM1Z0aj0bB9+/YsffOSU7C0dgkJCbRq1Yqvv/6aoUOHUrx48RR5KlasyNatW+ncubPuzUJ2wVyx0rt06QJg9M1ITiap/zVr1oxffvnlraFUkx7QIXHxfdJD1OrVqxk1ahR37twhMDCQc+fOceTIEYPADeYgf/78bN68mffffx9IDFN98OBBihUrxoABAyhVqhSrVq2iVq1afP75528tL8lRS2LNmjUG///++++pOjPu7u7Ur1+f69evp1mHvma+vr5MnjwZJycnSpYsSdu2bdm9e7fBm/Xt27cTGRkJJD70hoWF4ebmhqurK/fv3+f8+fPcuXOHGzducOTIEYMAG4BBsIlnz56latcnn3yiWxgOiS8+AO7cucPZs2d12gwePDhNZ+bYsWMGC2UPHTpEcHAwJUqUANCNlBpjzpw56br2lShRgp07d+pGW589e0b79u3TbB8k3uwrVKig+//HH39MkcfDw4NevXqlSI+KitI5BsbYt28fAQEBVK1alf79+/P69WsAIiIiWLNmjdEyk8ibNy+rVq2iU6dOKaITJrctic2bNzN//nzc3d3JlSsXvXr1Yvv27QYjemfOnOHq1atGy9KPHpVWWhKVKlXi5s2bBmmTJ0/m7NmzOk0bNWpE5cqVU5wDSf03iUKFClncmSlGfhYzmFoFK3BmiETZ4u1I4U66liDUFTZwnM3y03RoFcLDXVdpn1CLXUxkGXvxZhdq3ozmd+jQwWr3RUcUDON9xtKWa09eM7ZzM044hKL6dQg+zXyIX2fk3InS07nXVnAtkZi26U0Ah8s84DN+4xeG0Y453CQkQ3aZ+7nF3d2dxYsX6xxOwMBeW2fLli0ULFiQSZMmUbhwYa5cuUKXLl10QQE8PDwMnlUcHR354YcfKF26NNHR0ezbt4+hQ4cSFRWly+Pi4sK0adMoVqwYz58/Z9u2bUybNs1A8yJFijBnzhzc3Nx48uQJ69evTzHyvHTpUhwdHfnxxx/Jly8fV69epWPHjkZHVG0FqzszgoyTFdrFxMQwbdo0pk2bRrly5WjQoAFNmjSha9euFC5cGEgcsRk3bpzZL9qHDh2iZcuWZi1Tn+TOTIsWLTh8OHF/lqQh3vXr13Po0KFUy6hfvz7FixcnMjJS90Y5NVq0aEHRw2r60pSOzDXN+LeQmnYHDx6kRYsWZqlDo9Fw5swZAgMDyZ0791vz64eo/f777ylZsiSdOnXC0dGR5s2bG+zzExoaSo8ePTh+/LhZbAX46aefdI7M4cOHdX9D4pSj3377DUiMDrdkyZI091aBxIdKfZKPYqQ2qgGJD5fp2YtFX7PIyEj++OMPXYTBkSNHsn//fp0zDRg8QKtUKrp3787q1avx9PTE3d3dIAoQJD5Ud+7cWTe6kdYDqj76U8yePn3Kv//+q/t//fr1OmfG09OTFi1apHoOGdPo6dOnOmdGfwqfPuHh4bpRvrRo0KAB27Zt00XoefToEe3atUv1oV2fCRMm6P6+d+8eGzduTJEntRHQpP0f0sLb25vffvsNJycn3dS+X3755a0jTb/++qvBMU8N/b6TNLKXNDVx2LBh1KhRwyC6kr69z58/JyEhQTc6ox+aOQn9tIiICIPPkjsykBgZb9WqVQYPTMacmeQOWnr7ZIbQe2ifWfNT+gfU4C/NCZ5OKIXcRQkqUo1CB4l6btuReO89TxBbOM1iBtOO2kxiI0dJbH/Hjh2z3Jmxx45+NOUrOvCEFwzDhyNNZ4DzU4hKHHXe+aJa4oN/8od+/f9dS4C78Z3o/bhABdz5Ay8+YCaRRKfbPnM/t4SEhLwJp+xawmzlZiU+Pj6pTitr27atwf/Hjh1L8yUPJL5YfdvL1eXLl791dBoSR5EzOgvCmlht00ylUsm4ceNS3UBMkDpZrd3t27dZt24do0aNomzZsgZz1K25qVtmMbbPTEZJerO5c+fOdK2vaUR5TpH2Q3KavApJfVO0LEapVPLzzz8bODLjx48nX758yGQyg52Ek/P69Wu6du1K0aJF6dy5M+PHj8fHx4eQkMS3fEWLFjXYg8Mc6O89kny9xKlTp3R/y+Vy3Vv8tHjx4oXB/0nOfWr/J1GuXDlq136z58OGDRvw8PBALpcjk8nSXKeiv/9Nu3btGD58uO6B//79+wZOBSTe+MqWLUuNGjUYMGAA06ZN4++//9a9ofvggw8MplKFh4fr/k7NkahcubLB9MvChQuTkJCg2wxRf7oDkOYaJGMa6acl1ziJ169fv/Xa17t3bw4ePKhzZM6dO0eDBg3S5ci0bNnSYJ+HBQsWpOv8zgh//PEHT5480f0fHx/PkiVL0vyOk5OTwVqsAwcOULZsWd3eI2lNv/3ll1+IjY0FEtcEbt68WReqPDo62sBZU6lUBg5J8rVVBQsWNHBmLl++nKbdqWFsOp1+CHYgRdhas7CpG/k29edXPqXrpfIM0yxnHGsZ9bUXI0eONO7I6G1IKeu9Dc/vr+j63zUe8QGz2MJpVjCSw0ylD02Qq1MWY0k6UocTTGc4rZjIBtowkyPcgD+7g29dnbPid1dp8oP/Avw4TxCrGY0yA+/DxTOfwJJYzZmRy+VUrVo1zeFygXEsrd2AAQMYNWqUbl60Psk3gEo+NSA7YI43fl27dgUSh4rTQwPKcoY7ma9w58g3b88C/RL/D/SzyhspuVyeYmrZb7/9pnsA1Z/+lJwqVaqgVCoJCwtjx44dLFiwgE8//dRgYXKZMmUMHmz013uk5Silhv5+KA0aNDD4LPnaqKSHvrRI2pckiYEDBxr8n9oOzsnXF2zevJnHjx8jSRIVK1ZMczF1QECAbk6zvb29wajAqlWrDB4OFQqFbvTnypUrrF27lqlTp9KtWzd2796ty6c/Xe7OnTd908HBATe3lAEjMhIgARLXlBl7sw/QtGlTSpcurfu/RYsWulEZSKlxEjKZLM1r39SpU1m/fr1uxGPz5s289957Omf5bUycOFH3d1hYmC6oQnIOHz6MTCZL8aPfptRQqVQsXbpU9/+GDRvSHM2DxNFA/U36/Pz8uHv3LlqtlkKFCqU5kh0ZGalbNwMYjO5s3rw5xbTObdu26f6uVKmSwUhi0h4wSfz999+6v4cPH06HDh1S1J8nTx4GDx5skGYsgIz+dOaYmJh0H7OM8D5VOMo07JDTjB/St/ZjU7c3117X4micixr0Pw0JLGIPNfkGX/7lU9rwwVQ5zaiYSoHmIzeOLGMoc+nLAvxoxhR2ceHtX0yLqGAIOZ/4u9dWGHEuxUuzsazGAQXz6JfuYpM/txjrKwJBZhEBAAQpKF26NFOnTmXhwoUcP36cixcvEh4eTp48eWjfvr3BDVv/4chcpBbNDGDPnj1vXW9gaapVq0a5cuV49epVuqJ7DOzVjyp1q9KA11TnTZSpt82vtyR1KMN5gt6eMRX05+lCYj/YtWsX5cqVo0+fPql+b86cOTRr1owDBw4QHBzM06dPcXFxoXfv3ro8cXFxxMTE6P5/9OiRLrJK+/btmTNnDuHh4ahUKhYvXvxWWw8cOKB7gGvevDkHDhzg4MGDuLu7Gzgir1694tixY28t78yZM1y6dEm39mfgwIEUKFCAc+fO0bJlS4Npc/rcuXPHYArPzz//TK1atcidOzeDBg0yumO8Pj///DOtWrUC0D2sJyQk6KbJJeHi4kJAQACBgYGcOHGC0NBQXr58Sbly5WjXrp0un/7akTNnzhAbG6srt27dugbntkKhoH///rr/nz59anR6ZaFChXQ2Ojs706dPH3755ZcU+ZRKJcePH2ft2rUolUqGDBmi+0yr1WbqvPj5558NAjzcv3+fM2fOMHr0aIN8qZ13NWvWNIgCt2jRonQFGcgMixYt0o0UpTUil0RYWBjPnz/XjZolzbOXJIn+/fsbrHkyxs8//6xzRvWdImM6LFq0iJEjR1KwYEHkcjl79+7l119/xdXVlZEjR+ryHTlyxGDRcOXKlfH19eXevXvs27ePBw8e4ObmRs+ePQ2mOe7bt8/oVE79EbETJ06YfU1ofcqyitF8wx9sIvXok2khe/mQ/PYFeAop1mnEoeYPjrGe4+z7wIff149hG2eZwmZe8vaXJBmlFqXxZTj3Cac5UwkjZbCGFOhNs3N3d+f+/fsp8+hPORtxzuiUszjU9GcJ+/me0XzAMjIe5coaU/EEORfhzAhSRalU0rJly1Tf+p09e9YikbPSisgVERFhdWcmKYrZrl27DEapUmPwqMS1DtMxHAVIz/x6SzGO9vTl7Y5AagQHBxs80Dds2FA3yvHbb78ZPJwmx9XVVTeyZYyffvrJ4CFy8+bNuj6YK1cu3ZqG6OjodDkz48ePp169erpQu8b6tEajYdSoUUajNxlj8ODBHDp0SDd62aFDB92bRn9/f90DvT7h4eGsWLGCTz/9FEh02pN2d798+TJ3795Nc060n58fd+7cMZj6s2/fvlSjsJUvXz7V3aRfv35tMHVNpVJx6NAh3Tztxo0bGzgznTp1MnhgXrhwodFwxU5OToSGhup0GTJkiFFn5sSJE5QvX55vvvkmxWfTp0/n4sWLRu1Oi+RTBEuVKsW8efNS5EvtvNMflXn58qXB6Im5efnyZYbWDyQkJDBr1ixde/Lnz687Dx49esS+ffsMHLHkXL16lQMHDhisF7t+/brRkPJhYWH06NGDHTt2kCdPHooVK8YPP/xgkOfmzZsGLyD0KV26tIHTo8+lS5d0oaiT06RJE93fe/bsSbUtmSEPTixnKDPYmmlHBkC59RO8Wi9jdPIP9BbNS5u6EdRcYtD6KSygPxf5kd1cZAfnOMwNVJjopEkwhJZM4WPmsp1l7EdKGbbAOHqOSkhISJrrg97GU6LoxxJ28A13eCIinAmsitXmeKnValavXp0iZKjg7Vhau4ULF9K1a1d+/vlnTpw4QVBQENHR0bqQrQcOHGDMmDE0adKE6Oj0LwC0FUyNZpa0XsYmopjpR6EBcKuie2O4ePFi3cN+gQIFDLI1ta9FjTaZC3OtVqtZtWoVbdq0YcWKFYSFhREfH8/NmzcZP368bqG6MebPn8/8+fM5evQoDx48ICYmBpVKRUhICLt376ZXr1668LFJ/PLLL0ycOJGbN28SHx+fYXvv3r1LtWrVmDp1KqdPn+b58+doNBpiYmK4desWv/76K3Xr1tVF5koPly5dokGDBvz11188f/6cmJgYzp49S58+fXTx+o0xduxYfH19CQoKQqVS8fjxY5YtW0bz5s3fei5JkpTCeTP2UB4VFcWoUaP4/fffuXLlCk+fPkWtVvP69Wtu3ryJj48PderUSeEw6IcwTj6dSH+KWdLxN0ZsbKyBjvXq1dOFDNYnMDCQevXqsX79esLDw4mLi+PixYsMGDCAqVOnpqmBJa59ZcqUMYjw5evrm+q6HWsxf/58RowYwfXr11GpVISFhbFu3ToaNGiQrilZ+s4rkOoUOkgMJFKlShVdQIy4uDhevXrFhQsX+O6776hTp06KOmfPns2wYcPYsmULN27c4NmzZ6jVasLDw/H39+fTTz+lfv36BuuzkihZsqRuZEY/zLi5+JE+3OYJK/B/e+Y0MLj3Gkw/+2/RvN6038c84xN+5mN+IpJX/EhfbuDNUobwITVwyMS7ZLkK6q6WMY72fIw3S9mXfkcmGTt37szU9/S5QjBerOIXhlGClGG69bHoc4veuibKd0j8Sfpbf32pkSlz6cUOOXKy0f5C7xiy/3YLzhKcnZ11F7JcuXIZTCURCGyBpMgiqb1ZLFu2LLdv3yY2NpZChQrpQqumxTbG8xenWcdRs9pqFL2pD0kPvinevo04x7SrGkqHBDPgQfr3GhBYn9atW7N/f+KmdU+fPsXDw8Ns03HkcjlBQUG6oB7169dPde1KZrh37x6lSpUCEsNyJ19HIbAsSdcuSHQYPDw8UkQjsxYTJ05k9uzZAKxdu9Zg3dnbrslvozv1mUlv3mNK+qZiZYak6Vgh58G3Lj4+PkbtrUlJOlGXTtSlALk5xHX8CeAAAYTwPM0qSlCQA8Vno3aA5ne+slxb9EkepjmVEMhLGIIWibEYf8lhjNQ0ysj3IQP9IllbFDU64VxASe7Yc+Sq1ZJchZTkkj3AqeHHxEXLidrjg+ZhDNUeutHyYVk+iK7CC2JYgB+bOIlGLxS3s7Oz7lmgUKFC4tnWClhtZMbBwYEZM2a8dZ64ICVCO9MwRb+kKWb79u1LlyNjh5xalDZt8X9G0Htb6OXlleo0giVNqtP8cTRVSbmH0NsQ/S/zZEY7V1dXmjdvTvfu3Q0ihi1fvtys6wq0Wq1u2hvAuHHjzFa2uRB9L2M4ODjQvHlzOnbsaDAS8+eff9qMI6NQKHQbpMbHx+s2CTQH7uRjLv34nNVmefg3tf9d4gH/Ywt1+ZZOzOUyD+hFI84zmwP8wDjaU46iKb73PlXwZzLh5SSOjtNmjSMDifcSvWhouJYwGnRmPjvpSj08MR7JEax37uZ2d6Vy79p89P5G+vZbw4jp5/jy5Wy+utSS4bsb0GnjABoOdKVMbQ253V1Qa10pm8uO7h93YOBPQyl7uj33X1Vk6bPXrL0cQ12/zixdNocxE4ZTr0dDitQpjmO+jAemEZgXq62ZkclkuLu7WyaWfA5HaGcapug3d+5c5s5N/14xVfBAjYbbPHl75iwkPLcTaysWYHxARwaxLEPfFf0v82RGu5o1a6bYr+Xu3bsW2QNg7dq1fP7559SpU4ePP/6YyZMnG0Q6szai72WMIkWKpOg7cXFxTJs2zToGGWHAgAG6jT6XLl1q1o355tOPnZxnL5kLIZ0cc/a/qzzkKg9ZyG5++XEx7teKUP33knwp60SIs5yD9vc4GLWLKlW/YezNWMZpfPmwV8YiCmYV9wlnMyf5mo58ivF1oFl17rqUyEeJ5p4Ub+5JieaeuJbKz5Pzjwg+dIcLy47xOvQlr5++IvrJK+JfvAnMUJbC9KIxvXLFIJNgU8xF1nKCOzzBwdURl+L5cCmRD9fiealbvDIVqpWhXOcqRJbRoBXTz6yOCAAgEFiQunhyjqBMz2u2JItrunE2oAqV8eA6xheRC2yLJ0+e8O+///Ltt99abL3a2zZmE2RPIiIiOHnyJBqNxmCvMGvz66+/prl+J7N0pR41KEVjJr89sxlZvHgxJUqUyNDu9LK8SkKbwMjfl+EsKWn6uiItqMJUPkZ6pKVd5wpc33KGD7FNZwZgAbs4xQwq4M4t3r6Gy93dPUMapYZLiXyUfL8cJZp7UqJFWXIXcyX0bDDBh+6wb8wWHp+4jyra+FrLchTlQ6rTntpUowR7uMgXdRw4VFiBdvNWnV3xm7oRHhVKeEAoABf+CyLhhgttqUmNfOXgmdEqBFmEcGYEAgtSH0/OcdfaZhjlqbOCtRzlKzowlJQRpwS2QdKeJtmd9OzBIjAvDx48MOg7jo6OLFuWsZHY7Eg+cjGL3nzDH0SRtesXlEolbdu2fbOzeyp7gemvaVSpVLr1ZDGo2MeVN9HBPtwKJK41Tk/0TGvxmGf8wTG+oVO67ichISFvNtDMwH5pTgVyUaJlWSKaqogtlsDIwd8TcvoBwQfvsHvYJkJO3kcdk1KnKnjQntoUxpXCuFKRYrjhwhFusJ5j7OB8Yl858iYQytvsCuMlaziCc/w5vkxlREqQNVjNmVGpVHh7e9v0yWmrCO1MIyv1q4sn6zlu8Xoyy2L+4SyzqIg7N9PxNg1E/zMFoZ1pCP1M413Rbzq9OMMddnLerOWaql9qQVm8vLxS30RSb7TClFDKWcFCdnGGWVSlOAE8NPjMFO1cS+aj6oB6lOtSDbca7oRfDUWmgQInlHzT4xvUr9Musyv1+ImB7OYiwURwjUf8ykFOEkgcIqJuTsBqzoxWqyUgIMBa1WdrhHamkVX6FcaV4hTgAuabA25unvCCPzjGV3RgOL5v/wKi/5mC0M40hH6m8S7o15IqtKUmTfjh7ZkziKn66UYiSOmY5IQNJJ8QxRoOM4FO9Mdwn6aMaufg6ki5ztWoOqAuHk3LELTnBqfnHuC+fyCxEa91I19pOTIyZEygE8NpxRCWc4BrGWuQ/tYH5TtAhY5waycE+pk0NU5gfqwWzczR0ZGlS5fi6OhoLROyLUI708gq/eriyQ0eE41ldhE3F4vYw0fUpLyRKDrGEP0v8wjtTEPoZxo5Xb9cOLCA/kzjL57wwuzl53T9zMHP7KEZlahFKYP09GinyKWkSr+6fLxzGF5Pp1Pns6bc3XWdZcWnsbXrb9zYdJHYiLdHEU1iHn3pRn0+ZFbGHRkw3Eso0A92jkz8DalGdhNYB6uumXFycrJm9dkaoZ1pZIV+9SjDWRtdL6NPCM/ZyAnG0T7VSDTJEf0v8wjtTEPoZxo5Wb9v6cIjIllrwT29crJ+b0V/pCKVkYkIXrGSA0ygM59guFGrMe1kchklKz2nasMwynv/j+eB4VzfcJH9Y/8m6l5kpk2tRSl60IhGTHrrHj6C7I8IACAQWIh6lGUNh61tRrpYyG5OMYOyFOYOT61tjkAgEGSI2pSmP+/xPv/L+uiRSQ/5UcGoVCp8fHxy5rokfccljVGJpezlPLOph2eqL/RU+bREl9MwOvgHcLrBtWO5WNvwZ8KrLAWawD3Tpm9NowfL2ZcljowlwuQLMoZwZgQCC6DEnhqUtNlIZsl5zDM2c5Kv6MgoEZVFIBBkIxTYsZCBeOPHXWu8jNFfpL/J8KMOnir8LiTuM5YjHRwjPOc1PvzLt3ShG28e9CW5RPke1ak2ogEhDeJwvm/HrsEbeeAfiKT9zwFtbPrUrbbUxJMi9GGRyWWliv4olcDqWDWa2aRJk96Zk9ucCO1MIyv0q0YJXhFLEGEWq8PceLOL40ynOiW4QuoXatH/Mo/QzjSEfqaRU/UbS1sS0LKUfRatJzP6dcx7Fb9NIwHbj0aWId4y5Ww5+xlOK5rnqsqjFlrKfFiRyx+F0LBRay4sPUbT21WQq2Xc33/LrGbZY8dUPuZHthON8f1lzIJeW7/66is+/fRTy9UleCtWjWb27NkztFqttUzItgjtTCMr9Ktnw/vLpMYjnuHDv8ygF52Yl2o+0f8yj9DONIR+ppET9StHUcbSls7MRUOCRevKifplGr2H+dwlClOgaAz58jYmX9mC5HZ3IZdbHn4p9JwmlYby6sFzbu4N4J8hmwjccw0kieE+fS1i1kDeQ00Cf3DMIuULbBOrRjNbtmyZiAqSCYR2ppEV+tXDkzPZzJkBWMRuPClMe2qnmkf0v8wjtDMNoZ9p5DT9ZMj4iQGs4iCXeGDx+jKj386dOy1okXWQyWWUaO5Jix87MvTqN4yefYYP+9yhXKcq2CntCLsUwrV159j67SaeVzzAl+ULov4qkIkfj8PRwcFidhXChQl0ZgqbSUA4nO8SYs2MQGAB6uPJCvytbUaGiSaemfzNVD5mP1dQobG2SQKBQGCUQTSnMK78yA5rm5IqOWH/mCQKVHSj6sD6VOlXB7m9nLt+1zn6wx7uF1+BKs4efEel+M5ybvCcSNaoRnHjtIQlYzPMox8HuYY/OXsvJUFKhDMjEOhhjrnkHuSnIHm4xH3TDbICGznBMN5nBK1Ywl5rmyMQCN4xFi9eDCSuMUntmuxOPn6gOwNYSiw5aw2QLSG3l1O+a3XqeDWjSF0PAv++yp6hG7nvfxsp4b/RjxFpP0pu5AQxCjXLNo7kX9V3LOEf5GrQKoxkjgqmQ+0i+EHiWhzXEonrc96yOWUX6lGfsjS1wGapAttHODMCgR7mWKBZD0+u8pA41GawKOvRIjGJTazjM/7mLI95ZnKZ+g8nYudkgUCwePFilEolKpUKr8V7DXZXL1WqFPfv3wdSvybPpx/bOcdRbmah1e8Ozm65qTmiEbU+bYwmVs2Fpcf5q+MK4qMytwn0Prur/DtXxqExBxmraUvxSXJufSjhiMLwXrmpGx3f90l0ZlxLgHsdIFl/SebkFiQPc+jDeNbyjGgTWi3IrljNmYmLi2P06NHExdn27ui2iNDONCytXz3KcoY7Fik7qzhBIH9zliUMphveBvs2ZEY/pVJp/IPyHd48xNQaku63cNkVce6ahtDPNGxJP6VSyciRI/Hx8UncVT3wzXQsHx+fNKdndaUeNShFYyZnhak6bEk/S1G0fgnqfNaMij1q8ODgHf4ZsZm7e26AZNr8sLi4OD79fAxxmjjWcIgdvX+hop+c88xmEf+wikNpTms26C8YOrlz6MMxbuLHBZNsFGRfrBYAQC6Xkz9/fuRyq5mQbRHamYal9auPJ+cIskjZWckP/EkxCjCS1gbpJuu3qdsbZyXQD3aOTPyd9Bbuv83YFi9erBvRodfWNyM62Rhx7pqG0M80sot+aTky+cjFLHozkfVEEZOFVmUf/TKKndKOKv3qMuD0F3yyfxRxz2L4tfo8Nrfz5e7u6yY7MmConYRESE048L2Wr1jLJzTmOP+jHbUMvxQVDCHnU92MNBcOrGAEdSjDRNabbKMg+2K1M1KpVDJjxozU39gKUkVoZxqW1M8ZJVUpnu1HZgBeE89oVvItXaiIuy7dYvrp3bjSpHyHxJ+kvzv6JP7utRVGnLNpp0ecu6Yh9DONnKDfdHpxlrvs5HyW150T9NPHIa8Tjb5tzagHP9Dou9YErDnL0mJT+feLv3l+O9ysdRnVTgb/cJlWTOcndjGPfmxjPK4P//t8UzfwrQubuuHl5cXIkSN1IzKeFOYfvqMAeWjNdCJ4ZVZ7BdkLsWZGIDAjNSnFU6II4bm1TTEL5whiOftYzjA+ZJZlo5slm1pmMFde/zO96SgG01NaTNXNrxYIBDmPllShHTVpLBZ5m0SeYq7U+7I5NUY04snZh+wevIGgf6y39kiLxHqOs4NzfE47Rs8qy08MYBbbCOelQV475AzgPSbRjTUcZiZ/izDMAuHMCATmpB6enM2G+8ukxXz8aE01vqETM7DdUQ+BQJBzkSHjR/ryP7bwhBfWNidbUqBSYRp83ZLKvWtzx+86G1stJ/TsW0bCs5CkrQHWao/yA905w0y2cJrT3OEsdymDG/+jJ3bIGY4PB7hmbZMFNoJVnZnY2FhrVp+tEdqZhqX0q4dnjouuoyGBUfzKfr5nP1e4zCOb6X95cCIOFWoL7/xtTmxFu+yK0M80sqt+TShPbhxZy1Gr2pHt9JPJ8GxbiTpeTSne3JOANef4tdpcnt+JyHJT0qtdMBEMw4d6eNKeWgyiBQsZyGvi+ZHtrOEImmx0zRdYHqtGMxszZoy1qs/WCO1Mw5L61cOTBeyySNnW5DahzORvljGU5nHTbKL/9aQRs+nNL+xnHtljl21x7pqG0M80srN+PWnMFk5ZdUpRdtLPwdWR6oMbUHtME+ydFFxcfgK/AeuJCbdO6OLMaHeWu7qZDg7YI0OWbbc8EFgWq0Yzq1q1ao6LCpIVCO1Mw1L6eVIYZxwIwHaG7c3JSg5wj3Bm8olV+18hXPidMUyhOxs5QTfqW8WOzCDOXdMQ+plGdtXPGSWdqMMmTlrVjuygX/7yhfhg2ceMeTSV8t2qc/i73SwvNZ0TM/dbzpGJCn4TuCWVyJOmahePJsc5MiNGjOD69etERkZy6NAh6tRJfc2nvb09EydO5OrVq0RGRnLq1CnatGljkCd37tzMnTuXGzduEBERgb+/P7Vr1zbI4+bmho+PD3fu3CE8PJxt27bh6emZar1///03r1+/pkOHDqY11sJYNZrZuHHjckxUkKxEaGcayfUzCAFsAnXx5BL3s9WUp4wgIeHFKtpTm3nvfWmV/teROhxjGjHE04QpTGcLRclHZTyy3JbMIM5d0xD6mUZ21a8dtXhABAE8fHtmC2LL+rmWLkD71X0YfGk8dko71jVdxB/vLebm5ktoNRYezdIPt+9aQhdeXx9b1s4adO/enTlz5jB79myaNGnC1atX2b59O4UKFTKaf8qUKQwdOpTx48dTp04dVq5cyYYNG6hRo4Yuz9KlS2nZsiXDhg2jfv36+Pv74+fnR9GiRXV5Nm7cSKlSpejZsyeNGzcmODgYPz8/nJ2dU9T52WefIZkhLHdWYLuvFwSCLEKpVJrlAls/By7+T04ozxmvWEfNVRKltW5ZVm9ecuHDcObRj/Gs41NW8oLXxKFmL5fpQr0ss0UgEGQtPWnEZiuPytgqeYq58uHyHgy79g1aTQIrK81hz7BNhF0OsbZpKahQoQILFiwAQKVSGewZ867h5eXFqlWrWLt2LTdv3mTs2LHExsYyYMAAo/l79+7NvHnz2Lt3L/fv32flypXs3buXsWPHAuDo6EiXLl2YNGkSx48fJygoiFmzZhEUFMTw4cMBKFu2LA0aNOCLL77gwoUL3L59m88//xwnJyd69OhhUF/16tUZO3Yso0aNsqwQZkI4MwKBmciJkcyM8Y/dFR40B1/1UJyw/Fu2llThGNNwREEzpqTYX2IbZ+lCXbNs7CYQCGyLIuSlKRX5i1PWNsWmcHbLTSvvLowI/A6liwO/1ZjPnmGbiHpgu9sCvHr1CoVCASQ+zBuE33+HUCgU1KpVi4MHD+rSJEni4MGD1K9vfNq0UqkkLi7OIC0uLo5GjRoBidPQ7O3tiY+PN8gTGxury+Pg4KD7nn698fHxNG7cWJfm5OTEb7/9xpdffsnTp09NaGnWYbUAAA4ODjx58gQHBwcSEhJQq9UoFArs7Ox0eTQaDRqNBqVSaTDPUq1Wk5CQgIODAzKZTJeuUqnQarU4Ojoa1JVaelxcHHK5PMVbeWPpSQfczs5OdzICaLVaVCqVriMlYck2OTg4EBISgiRJOaZNaaWbu03J+x6ATCYzqDejbXKIt6Oi5M4Vh0c4yt6UY4t9j//slsllODg6Zvg4Afg3ekLN/XH8JA3kC8VakKXdpuQap6dNuewcmajpxCcJjZhst5l1CUdQKBQ42hkepwOaAJYxlOrP47hSLLFdcju7bNH3csL5lJXXCICQkBDdTTkntCkrj1NS/0tqnzXblFRO0u/U2tRD1ogTstu8UMbjiKNVj5MkSbrzN63jkVq6OfqeS8l81PRqTNVB9Qj+9zYb31tG5LXEB047G7juxcsT61UolSn6nlqt1tmVE86nJPTz5MmTx6Bd8fHxKUagChQogL29PWFhYQbpYWFhlC9fHmP4+/vj5eWlG3Vp2bIlnTp10tUVHR3NqVOnmDBhAjdv3iQsLIyePXvSoEED7t5NfMl669YtgoODmTZtGmPHjuX169d4eXnh4eFBkSJFdHX9+OOPnD59ml27sk8wI6s5Mz/++CMajYaffvqJo0ePsmrVKvr160ezZs10ebZv38727dv57LPPqFq1qi599erVHDlyhMmTJ+Pu/mZncm9vbwICAliwYAFOTk669EmTJvHs2TOWLVtmYMPo0aPJnz8/M2bM0KXFxsYyZswYKleuzLhx43TpISEhTJo0iSZNmjBo0CBdekBAAN7e3rRv357OnTvr0rOiTTKZLMe1KSuPU1LfA8ifP79BvRlt05Fpf3H/QQTfeU+z+b7n5laIMKBE8RJMWbYsU8dp+uwZ/DpvKR2meVKuc0MetJCl2SZHR0cKFy6s0+FtbRrR7BPG326BRglnhstQBHrCqiOptul+pXgGhCUw/r92lWzSJFv0vZx0PkHWXCNmzJiR49qU1cepR48eVm9TUjnFixcHSLVNg5zeJ6JvfpY1WpZmm7LqOBUpUoSffvopS46TfpvqdWnM86rxRJdQ8+LYU9Y1WUS/Vp/QbswUix6njLZpWmjiepnun32Wok0KhYJ8+fIB5Kjz6fTp07q/g4KCDOqdOXMms2bNwlS+/vprlixZwsWLF5EkiaCgINauXWswLW3YsGEsX76cu3fvotFouHTpEps3b6ZmzZpAosPYu3dvli9fzuPHj9FoNBw8eJC9e/fqHMV27drRvHlzg5Ga7IDM2dk5y+ZmODs7Ex4eDiRGVKhevTqnTp1CpVLlmDdfSVjyLZGdnR1169bl2LFjBrZk5zallW6Jt+MNGzbU9b0lS5Ygk8l0c08z06bP4z6kBAX4ynG9VdqUoZGZkeehaG1kTy7gsLpJho9TQkICjRo14vz589RVl2KtajQ9lD9zWhWYapt8fHwMNE61TQlaBqqbMYmurLA7yEL7PWhk2re2qb19HaY5fU7dcf2QPb2IfEX9bNH3csL5lJXXCP2+lzSqmt3blJXHyc7OjoYNG3L8+HHi4uKs2qZFixYxYsQIfH19GTFihNE2VYwvwna+ppbDd8TKVFY/TjKZjBYtWnDq1Cld/7No39Nq8WhZhkYTWlGkXnECVp3l4pLjPA+KsNm+Fz/oOACK3xql6HsrVqwgOjqaESNG5IjzKQkHBwdevHgBQJkyZYiJidF9ZmxkRqFQEBERQd++ffHz89Ol+/r64urqSq9evUgNBwcH8ufPT2hoKNOnT+ejjz6iXj3DNaPOzs64uLjw5MkT1qxZQ+7cuenevbtBHhcXF5RKJRERERw6dIgLFy4wbtw45s6dy6hRo9Bq3wSNsLe3JyEhgePHj9O2bdtUbbMmVhuZSUhIoG/fvhw/fhy1OjHcnlqt1v2tT2qLxJLPDUwi+bzCtNK1Wm2G0hMSEgxuoknoHhSTYYk2OTo6MnDgQE6fPp1j2vS2dHO2yd7ePkXfkyTJaDnpbVNdyrCLC9mi7yWtLZG0hm1O73FydHRk0KBBnDlzhsOqa8xhO7+ohvI+/+O59nWqGhjTWL9NBcnDEoZQjiL0YCFnEu6QPDBcam3ar7nMongNNUMiuCSTdGVmh76X3c+nrLxG6Pe95J9l1zallW7uNjk6Our6H1i3TUlRkpJ+G2tTX5qyldM8j3+ZapuSY8k26eun/7k5j1Ou4q6Ual2eUq3KUfL9ckhaiXM/H2FLt9+If2G46aRN9j2tZGCbft/Lnz8/0dGJ4aFzwvmUhL7z9erVKwNnxhhqtZqLFy/SokULnTOT5Cj7+Pik+d34+HhCQ0Oxt7enc+fObN2aMgx2TEwMMTEx5M2bl9atWzNp0qQUeV6+TDynPD09qV27NtOnTwdgwYIFrF692iDv2bNnmTBhArt3707TNmtiNWdGIMgpyJFRh9JMZbO1TbEKy9hHPTxZzjB6swiJjA/2FiUff/MVATykBf/jFRnbZVuFht2lXOly7R6Xqtq9/QuCHE+HDh0M3noKshdOKOlOA3rw09szZ2Oc3XJT8v1ylGpVnpKtypHb3ZXHJ+7xwP82ZxceJvTsQ6QE620UKrAMixcvxtfXl4sXL3Lu3DnGjBmDs7Mza9euBWDFihWEhIQwZUriNMK6devi7u7OlStXcHd35/vvv0culxtMeWzdujUymYzAwEA8PT2ZOXMmgYGBujIBunbtSkREBA8fPqRKlSrMmzePnTt34u/vD8DTp0+NLvp/+PAhDx48sKQkJiGcGYHARCrgjhw5N3hsbVOshher8GcS42jPAjL2AFmcAvzNeI5wna9YlylnCGBn6bzMOn2fqVXKZOr7gpxFx44dhTOTjelAbR7zjAvcs7YpZkWZ24HizT11zkvBKkV4evExD/wD+WfEnzw6fg9NbM7aHFKQki1btlCwYEEmTZpE4cKFuXLlCl26dNEFBfDw8DCY6uXo6MgPP/xA6dKliY6OZt++fQwdOpSoqChdHhcXF6ZNm0axYsV4/vw527ZtY9q0aQajSEWKFGHOnDm4ubnx5MkT1q9fz5w5c7Ku4RbCas6MVqslICDA4GAJ0ofQzjTMrV99PDlHENpMPoRnN4zpF00cQ/iFPXzLHi5xnUfpKqs0bvzNV+zmEt+xwSS7DhfLQ8GYR1SNjCXApJIshzh3TUPoZxrZSb9+NOMPjlnbDAMyo59TwVx4NC5Nscal8GhWhqL1SvDibgT3/W9zbOo/BB+6S9zztKcl5QS0Wi2xsRkbcc/p+Pj4pDqtLPnalGPHjlG3bt00y9u6davRaWf6LF++nOXLl2fIzly5cmUovzWwmjOjUqnw9va2VvXZGqGdaZhbv7p4cu4d2F8midT0u8YjlrOfhQzkI2a91bkrR1H+5is2c4pp/GWyXfH2cvaVL06He1E268yIc9c0hH6mkV30K4MbdSjDYDL20GVp0qNf/gpuFG9WBo8miQ5MvrIFCb/2hMfH73PplxNs77mGV4+j0iwjJ6JSqVKEIhYIzIXVNs1MWrykHxFCkD6EdqZhbv3q48kZ7pilrOxAWvp544cLTgzj/TTLqIwHO/iatRwxiyOThF+lUnS4b7sPCuLcNQ2hn2lkF/360JR/uMQzoq1tigHG9JMr7Kjcuzad1vfns5BpDL7wFZU+qcXL4Ofs99rKwvzf81v1eewdtZmAtefeSUcGErXLmzevQUQygcBcCGcmGyK0Mw1z6leA3JTGjXMEvT1zDiEt/eLRMI7f+Y6ueJDf6PdrUJJtjOcX9vMjO8xqm39ZD0q+jKcsRd6e2QqIczf9dOjQIcXfQj/TyA762SGnN41Zy1Frm5ICff2cCuai8fdtGP3gB5r88AGRN56yrcdqfsr7HRtbL+folH+4t+8W8VHGo229a9jb2+Pq6mptMwQ5FNu9ogkE2YC6eHKLUF5mMPpWTuYEgWzlNIsYzDB83rxdlaA3TZhN78Rwzuw3e92vHRQc9MhDhwe1WYjthpEUvB39BfxiMb/tsXjxYpT/7fK+d+9eOnbsyM6dOxOPU/n/HNFAP+j13xz+Td3SVW5n6hKHmiPcsJDlpqF21tJ8fgeqDKrLo2P32D1kA0F7b+lC3gsEgqxHODMCgQnUe8fWy6SXqfzFLwzjHLNYwl4co6DaZhlN6cZAlnGY6xare2fpvIwUzoxAYFGUSiUjR47Ex8cHPz8/Q2czMBXHU8/JUalU7Nmzhzt33kzRdULJD3RnJn9nOqqhpchbpgBNvv+A+91fkWtbHtY1XkTYlRBrmyUQCLDiNLOEhASOHj1qdEMiQdoI7UzDnPolrpfJZs5MVDCEnE/83WsrjDj35u1pOkiPfi+JpQ+L6ctiWlON9t/YoXwtowXTLOrIAOwr6UJlPChOAYvWkxnEuZs+Fi9ejLu7e+I/vbayU/0+9Noq9DMRq+i3qdubUZlAP52j4+XlRXBwMF5eXrqsXnxEKC/4i9NZZ99bKFi5CB3X9WPYtQnI7OWE/3CLnX3WCUcmgyQkJOg2zBQIzI3VRmbUajWrVq2yVvXZGqGdaZhLP3vsqEkpxvG7GazKQvSne4w4B+513vqVxYsXA4kPIB9++CHh4eGJuzeX7wAVOsKtnYkPKcmml5wE2m3qxvqpPrwqDOGjUu7kbQ4UuZRUaPgUt4pHIPopG6o9pXvcJxy4d44XdyN5cTeCl4+irD4VRJy76UOpVBIS8t/DomsJ/CLKgmuU0M9EbFk/D/Izhg/pwjyrj8o4uDhS4eMaVO1fl6INSnB11RlWVJxN1IPnVrUrO6NWq4mMjLS2GYIcitWcGYVCweDBg1m3bl3iQ5Eg3SgUCvr16ye0yyTm0q8qHsSh5g4pd8vNCeg7MPrs3buXfv36oVAoUOu9aQUM/3YtofvzVVHL2FiwShHqfdGcir1q8uL5Y4JDyiMB93iKZwF3KtWrRV7PAriWzIc2QSLqXiTP/3NuXtyN5PndCF49fMGrkChiI2Ms7uyIc9c0hH6mYcv6TaUH2zjLRe5bpf5chfPg2b4yZTtWofSHFQi/Gsq1tef5u8dqYiNeA7atn62jUCgoUKAAz549s7YpghyI1ZwZOzs7mjVrxoYNG8RFIYMI7UzDXPrVo2yOXi+jVCp1f+s7NLbS/wpWLkK/o15c33iR9e8t4Wn97YmjTCHnue07itPM5Dv+Rywq5PZyXErkI69nQfKWKUA+zwIUb+5J9SH1yeORF6cCuUhQaYgOfUl0yMv/fkcl/h0SxauQl7wOfcmrkCjinmV+gztb0S67kl79kk9Tw7VE4rTKdC5Cz6nYav9rTHnepwoNmZTldTvmc+Yj356U71KVkNPB3N4RwKEJO3kWGJ4ir63qlx2ws7Mjd+7cwpkRWAQRAEAgyCTZcr1MDiG3uys99ozgzIJDnJj5X1S0+m8+f0gkYURRlzIc5SZajZYXQZG8CDI+zcHOwZ7cRV3I7e763+/EvwtUdKPk++US/y/qgmM+ZzTxmjeOTuhLXj168d9P1Ju/Q16iVYt1HdbCYJqaPsmnRWYw0pbA/MiRMZNPWIAfYVhmGmpquDcoSedNA3h64RFLik0lJkys6RAIsiPCmREIMkldPFnDYWub8c6hzONAz93DuffPzTeOjBFOEEgjynOUm28tMyFeQ9T9Z0TdT/utob2T4o3T4+5CnmKu5HZ3pWi9EpTvmpc8Hq7kKeaKTC7j5cMXPL34mKcXH/Pk3EMen7wPsdqMNldgKskdlXRE2krxd5IDVGuIGOUxIzt37mQA7+GMEl/8s7Tu+uNa0PR/H3Hku92cW3QkS+sWCATmxWrOjEajYfv27Wg0GmuZkG0R2pmGOfQrSj6Kktdq87utiTX7n1xhR9ctg3n5KIq9o/9KM+9JAulOA7PWr4lVpznCAyCTy3B2y0OBCoUoXMuDwrWKUbl3LfKXL0TE9aecun8NZT4H4kLFZnoZxex9T98hSW3tl/66sFpDDL9fvgN2koxmt+9Sucb3rCrrSOyW7uaxzQLY2r3jqN8BzjCTz/gNNVkzkumYz5n2q3tTqFpRNrRcRujZ4HR/19b0y05oNBqioqKsbYYgh2J1Z0aQcYR2pmEO/epRhms84jXxZrLKSkQFG/5Ox7Qba/a/tit64ZjPmfUtliAlpD3KcYJAZtEbJfaoyLqHD0kr8frJS14/eUnw4TfTEJ0K5sKjSWmq9q/LwItfsWvwBoL22ObGgLaK1a99eudFUfLxZaArnahLPM2IfAQ9HsUyiII8IMJ6NqaB1fVLxgQ6c4H77OdqltSnP61sVe0FxL/I2GbHtqafTRKl5xzqrVfTbOrGixcvrGaWIGdjtX1mlEol48aNM1hkLEgfQjvTMId+9fDkDHfentHW2dQNfOu+eUhzLWEQhcwY1up/zf7XluLNyrC5vS/q16q35r/LU14SS01KWd64dBAb8ZoHewIpfSI/RybuotOG/rRZ3A07pZ21Tcs22Mq1ryLu7OVb8uLMQJZSkwl80LU8x9zz8C+TaU01q9qXGraiH0AF3OlHUyazMUvqqz2mKZ/4j+Ks92G2dluVYUcGbEs/m0V/XyHXEolBWVxLoFQqcXNzQyaTWdc+QY7Eas6MXC6natWqyOVWMyHbIrQzDXPoVw/PHB3JLC3SrV9UsO4tnUqlQqV6uwOSGjWGN6L26Cb82dYnQ4t0TxJIY8pnul5zk6TdrY2XWVVzPu4NStJ1y2Dh0KQTW7j2NaIcfkxgFYcZwQpOcwcJCY1cxuRGxfiGdaxkJIsZTBFcrWanMWxBvyRm8gmrOGTx0Pb2Tgo6rOlDo+9as6nNLyatj7El/bIbcrkcJycna5shyKGIM1IgyCAO2FOdkjkzkpkZHRD9N3ReXl4p9qtJL57tKtPKuzN/dfrVaLjUtEgKAmCLRN1/xsbWy3EulJsufw5ErhAOja3Tntps4HN+4E9+YpfRPH9zlib8gBJ7TjGTr+iAI4osttS2aUtNKuPBfFIJxmAmXEvlp//xsbiWys/q2gsSg3AIBIIch3BmBIIMUoNSPCOah+TA3YzN5ICYiyJ1itNpQ392DVzP4xP3Mvz9kwTSgLLY2eilLv5lHJs+/IXcxfLSeeMA5Pa2aacABtOCpQxhBL6s53iaeR/zjJGs4GO8+YDqHGEa71Epiyy1bRywZzq9mMEWXpHxqV7ppfQHFRh0bhwPjwSxodUyXj99ZbG6BAKBdbHanVOtVrN69Wqx8VQmENqZhqn61aMMZ3PiqEw6yar+51q6AD12DefIpN3c2nolU2XcJAQVGqqT9jqgrMKYdvFRcWz64BdcS+Wn0/r+wqFJA2td+ybSmYl0pjve7CP9ffEcQbRlNsvZx2pGsYyhFCC3BS1NG1u4d3xKG17wmg2csEwFMhmNvm1Nl78GsX/sVv794m+0GvOERLcF/bIrarWayMgc+AJQYBNY7a6ZkJDAkSNHSEgQG8tlFKGdaZiqXy1Kc4GMjxLkFLKi/zkVyEXPPSO4tu4c5xcfzXQ5EhKnuG0z62ZS0y7ueQwb2ywnX7lCdFjbF5mdcGh0RAVDyHmICrZY35MjYxjv04V6VMGD3DhQk5KMpDV/8gU9aUR7fuQ8QRkuW4vEKg7RmMk4ouAkM+hNE7Pan16sfe8oQl6+pD3fsgEJyezlyxV2dFzblxrDGvJH08VcX3/BrOVbW7/sTEJCAtHR0UiS+Y+7QGC1O6aDgwMzZszAwcHBWiZkW4R2pmGqfjUoyaV3cH+ZJCzd/xS5lPTYNZywS4858PVOk8uzpXUzaWkX9yyGja2XU7ByETqs6YNMLqL+AAYR9xwcHKg09Qby3tvMWkUn6vIVHRhJa3bwDfdZyp98yXtU4hi3+IhZ3OGJSXU8IYoh/IIXq5hAJ7bzNWUpbKYWpA9r3zum05M9XLLIyHbiZrojyFeuIL83XEjYlRCz12Ft/bIzDg4OuLu7i2hmAotgtX1mZDKZ6NiZRGhnGqbol49clMaNK6R/o7WchiX7n1xhR9e/BqF6FY/fgD/ADG/xThLIeDogQ2aRt8EZ4W3axUa+ZmPr5fQ+OIYOa/uya+B6s02RyQnIZDJiFAWRXGPMWu5YPmIuO1jFISDxPH9BjEX6y14uc4ybTKQz/vzAEv7hZ/ZkyV5I1rp3yJDxI32oTWnaMcfs5ecq4kLP3cOJDn3Jhvd/TVfo9swg7r2ZRyaToVCIQBgCyyDmMggEGaAGJQniKVGY92FKAMhktF/VG6eCudna9TcSVOaZyhHAQ+yQU5liZinP0sSER7Oh5VIKVHCj27ah2DuJBwBL0pzKFCUfG/QW9T/ntUUd39fEM5k/6cRcPqImh5lCI8pZrD5rIkfGTwygBZXpyFyeYt5d4POXL0T/E2N5eukxWzpbzpERCAS2i3BmBIIMUJNSXHyHp5hZklYLOlO0XnE2t/NFFR1vtnIT0HKKOzYz1Sw9xIRHs77lUpS5lPTa+ykOro7WNinHMpaPWIE/cWT9ou7LPOADZrKaw2zgc+bRj9zknGNth5wlDKE+ZenEXEJ4btby3RuUpN/xsVz74zy7h2wUo5i2ht56N4A8efKI4AkCi2A1Z0alUuHt7W3aPhbvKEI70zBFv5qUeqfXy4Bl+l/DCa2o9EktNn3oQ0x4+jfFTC+2snlmRrRTvYpn00c+xEa+pv+JzylUrWgWWGjbqFQqnoY9RdKaZ9SkBiWpQxl++296mTVIQIsP/9KMKZTGjWNMoxVVLVJXVt477LHDh+FUpTidmccTM4/IlO1YhV77P+XoD/9wdPIes5adGuLem0H01rupVCpGjhxp9XD/gpyJ1ZwZrVZLQEAAWq14k5JRhHamYYp+tYQzY/b+V31IAxpOeJ9NH/5C1P1nZikzOSe4ZRMjMxnVLiFew98fr+bGpkv0P/k5dce+B+/wfH2tVktcbJzZyvPiI9ZyhBe8NluZmeUhkXyMN/PYiS8jmMrHZt8fKavuHUrs+ZWRlKEwXZhPOC/NVrZMLqPZ/9rScV0/dg1Yz8Xlae/5Y07EvTfzCO0ElsRqzoyjoyNLly7F0THnDKlnFUI708isfm64UJS8XH2HF/+Deftf2Q5VaP1zV7Z0/pXwq6FmsM44l3lALhwoh3VHNzKjnZSg5fj/9rKpzS/U/eI9ev0zkryeBS1ope3i6OhI8eLFzRLprQxufERNlrPfDJaZjz84Rhtm0IpqbOZLs+5LkxX3DgfsWc0oipKPrsznGeYbaXUqmIue/4ykQvfq/N5wIYHbrpqt7PQg7r2ZR2gnsCRWXTPj5ORkzeqzNUI708iMfjUoSSChRGO+9RzZFXP0v0LVitLxj374DfiDh0czvn9HRlCTwFnu0tgGFllnVrvHJ+/zW415PL8TztArX/PezHYocinNbJ3tI5eb57Y1hg/5mzNmX8dhDoII4yNm8Yxo/JlMTUqarWxL3juU2LOaMeQlF93xNmuglGKNSjH44nhiI16zpv5PRN54arayM4K492YeoZ3AUogAAAJBOklcL/PA2mbkCJwK5uLjHcM49aM/gX9nzdvVkza030xmUb2KZ9+YLaxt/DPFm5ZhxK1vqdy7trXNyna44UJPGrGYfyxe1+LFi1m8eHHiP722wohzib/fwmviGYYPvvizja/pY6WNNtOL8r8Rmbw405OFvCLWbGXX/fw9eu3/lFNz/NnRZ62IWCYQCAyw2j4zAkF2oxalOMA1a5uR7ZHby+m6eRCPT93n5Kx/s6zek9xmAO9lWX2WJOxyCH80X0LFnjV5f34nao1uwr9eW3l66bG1TcsWjKA1h7lOIJab2piEUqk3euZaAtzrZOj7y9jHFR6wgpHUpjTfsTFL9qTJCArs+I1PyU9uerCQaMyzrkmZx4F2v35C0QYl2fD+MkLPvNtTfAUCgXGsGs1s0qRJIipIJhDamUZm9ashFv8Dpve/1j93ReniyO4hG81sWdqcJ4gC5KEk1ltvYu5z9+afl1hRcQ7BB+/Q7/hYPlj2MQ55c+5UDpVKxeOQEJOimeXGkcG0YFEWjMqkQD9UbQZGaY5xi1ZMpzol2cHXFCVfpqq3xL1DpoFf+RQ3XOlhxhGZQlWLMvDsOJR5HFhde4FNODLi3pt5hHYCS2LVaGbPnj0TkS0ygdDONDKjX1HyUYDcXOORBS3LHpjS/6oOqEfFHjXZ2uVXNLFZu99AHGoucI/GVMjSevWxxLmrjlFx9Ic9/FptLq4l8zHi5rdU6VfXbOXbElqtloQE00YlBtGcGzzmDHfMZFUG0AtVm4LyHRJ/INHBSebkhPCcjvzITULwZ3KmQo2bu//ZY0eDFXKKkpeP8TabI1OlX136nRjL9fUX2Nx+BbGR1o82B+LeawpCu5SMGDGC69evExkZyaFDh6hTJ/VRW3t7eyZOnMjVq1eJjIzk1KlTtGnTxiBP7ty5mTt3Ljdu3CAiIgJ/f39q1zachuzm5oaPjw937twhPDycbdu24enpqfs8X758zJ8/n4sXLxIREcHNmzeZN28eLi4u5m28mbFqNLNly5aJyBaZQGhnGpnRryYlucFjYhFvlTLb/9xquPPB0u5s772Wlw9fWMa4t3DCyutmLHnuvgiKZHP7Fewb/RfNZ7en5z8jyV3Utm9AGcXR0ZESxUtkOpqZEns+pU2WrJV5K8kdm0C/xJ/k6Dk28Wj4gjXMYRsb+JyfGcT3dMWLjxjIe3ShHi2pQg1KYo9diqLM2f9kCbCCETg/g4/5iZdmcGSc3XLTaX1/Wv3UmW0fr+b4//aabU8hcyDuvZlHaGdI9+7dmTNnDrNnz6ZJkyZcvXqV7du3U6hQIaP5p0yZwtChQxk/fjx16tRh5cqVbNiwgRo1aujyLF26lJYtWzJs2DDq16+Pv78/fn5+FC36Jornxo0bKVWqFD179qRx48YEBwfj5+eHs7MzAEWLFqVo0aJ899131KtXj5EjR9KmTRuWLVtmWUFMRAQAEAjSQS1Kc1ks/s80Dnmd6LZ1CCdn/csD/0Cr2WErm2dakltbr7Cy8hxeh75k6NVvKN+1mrVNshk+pgEveM0+rljblLTZ1O2Nk+NaIvFHj985QmfmEs5LXHGmKsX5iJoMpxX/oyeb+ZI7/MwGxjKKNjSiHHkw3/RDe+yov1JOSQpy9Aut6VHLZDKqD23AiJvfAvBr1bnc23fLDJYKBLaJl5cXq1atYu3atdy8eZOxY8cSGxvLgAEDjObv3bs38+bNY+/evdy/f5+VK1eyd+9exo4dCyQ6i126dGHSpEkcP36coKAgZs2aRVBQEMOHDwegbNmyNGjQgC+++IILFy5w+/ZtPv/8c5ycnOjRowcA169fp2/fvuzZs4d79+5x+PBhpk2bRrt27bCzS/mCxFawWgCAJO/c0dGRhIQE1Go1CoXCQCyNRoNGo0GpVBqE41Sr1SQkJODg4IBMbwM5lUqFVqtN4fmnlh4XF4dcLjdcoJlKuiRJxMfHY2dnh0Kh0KVrtVpUKhX29vbY27+R05JtSu3v7NymtNLN3abkfQ9AJpMZ1Ju8TbVVZdgrv4ydZGeTbcrK45SUJ91tio+n07p+RF57ysWFx3F0dLRIm9RyGRKJm+rJ7Ywfp/Px9/CQ8lPaoQihshdvbaul+57FjpMa9gzdRLlu1Wi38hPKd6rG4a/9UEerskXfSyK1vieTyXHQ+yy57fpl6dIlGK36kBV2B5A0ktnbpIpOnIIqs7MjwbMt9goF9nf3oNFodHZk5hoh/TcKldTepPSbyqfcZDdg5DhJUFFyp3FCORonlOdT2lCM/DxUPcN+sZavtR25wF1u2Yfy2O4FkkxK93Gyx44l6kHkDocWePNjLm+Trnv5yhei5aJOuJbMzz+D/+T+3kQnxsHBwaaue/prPRzT6HtppdvatTwr709JdSgUCuLi4nJEm5LQz5MnTx6DdsXHx6dYJ6RQKKhVqxbz5883qPPgwYPUr18fYyiVSuLiDANrxMXF0ahRIwCdTfHxhltHxMbG6vI4ODjovpe8rY0bN2bNmjVG63ZxceHly5e65yVbxGrOzJw5c8idOzfe3t4cPXqUVatW0a9fP5o1a6bLs337drZv385nn31G1apVdemrV6/myJEjTJ48GXd3d126t7c3AQEBLFiwwCCe+aRJk3j27FmKYbLRo0eTP39+ZsyYoUuLjY1lzJgxVK5cmXHjxunSQ0JCmDRpEk2aNGHQoEG69ICAALy9vWnfvj2dO3fWpVu6TXK5HEdHR7y9vXNMm7LyOOXNm1fX9wDy589vUK9Bm6pUodHnEvIvK3PrsMpm25RVx2n69Om6z9PTpj9CtlGkmgfVj3rQdmkji7VpS4ESPFBDieIlKNmkSaptuhzwgEW9pxD+noNVjpN+37P0+fTA7xaV9hcm/wd5qNWtAUWOOPFVj7E23/fs7OyIi4sz2ve0QHEPD6boHavkx8nd3R1JSnxAT2pTwRsSpZdLVPyqNUw7ZIE2PUts06MmHDnix9QZM3B376jLX7ly5UxdIxTFE0dlpixblqnj1N/bm86dO/Nxq064PCxAkQgnmkTXouXtilTWFkeyl/PKA156wOnwa+y8doAWvdrhWa5sYiEyWLHnD/adOMAP302m/a4i5AmFoAVFedEzcS1LZq57WrnE82rxPKsWz6mfD3Lt6+N8M+pz6Pz2Nlnr/hQTE6M7f421KQlbO59s5f6UN29eevXqxcqVK3NMmwBOnz6t+zsoyHDPtJkzZzJr1iyDtAIFCmBvb09YWJhBelhYGOXLG5854O/vj5eXl27UpWXLlnTq1EnnOEVHR3Pq1CkmTJjAzZs3CQsLo2fPnjRo0IC7d+8CcOvWLYKDg5k2bRpjx47l9evXeHl54eHhQZEiRYzWW6BAASZOnMiqVauMfm4ryJydnbNsQqqzszPh4eFAokBarZa4uLgc9fYhiax4Ox4bG5uj2pTVb4mS+t6SJUuQyWS64drkbSouK8Cx+KlUdPiKaE2szbYpiaw4TsntTs32Eq3K0X5DH9Y3W0LUrUiLtkk95CRSkdrInlxAvqJ+qm36QduNvHa5majYaJBujb6XZeeTTEatzxrTeMoHnJ53gJOz/FHYGb7LsqW+9/PPPwPw+eefp2iTNOIsAA6r3+y7ktz2RYsWAYkLbJPSf1WN4KYshLn2O23ufEpzZCZZe1u3bs3u3btZvHgxCoUCtVrNuHHjaNOmDXZ2duzdu5eEsu0AkAX6oSr1AXI7O5T3EtNlFTqScGM7CRoNigqdqXDjKNUf3MOz3KeUepVAmYd3KEZ+5CSOdNohxwUnnvCCV7I4NCTQU7mIaYtnM2LECHx8fIwep9TapHBUUHNoI+p+1Zy457H8O2YrD08F2Uzfe9txyps3r8Gb7ex+Lc/K+5OjoyOvX7/OUW2CxBGPFy9eAFCmTBliYt5MuzQ2MlOkSBHu3r1Ly5YtOXPmjC59xowZNG3alBYtWpCcggULsmTJEtq1a4ckSQQFBXHw4EEGDBhAwYKJETpLly7N8uXLadasGRqNhkuXLnHnzh1q1qypCy5Qs2ZNli9fTvXq1dFoNBw8eBCtVotMJqNr164GdebJk4edO3fy/PlzevTooRtltkWsNjKjUql0Q1dJ0S3UajVqdcoIR6mF8ks+nJZE8qG4tNKTHKr0pickJBgdaks6EZNjiTbJ5XKKFClCfHx8jmnT29LN2SatVkv+/PkN+p4kSUbLUalUVKQoN3hMVHy0zbYpK4+TXC4nf/78PHnyJEVkGn3bXUrko+2aXuwbvYWnl43vf2LWNv23UFjSSroyjbXpBIFMTehBXEJKja3R97LqfDo5z587/1yn4x/9KP1RRXb2+4MXdyNMblNW9z07O3s0anWKz/RtTxqVSUovEpeH5lTiK9YQnxBvU21KK12r1cLzB28+L98B6o9BG5j4mSRJaLVa4uPj8fPTCx4QoBcJLdAPLRAHyK9vo8izUzx58gS0WtSBfgQAAQDVvkzMv+l/b6KqBfpB+Q7kTVDgefcyJRvM5GARBc+3RRponJ425S9fiBpdGlN3bDNin8Vw6Ds/bv55SbfA39b7HiT2P2dnZ4PzNy3bs0ObUks3d5uS7hsvX74EckabktB3vl69emXgzBgjMjISjUaDm5ubQbqbmxtPnz41+p2IiAg++eQTHBwcyJ8/P6GhoUyfPp179+7p8ty7d4+PPvoIZ2dnXFxcePLkCWvWrOH+/fu6PJcuXaJRo0a4uLigVCqJiIjg0KFDXLhwwaC+3Llzs23bNqKjo/nkk09s2pEBKwYAUCqVzJgxw+gbXkHaCO1MI6P61aAkV8Tifx3p0c/OwZ6ufw3ixqaLXFt3LgutezunuI0nhSlE1kf6sva5G341lDX1fiLk5AMGX/iK6oONz8+2VZRKJcXc3TMczWwY77OLCzwhykKWWRD9YACBfvj90BYC/fDy8mLkyJF4eXmlu6g0+1+yenSR1QL9eHH3b84TxNbq5XjuVipddckVdpRsVZ7WC7sy8vZ3DL40nhLNPdk3egu/1ZjPjY0XbSpSWXqw9vmbnRHavUGtVnPx4kWDERiZTEaLFi0MRmqMER8fT2hoKPb29nTu3Jldu3alyBMTE8OTJ0/ImzcvrVu3NnzR8R8vX74kIiICT09PateubVBOnjx52LFjByqVih49eqTqSNoSVhuZEQiyCzUoyT9csrYZ2Qa5vZwufw5EE6/B/8tt1jYnBS+J5RqPaEg5dnLe2uZkOQnxGvzHbePu7ut0+L0v7o1KsW/MFrRq213caQq5caQvTemO99szC0zCMZ8zZdpWpFynqpT+qCKqV/Hc2XmNf7/YxoMDt7N8bymBwFZZvHgxvr6+XLx4kXPnzjFmzBicnZ1Zu3YtACtWrCAkJIQpU6YAULduXdzd3bly5Qru7u58//33yOVyfvrpJ12ZrVu3RiaTERgYiKenJzNnziQwMFBXJkDXrl2JiIjg4cOHVKlShXnz5rFz5078/f2BN46Ms7MzQ4cOxcXFRbfHTHh4uM3uEyScGYHgLdSgJHPYbm0zsgcyGe1+/QSXEvlY32IJCSrbfEBOCtH8LjozSdz/N5DVdb3pvm0Ivf8dxdbuq4iNsI3NCdMiv/1rHr58iASG06GSNplMtiFlb5pwixAucA+B+VHl19Lg6/fxbFeJYk1KE3Y5hDs7r3Fqjj9PLxmfXioQvOts2bKFggULMmnSJAoXLsyVK1fo0qWLLiiAh4eHgePg6OjIDz/8QOnSpYmOjmbfvn0MHTqUqKg3o80uLi5MmzaNYsWK8fz5c7Zt28a0adMMpogVKVKEOXPm4ObmxpMnT1i/fj1z5szRfV6zZk1dRLWAgAADmytVqkRwcLBF9DAVqzozsbHm2S34XURoZxrp1a8Y+XHFies8tLBF2YvU9Gu9sAvujUqxruki4qOMz2W2BU4SyHg6vj2jBbClczc6JIo/3ltCu98+YdDZcfzVaSXhV0OtbVaaDMu9i6+2fkUcGG4ymWwvFgAZMobzvngZoYep/c8xl5rSvWoR3jyeMY+nElIwjmL2pbi+4QI7+q4jOiQbTuXLALZ0/mY3hHaG+Pj44OPjY/Sztm3bGvx/7Ngx6tatm2Z5W7duZevWrWnmWb58OcuXL0/186NHj5IrV640y7BFrObMxMXFMWbMGGtVn60R2plGRvSrSSluEEI8tr34LStJTb9G37WmQvfqrGuyiJiwaCPftB1OEkglipGXXLwg60YjbPHc1cSp2dFnLY2+a02/Y2Px6/8Ht3cEvP2LViCj+rWhGk4o2fEOj8DpkxH95PZyijcvS5kPK5DHIy/ObrnJVf4UBYupeXrpfXilpVygG/KHGmaP+c3CltsGtnj+ZheEdgJLYjVnRi6XU7VqVa5fv26zc/BsFblcTuXKlYV2mSQj+onF/ykxpl/VAfVo8PX7rGu6iKgHz61s4duJJJo7PKEhZfmHy1lWry2fuydn/UvEtSd0WNuXU3P8OTn7X2ublIKM6jeC1vzKQTTY5nTHrOZt+snkMkq1qUCVfnUo274yqtcq7vpd58n5h8SEvyYm/BDje3/OjwMWWMF662PL56+tI7QTWBKrRjMbN26ciGyRCYR2ppER/WpQksvCmTEguX6l2lTgg6Xd2dr1NyKuPbGydennBIE0wvgGZZbC1s/d29sDWNd0ETVHNKLrlsE45nO2tkkGZES/PCFQH09+50gWWJY9SE0/15L5aPa/toy6P5l2v/bi1cMXbGzzC8uKT2PvqM2cWXCIgN/PErTnBrv/TBkZ6V3B1s9fW0ZoJ7AkVnNmBILsQA1Kckk4M6niVsOdLpsHsmf4JoIP3bG2ORkiKQiAwJDwq6GsqrMAmQyGXPmaEs09rW1S+ogKTvwhca+KMv9KbOUMz7DtKY/WQiaXUbZDFT72G87wW99RsEoR/hm5mWUl/sfh73bx5LzxdYLGwrwKBAKBNRHRzASCVBCL/9PGuUgePt45jJOz/uXGxovWNifDnCCQZQwlNw5EY/tx9I2xePFigMS9RlKJ5pUZ4p7FsLXbKmqOaMTHfsM59/MRjk39B63GhqeH6LV7stdErjAXH2xvqpy10ThpqT+hJVWG1EMmg0u+J/ln+CaiQ19a2zSBQCDIFFZzZiRJIiQkxGAXYUH6ENqZRnr1q0FJborF/ymQJInHT0PouLEfD/xvc3ruAWublCme8IJgIqlPWQ5wLUvqNPe5azBlw0g0L1O55HuSh0eD6LyhPyVblWNHn3VE3Ys0ez3pJb369acZ5wniBiI0cBJu1d1p/H0bgrq9pOi/Jdj/2Rbu7r6BlGDDDqqNIe69mUdoJ7AkVptmFh8fz6RJk7LFzqK2htDONNKrn1gvY5z4+HjOFL+JRq3hn5F/WtsckziZxetmsuO5G3njKWsaLCTk1AMGX/yKKn3rWM2W9OgnQ8ZgWuCLfxZaZrsUa1SKj3cOo9+JsUSHvmR5+ZlsauvDnZ3XhCOTQbLj+WsrCO0ElsRqzoydnR3vvfcednZ21jIh2yK0M4306iecGeM0/r4Nnu9XZEeP3212U8z0coJAGlMhy+rLruduQrwG/y+3saP3Wt737kyHtX1R5nHIcjvSo18jyuGEkv1czULLbI9SbSrQ5+AYeuwZQdjlEH4pPYODX+2gRvEq2a7/2QrZ9fy1BYR2AktiNWdGoVAwaNAgFAqFtUzItgjtTCO9+tWklHBmklG+SzUafPM+FU4XRv0i+79hO0kgtSiFE1kTYSe7n7tBe27wW/V5OBfKzZBLX+PeoGSW1p8e/XrSiL85+26GY5bJKN+1GgPPjqPjur4E7b3J8hL/48ik3cSER2f7/mdthH6ZR2gnsCQimplAYIRi5CcvzlznkbVNsRncqrvTfk0f9g79E4fnOePtWjARhBFFHUpb2xTT0YvmRa+tMOKcLihAhw4dzFbN66ev+LOtL+cXH+UT/1HU+rSx2co2FUcUdKIOmzlpbVOyFLm9nKr96zIs4Bta/9yVgN/PsrzUdE7N8Sf+ZZy1zRMIBAKLIqKZCQRGqEFJbvCYONTWNsUmcHbLTff/IpcF+d2Adta2yHyc5DaNqcAxblnbFNPQj2LmWgLc36xtGTlyJB9++GFi1LPy/zk2gX6Zj4AmSZxdeJiQM8F02zqYglWL4v/F31aPdvYhNXhKFBe5b1U7sgp7RwXVBten4Tfvk6DScGqOPwHrzqNVv4OjUgKB4J3Fas6MVqslICBA7ASbCYR2ppEe/cR6mTfYOdjT7e8hPDx0h1M/+qNUKnNU/ztJIF2plyV1WevcDQkJeRP5LFBvnxATI6A9PnGPNfW86b5jGL32fsrfPVYT9yzGpDLT4m369aQRm96BURllHgdqfdqEeuOa8/rJKw5+s5NbWy4jadOOFCXuHaYh9Ms8QjuBJbHaNDOVSoW3tzcqlcpaJmRbhHamkR79hDPzho98eiKTydgzIjFyWU7rfye4RV08UWbBu50s0y4qGELOG2wiaak6Xz58wbomi4h9FsPA019QoFJhi9QDaetXgNy0pAp/ccpi9Vsbx/zONJv2EaMf/EC5zlXZPWQjq2rN5+bmS291ZCDnnbtZjdAv8wjtBJbEas6Mvb09nTt3xt5ezHTLKEI700iPfsKZSaTB1+9TomVZtnb9jYT4xP12clr/u8NTXhJLTUpZvC5zaLd48WLdZpmpOimbuoFvXd30MS8vr8QpZhZCHaNiW881XFt3nv4nPqdM20oWqSct/bpSn7Pc5RHPLFK3Ncnt7sr78zsx+sEPFK1fgi2df2Vd00UE7bmRoXJy2rmb1Qj9Mo/QTmBJhDOTDRHamcbb9HMnH/nI9c4v/i/bsQqNJ7dhS6eVvH76SpeeE/vfSQJpnAX7zZhDO6VSqZsyZmknJUNIEsem7WXP8E103jSAxt+3QSaXmbWKtPTrSSP+zGFTzPKWKcCHv/Rg5J3vcC2Vn/UtlvJnW18eHg3KVHk58dzNSoR+mUdoJ7AkolcJ3nmSv9muQUluEvJOL/7PX74QHdb2ZdfA9YRdDrG2ORbnJIF8QA0WstvapmR7bv11meeB4XT+cyAlWpRlZ791Bs6wJWhFVUrjxg7OW7SerKJglSI0+rY1FbpX58amS6yu403kjafWNksgEAhsEuHMCN55kr/ZftenmMkVdnT8oz+XfE4S+Pe7sfHgSW4zme7YISeBd2iBalIoZ8h8ZDMjhF0JYXWdBXy47GOGXP6avaM2W6wvOaJgDn2YzhZeEWuROrKKAhXdaDr1I8p2rMKVVWdYUXE2UQ+eW9ssgUAgsGms5swkJCRw9OhREhJECMmMIrQzjbfpV5NS7ONKFltlOzT7X1tkMjgyyfgoRU7sfzd4jJoEqlPComF9bU675OGczYj6tQq/geup2r8ubZZ0p8kPH3Jixn5ubb0C0tsXqxvDmH6f05ZIXrGWo+YyPcvJW6YATX74kIo9a3B11Rl8ys0iOiTK7PXYXP/LZgj9Mo/QTmBJZM7Ozpm7q2QCZ2dnwsPDAciVKxcxMZYL4SkQZJYbeNOPJZwnc/PSszMlWpSl+46hrKn3E89uhVnbnIwx4lzi3ioh5xMXv2eQtYzhFLdZyj4LGGc+fHx8gMS9Y8zKiHOJv//TTok9rahKV+qhIoHJbOI5rzNVtJ2DPdWHNKDhxFZoYtVcXH6cgN/PEffc+D0gvW30pDAH+IEOzOEqDzNlmzVxKZ6XxpM+oEr/OtzYcJHj0/cRdT/nBTAQCHIyzs7OvH6deG0sVKiQeLa1AlYLAKBQKBg8eDAKhcJaJmRbhHamkZZ+SYv/r2XDByNTcczvTIe1fTnw1Y40HZmc2v9OEEgjCwcByA7alaUIC+jPTbyZRk/uEU5uHDnMFJpRMVNlJsRruLj8OD5lZ3J82l7Kd63GmEdTaL+qN+4NSqa7nOT6/Uhf1nIk2zkyzoVy03phV4bf+hZFLiW/1ZjP7qEbLe7IZIf+Z8sI/TKP0E5gSazmzNjZ2dGsWTPs7OysZUK2RWhnGmnp9y4v/v/IpyehZ4K5vCLtiFA5tf8lOTNyzBuBSx9b1q5haDR//BPEIaZgh5zueFOf75jNNgaxjPn4sZbPmEjnTNehVSdwfcMF1rdYyuq63sRHxdHzn5EMvjieOp81o0L3GlTsWZNoTw0xJTQUa1SK/BXcsHdMfADS1284rahAUeaw3VwSWBwHF0eaTfuIkXe/x7VUPn6vv5Cd/dbx/HZ4ltRvy/0vOyD0yzxCO4ElEQEABAI93tXF/9WHNKBYo5L8Wn2etU2xGlcJRgZUwSPbvek3hbIUYSof0/ifIFZULcSXwRMI42WKfL9zhJPc5k++wAklU9hsUr2RN57y7xd/c+hbPyr1rEnlvnVQ5nZAm6DlpacGSSHRaeMAnAo4Y6e0J+xyCE/PPeJlGRUflmrAdze70I0FRBNnkh1Zgb2jgtqjm9Dw21aEXw1l0we/EHLq3bvOCAQCgSUQzoxAoEcNSrH/HVv8n69cIVot7MLWrquIe/buzvXVInGK2zSh4jvhzMiRMZ1eDOA91nKUsb0r88zRHi6mdGSSuE0oXZnPDr4mFpVZRkU0sWqurjnL1TVndWlJa2b+N/J/AOTxyIt7w5KUaOrJqzIqql7swtLoaDxPtcbp1AMen3rAk/MPQSth76zE3sGO6CevdBu9WguZnZxqg+rRdOpHxDx9xY4+67i//5ZVbRIIBIKchtWcGY1Gw/bt29ForHuzyY4I7UwjLf1qUJL57LSCVdZBrrCj0/r+XPrlBA/8A9P1nZzc/45zi8aU5xf2W6R8W9JuNB/Qhmq0YBp3eQqOX6Xre/cJpxsL2M43qNDgzS4LWwqvHr3g1l8vePH3AxZ915zV2sP8Ue0C7g1L4t6wJNWHNCBvmQK6/FpNAshkPL8TQcS1J0Rce0J4QCgR157wLDAcrdrCEZVkMip0r857M9oB4P/lNm5tyXwUN3NhS/0vOyL0yzxCO4ElsbozI8g4QjvTSE2/ouQj/zu2+L/p1A+RyWWphmE2Rk7ufycI5AvaI0OGhPkfPG1Fu8p48DWd6Mr8REcmg9zhKd1YwC4mcJ1H/MNlC1hpiBJ7ViaM4GhMAD+yDc5C6Nlgzi9ODMmszOOApJXQxKqRtBK53V0pWKUIhaoUoWDVIpRqU56CVYpg76jg+e1wwgOe6BydiGuhPLsdgZRg+h5Dnu0r02zaRzi75ebYtL1cXX3WLOWaA1vpf9kVoV/mEdoJLInVAgAolUrGjRuHUqm0lgnZFqGdaaSmX01KcovQd2bxf7HGpak79j129ltHgir9b6pzcv+7QjD2yKlMMYuUbwvaKbFnOcNYyl4ucC/T5dwihG/4g58YSEHymNFC4yygPw4yBXe8XIzqp3oVj/q1Ckmb6IRGh0Rxf/8tzi48zJ5hm1jb6Gd+cvkWH88ZHBi/g9CzweQtnZ+GE95n4LlxfPX6R4Zc/ppO6/vT+Ps2lOtclXxlCyKTpyMghExG2Q5VGHh2HG1X9OLauvP4lp/NlV9P24wjA7bR/7IzQr/MI7QTWBKrjczI5XKqVq2KXG41fyrbIrQzjdT0e5cW/ytzO9Dh9z4c+X43kTcy9mY+J/e/BLSc4g6NqcA1Hpm9fFvQ7lu6EI/aLNPDtnKGj6jBTwygP0vNYJ1xvPiI96hER+V8ptaaY5J+Lx++4OXDFwTtufEmUSbDtVT+xFGc/0ZyKnSvToFKhZEkiWc3wwxGcsIDQol68BxlbiXVBtan9mdNcXBx5NSP/lzyOYkmzjZfiNhC/8vOCP0yj9BOYElEAACB4D9qUIp/35HF/+97dybq3jPOLc6+u6ZbihP/rZtZgb+1TTE7tSnNYFrQmuloMM+6kW9YzxGm0Jem/MExs5SpzwdUZxzt6cRcwmSpBycwCUki6l4kUfciueN3TZcsk8vIW6ZA4nS1qkVxq+FO5T61KVDRjQR1AkgQfjWU49P2cvOvy5ZfiyMQCASCFAhnRiD4j3dl8X/ZjlWo+HENfq021+oLkm2R49ziMz602LoZazKDXizhH+5kYp1MarzgNZ+xijWM5gSB3CP1DVczihNK5tGPCaznKg9xxNFsZacHSSvx/E4Ez+9EcHt7gC5dbi8nX9mCyO3tCA8IzVKbBAKBQGCI1cb71Go1q1evRq22zeF4W0ZoZxrz58/HwcGB+fPn69LelcX/zoVy03ZlL/aN2cKrx1GZKiOn978rBOOAggoUNXvZ1tSuC/XwID/L2Gf2so9wg7UcZQUjUJrxHdko2hDKc/4kcSNXW+l7Wo2WyJth2c6RsRX9sitCv8wjtEvJiBEjuH79OpGRkRw6dIg6deqkmtfe3p6JEydy9epVIiMjOXXqFG3atDHIkzt3bubOncuNGzeIiIjA39+f2rVrG+Rxc3PDx8eHO3fuEB4ezrZt2/D09DTI4+DggLe3N8HBwTx9+pQ//vgDNzc38zXcAljNmUlISODIkSMkJIhh+YwitDMNhUJB3759USgUurR3ZfH/R749eXDgNtc3XMh0GTm9/2lI4Ax3aEIFs5dtLe0csOcHujOdrcSgskgd09mCFokf6G6W8hxfwFjaMolNurSc3vcsjdDPNIR+mUdoZ0j37t2ZM2cOs2fPpkmTJly9epXt27dTqFAho/mnTJnC0KFDGT9+PHXq1GHlypVs2LCBGjVq6PIsXbqUli1bMmzYMOrXr4+/vz9+fn4ULfrmxdzGjRspVaoUPXv2pHHjxgQHB+Pn54ezs7Muz48//ki7du3o378/H374IUWLFmX9+vWWE8MMWM2ZcXBwYMaMGTg4OFjLhGyL0M40ZDKZwW94Nxb/Vx9cn6L1irNv9BaTynkX+l/ifjPmd2aspd2ntCGSV/zFaYvVoSaB4fjQmyZ8RI23f+EtVN4hYz9XOEeQLu1d6HuWROhnGkK/zCO0M8TLy4tVq1axdu1abt68ydixY4mNjWXAgAFG8/fu3Zt58+axd+9e7t+/z8qVK9m7dy9jx44FwNHRkS5dujBp0iSOHz9OUFAQs2bNIigoiOHDhwNQtmxZGjRowBdffMGFCxe4ffs2n3/+OU5OTvTo0QMAFxcXBg4cyMSJEzl8+DCXLl3i008/pVGjRtSrVy9rxMkEVnNmZDIZ7u7uBg+UgvQhtDM/ic7MfWubYTFcSxeg1cKu7Bq8kbjnMSaV9S70vxME0pjyZi/XGtoVwoUvaMckNll8DdADIhjH7yxiMMXIn+lyXIOh+BkZ/8PQ8X4X+p4lEfqZhtAv8wjt3qBQKKhVqxYHDx7UpUmSxMGDB6lfv77R7yiVSuLi4gzS4uLiaNSoEZA4Dc3e3p74+HiDPLGxsbo8SY6kfjmSJBEfH0/jxo0BqFWrFkql0sC2wMBAgoODadCgQWabbHGsFgDA0dFR9zshIQG1Wo1CocDOzk6XR6PRoNFoUCqVBuH81Go1CQkJODg4GJwYKpUKrVarK/tt6XFxccjl8hRxz42lJx1wOzs7g+lJWq0WlUql60hJWLJNqf2dnduUVrq525Rko1wuR6FQoFarqUFJFiv34yh3zJZtettx6rimD9fWnuP+/lsmtykpj7XbBIbHSS2XIZEYgUpuZ2fScbopPSFXvAPlKcod+VOztckc173k+r+tTRPtunBEusll5SMccUz9OP33W78cSZJ0a8zUajVfffUVqm4bkSSQNnQxepy2q8/RSF6Bv6Xx9FT+zBNZVIbPp6p/y7n7vkT44dcGi/5tte9ll2tEUh0KhYK4uLgc0aYksuI4JaH/WXZvk+h7ph8n/Tx58uQxaFd8fLxB3wEoUKAA9vb2hIUZBksJCwujfHnjL9H8/f3x8vLSjbq0bNmSTp066eqKjo7m1KlTTJgwgZs3bxIWFkbPnj1p0KABd+/eBeDWrVsEBwczbdo0xo4dy+vXr/Hy8sLDw4MiRYoAULhwYeLj44mKMlxTGxYWRuHChY3aZgtYzZmZM2cOuXPnxtvbm6NHj7Jq1Sr69etHs2bNdHm2b9/O9u3b+eyzz6hataouffXq1Rw5coTJkyfj7u6uS/f29iYgIIAFCxbg5OSkS580aRLPnj1j2bJlBjaMHj2a/PnzM2PGDF1abGwsY8aMoXLlyowbN06XHhISwqRJk2jSpAmDBg3SpQcEBODt7U379u3p3LmzLt3SbZLL5Tg6OuLt7Z1j2pRVx8nDwwMADw8P+vXrx55Vf1NQ5sLIn8eT4CDLlm1K6zi9LKMionYc0UsS900xtU3Tp0/XfW6tNiWhf5y2FCjBAzWUKF6Ckk2amHycXs/X0jywCtFuMrO2KW/evCZd94oWLYpCodDZmlabXCPs6Se9x6H/yVhWuE7ax+kyODo5GmgQEhKCUqlkxIgR/PPPPyxbtoxpoU2IjYslDFI9ToEDlLQOcuPQzZmc+EbGpqM70n0+5XoiUWiKxNkhWhZ0yh59LztdI/LmzUuvXr1YuXJljmkTZM1xiomJ0Z2/OaVNou+ZfpxOn34zfTco6M20WICZM2cya9YsTOXrr79myZIlXLx4EUmSCAoKYu3atQbT0oYNG8by5cu5e/cuGo2GS5cusXnzZmrWrAkkOoy9e/dm+fLlPH78GI1Gw8GDB9m7d2+2HzGTOTs7Z1nsUWdnZ8LDwwEoVKgQJUqU4ObNm6jV6hzz9iEJS75RkcvleHp6cu3atXTZnh3alFa6udu0fPlyhg8fzooVKxg9ejSt1VX4jq60cZydbduU2nFyyOPIwCtfcey7PVxbf94sbdJoNFSsWJGgoCC02je7m1u776mHnEQqUhvZkwvIV9Q3+Th5aT6kvKYwI+UrzdYmpVJJxYoVTbru+fr6AujmSqfVphXaEbywi+F7xZ9vP04DEveIcfy9qUGbFi1axMiRI/H19WXs2LHEDzqeGNHbp06ax8lebs9sTS+aaivQVb6AhwkR6ep7P6i78VGdFpwdKvH5558b2GirfS+7XCPkcjkVK1bk2rVrxMfH54g2JZFVIzM1a9bk5s2buv6X3dsk+p7px8nBwYEXL14AUKZMGWJi3kzlNjYyo1AoiIiIoG/fvvj5+enSfX19cXV1pVevXqSGg4MD+fPnJzQ0lOnTp/PRRx+lWMvi7OyMi4sLT548Yc2aNeTOnZvu3Q0Ds7i4uKBUKomIiODQoUNcuHCBcePG0bx5c3bv3o27u7vB6MyNGzdYunQpS5YsSdU2a2K1kZmYmBguXDCMqJR0c09O8o6QRPK5gUkkn1eYVrpWq81QekJCgtFoHEknYnIs1aarV68aTU/LdltvU1rp5mxT0k1Iq9Xqpphd4r7RcrJLm1I7Tg2/aM2Le5Fc/v3NmyNztCkgIMBITiv3PW3iexlJK+nKNOU4HeEag3jP7G0y9bon/bc3kLH50/rUpjStqEr9hO+ISzD8LDXbjZWjX29cXBw8fxMoQ9P9TzQAm7qlbBNqvmQN8+jLloRxdGEeIarnBvk6dOiAn5+f7jg5oaQnDbjYwngbwUb7nhFs9Rqh3/9ySpv0sXSbkp+/kP3bJPqeacdJ3/l69eqVgTNjDLX6/+zdeXgT1f7H8XfSJi0tS0V2EBARvFwuKquIxYKAyCKbCwgiCAKyakFRKCKyCGjrAkUK/ARFXC6LVBEFRZCC7IJQEJC1SEvLvpTuye+P3oamLV3mJJmk/b6epw9lcjJzzmdO0pzMzJk09u7dS1BQkG0wYzAYCAoKIiIiIt/npqSkEBcXh7e3N926dWPVqlW5yty8edN2FLFdu3aEhITkKnPtWuYNiO+55x4aN25sO+q9d+9eUlNTCQoKIjIyEoB7772XmjVr2h2Bcje6TQDg6+tLeHh4rtGzKJhkV3Rz5swhIiKCOXPmkJ6ezo8//mh7M8oazBQ35WqXp1nwo/wy+luHrrek9L+9nKIspaiL484TdmV2k3mK+fxMAtccu+JveuYavADw7KrMn2ysWHmNZfzGISJ5jWrcYff40KFDmTNnTuZ/6nWhe+XB/MMlztVIzfNDTUnpe84i+amR/LST7OzNmTOHgQMH0rdvX+rXr89HH32En58fS5cuBWDhwoVMmTLFVr5p06Y8+eST1K5dm4cffpjIyEiMRiMffPCBrUy7du1o3749tWrVom3btvz4448cPXrUtk6AHj16EBgYSO3atencuTPff/8933//PRs2bAAyBzmfffYZM2fOpHXr1jzwwAPMnz+f7du3s2vXLhelU3S6HZkB7M5zFEUj2RWN2Wxm6NChREREMGbMGObNm8fYsWMBaEQtQllTwBo8T9v3n+TQl38Qv/cfh6+7JPS/VNLZxXFaUZ9jxDtsva7I7jEaUo+q9GWOczeUfVBTrmaeRaxYeZ1lzOI5InmN7rzPWS4Bt67JAeDoGl5kIovZyGejN992kyWh7zmT5KdG8tNOsrtl5cqVVKhQgZCQECpXrsz+/fvp3r27bVKAGjVq2J1K6+vry1tvvcXdd9/NjRs3WL9+PYMGDbI7Faxs2bJMmTKF6tWrc/nyZVavXs2UKVPsjiJVqVKFmTNnUqlSJc6dO8eXX37JzJkz7eo2fvx4LBYLy5Ytw8fHh19++YVXX31Vqb33338/9evXx8/PjyVLliitKy+6DmaE0FsVAqhAGQ7i+A/8eqrVpi612tVjwb3qFx6WZL//734zn3H7D9fuxoiBt3iKUNZwg7xPwcjT1Zhbvz+7KnNwcjUGOK9cp+wDmnVMYBxL+Yk/7co8SG3qUsWp98IRQgh3ERERcdvTyp544gm7/2/ZsoWmTZvmu75Vq1bledpZdp988gmffPJJvmVSUlIIDg62mxRBqwcffJCIiAjuu+8+IPN05a+++opjx45RtmxZunTpQlRUlPJ2dDvNTAh3EMh97Oc0SU66K7oeDF5GHvuoB1unrOPm+Rt6V8ejZd480/H3m3Gmp3gIf3z4jN+K9sTsp4+VqwnVmtz2aItW4/mSKazgYwaykCH4XANDOtxJaYbQjm/YRiJ5nxsvhBDCc9SrV4+1a9dy3333YTAYbD8pKSmsWbMGo9FIjx49HLIt3QYzqamphISE3PZiL3F7kp2a7Pl14kHWsk/vKjnUA0Na4mXyYs/cLU5Zf0nqf39wkjsoTR0qOWR9zs7OB2/epDsz+JY0cl+4WmhXYyB2D1yNITU1lR9//FFznbNfrwaw/NnXadWtBgYMdH7dSM8RXhzhQ9rxH/6PjfmuqyT1PWeQ/NRIftpJdiXPhAkTKF26NBaLJdfkAVnX32TdrFOVbqeZWSwWLl26ZHdOoCgcyU5NVn5mixdtachMIvWuksP43uFH66lP8F3fL7CkKXyYzUdJ6n8ppLOHEzxMfU6QUPATCuDs7F6kDZe4wbcoXqiZ7VqYUd9kng4xatQoTavKfr1alvO+RgYTgWHKf7B4WRk58VVSyD2LU04lqe85g+SnRvLTTrIreR599FGsViuTJ09mx44d/Pzzz7bHYmIyT2vOfu8gFbrOZjZv3jyZ2UIDyU5NVn6Pme4nniscIVbvKjlM4DsdObvtFCfXHXbaNkpa/9vKEVpR3yHrcmZ2ZSnFq3RmCiuw4rLbhxVdttPZBr01kpcmjirUQAZKXt9zNMlPjeSnnWRX8pQtWxaAP//8M9djWffp8fPzc8i25JoZUWJ1tDRiLXv1robDVGxYlUYvtmDDq6v1rkqx8rsbXDczZ84c22laqal5T1s8io78yWk285erqyeEEELYiY/PnAX0sccey/VYz56ZX2idPXvWIduS2cxEyWSx0j7jP7xAuN41cZjHPuzOnrlbuHzsgt5VKVZ2c4IKlKEWFTiNPtlmvzt1Xqd7VaQsL/EY3XnPldUSQggh8vTrr7/ywgsvMGbMGNq0aWNbvnbtWgIDA7Farbb726iSIzOiRCp/LPPfXRzXtyIOUq/7f6jw7yr8Pm293lUpdpJJ4w9OOuxUM2cYRUc28xf7OK13VYQQQghmz57NlStXMBgMNGrUCKs18/TnRx55BIArV64QGhrqkG3pNphJTk5m+PDhJCcX4T4IApDsVCUnJxP93i/8xD4s7nxtQSF5+XjTNrQbv735A6nXnT+tbUnsf1v/d78ZVc7IrjLlGMCjzOY7h63TXZXEvudIkp8ayU87ya7kiYmJoWvXrvz11192UzMbDAYOHTpE165dHXaamW6DGaPRSPny5TEa5eBQURWH7Lp06aLbto0GI514gB8N+3SrgyM1HxtE0sVEDnymOINVIRWH/ldUjrrfjDOyG80T/MIBojnjsHW6q5LY9xxJ8lMj+Wkn2ZVM+/bto3nz5jz88MP079+f/v378/DDD9OiRYs8JwbQSrdeZTabmTZtmt254KJwPDG7nPeaIHBC5l3GdfAfUy2qed/JDvMJXbbvSKWrlaPlm+34efQqsLrmKJMn9j9VuzlBFQK4izuV1uPo7KpyB88TWCKOykDJ7HuOJPmpkfy0k+xKtgMHDvDtt9/y7bffcuDAAYevX4bIwiWy7jWR9Ua25o9ztx58dpXLBjYVjsCnaUP55yFINqS5ZJvO1Db0SY5+e4DY7XKthDMlkcofnHTIqWaO9ApPsI4/OVyMphcXQgjh+V566SXWrl3LggULcj22cOFC1q5dy0svveSQbclgRugj270mKFcz88eJvJLhXfrwcLiRCK8N7H/e4NTtuULtdvWo0/Ff/Dqu+Nz00539zlG3mgSgCuV4jkd4j+/1rooQQghh54UXXuCRRx4hOjo612P79u0jMDCQF154wSHb0nVq5qSkJD0379GKVXZXY279nnWEJtsdyLWa89EcKh03EvfxTjqNN5Lc6Al+7HGNz2dFcX9Kd+X168nLx5sO857itwk/cDPhhsu3X6z6XyH9zhHe53nl9Tgqu2G05xcOcJQ4h6zPU5TEvudIkp8ayU87ya5kqVOnDkCeg5m//vrLrowq3QYzycnJjBgxQq/Ne7Ril132gYuDjtAEch9dZvhiuglLSKZT8jRq3PUf1kxZA+Dx+T30eltSriSxL+J3l2+72PW/QtrFcapzB9Upz1kuaVqHo7Irhx8DCKIHjpnW0lOU1L7nKJKfGslPO8mu5PH2zhxi1KhRI9djWcuyyqjSdTazhg0byswWGhTr7K7G3DpS8+wqGLK7SNfTVKAM8xjEZwzneBsra2dZCOEb9nGaNT9kDmQ8Pb+AOnfSYnxb1r28AqvF9VNLe3p+WiWSwj5OK81q5qjsXqQNf3CSvZxUWo+nKal9z1EkPzWSn3aSXclz+vRpDAYD48ePp27durbldevW5fXXX7eVcQRdZzMLDg6WmS00KNbZZb+WJrtCDGxK48tvTMYHEw8zieNtrFi9cpfz9Pzaz+3FgSW7OLdHn6l4PT0/FVs5onTdjCOyK4WZITzGR/yoeR1Okf2LiHpdoGsE1OtCamoqERERpKamKm+iJPc9R5D81Eh+2kl2Jc/atWsBuOuuu9i1axd//PEHf/zxB7t27aJWrVpYrVZbGVW6XjMjRL6yD2pyDmLq/e8+NUfX2H5/6aiV46XSGXTXP3D0qkM+PLmb+j0bUaVxDb7r87neVSmRfucIM3nO6duZM2cOZrOZ1NRURo0aZdeX+9CKWC7zG4ecXo8iyf56Pbom8wcYNWqNThUSQgihlw8++IBnnnmGGjVq4O3tbTs6YzBkTsB09uxZPvzwQ4dsSwYzwjPkPFpzdI3d76Xx5WVmMihpPhw9DMCoUaNcWEHnM5f24bGPevDr2EhSrspdlPWwk2PUpAJVCOAcVxy67uwDmJyy+rI3Xozkcd5muUO3XZDvv5cZ04QQQhTelStXeOyxx/joo4/o0KGD7RRDi8XC+vXreeWVV7h8+bJDtqXbYMZqtRIbG4vVRTf6K04ku9wG05YjxBLF4QLLemp+rSY/zuW/z3Nw2R5d6+Gp+TnCDVL4k9O0oh4r2Vnk5+eXXda9mCIiIhg6dGiez+/HIySTxhr+KPK2VaxZ4x5HV0py33MEyU+N5KedZFcyxcbG8vTTTxMQEGCbuezEiRNcuXLFodsx+Pn5uaxn+fn5cf78eQD8/f25efOmqzYtdJb1AS2/D2palcaHP5jFYCLYzF8OXbe7qPifqvTf/gpLmoRy8XCC3tVxT0N2Q7UmELsHFjR12mYm8xTlKEUwSx263oJeI/74sJMZjGMpP7LPodsWQgihjZ+fH4mJiQBUrFhRPtvqQLcjM15eXrRu3ZqtW7eSkZGhVzU8kpeXF61atZLs/udF2vI35wo9kPG4/AwGHv/kaXZ9+JtbDGTcNr+si8+zz4YHDrlnUXZbOcI0ntX0XJXshtOBkySU6IGM2/Y9DyH5qZH8tJPsir9PPvkEgNmzZ3Py5Enb//NjtVoZPny48rZ1G8yYTCYGDBjAzp07pWMXkWR3iz8+DKcDw1hY6Od4Wn6NBjSjTPVy/D7tZ72rArhxfjkHLQ66Z1FO2/mb2lSkMuWI52qRnqs1u4qUZQSP8zQfFLW6xYrb9j0PIfmpkfy0k+yKv379+mG1WlmyZAknT560/b8gjhjMyITfwqP15RFOc55N7jazk4P4lvcjaHZXfh61ivSkNL2rI4AbJHOAGKX7zWSZM2cOc+bMAch3CuNxdGEjB9nFceVtCiGEEK5gMBjy/XEUmc1MeCxvvHiZDoTwjd5VcZqgmV04u/Ukx9Yc1LsqIpvfOcrD1OdbdimtJ/s9F243+95/uIvneIQ2TFHalhBCCOEsTzzxBAAHDx60+78r6DaYsVgsREdHY7FY9KqCx5LsMvWgGamk8SN7i/Q8T8mvesvaNOjTmEX/nqV3Vex4Sn7O9DtHmcxTRX5eUbMLogH/xzBmsppjxBd5e8WN9D01kp8ayU87ya7427Jli+13s9lsO8UsNjaWkydPOnXbMpuZcAlnzGb2G2+ziA0sJcoh63MnBi8jA/cEc+irvWyftUHv6nimIbsz/3XCzGZlKcXffERDxnGea5rXExERAZDna6I/rXmHZwjmc1ZpmAZaCCGE88lsZnm7evUqBoOBl156iW++ce4ZNLpdM+Pt7U23bt3w9pYz3YpKsoPHaEgFyvBfthX5uZ6Q34PDHsbLx5udYZv0rkounpCfs10jiYOcoSX3Ful53t7erFixgrlz5wKZ18lUq1bNrkx9qhHBS0ykB8/yoQxkspG+p0byUyP5aSfZlTyxsbEAXLp0yenbksGMB5LsYBQdieAXUkgv8nPdPb9SFfxpPfUJfh79LZY095v1xd3zc5WtHKEV9Yv0HG9vb0qXLm27VmbUqFG2ozNNqMNSRvAzE7nKTdoylR0cc3i9PZn0PTWSnxrJTzvJruRZvHgxBoOBp59+2unbkl4lPM6D3M0D1KY/4XpXxSkendGZ0xuPcernI3pXReTjd44ygR6FKps1Y9lrr71GmTJlSEu7NTPd9TUn+JaxPEBtPmUTY1lKgsKpa0IIIYTe4uLiOHnyJL1796ZWrVr89NNPJCQk5Jqu+csvv1TelkzNLDzOKB7nM37jGkl6V8XhqjS5iwbPNebX4NV6V0UUYBt/U4+q3EnpAsuazWbb0Zgjfx1m2atzGM+TbGIyEbzEZg5zP68zlZUykBFCiBJgyJAhHDp0iIsXL7Jp0yaaNGly27Le3t688cYbHDhwgIsXL7J9+3bat29vV6Z06dLMnj2bv/76iwsXLrBhwwYaN25sV8bf35/Q0FCOHj3KhQsX2L17N4MGDbIrU7lyZRYtWsSJEydISEhg69atdOvWrcjtmzdvHrVr1wagZcuWTJkyhU8++YT58+fbfgpzY83C0G0wk5GRQVRUlNw8SYOSnN09VKYD9zOfXzSvw23zMxhoP7cnO9/byNXTl/WuzW25bX4udoVEdnKM7xnPCDpQkbK5ygTgzwPUosZOAw1XGliWMoJ2w1NZkjqMu6lEOOt4kPF8wA/FcnDuaNL31Eh+aiQ/7SQ7e7169WLmzJm8++67tGrVigMHDhAZGUnFihXzLD958mQGDRrEuHHjaNKkCYsWLeKrr77i/vvvt5UJDw+nTZs2DB48mObNm7NhwwbWrFlD1apVbWVmzpxJ+/btGTRoEI0bNyY8PJywsDA6depkK7Nw4ULuvfdenn76aZo3b05kZCRLly6121ZhFXSfGUfda0ZmMxMu4ajZzEJ5HhPejGaxA2vnHv4zoDmt3urAogazSE+WG2QqK8RsZlmnf40aNQrqdaFLvxGs+SIcjq6BZ1dlFvqmZ65yABxdg2+vlXQ6m0qf7TtpRX3OcQUDBgxkznhWFj/Ocw1jnTJcuctK+G9fsJ/T7CcGCy576xVCCOEkWmYz27RpE3v27GHs2LFA5of+o0ePMn/+fEJDQ3OVP3bsGLNnz2bBggW2ZcuWLSM5OZlBgwbh6+tLfHw8zzzzDOvWrbOV2bJlC+vXr+edd94BYNeuXaxYsYJZs2bdtkx8fDyvvPIKX331la1MTEwMkyZN4rPPPit0Lm+++Wahyr377ruFXuft6HbNjMlkYuDAgXzxxRd254+LgplMJvr16+f22c2ZMwez2Uxqamq+dzcvrEqU5Rla8hhTlerljvn5lPUlaGYX1g1b7vYDGXfML09XY279nm0AYvd7dkfXwM48lueU7fFkbwOravmwavsH9H/saZ5s3I4tW7ey9QzcqNOKmLPfk3gskjmvZg6Gvvp9G/369ePgF19gcefs3JTH9D03Jfmpkfy0k+xuMZlMPPjgg7z//vu2ZVarlY0bN9K8efM8n2M2m0lOTrZblpycTMuWLYHM09C8vb1JSUmxK5OUlGQrA7B9+3Y6d+7M559/TlxcHK1bt6Zu3bqMHz/eVmbHjh306tWLn376iStXrtCrVy98fX2Jiir8bTAeeOABrl69itls5uDBg/z888+Ffq4Wug1m/P39CQwM5NtvvyUxMZG0tDRMJhNeXl62Munp6aSnp2M2mzEab50Rl5aWRkZGBj4+PnaHqFJTU7FYLPj6+tpt63bLk5OTMRqNdnfhvt1yq9VKSkoKXl5emEwm23KLxUJqaqqtI2XJyMhwWpt8fX0JDAzkq6++slu3u7XJx8eHIUOGsGDBAkaPHm1bbjQaNe2nlw2PE2U9Qoz5Mr74am6TO/a91tM6c+HAOY6uPuDWfQ8yv0HKyi/7m6s79b20tDQyvumZ2SZfX4jJPC0x1WjEcnRNZpt8fXnttdeAW33yl19+udXeyOdsdc8ql/WYrU2Rz/G/B/hmy3d8vmH5rTad/y+Q+Udo1KhRtpnM3K3v6b6fimPfc9P9lPW3Y8WKFcWmTVlcsZ+8vLxy9T9Pb5P0PfX9lL1MmTJl7NqVkpKS60vcO++8E29vbxISEuyWJyQkUK9ePfKyYcMGRo0axdatWzlx4gRt2rThySeftG3rxo0bbN++nfHjx3P48GESEhJ45plnaNGiBcePH7etZ+zYscydO5djx46RlpaGxWJh5MiRbN261Vbm+eef5/PPP+eff/4hLS2Nmzdv0qdPH06cOJFn3XIKDw/n+eeft1u2Z88eevTowZUrVwq1jqLSbTAzc+ZMSpcuTVhYGFFRUSxevJh+/foRGBhoKxMZGUlkZCQjR46kYcOGtuVLlixh8+bNTJo0ye4eDWFhYURHRxMaGkqpUqVsy0NCQrh06RLz5s2zq8Pw4cMpX74806ZNsy1LSkpixIgRNGjQgODgYNvy2NhYQkJCaNWqFQMGDLAtj46OJiwsjM6dO9tdIOXsNhmNRnx9fQkLC3PbNvn4+ABQtWpVu+y17Ke7Aqoy7Orj7HjFwLx75ym3KSAgwG36XkpABjFdb1D5vya+Arfve1OnTrU9frs2ZfGU15Mr3yPcqe85qk1ZpO+5/34KCAjg2WefZdGiRcWmTeCa/XTz5k3b67e4tEn6nvp+2rFjh+33nB/4p0+fzowZM1D12muvMXfuXPbu3YvVauXEiRMsXbqU/v3728oMHjyYTz75hOPHj5Oens6+fftYvnw5DzzwgK3Myy+/TLNmzXjqqac4c+YMrVq1IiwsjLi4ODZu3AjApEmTKFeuHJ07d+bixYt06dKFzz//nA4dOnDw4MF869m/f3+7OmVp0qQJs2bNcthN03PS7ZqZ6tWrM23aNIKDg+UbyiK2KWsQM3z48FwZu1ObPv744zyPzGjZTyMNj9OZxvTw+UC5TVmDaHfpe71+HEz83rNsmfCj2/c9yPx2PDw8nODgYPl23MP7niPaJH3Pc/ZT1t+OMWPGcP369WLRpiyu2E9ms5l58+bZ9T9Pb5P0PfX95OPjYzviUKdOHbtrZvI6MmMymbhw4QJ9+/ZlzZpbpy0vWLCAcuXK8eyzz3I7Pj4+lC9fnri4OKZOnUrHjh1p1qyZXRk/Pz/Kli3LuXPn+OyzzyhdurTtVLG4uDh69+5td11NeHg41atXp3v37tx9991ER0fTtGlT/vrrL1uZNWvWcPz4ccaMGXPbugH8/PPPPPTQQwCcOnWK69ev07BhQwwGAykpKVSrVk3pcoPb0e3IzI0bN4iMjOTGjRukp2fe+DAtLS3Pcylv1/Cc5wZmyXleYX7LLRZLkZZnZGTkORtH1gsxJ2e0KT09ncjIyNtu013alDWXuNVqzXO7hd1Pvph42dqBV1iS6zEtbXKnvlerS33uqF+R5U8uJDU5RXObXNX3IPPc3Jz5ZW+TO/S9LO72HuFOfc8T95P0vfyXF9SmrL8dSUmZM+cVhzbl5Mw2ZeWXs/95cptut1z6XuH3U/bB1/Xr1wucACAtLY29e/cSFBRkG8wYDAaCgoJsN1G+nZSUFOLi4mw3IV21alWuMjdv3rQdRWzXrh0hISFA5iDKbDbnus9LRkaGrQ1+fn5AZia3K5OfBg0aYLVaWbJkie1L7D59+rBgwQLMZjN169bl0KFDBa6nqHQbzGR1bFF0JS2752nNOa7wMwccsj53yc/kZ6ZtaDc2vv49qdfzfqN2R+6SnyeS7NRIfmokPzWSn3aSnb05c+awYMEC9u7dy+7duxkxYgR+fn4sXboUyJweOTY2lsmTJwPQtGlTqlWrxv79+6lWrRoTJ07EaDTywQe3zlZp166dbVa0e+65h+nTp3P06FHbOq9fv87mzZuZPn06SUlJxMTEEBgYyHPPPccbb7wBwJEjRzh27Bgff/wxEyZM4NKlS3Tt2pW2bdvy1FNPFdiusmXLYrVaWblypW3ZihUrbLOwlS5d8H3ZtNDtPjNms5ng4OBch/xEwUpSdj54M5qOvM/3Dlunu+T30JuPcS3mMge/2K1rPYrKXfLzRJKdGslPjeSnRvLTTrKzt3LlSiZMmEBISAjbtm2jUaNGdO/e3TYpQI0aNahSpYqtvK+vL2+99RZ79uzhq6++IjY2lnbt2nH16lVbmbJlyxIWFsbevXtZuHAhv//+O926dbM7ijRgwAD27NnDp59+yp49ewgODmbKlCksWrQIyBx09uzZkwsXLrBixQp27NjBc889x5AhQ+xOTStI9iNd2Y/AOeq+MjnpdmTGaDTSsGHDQh22EvZKUnbP8QgXucFP/OmwdbpDfgF17qR5cBBftPpYtzpo5Q75eSrJTo3kp0byUyP5aSfZ5RYREXHb08qeeOIJu/9v2bKFpk1vf880gFWrVuV52ll28fHxDBs2LN8yx48fp2/fvvmWKchrr71mu0Y+v+VWqzXP67+LSrfBjBAFMeHFGJ5gEv/FWsxuMPjYB9058Nku4ved1bsqQgghhBAO06FDB7v/Z12nk3M5IIMZUbz15mFukMwa/tC7Kg5V54l/UaPV3UTUU5+uUQghhBDCXRTlVLKckxFopdtgJi0tjSVLlpT4O8FqURKy88aLMXRiBt86/KiMnvkZvY20De3G5kk/knwp/xlP3FVJ6H/OItmpkfzUSH5qJD/tJLuSwRH31NFCt/vM+Pv7Fzh9nfBsERERDB061PZvUfTmYV6hEw8zCUsxOsWs8fBWNB7xCP/X6D2sGZaCnyCEEEIIt+Xn50diYiIAFStWlM+2OtDtSiwfHx+mTZtmu0u8KLzinp0XRoLpTBg/OGUgo1d+PmV9eeTtjvw67juPHsgU9/7nTJKdGslPjeSnRvLTTrITzqTbYMZgMFCtWjWnTdNWnBX37HrQDAMGVrLDKevXK7+WE9oRv+8sJ378q+DCbqy49z9nkuzUSH5qJD81kp92kp1wJpkjT7gVIwaC6cIH/EAGnnv0IqdytcvTZFQgv46Vm4YJIYQQQjiKDGaEW3mSpvhi4r9s17sqDhU0swuHvvyD8wfi9K6KEEIIIUSxodtgJjU1lbCwMFJTU/WqgscqrtkZMBBMZz5iLelkOG07rs6vZlBd7u54H5tD1rpke85WXPufK0h2aiQ/NZKfGslPO8lOOJNuUzNbLBaio6P12rxHK67Z9aAZpfHlK3536nZcmZ/R20j7ub3YMvknEuOvu2SbzlZc+58rSHZqJD81kp8ayU87yU44k25HZnx9fQkPD8fX11evKnis4pidF0bG8yTv8T2ppDt1W67Mr8moQKwWC3vmbnH6tlylOPY/V5Hs1Eh+aiQ/NZKfdpKdcCZdr5kpVaqUnpv3aMUtu948jAUr/2WbS7bnivz8q5Tlkbc78vPIVR49FXNeilv/cyXJTo3kp0byUyP5aSfZCWeRCQCE7sx4M46uzOK7YjWDWZv3unJszUHObD6ud1WEEEIIIYolGcwI3fWnNVdIJJLdelfFYWq3r0/drv9m42vf610VIYQQQohiy+Dn5+f4W6zfhp+fH+fPnwegTJkylC1blnPnzmGxFJ9v413BaDRSpUoVt88uIiKCoUOH2v7Niy8m9jCTYD5nHX+6pF7Ozs/kb2bQgdfZPnMD+xa45rQ5V/KU/ueOJDs1kp8ayU+N5Kddcc7Oz8+PxMREACpWrMjNmzd1rlHJo9uRGYvFwqVLl4pdp3aF4pRdZx7kMjdcNpAB5+fXelonrp2+zL6FxeteOVmKU/9zNclOjeSnRvJTI/lpJ9kJZ9J1NrN58+bJzBYaFKfsnuMRvmSrS7fpzPyqtajF/YMf4seXvgGryw56ulRx6n+uJtmpkfzUSH5qJD/tJDvhTHLNjNDNXdzJQ9zLcorHEQwvsxdP/F9vtr6znsvHLuhdHSGEEEKIYk8GM0I3vXmYXzjAea7pXRWHaDmhPRnJaewM26R3VYQQQgghSgQZzAhdGDDQh1YuP8XMWSo2rErzcUGsffHrYndPGSGEEEIId6XbbGb+/v5YLBaSk5NdtflixdfX1+2zy282s0DuYz6DacTrutxbxpH5GYwGnt82hlM/H2VzyFqHrNPdeUL/c1eSnRrJT43kp0by0664ZiezmelPtyMzRqOR8uXLYzTKwaGiKg7Z9eURvmGbLgMZR+fXdExrfMr6snXqeoesz90Vh/6nF8lOjeSnRvJTI/lpJ9kJZ9KtV5nNZqZNm4bZbNarCh7L07Mrhx+daazbKWaOzK9c7fIEvvMEawd9Q0ZKugNq5/48vf/pSbJTI/mpkfzUSH7aSXbCmWSILFzuSZpwkDMc45zeVVHWfm4vopfu5uzvJ/WuihBCCCFEiSODGeFyPWnOSnbqXQ1l93ZrSNVmd/HbhB/0rooQQgghRImk62AmKSlJz817NE/NrgrlaMG9RLJL13qo5mfyM9Puox5sev17Uq545r5Q4an9zx1IdmokPzWSnxrJTzvJTjiLrrOZyYwPxVtes5kNoz3t+A9PEaZz7dS0nt6Ju1rfw7LWc8HqspeQEEIIIdyIzGamP11nM2vYsKHMbKGBJ2fXk+asYoeudVDNr3z9SjR75VHWD19RIgcyntz/9CbZqZH81Eh+aiQ/7SQ74Uy6zmYWHBwsM1to4KnZ3U0l/k0N1vCHrvVQza/9xz3ZF7GN8wfiHFwzz+Cp/c8dSHZqJD81kp8ayU87yU44kwyRhcv0oBkbiOYannvebN0u/6bSA9XYMuUnvasihBBCCFHiyWBGuEwvWrDKg2cx8zJ78dgH3dg8cS0pV4vfXYyFEEII4RpDhgzh0KFDXLx4kU2bNtGkSZPblvX29uaNN97gwIEDXLx4ke3bt9O+fXu7MqVLl2b27Nn89ddfXLhwgQ0bNtC4cWO7Mv7+/oSGhnL06FEuXLjA7t27GTRoUK7tNW/enLVr15KQkEBcXBzr1q3D19fXMQ13At0GM1arldjYWKwl8JoDVZ6Y3b+pQXXKs44/9a6K5vyajnmUlGsp7P9U32t+9OaJ/c9dSHZqJD81kp8ayU87yc5er169mDlzJu+++y6tWrXiwIEDREZGUrFixTzLT548mUGDBjFu3DiaNGnCokWL+Oqrr7j//vttZcLDw2nTpg2DBw+mefPmbNiwgTVr1lC1alVbmZkzZ9K+fXsGDRpE48aNCQ8PJywsjE6dOtnKNG/enNWrV7NhwwYeffRRWrduTUREBBaLxXmBKJLZzITTZJ/N7PTQn6hFBYayUO9qaeJfpSxDjrzJ8s4L+WfLCb2rI4QQQgg3oGU2s02bNrFnzx7Gjh0LgMFg4OjRo8yfP5/Q0NBc5Y8dO8bs2bNZsGCBbdmyZctITk5m0KBB+Pr6Eh8fzzPPPMO6detsZbZs2cL69et55513ANi1axcrVqxg1qxZty2zceNGfv31V6ZOnaohDX1467Vhf39/WrZsyfbt20lNTSUtLQ2TyYSXl5etTHp6Ounp6ZjNZrsZMNLS0sjIyMDHxweDwWBbnpqaisViyXUo7HbLk5OTMRqNuS5Iy2u51WolJSUFLy8vTCaTbbnFYiE1NRVvb2+8vW/FmZGR4bQ2eXl50bRpU7Zs2WJXF3drU1Y7DAYDXQ1NeM97Db5evrrvJx8fHx566KEi9b22s7pyat0R4radBiixfS9r/S1btmTPnj1kZGQUiza5c99z9zZJ3/Oc/eTl5cVDDz3E1q1bSU5OLhZtyuKK/WQwGAgKCmL79u22/ufpbZK+p76fspcpU6aMXbtSUlJITU2126bJZOLBBx/k/ffft9vmxo0bad68OXkxm80kJ9uf3p6cnEzLli0BbHVKSUmxK5OUlGQrA7B9+3Y6d+7M559/TlxcHK1bt6Zu3bqMHz8eyByMNW/enG+++YYNGzZQp04djhw5wpQpU9i2bVuedXMHug1mQkNDKV26NH379iUqKorFixfTr18/AgMDbWUiIyOJjIxk5MiRNGzY0LZ8yZIlbN68mUmTJlGtWjXb8rCwMKKjowkNDaVUqVK25SEhIVy6dIl58+bZ1WH48OGUL1+eadOm2ZYlJSUxYsQIGjRoQHBwsG15bGwsISEhtGrVigEDBtiWR0dHExYWRufOnenWrZttubPbZDQa+fPPPwkLs79fiyPaZLFYGDx4sHKbfHx8ALg7vSJ1vI10+/gluvgY3GI/BQQEFLrv3RN0H/90TKT2t2W42OpEie97U6dOZcCAAXZ18fQ2uWvf85Q2ZZG+5/77KSAggLvvvptFixYVmzaBa/bTzZs3GTFiBH379i02bZK+p76fduy4der5iRP2Z25Mnz6dGTNm2C2788478fb2JiEhwW55QkIC9erVIy8bNmxg1KhRbN26lRMnTtCmTRuefPJJ28Dpxo0bbN++nfHjx3P48GESEhJ45plnaNGiBcePH7etZ+zYscydO5djx46RlpaGxWJh5MiRbN26FYDatWsDMGHCBCZOnMj+/ft57rnn+OGHH2jWrJndutyJbqeZVa9enWnTphEcHExiYmKx+fYhizO/UfH19SUsLIzhw4fnytgRbZo7dy6DBw9WbtPHH3/MkCFD2NRjAf9EHmCweeFt25Tfckfvp9KlSxMWFla4vufjQ5/Nwzm17ig7Zmwo8X0PMo+0hYeHExwcbPdNkSe3yS37noe0Sfqe5+ynrL8dY8aM4fr168WiTVlcsZ/MZjPz5s2z63+e3ibpe+r7ycfHhytXrgBQp04du9PM8joyU6VKFY4fP06bNm3YufPWpEjTpk3jkUceISgoiJwqVKjA3Llz6dSpE1arlRMnTrBx40b69+9PhQoVALj77rv55JNPCAwMJD09nX379nHs2DEeeOAB2+QCY8aMYcCAAUyYMIEzZ87QqlUrpkyZQp8+fdi4cSMtWrTg119/5b333uPtt9+2bX/Hjh389NNPTJ48OVfd3IFuR2ayvxGkpaUBmZ026/fscnaELDkPp+Vcd2GWWyyWIi3PyMiwO70hS9YLMSdPa9OcOXOoXLkyAOm9/kt6uZpwNQa+6WkrX9g2ZV3oV+0PA59Y9uR5iNQVbcouPT29SH3v3qf/g1+VMmx9dz3pybce13s/5WyTK/te1h+J5OTkXI95apvyW65X3/OUNknf87z9JH3vlqK2Keux7I97epuk76m1Kfvg6/r16wVeM3Px4kXS09OpVKmS3fJKlSoRHx+f53MuXLhA79698fHxoXz58sTFxTF16lROnjxpK3Py5Ek6duyIn58fZcuW5dy5c3z22WecOnUKyHz/fPvtt+ndu7ftupro6GgaNWrEmDFj2LhxI+fOnQPg8OHDdts/fPgwd911V77t0pNus5lZLBaio6PdenYEd+XM7MxmM7GxsZn/KVcTqjXJ/FejatxBwBncYhazLIXNz+RvJmhWFzaO+470pNxvuiWVvHa1k+zUSH5qJD81kp92kt0taWlp7N271+4ITNb1WNmP1OQlJSWFuLg4vL296datGz/88EOuMjdv3uTcuXMEBATQrl071qxZA2Req2M2m3PNKJeRkWEbkJ0+fZrY2FjuvfdeuzL33nsvMTExWprrEjKbmbATEREBwNChQ2HI7szBTOweWNBU07p2Df2G4Pv60ODwS46uqtO1nt6JGq3u5sugcL2rIoQQQgg3pGU2s169erFgwQJGjx7N7t27GTFiBD179qRx48YkJCSwcOFCYmNjbad1NW3alGrVqrF//36qVavGxIkTqVWrFq1ateLq1asAtGvXzjYr2j333MP06dNJTk6mffv2tiNJP/74IxUqVCA4OJiYmBgCAwP58MMPeeONN1i0aBEAI0aMYOLEiQwfPpz9+/fTt29fxowZQ7NmzeyOBLkT3Y7MZI0qs593KArHZdldjckcyFyNgWdXZQ5unl1VpFV05kHOPuBe88oXJr+AeyrQ7JVH+WXMty6smWeQ1652kp0ayU+N5KdG8tNOsrO3cuVKJkyYQEhICNu2baNRo0Z0797dNilAjRo1qFKliq28r68vb731Fnv27OGrr74iNjaWdu3a2QYyAGXLliUsLIy9e/eycOFCfv/9d7p162Z3StyAAQPYs2cPn376KXv27CE4OJgpU6bYBjKQeb+a0NBQZs2axfbt2wkKCqJr165uO5ABHa+ZyerY69aty/McUXF7Lssu23UytqM0BZgzZw4Ao0aNgkuptDLex3f/vv25x3ooTH7tPujOgSU7Sfgz1sW1c3/y2tVOslMj+amR/NRIftpJdrlFRETYzobJ6YknnrD7/5YtW2jaNP8zZFatWsWqVfl/4RwfH8+wYcMKrFtoaGie97txVzJEFoVzNcb+36wjNNkHPGA3I8imN7+mFq0ZPOldV9TQYe7p1IBqLWux5oUv9a6KEEIIIYTIhwxmROHkGLQUZlKAXrRgDX84qULO4eXjTbuPurN54lqSL8s1XUIIIYQQ7ky3a2YyMjKIiorKc9o7kT9PyO5fVKc59/AlW/WuSi755dc8OIiUq8n8uWi7DjXzDJ7Q/9yVZKdG8lMj+amR/LST7IQzyWxmwo7dbGb5GbI7898cs5xlPT9p6O9kYGEsSx1eR2cpUyOAl/56g6/bf0Ls9tN6V0cIIYQQbk7LbGbCsXQ7MmMymRg4cKDd3VVF4bhFdldjbl0/U69L5g+ZN7wyXEylFy2Yzy/61S8ft8uv7ftPcmTFnzKQKYBb9D8PJdmpkfzUSH5qJD/tJDvhTLoNZry8vAgMDMTLy0uvKngst8jum563rqM5uibzh8xZzP6esJ6tHOFv4vSrXz7yyq9Wm7rc3fE+Nr2xRseaeQa36H8eSrJTI/mpkfzUSH7aSXbCmXQbzIjiyQdvBtKG+fysd1UKzehtpN3HPdn69joS46/rXR0hhBBCCFFIMpgRDtWTFlzkOps4pHdVCq3xiEfAYGDP3Ci9qyKEEEIIIYpAt8FMeno6kZGRcvMkDdw1u7pU4TW6uv1Rmez5+VcpyyNvd+SXUSuxpFv0rppHcNf+5wkkOzWSnxrJT43kp51kJ5xJZjMTdgo9m1kOXWjMxwxgIb8yi0gsuKxbaWbwMtJnw8tcOXGRtS9+rXd1hBBCCOFhZDYz/el2ZMZsNhMcHGx3x3hROO6UnQEDk+jFRwxgBJ/yLqvdfiCTlV/bmV3xvcOP9SNW6l0lj+JO/c/TSHZqJD81kp8ayU87yU44k7deGzYajTRs2BCjUS7bKSp3yc6AgTCepxX16cB0jhOva30Ky2g0UrtTfaxNK7KkWRjpSWl6V8mjuEv/80SSnRrJT43kp0by006yE86k22BGeDYDBj6gPy25lyd5j3Nc0btKhVauzp2ce+Qm619YweW/z+tdHSGEEEIIoZEMZkSRGTHwIQNoRh268R7nuKp3lQrNJ6AU3Vb1p9xRM8cjD+pdHSGEEEIIoUC3wUxaWhpLliwhLU1O8SkqR2c3Z84cIPOGl6mpqfmWNWLgIwbQhDp0533iPWggYzR50XPVQC4ciufwR1ul72kkr13tJDs1kp8ayU+N5KedZCecSWYzE4WewcyIgTkM5AFq04P3SeCaK6rnMJ0X9+HOBpX5MihcrpMRQgghhDKZzUx/ul2J5ePjw7Rp0/Dx8dGrCh5Lj+yMGJjLi9xPLbp74EDmofGPUbNNXVY++X94WYzS9xTIa1c7yU6N5KdG8lMj+Wkn2Qln0u00M4PBQLVq1TAYDHpVwWPpkV0Y/fkPNenO+1zgusu26ygnfz7CsTUHSYy/jq+vr/Q9BfLa1U6yUyP5qZH81Eh+2kl2wplkAgBRoBB6Esh9dGKmRw5kAOL/+EfvKgghhBBCCAeTwYzI1zDa05dH6MxMj7rYXwghhBBCFH+6TQBQpkwZateuzaFDh7BYLK6qQrFgNBpp0KCBUnbZZzCbM2cOtWvXpmvXrnZlutKEj3iBHoTyJ6eV6+0uHJFfSSb5aSfZqZH81Eh+aiQ/7YpzdjIBgP5kNrMSKucMZhEREXazmRkxsJ3pvMd3LGe7LnUUQgghhHBnMpjRn26zmfn6+hIeHo6vr69eVfBYzsju+++/t/t/Bxrhgzffssth23AX0vfUSH7aSXZqJD81kp8ayU87yU44k67XzJQqVUrPzXu0wmQ3Z84czGYzqampjBo1Cp5dlfnANz1zlV2zZo3d/4fRnkX8SjoZDqmvu5G+p0by006yUyP5qZH81Eh+2kl2wllkAoBiJvsABqBmzZocO3Ys88FyNQu1jobcxYPczQvMc1Y1hRBCCCGEUKbbaWbCOcxmM0OHDsVsNjNq1CjCw8Mzj8oUwVDa8TVbuYqc9ymEEEIIIdyXboOZ1NRUQkJCbEcQROEVJbucp48VpBJl6UFzFrJBa/XcnvQ9NZKfdpKdGslPjeSnRvLTTrITzqTbYMZisXDp0qViN0WfKzgzu4EEsZlDHCPe4et2F9L31Eh+2kl2aiQ/NZKfGslPO8lOOJOus5nNmzdPZrbQQHN2V2Myf8j8liTnNyQmvOjPoywoxkdlQPqeKslPO8lOjeSnRvJTI/lpJ9kJZ5JrZkqSb3raZjIbNWpUrmtpnuABEknmN/7So3ZCCCGEECXCkCFDOHToEBcvXmTTpk00adLktmW9vb154403OHDgABcvXmT79u20b9/erkzp0qWZPXs2f/31FxcuXGDDhg00btzYroy/vz+hoaEcPXqUCxcusHv3bgYNGnTb7X777bckJibSpUsXtcY6mQxmhM0AgviM37DisvuoCiGEEEKUKL169WLmzJm8++67tGrVigMHDhAZGUnFihXzLD958mQGDRrEuHHjaNKkCYsWLeKrr77i/vvvt5UJDw+nTZs2DB48mObNm7NhwwbWrFlD1apVbWVmzpxJ+/btGTRoEI0bNyY8PJywsDA6deqUa5sjR47EavWMz4MymBEA1KUyzanLV/yud1WEEEIIIYqtUaNGsXjxYpYuXcrhw4cZPXo0SUlJ9O/fP8/yffr04b333mPdunWcOnWKRYsWsW7dOkaPHg1knsbXvXt3QkJC2Lp1KydOnGDGjBmcOHGCl156ybaehx56iGXLlhEVFUVMTAyLFy/mwIEDNG3a1G57jRo1YvTo0bz88svOC8GBdBvMJCcnM3z4cJKTk/WqgsdyRnYv8Cjfs4dL3HDYOt2V9D01kp92kp0ayU+N5KdG8tNOsrvFZDLx4IMPsnHjRtsyq9XKxo0bad68eZ7PMZvNubJLTk6mZcuWQOZpaN7e3qSkpNiVSUpKspUB2L59O507d7YdrWndujV169Zlw4Zb10qXKlWKTz/9lFdffZX4eM+YDEq3m2b6+flRpkwZ4uPjSUtLIy0tDZPJhJeXl61Meno66enpmM1mjMZb4660tDQyMjLw8fHBYDDYlqempmKxWHJdYHa75cnJyRiNRsxmc4HLrVYrKSkpeHl5YTKZbMstFgupqam2jpQlIyPDaW0yGo3ccccdxMXF5ap7FoPBYPec/Nrkb/Slj6UVA80R+Bp9dWlTfssdvZ/MZjOVK1eWvqexTenp6ZQvX54rV67YzUzjyW2SvucZ+0n6nlqbjEYjlStXJjY2lpSUlGLRpiyu2E8AVatWJT4+3tb/PL1N0vfU91P2MmXKlLFrV0pKSq7Jlu688068vb1JSEiwW56QkEC9evXIy4YNGxg1apTtqEubNm148sknbdu6ceMG27dvZ/z48Rw+fJiEhASeeeYZWrRowfHjx23rGTt2LHPnzuXYsWOkpaVhsVgYOXIkW7dutZWZNWsWO3bs4IcffsizLu5It8FMWFgYpUuX5sqVK0RFRXH+/HkqVqxIYGCgrUxkZCSRkZGMHDmShg0b2pYvWbKEzZs3M2nSJKpVq2a3zujoaEJDQylVqpRteUhICJcuXWLePPs72g8fPpzy5cszbdo027KkpCRGjBhBgwYNCA4Oti2PjY0lJCSEVq1aMWDAANvy6OhowsLC6Ny5M926dbMtj4qKYvHixfTr188pbTIajbzyyiuEhYXZtSk9PR2AmjVr2tpbUJvG3tsb4w1/Br4zloEGg25tcuV+CggIsPW94tKmLM5u09SpU5k0aRI5eXKbpO95xn6SvqfepoCAANauXcuiRYuKTZvANfvp5s2bhIaGcuXKlWLTJul76vtpx44dtt9PnDhht93p06czY8YMVL322mvMnTuXvXv3YrVaOXHiBEuXLrU7LW3w4MF88sknHD9+nPT0dPbt28fy5ct54IEHbGVefvllmjVrxlNPPcWZM2do1aoVYWFhxMXFsXHjRjp16sSjjz7Kww8/rFxnVzL4+fm57OoePz8/zp8/D0D16tWZNm0awcHBJCYmMnfuXEaOHFlsRurO+EYlNDQUgIkTJ9J/2nI+mf8JXsfWktrzawDMq3rz0UcfMXToUBYsWGA7l7KgNv3EBFZ772aJ92aXt0mP/VS6dGnCwsJsfa84tMmV+8lgMBAeHk5wcLDdYW9PbpP0Pc/YT9L31Nrk6+tLWFgYY8aM4fr168WiTVlcsZ/MZjPz5s2z63+e3ibpe+r7ycfHxzbArVOnDjdv3rQ9lteRGZPJxIULF+jbt6/djc0XLFhAuXLlePbZZ7kdHx8fypcvT1xcHFOnTqVjx440a9bMroyfnx9ly5bl3LlzfPbZZ5QuXZpevXrh6+tLXFwcvXv3Zt26dbby4eHhVK9ene7duzN79mxefvlluyPf3t7eZGRksHXrVp544onb1k1Puh2Zyf5GEBYWRs2aNQkLC8ucLvjZVZmF/jeN8O3uGJvz3MCc6y7McovFUqTlGRkZZGRk5Fqe9ULMKetUkpy0tCnrxZOcnMwDfmfwOrY2s44Ztw53p6amEhERQUpKSq7659WmQO7jHiqzLD2K5HT7x1zRpsIud+R+yt73strh6W1y5X7K+iORnJxcqD6W33J3aVN+y6Xvuc9+kr6X//LCtkn63i1FbVPWY9kf9/Q2Sd9Ta1P2wdf169ftBjN5SUtLY+/evQQFBdkGMwaDgaCgICIiIvJ9bkpKCnFxcXh7e9OtWzdWrVqVq8zNmze5efMmAQEBtGvXjpCQECBzEGU2m3PNUJaRkWFrQ2hoKEuWLLF7fNeuXYwfP561a9fmWzc96TaYgcxDfJB5YdMTTzyR907MMbApjC5dutiNdoujrOwAu2xy3jumICH05GN+5DpJBRcuRuzyE0Um+Wkn2amR/NRIfmokP+0ku1vmzJnDggUL2Lt3L7t372bEiBH4+fmxdOlSABYuXEhsbCyTJ08GoGnTplSrVo39+/dTrVo1Jk6ciNFo5IMPPrCts127dhgMBo4ePco999zD9OnTOXr0qG2d169fZ/PmzUyfPp2kpCRiYmIIDAzkueee44033gAgPj4+z4v+z5w5w+nTp50di2a6HpkZMWJE3g9mH7iUq1mk9c6ZM4e6devy+OOP53mUpzjIN7sieIIHqEF5FvGrA2rlORyVX0kl+Wkn2amR/NRIfmokP+0kO3srV66kQoUKhISEULlyZfbv30/37t1tkwLUqFHD7lQvX19f3nrrLe6++25u3LjB+vXrGTRoEFevXrWVKVu2LFOmTKF69epcvnyZ1atXM2XKFLujSAMGDGDKlCl8+umn3HHHHcTExDBlyhQWLVrkusY7gW6DGaPRSMOGDTl06JBD15vrKE8RB0OewGg00qBBAw4dOmTX2Yu0Dgy8SXfeZw1J5H1Yt7hyRH4lmeSnnWSnRvJTI/mpkfy0k+xyi4iIuO1pZTmvTdmyZUuue8HktGrVqjxPO8suPj6eYcOGFame/v7+RSqvB93uM2M2mwkODr7t1MLi9hyRXU+a44cPXxDlwJp5Bul7aiQ/7SQ7NZKfGslPjeSnnWQnnEnXa2Zc4mrMrd+L4SlnWnjjxXi6MYtI0sh9cZsQQgghhBCeoPgPZm43cCnBA5uBBJFEKivZUXBhIYQQQggh3JRugxmr1UpsbGyuKeKcSmFiAXeikl05/HiNrgxlIRZcmL0b0aXvFSOSn3aSnRrJT43kp0by006yE86k22AmJSXFNve1KBqV7ILpzF5OsZGDDq6V55C+p0by006yUyP5qZH81Eh+2kl2wpl0mwDAy8uL1q1b290B1lWMGBi35xz/uZD/jY3cldbsalGBgQQxmf86qWaeQc++VxxIftpJdmokPzWSnxrJTzvJTjiTboMZk8nEgAEDMJlMLt92GP3pd/gia747xlDauXz7qrRmN4lerGQHh4l1Us08g559rziQ/LST7NRIfmokPzWSn3aSnXAm3QYzenmbpwjkPjp2r0fPzvcwhMf4itFUoqzeVXOqh7iXdvyHd1mtd1WEEEIIIYRwiBI1mBnNEzzNQ/QijHP+JvZU9ieId7jKTbYxjUG0wasYRuKDNx/Qn9l8RwLX9K6OEEIIIYQQDqHbJ3eLxUJ0dHTBd4K9GnPrXjHPrro1pXIR3UlpnieQp/mQU5y3Lb9OEsNYxIvM5yUe42dC6ExjKlBG03ZcodDZ/c9rPMk1kpjPz06umWcoan7CnuSnnWSnRvJTI/mpkfy0k+yEM+k2m1lqaiphYWEFF3TQdMoXuUFLJpF+m5tE/sYhWvM2Q2nH6zzJv6jGaS6wj1McJ54TJHDif/9e4obmejhCobMD7qcWL/EYHZheYqdizqko+YncJD/tJDs1kp8ayU+N5KedZCecSbcjM97e3nTr1g1vb9eNp243kMmSSjpz+IlHeZt7GMNrfMEBzlCFAPrxCEsYzlE+5Dgfs44JjKIjFXW41qaw2Znw4iMG8BFrOVLCL/rPTo++V5xIftpJdmokPzWSnxrJTzvJTjiTZw1msp9yVq9L5g9knno2ZLfmU9Dycp0kNnGIj/mRV/iMJ3mPhoyjFiN4ktks4lda8y/2MYvFvExNKjhs2wUpbHYj6YgVKx/zk4tq5hnkTVWN5KedZKdG8lMj+amR/LST7IQzeVavyn7K2dE1t34vVxOqNfnff87jTImkcJB/OMg/LGc7NanAa3TlS0bRkRncIMWp2y+su7iTMTxBD94v8IiUEEIIIYQQnqj4Td3lYjFcYAxLOMtlwhmEAYPeVQJgOr1ZxQ72ckrvqgghhBBCCOEUug1mMjIyiIqKIiPDAUcNrsZA7B64GkNqaioRERGkpqaqr7eQLFgZwgL+RQ3G0cXp2ysou3b8h4e4l2l86/S6eCKH9r0SSPLTTrJTI/mpkfzUSH7aSXbCmQx+fn4um+LKz8+P8+czTwPz9/fn5s2bAERERDB06FDbvy4xZHfmvwua2i2eM2cOZrOZ1NRURo0adeu6nKNr7H/Puj4n26lv9anGT7zJCD5lLXsdXuWIiAiAfDPywZso3mEuP/E5mx1eByGEEEIIkcnPz4/ExEQAKlasaPtsK1xHtyMzJpOJgQMHYjKZ9KpCnsxmM0OHDsVsNmcuOLrm1vU52X/P7n/3vzlCLC+ziHkMohn3OK2O+WU3ko5cIZEviHLa9j2du/Y9TyH5aSfZqZH81Eh+aiQ/7SQ74Uy6DWa8vLwIDAzEy8tLryqo+abnraMy5Wra7oHzE3/yNstZxijqUsUpm75ddjWpwGieYDzL5J4y+fD4vqczyU87yU6N5KdG8lMj+Wkn2Qln8qzZzBwpa4pnyDx9rH5XOPK9Q665WcJvVCGA5bzKE8zgHFcdUOGCTedZVrBdLvoXQgghhBAlQskdzOSc5vl/p4+NGpXHaWQazCSSKgTwNa/QldlcJ8kh672d9vyHFtxLCyY6dTtCCCGEEEK4C91OM0tPTycyMpL09HS9quB0Y1lKLJf4nOGYHThuzJmdD97MoA9TWcllEh22neKqJPQ9Z5L8tJPs1Eh+aiQ/NZKfdpKdcCYZzDhRBhYGE4EfPoTzosPuQZMzu1F05DKJfMEWh6y/uCsJfc+ZJD/tJDs1kp8ayU+N5KedZCecSbfBjNlsJjg4+NasYcXUTVJ5jo9pRE3epQ8m1C9+y55dN5oyko68zhdY5aL/Qikpfc9ZJD/tJDs1kp8ayU+N5KedZCecSbfBjNFopGHDhhiNulXBZS5yg6f5kJbUYzNv05Z/K60vK7vu1mZ8xAAG8gn7OO2g2hZ/JanvOYPkp51kp0byUyP5qZH8tJPshDNJr3KRGC7QlndYyK9EMIQvGEkDamheX/XtVman9eEF5rGRgw6sqRBCCCGEEJ5BBjMulIGFT9lIcyZwivP8xJssYTgNuavQ6/BKhUlpPbj/MyuDTQv5jUNOrLEQQgghhBDuS7fBTFpaGkuWLCEtLU2vKjjO1Zhb9615dhUM2Z35721cJpEQvqEZEzjDBX7gDZYygvuple9m7jwGj0018kBGLcb851s2WqId2YoSo1j1PR1IftpJdmokPzWSnxrJTzvJTjiTwc/Pz2VXjfv5+XH+/HkA/P39uXnzJgAREREMHTrU9q9HG7IbqjWB2D2woGmhnlKRsoygAwMI4neO8B7f2934shRmJtCdl3zac/BJK+2XD8UiF/sLIYQQQujKz8+PxMTM22JUrFjR9tlWuI5uR2Z8fHyYNm0aPj4+elXBbZznGm+zgia8wV/E8i3j+IoxNKEOLajLJt7iQe5mw0QLx9pZMfmYJTsF0vfUSH7aSXZqJD81kp8ayU87yU44k26DGYPBQLVq1TAYHHPvleLgIjeYykoa8wYHiGEFr/INr/B/bORJZnOjcmY5yU6N5KdG8tNOslMj+amR/NRIftpJdrkNGTKEQ4cOcfHiRTZt2kSTJk1uW9bb25s33niDAwcOcPHiRbZv30779u3typQuXZrZs2fz119/ceHCBTZs2EDjxo3tyvj7+xMaGsrRo0e5cOECu3fvZtCgQbbH77jjDt5//3327t3LhQsXOHz4MO+99x5ly5Z1bOMdTCYAcEOXuMEMvmXdLNg028R/5nTHgpXU1FRSU1P1rp4QQgghhNCoV69ezJw5k3fffZdWrVpx4MABIiMjqVixYp7lJ0+ezKBBgxg3bhxNmjRh0aJFfPXVV9x///22MuHh4bRp04bBgwfTvHlzNmzYwJo1a6hataqtzMyZM2nfvj2DBg2icePGhIeHExYWRqdOnQCoWrUqVatWZcKECTRr1oyhQ4fSvn175s2b59xAFMlgxo0ZAswMeH2o7SZTo0aNYtSoUTrXSgghhBBCaDVq1CgWL17M0qVLOXz4MKNHjyYpKYn+/fvnWb5Pnz689957rFu3jlOnTrFo0SLWrVvH6NGjAfD19aV79+6EhISwdetWTpw4wYwZMzhx4gQvvfSSbT0PPfQQy5YtIyoqipiYGBYvXsyBAwdo2jTzGu9Dhw7Rt29ffvzxR06ePMlvv/3GlClT6NSpE15e6jd9dxZvvTZsNBqZO3cuRqPRdtjRYDDg6+trK5Oenk56ejpms9nuRktpaWlkZGTg4+Njd8gyNTUVi8Vit478licnJ2M0GnPdkTav5VarlZSUFLy8vDCZTLblFouF1NRUvL298fb2JsVoyLw0/3/1MplMdh2goDaFh4djMplIS0sjPT2diIgIUlNT7epuNBr54IMPci13VpuyZGRkkJaWVuQ2udt+yt73srL29Da5cj+lp6cTFhaG0Wi0e8yT2yR9zzP2k/Q9tTZl9T+rNXMCmeLQpiyu2E+pqam212/W457eJul76vspe5kyZcrYtSslJSXXGTUmk4kHH3yQ999/326bGzdupHnz5uTFbDaTnJycq+4tW7YEuPUZNCXFrkxSUpKtDMD27dvp3Lkzn3/+OXFxcbRu3Zq6desyfvz4PLcLULZsWa5du0ZGRsZty+hNt8FMWFgY6enpALZz8cqXL293KCsyMpLIyEhGjhxJw4YNbcuXLFnC5s2bmTRpEtWqVbNbZ3R0NKGhoZQqVcq2PCQkhEuXLuU6TDZ8+HDKly/PtGnTbMuSkpIYMWIEDRo0IDg42LY8NjaWkJAQWrVqxYABA2zLo6OjCQsLo3PnznTr1o0pcTU5nQZ3li/PRaBfv34EBgYWuk01a9aka9eu/PTTT8TGxtraFB4enqtNZrPZJW3KEhUVxeLFi4vcJnfcT9ImtTYdO3as2LWpOO6n4tgm6XvSJj3bNHLkyGLXpuK4n1zZph07dth+P3HihN12p0+fzowZM+yW3XnnnXh7e5OQkGC3PCEhgXr16pGXDRs2MGrUKNtRlzZt2vDkk0/aBk43btxg+/btjB8/nsOHD5OQkMAzzzxDixYtOH78uG09Y8eOZe7cuRw7doy0tDQsFgsjR45k69ateW73zjvv5I033mDx4sV5Pu4udJuauXr16oSEhDBhwgRmz57NkCFDWLBgge2QGXjmSD1lwFasVRpD3B8Q0aRQ3z6EhoZitVoZOXKk3ZGZsWPH5ll3X19fpk+fztixY3NlLN8SFdym0qVLM2PGDCZMmEBiYmKxaJMr95PBYOD9999n4sSJdt8UeXKbpO95xn6SvqfWJl9fX2bMmMH48eO5fv16sWhTFlfsJ7PZTFhYGBMmTLD1P09vk/Q99f3k4+PDlStXAKhTp47d1Mx5HZmpUqUKx48fp02bNuzcudO2fNq0aTzyyCMEBQWRU4UKFZg7dy6dOnXCarVy4sQJNm7cSP/+/alQoQIAd999N5988gmBgYGkp6ezb98+jh07xgMPPGCbXGDMmDEMGDCACRMmcObMGVq1asWUKVPo06cPGzdutNtmmTJl+P7777l8+TJPP/207QCEO9LtyExycjK+vr4kJyfbDjtardZch9GA2170nvNwWvZ1F3a5xWIp0vKMjIw8D7VlvRCx/G9s+L82paWl5XmTqOxtyv6iGDFiRKHqnvVNhEvalENh2pSdu+2n7H0vqx2e3iZX7idfX19KlSpFcnJyrsc8tU35LZe+5z77Sfpe/ssL0yZfX1/pe9kUtU1Zr9/sj3t6m6Tvqe2n7IOv69evF3ifmYsXL5Kenk6lSpXslleqVIn4+Pg8n3PhwgV69+6Nj48P5cuXJy4ujqlTp3Ly5ElbmZMnT9KxY0f8/PwoW7Ys586d47PPPuPUqVNAZv5vv/02vXv3Zt26dUDm0aZGjRoxZswYu8FM6dKlWb16NTdu3KB3795uPZABmQDA8a7GZN4w82oMAF26dKFLly65fqdel8wfbp2LK4QQQgghiq+0tDT27t1rdwTGYDAQFBRkd6QmLykpKcTFxeHt7U23bt344YcfcpW5efMm586dIyAggHbt2rFmzRog81ods9lsO4CQJSMjw25AVqZMGb777jtSU1N5+umnbzuQdCe6HZkptr7pafffrE6U83eO3vpdZigTQgghhCgZ5syZw4IFC9i7dy+7d+9mxIgR+Pn5sXTpUgAWLlxIbGwskydPBqBp06ZUq1aN/fv3U61aNSZOnGibDCpLu3btMBgMHD16lHvuuYfp06dz9OhR2zqvX7/O5s2bmT59OklJScTExBAYGMhzzz3HG2+8AdwayPj5+TFo0CDKli1ru679/PnzWCwWV8ZUeH5+flZX/VSoUMGapXTp0tZq1apZjUajNSIiwgrY/pWf/H+MRqMtO73r4ok/kp/kJ9l55o/kJ/lJfp75U5yz8/Pzs322rVChQqE/E7/66qvW06dPW5OTk607d+60tm7d2vbYb7/9Zl26dKnt/x06dLAeOnTImpSUZD1//rx12bJl1jp16titr1+/ftbjx49bk5OTrXFxcdZPPvnEWqVKFbsyd999t/Xzzz+3nj171nrz5k3r4cOHrePHj7c9/vjjj1tv57777nPZeKGoP7pNAODv7287TzEiIoKhQ4fa/hUFyzpvV2gj+amR/LST7NRIfmokPzWSn3bFNTs/Pz8SExMBqFixYoHXzAjH0+2aGV9fX+bNm5drxglRMMlOjeSnRvLTTrJTI/mpkfzUSH7aSXbCmWQCACGEEEIIIYRHksGMEEIIIYQQwiPJYEYIIYQQQgjhkWQCAA9VXC+kcxXJT43kp51kp0byUyP5qZH8tCuu2ckEAPrT7ciM0WikfPnydjfqEYUj2amR/NRIftpJdmokPzWSnxrJTzvJTjiTbr3KbDYzbdo0zGazXlXwWJKdGslPjeSnnWSnRvJTI/mpkfy0k+yEM8kQWQghhBBCCOGRZDAjhBBCCCGE8Ei6DmaSkpL03LxHk+zUSH5qJD/tJDs1kp8ayU+N5KedZCecRdfZzLJmfJDZzIQQQgghhKeR2cz0p+tsZg0bNpSZLTSQ7NRIfmokP+0kOzWSnxrJT43kp51kJ5xJt14VGhpKREQEZrOZ1NRUIiIiSE1N1as6HsVsNhMcHCyzgmgk+amR/LST7NRIfmokPzWSn3aSnXAmb702bDKZuH79OgCjRo3SqxpCCCGEEEIIDyXH+4QQQgghhBAeSdfBTFpaGlary+YfKDasViuxsbGSnUaSnxrJTzvJTo3kp0byUyP5aSfZCWfSbTazTz/9lPT0dJm9TAghhBBCeCSZzUx/uh2ZMRgMlC5dGi8vL72q4LG8vLxo3bq1ZKeR5KdG8tNOslMj+amR/NRIftpJdsKZdD3N7M4778RkMulZBY9kMpkYMGCAZKeR5KdG8tNOslMj+amR/NRIftpJdsKZZAIAIYQQQgghhEeSwYwQQgghhBDCI+k6mElKSsJisehZBY9ksViIjo6W7DSS/NRIftpJdmokPzWSnxrJTzvJTjiTzGYmhBBCCCGEBjKbmf50nc0sICAAb29vvargsby9venWrZtkp5Hkp0by006yUyP5qZH81Eh+2kl2wpl0Pc2sXLly0rE1kDcFNZKfGslPO8lOjeSnRvJTI/lpJ9kJZ5IJAIQQQgghhBAeSQYzQgghhBBCCI+k62Dmxo0bZGRk6FkFj5SRkUFUVJRkp5Hkp0by006yUyP5qZH81Eh+2kl2wpl0m81s/vz51KhRg65du7pq80IIIYQQQjiMzGamP92OzLzxxhuUKVMGk8mkVxU8lslkYuDAgZKdRpKfGslPO8lOjeSnRvJTI/lpJ9kJZ9JtMOPl5UVaWhpeXl56VcFjeXl5ERgYKNlpJPmpkfy0k+zUSH5qJD81kp92kp1wJt3myLvzzjs5f/48FSpUIDk5Wa9qeCRfX198fX0lO40kPzWSn3aSnRrJT43kp0by0644Z+fn56d3FUo8l14zU69ePfbu3euqzQkhhBBCCOESDz74IEePHtW7GiWOTM0shBBCCCGE8EguPc3sn3/+sf1euXJlypQpQ3x8PBaLxZXV8HhGo5HKlStLdhpJfmokP+0kOzWSnxrJT43kp11xzi77TL3ZP+cK19HtmpkbN25w7dq1YnfupKukp6dLdgokPzWSn3aSnRrJT43kp0by006yE86i22lmvr6+zJs3D19fX72q4LEkOzWSnxrJTzvJTo3kp0byUyP5aSfZCWeSa2aEEEIIIYQQHkkGM0IIIYQQQgiPJIMZIYQQQgghhEdy6X1mss/44O/vj8VikYvBNPL19ZXsFEh+aiQ/7SQ7NZKfGslPjeSnXXHNzs/Pj8TERAAqVqzIzZs3da5RyaPbkRmj0Uj58uUxGuXgUFFJdmokPzWSn3aSnRrJT43kp0by006yE86kW68ym81MmzYNs9msVxU8lmSnRvJTI/lpJ9mpkfzUSH5qJD/tJDvhTDJEFkIIIYQQQngkGcwIIYQQQgghPJKug5mkpCQ9N+/RJDs1kp8ayU87yU6N5KdG8lMj+Wkn2Qln0XU2M5nxQQghhBCieOsxbCZ+pQMAuHnjCt/Of0PfCjmQzGamP11nM2vYsKHMbKGBZKdG8lMj+Wkn2amR/NRIfmokP+38ygRQqWJ5KlUsbxvUCOEous5mFhwcLDNbaCDZqZH81Eh+2kl2aiQ/NZKfGslPCPckXy8IIYQQQgghPJIMZoQQQgghhBAeSbfBjNVqJTY2FqvVZfMPFBuSnRrJT43kp51kp0byUyP5qZH8hHBPMpuZEEIIIYRwmr7j5lOpYnkAEs5fYtn7w3SukePIbGb60+3IjJeXF61bt8bLy0uvKngsyU6N5KdG8tNOslMj+amR/NRIfgoMeldAFGe6DWZMJhMDBgzAZDLpVQWPJdmpkfzUSH7aSXZqJD81kp8ayU8I9yQTAAghhBBCCCE8kgxmhBBCCCGEEB5Jt8GMxWIhOjoai8WiVxU8lmSnRvJTI/lpJ9mpkfzUSH5qJD8h3JPMZiaEEEIIIZxGZjMTzqTbkRlvb2+6deuGt7e3XlXwWJKdGslPjeSnnWSnRvJTI/mpkfwUyGxmwolkMOOBJDs1kp8ayU87yU6N5KdG8lMj+QnhnmQCACGEEEIIIYRHksGMEEIIIYQQLjJ48GB27NhBXFwccXFx/Prrr3To0MH2uI+PD2FhYcTExBAfH8+yZcuoVKmS3Tpq1KjBypUrOX/+PKdOnWL69Om5bugaGBjI1q1buXTpEvv376dfv3656jJkyBAOHTrExYsX2bRpE02aNLF7vDB10Ztug5mMjAyioqLIyMjQqwoeS7JTI/mpkfy0k+zUSH5qJD81kp9wlLNnz/LWW2/xyCOPEBgYyG+//cY333zDv/71LwBmzZpFp06deP7553n88cepWrUqX375pe35RqORVatWYTabeeyxxxgyZAh9+/Zl0qRJtjK1atVi5cqVbN68mZYtWxIeHk54eDjt2rWzlenVqxczZ87k3XffpVWrVhw4cIDIyEgqVqxoK1NQXdyBzGYmhBBCCCGcRmYzK9iZM2eYOHEiq1ev5vTp0wwcOJDVq1cDUK9ePfbu3UtQUBC7du2iQ4cOrFixgrp165KQkADAoEGDmDp1KrVq1SItLY2pU6fSsWNHmjVrZtvGkiVLCAgIoHv37gBs2rSJPXv2MHbsWAAMBgNHjx5l/vz5hIaGUrZs2QLr4g50u4qtTJky9O3bl6+//prk5GTS0tIwmUx2h8jS09NJT0/HbDZjNN46iJSWlkZGRgY+Pj4YDLemyEhNTcViseDr62u3rdstT05Oxmg0YjabC1xutVpJSUnBy8sLk8lkW26xWEhNTcXb29vuosCMjAyntclkMvHUU0/xxRdf5Dqk6Kltym+5o9tUqlQpevfuLX1PY5usVivPPfccK1asIC0trVi0SfqeZ+wn6XtqbTKZTPTu3Ztly5Zx8+bNYtGmLK7YT15eXgwYMICvv/7a1v88vU2u2k+GHLOZFYc2ZW9LljJlyti1KyUlhdTUVPJjNBrp2bMn/v7+7Ny5kwcffBCz2czGjRttZY4ePUpMTAwtWrRg165dNG/enIMHD9oGMgC//PILH3/8MQ0aNODPP/+kefPmdusA2LBhA7NmzbLV+8EHH+T999+3a/vGjRtp3rw5QKHq4g50G8y89957lC5dmpYtWxIVFcXixYvp168fgYGBtjKRkZFERkYycuRIGjZsaFu+ZMkSNm/ezKRJk6hWrZpteVhYGNHR0YSGhlKqVCnb8pCQEC5dusS8efPs6jB8+HDKly/PtGnTbMuSkpIYMWIEDRo0IDg42LY8NjaWkJAQWrVqxYABA2zLo6OjCQsLo3PnznTr1s223NltMhqNfPvtt4SFhRWbNrlyPwUEBEjf09imqVOnEhgYaLduT2+T9D3P2E/S99TbFBAQgNVqZdGiRcWmTeCa/XTz5k2eeOIJWrZsWWza5Kr9tOWE/WimOLQpy44dO2y/nzhxwm6706dPZ8aMGeTl3//+N7/++iu+vr7cuHGDPn36cPjwYRo1akRKSgpXr161K5+QkEDlypUBqFy5st1AJuvxrMfyK1OuXDl8fX0JCAjA29s7zzL16tWzraOgurgD3U4zq169OtOmTSM4OJjExMRi8+1DFmd+o+Lr60tYWBjDhw/PlbGntim/5Y5uU+nSpQkLC5O+p7FNBoOB8PBwgoODSU5OLhZtkr7nGftJ+p5am7L+dowZM4br168XizZlccV+MpvNzJs3z67/eXqbXLWfnhr1IRUr3DrN7L8fjfL4NmXx8fHhypUrANSpU8fuNLP8jsyYTCbuuusuypYtS48ePXjhhRfo2LEjjRo1Yv78+ZQvX96u/G+//WYb2M2ZM4eaNWvaDapKlSrFhQsX6NGjB+vXr2ffvn188cUXdkdeHn/8cVatWsWdd95JQEAAx48fp02bNuzcudNWZtq0aTzyyCMEBQXxzDPPFFgXd6DbkZnsbwRZh2vT0tLsTh3IcruOkJKSku+6C7PcYrEUaXlGRkaeF/9lvRBzkja5X5uk76m1KeuPRHJycq7HPLVN+S2Xvuc++0n6Xv7LC9sm6Xu3FLVNWY9lf9zT2+SK/ZTzW/Pi0KYs2Qdf169fL/Q1M2lpabYjOfv27aNJkyYMHz6clStX4uPjQ7ly5eyOiFSqVIn4+HgA4uPjadq0qd36smYYy14m56xjlSpV4urVqyQnJ3Px4kXS09PzLJN9HQXVxR3oNptZeno6kZGReb5wRf4kOzWSnxrJTzvJTo3kp0byUyP5CWcyGo34+Piwd+9eUlNTCQoKsj127733UrNmTdspbTt37uTf//633axjbdu25erVq/z111+2MtnXkVUm6yhMWlqa7UL+LAaDgaCgIFuZwtTFHchsZkIIIYQQwmlkNjN7U6ZMYf369Zw5c4YyZcrwzDPPEBwcTLdu3fj111/58MMPefzxxxk6dCjXrl0jNDQUgMceewzIHPhs376duLg4QkJCqFy5MosWLWLJkiW8/fbbQObUzLt27WLBggV8/vnnPProo7z//vv06tWLX375BcicmnnBggWMHj2a3bt3M2LECHr27Enjxo1t19IUVBd3oNuRGbPZTHBwcK7zF0XBJDs1kp8ayU87yU6N5KdG8lMj+SkwFFykJKlYsSILFy5k3759/PDDDzRp0sQ2kAEYP348P/74I8uWLWP9+vXEx8fz3HPP2Z5vsVjo1asXGRkZ/PrrryxatIgvv/ySqVOn2sqcPn2aXr160bZtW7Zv387o0aMZMWKEbSADsHLlSiZMmEBISAjbtm2jUaNGdO/e3W5SgILq4g50u2bGaDTSsGFDu3MNReFIdmokPzWSn3aSnRrJT43kp0byE46S1wRO2aWkpBAcHGw3y1pOZ86coWfPnvmuJyoqiocffjjfMhEREURERCjVpbAaN25Mnz59qF+/PqVKlaJLly706tULgO+++44bN25oWq9ugxkhhBBCCCFE8TdlyhReffVVIPPanKxZ48aMGcO//vUvDAYDy5Yt07Ru+XpBCCGEEEII4RTPPvsswcHBGAwGuym2AX744QcMBoPdNNNFpdtgJi0tjSVLluQ5NZ/In2SnRvJTI/lpJ9mpkfzUSH5qJD8htBk2LHPChyNHjthd15O1DOC+++7TvH7dTjPLyMhg8+bNem3eo0l2aiQ/NZKfdpKdGslPjeSnRvJT4LJ5c4U7atCgAVarlSlTpthmNc5y7tw5AKpUqaJ5/bodmfHx8WHatGn4+PjoVQWPJdmpkfzUSH7aSXZqJD81kp8ayU+BzGYmIM+bkFavXh1A6YinboMZg8FAtWrVcp07Jwom2amR/NRIftpJdmokPzWSnxrJTwhtjh49CkBwcDCVK1e2Lb/rrrt49dVXsVqtttPNtJAJAIQQQgghhBBO8d///heDwUDz5s1ZunQpVmvmeYcHDx6kfv36AHz99dea1y+DGSGEEEIIIYRTzJs3j99++y3XbGZZ/9+0aRMLFy7UvH6Dn5+fyy7L8vPzs134U6ZMGWrXrs2hQ4ewWCyuqkKxYDQaadCggWSnkeSnRvLTTrJTI/mpkfzUSH7a9X1tPpUqlAcg4fwllr0/TOcaOY6fnx+JiYkAVKxYkZs3b+pcI/fk5eXFyJEjefbZZ6lbty4Ax44d45tvviE8PJz09HTN69ZtMOPv7y87XAghhBCimOs7bj6VKspgRjiHbqeZ+fr6Eh4ejq+vr15V8FiSnRrJT43kp51kp0byUyP5qZH8FMicCcKJdLvPDECpUqX03LxHk+zUSH5qJD/tJDs1kp8ayU+N5CeENo8++igvvvgi99xzD+XKlcs1K6DVauU///mPpnXrOpgRQgghhBBCFF/Dhg1j9uzZt33cYDDYZjjTQgYzQgghhBBCCKcYM2aMU+/PpOtsZmXLluXcuXMyK0gRGY1GqlSpItlpJPmpkfy0k+zUSH5qJD81kp92MptZyXb+/Hl8fHxYuHAh06dP59KlSw5dv24TAFgsFi5duiRvCBpIdmokPzWSn3aSnRrJT43kp0byU+Cyr82FO9q1axcAGzZscPhABnSezWzevHkyK4gGkp0ayU+N5KedZKdG8lMj+amR/BTIbGYl2uuvv87Vq1eZMmUKjzzyCP7+/g5dv1wzI4QQQgghhHCK6Ohovv76a4YNG8batWvzLGO1WilXrpym9ctgRgghhBBCCOEUb775JkOHDsVqtTplIgAZzAghhBBCCCGcYvDgwbZBzI0bN7hy5YpDrz3TbTYzf39/LBYLycnJrtp8seLr6yvZKZD81Eh+2kl2aiQ/NZKfGslPm77j5lOposxmVlLFxcXh7+/P22+/TVhYmMPXr9sEAEajkfLly2M06lYFjyXZqZH81Eh+2kl2aiQ/NZKfGslPgUwAUKJlXSdz8uRJp6xft1ek2Wxm2rRpmM1mvargsSQ7NZKfGslPO8lOjeSnRvJTI/kJoc2cOXM4efIk77//Pv379+ff//43NWrUyPWjlVwzI4QQQgghhHCKzZs3A2AwGJg7d26eZWQ2MyGEEEIIIYTbMRgMWK1W2++OpuuJn0lJSXpu3qNJdmokPzWSn3aSnRrJT43kp0byE44wbtw4Nm/ezLlz5zh16hRff/019957r10ZHx8fwsLCiImJIT4+nmXLllGpUiW7MjVq1GDlypWcP3+eU6dOMX36dLy8vOzKBAYGsnXrVi5dusT+/fvp169frvoMGTKEQ4cOcfHiRTZt2kSTJk2KXJf8bNmyhS1bthAVFXXbny1bthR6fTnpOpuZzPgghBBCCFG8yWxm9lavXs2KFSvYs2cP3t7evP322zRo0IAmTZrYnv/hhx/SsWNHhg4dytWrVwkLC8NisdCuXTsgc0KK7du3Ex8fz8SJE6lSpQoLFixgyZIlvP322wDUqlWLXbt28X//938sWbKEoKAgZs+eTa9evfjll18A6NWrFwsXLmTMmDHs2rWLESNG0KNHDx588EHbZ/aC6qI33QYzZcqUoXbt2hw6dMihc02XBEajkQYNGkh2Gkl+aiQ/7SQ7NZKfGslPjeSnXd/X5lOpggxmbqdChQqcPn2aDh06sHXrVsqWLcvp06cZOHAgq1evBqBevXrs3buXoKAgdu3aRYcOHVixYgV169YlISEBgEGDBjF16lRq1apFWloaU6dOpWPHjjRr1sy2rSVLlhAQEED37t0B2LRpE3v27GHs2LFA5mlgR48eZf78+YSGhhaqLnrT7ZqZsmXLEhwcTHBwMImJiaSlpWEymewOj6Wnp5Oeno7ZbLabCjEtLY2MjAx8fHzszr1LTU3FYrHg6+trt63bLU9OTsZoNOaamSSv5VarlZSUFLy8vDCZTLblFouF1NRUvL298fa+FWdGRobT2uTr60twcDDDhw/Plauntim/5Y5uU+nSpaXvKbTJYDDY8st+vwVPbpP0Pc/YT9L31NqU9bdjzJgxXL9+vVi0KYsr9pPZbM7V/zy9Ta7aTzmvkigObcrelixlypSxa1dKSgqpqakUpGzZsgBcvnwZgAcffBCz2czGjRttZY4ePUpMTAwtWrRg165dNG/enIMHD9oGMgC//PILH3/8MQ0aNODPP/+kefPmdusA2LBhA7NmzbLV/cEHH+T999+3a//GjRtp3rx5oetSkDfeeKPAMgAzZ84sVLmcdBvMzJw5k9KlSxMWFkZUVBSLFy+mX79+BAYG2spERkYSGRnJyJEjadiwoW35kiVL2Lx5M5MmTaJatWq25WFhYURHRxMaGkqpUqVsy0NCQrh06RLz5s2zq8Pw4cMpX74806ZNsy1LSkpixIgRNGjQgODgYNvy2NhYQkJCaNWqFQMGDLAtj46OJiwsjM6dO9OtWzfbcme3yWg04uvrm+vmQ57cJlfup4CAAOl7Gts0depU2+PFpU3S9zxjP0nfU29TQEAAzz77LIsWLSo2bQLX7KebN2/aXr/FpU2u2k9bTtgPZ4pDm7Ls2LHD9vuJEyfstjt9+nRmzJhBfgwGA7Nnz+b333/n0KFDAFSuXJmUlBSuXr1qVzYhIYHKlSvbymQfyGQ9nvVYfmXKlSuHr68vAQEBeHt751mmXr16ha5LQSZOnGibACA/Wgczup1mVr16daZNmybfUGpoU9YgRo7MaP92PCwsTPqexjYZDAbCw8Pl23Hpe9L3PGw/Zf3tkCMz2o/MzJs3T47MaGjTU6M+pGK208z++9Eoj29TFh8fH65cuQJAnTp17E4zK8yRmQ8//JAOHTrQrl07YmNjAXjmmWeYP38+5cuXtyv722+/2QZ3c+bMoWbNmnYDq1KlSnHhwgV69OjB+vXr2bdvH1988YXdkZfHH3+cVatWceeddxIQEMDx48dp06YNO3futJWZNm0ajzzyCEFBQYWqS0GuX79+28esVqtttrOsI1RFpduRmaSkJGJjY0lKSqLLoKn4lQ7g5o0rfDs/96Go23WElJSUPJdn/yNX0HKLxVKk5RkZGWRkZORanvVCzCktLY20tLRcy1XaZLVaiY2Ntb3gClt3d25TQcsd2absfS+rHZ7eJlfuJx8fH1t+OZ/jqW3Kb7n0PffZT9L38l9eUJuy/nZk1bk4tCknZ7YpK7+c/c+T23S75Q7vezmWF4c2Zck++Lp+/XqRrpkJDQ3liSeeoEOHDraBDEB8fDw+Pj6UK1fO7ohIpUqViI+Pt5Vp2rSp3fqyZhjLXibnrGOVKlXi6tWrJCcnc/HiRdLT0/Msk30dBdWlIMOG5b5G6s4776R9+/YEBQVx+PBhPvjgg0KtKy+6DWZSUlIICQkBwK90AJUqliehgOeITNmzE0Un+amR/LST7NRIfmokPzWSnwKXnQPkOUJDQ3nyySfp2LEjp0+ftnts7969pKamEhQURGRkJAD33nsvNWvWtJ3WtnPnTl5//XUqVqxoO+upbdu2XL16lb/++stW5vHHH7dbd9u2bW1HYdLS0mwX8q9ZswbIPAIeFBREREREoetSkGXLluW5/OOPP+bTTz/lqaeeynU0rSh0u8+Ml5cXrVu3zjUftiiYZKdG8lMj+Wkn2amR/NRIfmokPwWOv0+iR/vggw/o3bs3AwcO5MaNG1SuXJnKlSvbPtBfu3aNzz77jJkzZ9K6dWseeOAB5s+fz/bt220X3P/yyy8cPnyYRYsW8Z///Id27doxefJkFixYYDvCtWjRImrXrs20adOoV68eL730Ej179mTu3Lm2usyZM4eBAwfSt29f6tevz0cffYSfnx9Lly4tdF1UbNu2DYPBwKhRozSvQ7cjMyaTiQEDBtidoycKJ3t2eR0CFfmT/NRIftpJdmokPzWSnxrJTzjKkCFDAFi3bp3d8qFDh/LFF18AMH78eCwWC8uWLcPHx4dffvmFV1991VbWYrHQq1cvPvroI3799VcSExP58ssvbROlAJw+fZpevXoxa9Yshg8fztmzZxkxYoTtHjMAK1eupEKFCoSEhFC5cmX2799P9+7d7SYFKKguBWnVqlWuZV5eXlSuXJnRo0cDcNdddxV6fTnpNpgRQgghhBCipPH39y+wTEpKim0q8Ns5c+YMPXv2zHc9UVFRPPzww/mWiYiIsJ1WprUu+fnpp5/ync3MarVy9OhRTesGGcwIIYQQQgghnCj7bHQ53bhxo9D3osmLboMZi8VCdHS03EVXA8lOjeSnRvLTTrJTI/mpkfzUSH5CaJPXBABWq5Vr165x/Phxli9fbrthqBa63WfG39/fNn1d33HzM2czO3+JZe/nnr5NCCGEEEJ4pqzPeUCx+6zn5+dHYmIiABUrVizS1MzCMXSbzczb25tu3brZ3XhIFI5kp0byUyP5aSfZqZH81Eh+aiQ/BTKbmXAi3V6RWW8KOWdyEAXLnl1eN9gS+ZP81Eh+2kl2aiQ/NZKfGslPiMJZu3ZtkZ9jtVrp3Lmzpu3J1wtCCCGEEEIIhwgMDMx39rKcDAZDkcrnJIMZIYQQQgghhMPkN3uZo+k2mMnIyCAqKkpuPKWBZKdG8lMj+Wkn2amR/NRIfmokPyEKp0GDBi7dnsxmJoQQQgghnEZmMxPOpNtsZiaTiYEDB2IymfSqgseS7NRIfmokP+0kOzWSnxrJT43kp0BmMxNA48aNmTlzJitWrGDFihXMnDmTxo0bK69Xt8GMl5cXgYGBeHl56VUFjyXZqZH81Eh+2kl2aiQ/NZKfGslPCO2mTJnCpk2bGD58OB06dKBDhw4MHz6cTZs2MXnyZKV16zaYEUIIIYQQQhRv3bt3Jzg4GMicGCDnz9ixY+nWrZvm9ctsZkIIIYQQQginGDJkCAApKSksWLCA3bt3Y7VaadasGS+99BKlSpVi6NChREZGalq/boOZ9PR0IiMj5cZTGkh2aiQ/NZKfdpJdwXoMm4lf6QAAbt64wrfz37A9JvmpkfzUSH5CaNOoUSOsViuTJ09m3rx5tuWrV6/m7NmzzJo1i0aNGmlev+6DGVF0kp0ayU+N5KedZFcwv9IBt2Y9yvGY5KdG8lMj+Slw2by5wh2VKlUKgOPHj+d6LGtZVhktdLtmxmw2ExwcjNls1qsKHkuyUyP5qZH8tJPs1Eh+aiQ/NZKfApnNrEQ7e/YsAKNGjSIgIMC2PCAggFGjRtmV0UK3IzNGo5GGDRtiNMocBEUl2amR/NRIftqpZpffKVglgfQ9NZKfGslPCG3WrVvHsGHDaN26NX///TcnT54E4O6778bHxwer1cq6des0r19ekUII4SGyTsGqVLG8bVAjhBBCuLP33nuPhIQEDAYDvr6+3Hfffdx33334+vpiMBiIj4/nvffe07x+GcwIIYQQQgghHObjjz8mMDAQgISEBNq0acMvv/yC1Wq1TclstVr5+eefadeuHQkJOa+SLDzdTjNLS0tjyZIlpKWl6VUFjyXZqZH81Eh+2kl2aiQ/NZKfGslPiMIbOHAgAwYMICEhgVWrVrF8+XJ69OhBQEAA99xzDwAnTpzg8uXLytvSbTCTkZHB5s2b9dq8R3NWdiXlfHzpe2okP+0kOzWSnxrJT43kp0BmMyuxKlWqxLBhwxg2bBgxMTGsWLGClStXcuDAAYdtQ7fTzHx8fJg2bRo+Pj56VcFjOSu7knI+vvQ9NZKfdpKdGslPjeSnRvJTILOZlThhYWGcPHnSdkqZwWCgZs2aBAcHs3XrVnbv3s0bb7xB3bp1lbel22DGYDBQrVo1DAbp4UUl2amR/NRIftpJdmokPzWSnxrJT4jCmzx5Mvfffz+PPPIIoaGhnDhxwm5gU69ePSZMmMAff/zB1q1beeWVVzRvSyYAEEIIIYQQQjjcn3/+ydtvv20b2HzwwQe5jtg0atSId955R/M2ZDAjhBBCCCGEcKo///yTt956i0aNGtGjRw/++ecfrFb1C6p0G8ykpqYSFhZGamqqXlXwWJKdGslPjeSnnWSnRvJTI/mpkfyEo7Rq1Yrly5dz7NgxEhMT6dKlS64yISEhHD9+nAsXLrBmzRrbDGBZ7rjjDj799FPi4uI4e/Ys8+bNw9/f365Mw4YNWb9+PRcvXuTIkSO8+uqrubbTo0cP/vjjDy5evMjOnTt5/PHHi1yXwrrjjjt44YUX+O6771i+fDnVq1fXtJ6cdBvMWCwWoqOjsVgselXBY0l2aiQ/NZKfdpKdGslPjeSnRvJT4MDZzHoMm0nfcfPpO24+PYbNdNyKXcjf358DBw7kObgACA4O5uWXX2b06NEEBQWRmJhIZGSk3eQTn376Kf/617/o2rUrTz31FK1atWLu3Lm2x8uUKcN3333HmTNneOSRR5g4cSITJkxg4MCBtjItWrRgyZIlfP755zz88MN8SfV22AAAHedJREFU//33fP311zRo0KBIdclPuXLl6N+/P6tXr+b48ePMmTOHoKAgvL29baeZXbx4kU8//bSoMdroNpjx9fUlPDwcX19fvargsSQ7NZKfGslPO8lOjeSnRvJTI/kpcOCcCcVh5tX169fzzjvv8P333+f5+IgRI5g9ezY//PAD0dHRvPTSS1StWpWuXbsCUL9+fTp06MDw4cPZvXs327ZtY9y4cTz11FNUqVIFgGeffRaTycSwYcP466+/WLFiBZ988gmjRo2ybWf48OH8/PPPfPjhhxw5coSpU6eyb98+hg4dWui63E6/fv1YtWoVJ0+eZO7cubRt2xaTyWQbwFy/fp2vvvqKXr16cc8993juBAClSpXSc/MeTbJTI/mpkfy0k+zUSH5qJD81kp9wttq1a1OlShU2btxoW3bt2jV27dpFixYtgMwjKpcvX2bv3r22Mr/++isWi4VmzZrZymzdutXuJq+//PIL9evXJyAgwFYm+3ayymRtpzB1uZ1PPvmEdu3a2Q1gkpOTWb16Nf369ePuu+9myJAhrF+/noyMDA1J3aLbTTOzvtnw9fW9NWI3YPeNR3p6Ounp6ZjNZozGW+OutLQ0MjIy8PHxsZsiMTU1FYvFkutbk9stT05Oxmg0YjabC1xutVpJSUnBy8sLk8lkW26xWEhNTcXb2xtv71txZmRkkJaWhslkwsvLy6Ftut3vym3K8c2JK9uU33JH76fsfa+4tMmV+ymrTHFqk6f0PTv/e7/Uu00O30/Z34dy/E2QvqfWpqxtmEwmkpOTi0WbsrhiP2XJ/pint8lV+ynngRlnvUfo0feylylTpoxdu1JSUop8jVXlypUBSEhIsFuekJBApUqVgMwbUZ4/f97u8YyMDC5fvmx7fuXKlTl16lSudWQ9duXKFSpXrpzndrKvo6C65MdgMJCens6vv/7K8uXL+f7770lMTCzweUWl22Bm5syZlC5dmrCwMH77O/P8U29vb+bNm2crExkZSWRkJCNHjqRhw4a25UuWLGHz5s1MmjSJatWq2ZaHhYURHR1NaGio3bcnISEhXLp0yW7dkHl4rXz58kybNs22LCkpiREjRtCgQQOCg4Nty2NjYwkJCaFVq1YMGDDAtjw6OpqwsDA6d+5Mt27dbMujoqJYvHgx/fr1IzAw0OFtMhqN+Pr6EhYW5rA2bTlh/3bj6ja5cj8FBAQQFhZWrNqUpaA29Rv7MXj5YPaC5rWsRW7T1KlTbY+7S5s8aT+p9L3sfHx8mDdvnlu0KYsj9lP29yEfs49d/aXvqbcpICCAZ599lkWLFhWbNoFr9tPNmzdtr9/btWnnaQOp6XD5Yjx/b/nC7dvkqv2U8/OFs94j9Oh7O3bssP1+4sQJu+1Onz6dGTNmUBJFRUWxfPlyVq9ezeXLl526LYOfn58DL8vKn5+fn20kWbFiRcqUKUN8fDw9RoRRqUJ5Ei5cYuWcV2zlPfHbhyzO/EbFaDRyxx13EBcXV6i6F7ZNvUZ9SKUK5QFIOH+Jbz4cWSy/JTKbzVSuXJn4+HjS0tKKRZuKsp/6vjbf7vVW1Dalp6dTqVIlrly5YnchrKe+nvJb7m59r/er4VSq+L/X6P/2n95tcvR+snsfyuNvgvQ97W0yGo1UrlyZ2NhYUlJSlNrU+cUp+PqX4+b1K/y45G3d2pTFVUdmatWqRXx8vK3/5ax7Vv9NOH+Jr8KGu32bXLWfcn6++O9Ho5zyHqFH3/Px8eHKlSsA1KlTh5s3b9oeK8yRmcTERJ599lnWrFkDZJ7adfDgQVq2bMn+/ftt5X766ScOHDjAa6+9Rv/+/ZkxYwY1atSwPe7l5cWlS5fo168f33//PQsXLqRMmTL07t3bVqZ169b8+OOPVK9enStXrnD48GHmzJlDeHi4rczEiRPp2rUrDz30UKHq4g50OzJz8+ZNbty4QXJy8q1ZLqyZHSun23WElJSUPJfntY7bLbdYLEVanpGRkee5fVkvxJyyPrDkpNomi8VS5LoX2KYcw1pXtym/5Y7eT3FxcXbPKw5tyul2bbrd660obbp06ZJbtcmT9pNq37PJsf88oe8Vaj9lfx/K42+C9D21NsXFxdnqptImX79ymR/ab/N325Vtys7Z+ynn6zdX3a23WZ6Nu7XJJfspx+cLZ75HgGv7XvbB1/Xr1+0GM1qcOnWKc+fOERQUZBtAlClThmbNmrFo0SIg82jQHXfcwQMPPMC+ffsACAoKwmg0smvXLluZyZMn4+3tbatv27ZtOXLkiG3wtWPHDoKCguwGM23btrUdbSpMXdyBrrOZzZs3T2YF0UCyUyP5qZH8tHNkdt4ms8dPT1pU0vfUSH5qJD8F2c4yK4nvXTn5+/vTqFEjGjVqBGQejWnUqJHtSEt4eDivv/46nTp14t///jcLFy4kLi7ONvvZkSNHWL9+PeHh4TRp0oSHHnqI0NBQVqxYwblz5wD473//S1paGp988gn/+te/6NWrF8OHD2fOnDm2esybN4/27dszevRo6tWrx4QJE2jcuDERERG2MgXVxR3odmRGCCGEAoPh1ilnOldFCCEKTd67aNy4MT/99JPt/7NmzQLgiy++YOjQoYSFheHn58fcuXMpV64c27Zto3v37nZHqF588UXCwsL44YcfsFgsREZGMm7cONvj165d48knnyQsLIwtW7Zw8eJFZs6cyeLFi21lduzYwcCBA3nrrbd4++23OX78OL179+bQoUO2MoWpi95kMCOEEEIIIYSLREVF4e/vn2+ZadOm2U1YkNPly5ftboCZl+joaDp06JBvmW+//ZZvv/1WqS560/U+M0IIIYQQQgihlW6DmeTkZIYPH37bC9LE7Ul2aiQ/NZKfdpKdGslPjeSnRvJT4LJ5c0VJpNtgxmg0Ur58ebtZIEThSHZqJD81kp92kp0ayU+NO+XXY9hMj7sA3J3y8zg575ophAPp9oo0m81MmzYt15zfomCSnRrJT43kp51kp0byU+NO+fmVDqBSxfL4lQ7QuyqF5k75CSFukQkAhBDFQo9hM/ErHcDNG1f4dv4belen2JBchRCukPVeA8j7jSgSGcwIIYqFrG96S+pUn84iuQohXCHrvQZK7pTNQhtdT/xMSkrSc/MeTbJTI/mpkfy0k+zUSH5qJD81kp8Q7ke3IzPJycmMGDFCr817NMlOjeSnRvLTTrJTI/mpkfzUSH4KZDYz4US6zmbWsGFDmRVEA8lOjeSnRvLTTrJTI/mpkfzUSH4KZDYz4US6zmYWHBwss4JoINmpkfzUSH7aSXZqJD81kp8ayU8I96TbaWbdh81mywkDnV+colcVhBBCCCGEA8hsZEIvug1mKla4g9S0DFJSysm5lEKIEkf+8AshihOZjUzoRaZm9kBWq5XY2FisVhkFaiH5qZH8tMuenfzhLzrpe2okPzWSnxDuSf/BjLwnFFlKSgohISF6V8NjSX63aLkhouSnnWSnRvJTI/mpkfwUyGc94UT6T8khM1wUmZeXF61bt8bLy0vvqngkye+WrKMDWac7FYbkp51kp0byUyP5qZH8FMhnPeFE+g9mRJGZTCYGDBiAyWTSuyoeSfJTI/lpJ9mp6T50BnVbD6R3cDg9hs3UuzoeR/qfGslPCPek/2lmQghRwnmbzPQdNx+QyQDy4+tfjnJl/KGMPwly2orwIDLhhxDOI4MZIYTQm8EgkwEIUYzJhB/OIV8ECSiGgxktFzR7GovFQnR0NBaLRe+qeIzs/eKHT9+S/BRI/9NOshN6kv5XNDmPpsjfDjckXwQJ3GEw4+BTBbK+/SjOnTo1NZWwsDC9q+FRsvcLya9g+Z0SIflpJ9kpctNTyzzlFCLpf0WT82iK5KfATV+7onjQfzBjQDp5EXl7e9O5c2d++OEH0tPT9a6Ox5H8CpbfKRGSn3bZsxMauOmMSJ5yCpG8dtXomZ+7Dpiz18vbZL59QTd97YriQWYz80De3t5069YNb2/1sWiPYTPpO24+fcfNz/+NqBhxZH4lkeSnnWQn9CT9T42e+WUNmIs6lb6zZa8XhqKPWLKueSlJn0GE48k7miJHf1vi6mt+sn+jeOlqotO3J4QQQggB2F3zIp9BhFYymFHk6NMLSsI1P+4k+2DU6O2N5X+nDrjTYXxRfHR+cQpbThjoNepDvL3lW8jCyP4FjxBCCJGTDGY8UEZGBlFRUWRkZOhdFY+UPb+cR6YqVCwLuPd5785S2HOfpf9pl/0+KfItZOEU9Qsed722wB3Ia1dNScsv5xcJ8roS7kr/wYxc/F9kaWlpLF68WO9qFMhdp8n2lPxcrbCnHEp+RWM3SJSjMWoK8ffCUy7G14Oer92cg0xPVNT8Cn1xvJvK+UWC0uvKwz7ryZcinkX/wYwOs5k5s5M66wN89jonJV6hXPIRvvjiC9LS0pTW5cw3WHc9Zc5kMtGvXz+++OILvavikbLnp6X/lTSq16U56/XqyPdBl/3hL2EzIjk6Vz1fu54+yPQ2men72ny8vb25fuUCqz4peF8U12tSs9+ostDvSR722s2vv+Z8Xa77/B3XVk7kov9gRgfOfFN11gd4uzobILBZIF999ZWmP0iO/HCV/TqTnNec6Cm/bwG9vLwIDMzM73Zy3lUYcOlRJne+lid7fjKYcb7CvF613AXbke+Den9QVR3wueu3sI7O1RNeu2773mcwUKlC5r5QnZbZ4+9aX8Iv2tf7/U7kpttgxuTtBYCPyRusYDZ54WPyxs/PL8/yTw6eip9/OQBuJl7lu0WT8iznY/IucF1ZZbJ+v125wsi5Lii4LdnlbNft6p9zO97emY8bjYWbXTv7drxMZtu6zNnWay5kLnfcUYGKFe8A4NLVm5SvlPv38+cLl0X2ehm8vbH+749E9t/z29+3k72OedUlKz+f27TfbDZRpWI5u+dXrHgH58+r9Zf85NxH5QP8gdy5qm4/ex8Dcv2e+e/t+4Kvr2+R+58rFOa1n11h31McVS+4/estv7wL9fwc/bX36FD8/MsV6r0SwM/PjxffXATkzsJZ76m3yz+/91QM5LmdnO9JhanL7V5vWl5jjvybkt96s+9XoMB9nJMjX7uF6Re3+7uT39/K2/19ceZ77+3c7rVXmNdCfu+p2V+vl67c/rV3u7o4so/llLXPcn4euW1bHPk+VsSMi/Kcosovb1ftC1F4Bj8/P5ed5FWhQgVOnz7tqs0JIYQQQgjhErVq1eLChQt6V6PEcZ+vVYUQQgghhBCiCFx6ZAYyj85A5rm7J06coE6dOly/ft2VVfB4ZcqUkewUSH5qJD/tJDs1kp8ayU+N5Kddcc8u61QzOSqjD5dfM5O1o8uUKQPAzZs3uXnzpqur4dG8vDLP1ZTstJH81Eh+2kl2aiQ/NZKfGslPu+KeXXFskyeR08yEEEIIIYQQHkkGM0IIIYQQQgiPpNtgJiUlhenTp5OSkqJXFTyWZKdG8lMj+Wkn2amR/NRIfmokP+0kO+FMLp8AQAghhBBCCCEcQU4zE0IIIYQQQngkGcwIIYQQQgghPJIMZoQQQgghhBAeSQYzQgghhBBCCI+kaTDTvHlzrl27xsqVKx1WkQEDBrB+/Xr++ecf/vnnH9asWUOTJk3syiQmJub588orrzisHq6gV37+/v6EhoZy9OhRLly4wO7duxk0aJDD6uAKemVXqVIlIiIiOHbsGOfPn2f16tXcc889DquDqzgjvyeffJKoqCjOnj1LQkIC27Zto0+fPrnKhYSEcPz4cS5cuMCaNWskv/8prvlFRESQmJjIRx99lOuxsLAwEhMTiYiIcOg2C8rotddeY8OGDZw/f56zZ886dNuO5m751axZk3nz5nHw4EEuXLjAgQMHmDhxIiaTyaF1cBR3yw/gv//9L4cPH+bixYscP36cRYsWUaVKFYfWwRHcMbssZrOZbdu2kZiYSKNGjRxaB+G5NA1mXnjhBebPn0+rVq2UX4hGoxGDwUDr1q1Zvnw5nTp1om3btvzzzz989913VK1a1Va2Tp06dj/Dhg3DYrGwevVqpTq4ml75zZw5k/bt2zNo0CAaN25MeHg4YWFhdOrUSbVJLqNXdl9//TW1a9fmmWee4eGHHyYmJoY1a9bg5+en2iSXckZ+ly9fZvbs2bRt25YWLVqwdOlS5s+fT7t27Wxlg4ODefnllxk9ejRBQUEkJiYSGRmJj4+PapNcSvIrmjNnzvDUU0/h6+trW+bj48MzzzxDTEyMQ7dVmIzMZjPffvstixYtcui2ncWd8qtfvz5Go5HRo0fTtGlTxo8fz+DBg5kyZYpD6+FI7pQfwObNm3n++ed54IEHeO6557j77rtZtmyZQ+vhKO6WXZbp06cTFxfn0O0Lz1fkwYy/vz+9evVi4cKF/PTTT/Tr18/2WGBgIImJiTz++OPs2LGDixcvsnHjRho0aGAr069fP86ePUunTp3YvXs3ly9f5q677uLFF19k4cKF7N+/n6NHjzJ8+HCMRiNt2rSxPTc+Pt7up3PnzmzevJlTp06ppeBCeub30EMPsWzZMqKiooiJiWHx4sUcOHCApk2bujQDrfTKrm7durRo0YJXXnmFP/74g7///psxY8ZQqlQpnn76aZfnoJWz8ouKiuL777/nyJEjnDx5knnz5hEdHU3Lli1tzx0xYgSzZ8/mhx9+IDo6mpdeeomqVavStWtXl2agQvIrun379nH27Fm6detmW9atWzf++ecf/vzzT9uy9u3b8/PPP3P27FliYmJYsWIFd999t+3xtWvXEhoaarfuChUqcPnyZYKCgoDCZTR9+nTmzp3LwYMHndRix3Kn/H7++WeGDRvGhg0bOHXqFGvXruWjjz7iySefdGICatwpP4C5c+eya9cuzpw5w44dOwgNDaV58+Z4e3s7KQHt3C07gA4dOtC2bVsmTJjghBYLT1bkwUyvXr04evQof//9N19//TX9+/fPVWb69Om8+eabtG7dmgsXLrB8+XK7F6ufnx/BwcGMGDGCpk2bcv78+Vzr8PPzw2QycenSpTzrUalSJTp27Mhnn31W1CboSs/8tm/fTufOnW1HHFq3bk3dunXZsGGDE1rqeHpll/XtUHJysq2M1WolJSWFhx9+2NHNdBpX5RcUFMS9997L1q1bAahduzZVqlRh48aNtjLXrl1j165dtGjRwgktdQ7JT5vPP/+c559/3vb//v37s3TpUrsyfn5+zJkzh8DAQLp06YLFYuHrr7/GYDAAsGTJEp555hnMZrPtOb179yY2NpZNmzZ5fEb5cef8ypYty+XLlx3VVKdw1/zuuOMOnn32WbZv3056erojm+ww7pRdpUqVmDt3LoMHD+bmzZvOarLwUEUezPTv35+vv/4ayPympmzZsgQGBtqVeffdd/n11185ePAgQ4YMoVKlSnbf3pjNZl599VV27NjB33//TVJSUq7tTJ06lbi4OLsOnl3fvn25fv06kZGRRW2CrvTMb+zYsRw+fJhjx45x5coVVq9eTXBwsO1Dk7vTK7sjR44QExPDlClTCAgIwGQyERwcTI0aNdzyfOfbcWZ+ZcuWJT4+nitXrrBy5UrGjRvHr7/+CkDlypUBSEhIsNtWQkIClSpVclp7HU3y0+brr7+mZcuW3HXXXdx111089NBDthyzREZG8t1333HixAn279/Pyy+/TMOGDfnXv/5lexygS5cutuf069ePL774AvD8jPLjrvllner9f//3f45pqJO4W35Tp04lISGBf/75h7vuuotnn33WsQ12IHfKLiIigkWLFrF3717HN1R4vCINZu69916aNm3K8uXLAcjIyGDlypW88MILduV27Nhh+/3y5cv8/fff1K9f37YsJSWFAwcO3HY7Y8eO5amnnqJPnz6kpKTkWeb555/nm2++ue3j7kjv/F5++WWaNWvGU089xSOPPMKbb75JWFiY3alo7krP7NLT0+nTpw/33nsvZ8+e5cKFC7Ru3Zp169ZhsVgc2UyncXZ+169fp2XLlrRu3ZopU6bw7rvv5vqg78kkP+0uXLhgOy3v+eef56effuLixYt2Ze655x6WLFlCdHQ0cXFxHDp0CIC77roLyMwt+9GwBx54gAYNGtg+EBVn7phf1apVWb16Nd9++y1LlizR3jgXcLf8PvzwQx5++GG6du1KRkYGCxcuVGyh87hLdi+//DKlS5fm/fffd1DLRHFTpBM1X3jhBUwmE8eOHbMtMxgMpKSkEBwcXOj15PVteJYxY8YQHBxMly5diI6OzrPMww8/TP369XN9kHB3eubn6+vL22+/Te/evVm3bh0A0dHRNGrUiDFjxtz2CJi70Lvv7du3j5YtW1K2bFnMZjMXLlxg06ZN/PHHH0VvjA6cnZ/VauXEiRMA7N+/n/r16zNu3DiioqKIj48HMk8TOHfunO05lSpVyndg6U4kPzWff/45YWFhAHnmtXz5cs6cOcPIkSOJi4vDaDSye/duu5mylixZwrZt26hWrRr9+vXjt99+48yZMwDFIqP8uFN+VapU4ccff2THjh2MHDnS4W11BnfK7+LFi1y8eJFjx45x+PBh/v77b5o3b87OnTsd3m5HcIfsHn30UVq0aJHrlMaoqCi++eYbhgwZ4thGC49T6CMzXl5ePPfcc7zxxhu0bNnS9vPQQw8RFxdndyF08+bNbb8HBARQt25djhw5UuA2Xn31VcaPH0/37t3zPZT4wgsv8Mcff3jUHym98zOZTJjNZqxWq93yjIwMjEb3vt2Q3tlld+3aNS5cuMA999xD48aN+eGHH9Qa5wKuyC8no9FoO0f61KlTnDt3znaxJ0CZMmVo1qyZ3ZEMdyX5qfv5558xm82YTCZ+/vlnu8fKly9P/fr1mTVrFps2beLIkSMEBATkWsfBgwf5448/GDhwIM888wyff/657bHikFF+3CW/qlWr8tNPP7Fv3z6GDh2a6++Ju3KX/HLK+tvrzrMSukN248aN46GHHrK99/bs2RPIPPX37bffdnibhecp9JGZJ554goCAAD777DOuXbtm91hkZCQvvPACEydOBODNN9/k0qVLJCQkMHnyZC5evMj333+f7/qDg4MJCQlh4MCBxMTE2M6jvHHjBomJibZyZcqUoUePHrz55puFbqQ70Du/69evs3nzZqZPn05SUhIxMTEEBgbaPqS5M72zA+jRowcXLlzgzJkz/Pvf/+a9997j+++/94jJE5yd37hx4/jjjz84ceIEPj4+PP744/Tp04cxY8bYyoSHh/P6669z7NgxTp8+zaRJk4iLiytw3e5A8lNnsVho3Lix7ffsLl++zIULF3jxxRc5d+4cd911F++8806e61myZIntPhffffed3WOFyahGjRqUL1+eGjVq4OXlZbtPxfHjx+3+zrgbd8gvayBz5swZ3nzzTSpWrGh7bta36+7KHfJr2rQpTZo0Ydu2bVy+fJk6deowadIkjh8/7tYDbnfI7p9//rErf+PGDQBOnjxJbGysQ9opPFuhBzMvvPACGzduzPXHHLBdSN6wYUMAJk2axHvvvcc999zD/v37efrpp0lLS8t3/YMHD8bHx4cvv/zSbvn06dOZMWOG7f9PPfUUBoPBdu66p3CH/AYMGMCUKVP49NNPueOOO2wXtbv7PRfcIbsqVaowc+ZM26HwL7/8kpkzZzqohc7l7Pz8/Pz44IMPqF69OklJSRw9epRBgwbZ3VgyLCwMPz8/5s6dS7ly5di2bRvdu3f3iGveJD/HuH79ep7LrVYrAwYM4L333mPXrl38/fffjBs3znY6bHbLly9n9uzZLF++PFfbC5PRpEmT7KbU3rZtGwAdO3YkKirKEc10Gr3ze+yxx6hbty5169a1O90SMqctd3d655eUlES3bt2YOHEi/v7+nDt3jp9//plZs2aRmprq+AY7kN7ZCVEQg5+fn8OOEwcGBvLTTz9RrVo1rl696qjVlhiSn3aSnRrJT43k5xo1a9YkOjqa1q1bs2/fPr2r43EkPzWSn3aSnXAm97tTkxBCCJGNt7c3d955J5MnT2bnzp3yYaiIJD81kp92kp1wBfe+8lsIIUSJ17JlS06cOEHjxo3triUShSP5qZH8tJPshCs49DQzIYQQQgghhHAVOTIjhBBCCCGE8EgymBFCCCGEEEJ4JBnMCCGEEEIIITySDGaEEEIIIf6//TogAQAAABD0/3U7An0hsCQzAADAkswAAABLMgMAACzJDAAAsCQzAADAUkq2OYJ3DrV0AAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 800x575 with 4 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x575 with 4 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "def plot_last_n_days(data, num_days_back=100, **kwargs):\n",
        "    endPeriod = query_swaps_ohlcv.index[-1]\n",
        "    startPeriod = endPeriod - pd.Timedelta(days=num_days_back)\n",
        "    dataToPlot = data.loc[(data.index > startPeriod) & (data.index < endPeriod),:]\n",
        "    title=f\"STETH/ETH last {num_days_back} days\"\n",
        "    title+=f\"({startPeriod:%b%d}-{endPeriod:%b%d})\" if startPeriod.month != endPeriod.month else f\"({startPeriod:%b%d}-{endPeriod:%d})\"\n",
        "    mav = [10]\n",
        "    if num_days_back > 3:\n",
        "        mav.append(50)\n",
        "    if num_days_back > 10:\n",
        "        mav.append(100)\n",
        "    fancy_plot(dataToPlot, mav=mav, title=title)\n",
        "\n",
        "plot_last_n_days(query_swaps_ohlcv, num_days_back=8)\n",
        "plot_last_n_days(query_swaps_ohlcv, num_days_back=3)\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.10.6 64-bit",
      "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": "3.10.11"
    },
    "vscode": {
      "interpreter": {
        "hash": "369f2c481f4da34e4445cda3fffd2e751bd1c4d706f27375911949ba6bb62e1c"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}