1inchparser.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# print(zero_ex_it)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# \\# print(test_req[x])\n",
    "# print(test_req)\n",
    "# test_req.info()\n",
    "# print(zero_ex_it)\n",
    "# test_req = json.dumps(test_req)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>network</th>\n",
       "      <th>logId</th>\n",
       "      <th>version</th>\n",
       "      <th>action</th>\n",
       "      <th>orderHash</th>\n",
       "      <th>taker</th>\n",
       "      <th>remainingMakerAmount</th>\n",
       "      <th>transactionHash</th>\n",
       "      <th>blockNumber</th>\n",
       "      <th>createDateTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <th>4</th>\n",
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      "text/plain": [
       "         id  network         logId  version action  \\\n",
       "0  14760396        1  log_e72dc908        2   fill   \n",
       "1  14760404        1  log_1c2fcc02        2   fill   \n",
       "2  14760420        1  log_fd00a1e7        2   fill   \n",
       "3  14760520        1  log_49574226        2   fill   \n",
       "4  14768119        1  log_950708df        2   fill   \n",
       "\n",
       "                                           orderHash  \\\n",
       "0  0x1e7e936b0112a5447fc9999a175f668f6e3684f344fc...   \n",
       "1  0x1e7e936b0112a5447fc9999a175f668f6e3684f344fc...   \n",
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       "3  0x1e7e936b0112a5447fc9999a175f668f6e3684f344fc...   \n",
       "4  0x1e7e936b0112a5447fc9999a175f668f6e3684f344fc...   \n",
       "\n",
       "                                        taker  remainingMakerAmount  \\\n",
       "0  0xf2f400c138f9fb900576263af0bc7fcde2b1b8a8  93210781650543027035   \n",
       "1  0xf2f400c138f9fb900576263af0bc7fcde2b1b8a8  43188467247487406487   \n",
       "2  0xf2f400c138f9fb900576263af0bc7fcde2b1b8a8   6142818430381748868   \n",
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       "4  0xf2f400c138f9fb900576263af0bc7fcde2b1b8a8     29100228148202054   \n",
       "\n",
       "                                     transactionHash  blockNumber  \\\n",
       "0  0xfcabcd0c9beac0a45b6dad7fcee734f346a9aa799241...     15157679   \n",
       "1  0x0a6cef3922636cebb6996653e611ce835b13f7b8c055...     15157680   \n",
       "2  0x06d356d248e3d5732f367d3ff55b26256f63b82ff1d1...     15157681   \n",
       "3  0x2dcbcd63b645a166083bc6b6644b123fa374b035b3f8...     15157688   \n",
       "4  0xf04dc23105c537c61b27fceba5aeae3248f1ffd2a36a...     15158758   \n",
       "\n",
       "             createDateTime  \n",
       "0  2022-07-17T03:08:09.179Z  \n",
       "1  2022-07-17T03:08:18.192Z  \n",
       "2  2022-07-17T03:08:39.194Z  \n",
       "3  2022-07-17T03:10:18.247Z  \n",
       "4  2022-07-17T07:12:48.930Z  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "import pandas as pd\n",
    "def pull_order_hist_by_hash(hash):\n",
    "    fixed_into_pd = pd.DataFrame(((requests.get(f'https://limit-orders.1inch.io/v2.0/1/limit-order/events/{\"0x\" + hash.lower()}').json())[list((requests.get(f'https://limit-orders.1inch.io/v2.0/1/limit-order/events/{\"0x\" + hash.lower()}').json()).keys())[0]]), columns=['id', 'network', 'logId', 'version', 'action', 'orderHash', 'taker', 'remainingMakerAmount', 'transactionHash', 'blockNumber', 'createDateTime'])\n",
    "    fixed_into_pd.head()\n",
    "    return fixed_into_pd\n",
    "pull_order_hist_by_hash(hash = '1E7E936B0112A5447FC9999A175F668F6E3684F344FCF013F5EAC034338ACB95')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'st' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mc:\\Users\\massn\\21\\21\\1inchparser.ipynb Cell 4\u001b[0m in \u001b[0;36m<cell line: 8>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000003?line=5'>6</a>\u001b[0m sort_by_dict \u001b[39m=\u001b[39m {\u001b[39m'\u001b[39m\u001b[39m1\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mcreateDateTime\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m2\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mtakerRate\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m3\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mmakerRate\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m4\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mmakerAmount\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m5\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mtakerAmount\u001b[39m\u001b[39m'\u001b[39m}\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000003?line=6'>7</a>\u001b[0m sort_by_choice \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39m1\u001b[39m\u001b[39m'\u001b[39m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000003?line=7'>8</a>\u001b[0m sort_by_choice_st \u001b[39m=\u001b[39m st\u001b[39m.\u001b[39mselectbox(\u001b[39m\"\u001b[39m\u001b[39mSort by\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mlist\u001b[39m(sort_by_dict\u001b[39m.\u001b[39mkeys()))\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000003?line=8'>9</a>\u001b[0m sortBy \u001b[39m=\u001b[39m sort_by_dict[sort_by_choice]\n\u001b[0;32m     <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000003?line=9'>10</a>\u001b[0m limit \u001b[39m=\u001b[39m \u001b[39m100\u001b[39m \u001b[39m#  limit -Number of limit orders to receive (default: 100, max: 500)\u001b[39;00m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'st' is not defined"
     ]
    }
   ],
   "source": [
    "chainID_dict = { \"Ethereum\": 1, \"Binance Smart Chain\": 56, \"Polygon\": 137, \"Optimism\": 10, \"Arbitrum\": 42161, \"Gnosis Chain\": 100, \"Avalanche\": 43114, \"Fantom\": 250 }\n",
    "chainId_choice = \"Ethereum\"\n",
    "# chainId_choice_st = st.selectbox(\"Select Chain ID\", list(chainID_dict.keys()))\n",
    "chainId = chainID_dict[chainId_choice] \n",
    "page = 1 #  page -Pagination step, default: 1 (page = offset / limit) \n",
    "sort_by_dict = {'1': 'createDateTime', '2': 'takerRate', '3': 'makerRate', '4': 'makerAmount', '5': 'takerAmount'}\n",
    "sort_by_choice = '1'\n",
    "sort_by_choice_st = st.selectbox(\"Sort by\", list(sort_by_dict.keys()))\n",
    "sortBy = sort_by_dict[sort_by_choice]\n",
    "limit = 100 #  limit -Number of limit orders to receive (default: 100, max: 500)\n",
    "# limit_st = st.number_input(\"Limit\", value=100, min_value=1, max_value=500)\n",
    "status_dict = {'_1_': \"%5B1%5D&\", '_12_': \"%5B1%2C2%5D&\", '_123_': \"%5B1%2C2%2C3%5D&\", '_2_':\"%5B2%5D&\",'_23_':\"%5B2%2C3%5D&\",'_3_':\"%5B3%5D&\"}\n",
    "status_choice = '_123_' #  statuses [1,2,3] 1 - valid limit orders, 2 - temporary invalid limit orders, 3 - invalid limit orders\n",
    "# status_choice_st = st.selectbox(\"Status\", list(status_dict.keys()))\n",
    "status = status_dict[status_choice]\n",
    "takerAsset = '0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48'\n",
    "makerAsset ='0xdac17f958d2ee523a2206206994597c13d831ec7'\n",
    "ping_limit_orders = requests.get(f'https://limit-orders.1inch.io/v2.0/{chainId}/limit-order/all?page={page}&limit={limit}&statuses={status}sortBy={sortBy}&takerAsset={takerAsset}&makerAsset={makerAsset}').json()\n",
    "ping_limit_orders = pd.DataFrame(ping_limit_orders)\n",
    "ping_limit_orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...\n",
       "1    {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...\n",
       "2    {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...\n",
       "3    {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...\n",
       "4    {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...\n",
       "Name: data, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "import pandas as pd\n",
    "all = requests.get('https://limit-orders.1inch.io/v2.0/1/limit-order/all?page=1&limit=10&statuses=%5B1%2C2%2C3%5D').json()\n",
    "# all = all['data']\n",
    "all = pd.DataFrame(all)\n",
    "all = all['data']\n",
    "all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
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       "      <th>signature</th>\n",
       "      <th>orderHash</th>\n",
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       "      <th>remainingMakerAmount</th>\n",
       "      <th>makerBalance</th>\n",
       "      <th>makerAllowance</th>\n",
       "      <th>data</th>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0xd6610a6561c527a782089462133ca8c92b0d106b4411...</td>\n",
       "      <td>0x1fc537dd1a889f2190ae9ba54f0ce62aed4ae08abf7b...</td>\n",
       "      <td>2022-07-18T11:41:51.824Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>24005864980732.177263969150000000</td>\n",
       "      <td>4.1656E-14</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           signature  \\\n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "1  0x01c59904ba624b0661753d9c1a08ef5e2629db9a5945...   \n",
       "2  0xa5dc81078dea7b67eaa76e9cde3d9f7872e40014e27e...   \n",
       "3  0x9c840ac4fe257b10a542b6ec3f8523e6691b1b44eefd...   \n",
       "4  0xd6610a6561c527a782089462133ca8c92b0d106b4411...   \n",
       "\n",
       "                                           orderHash  \\\n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "1  0x69dd689671f984f81746c76acda2c7b2d5f33b9b05d9...   \n",
       "2  0x01292181db588007dbe2e043869242ed39eaad216a25...   \n",
       "3  0x305c7b9d8b5961df2b4a3e2407f608b8f4d49747e2ad...   \n",
       "4  0x1fc537dd1a889f2190ae9ba54f0ce62aed4ae08abf7b...   \n",
       "\n",
       "             createDateTime remainingMakerAmount makerBalance  \\\n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "1  2022-07-18T11:41:52.874Z          20000000000            0   \n",
       "2  2022-07-18T11:41:52.724Z          20000000000            0   \n",
       "3  2022-07-18T11:41:52.428Z          20000000000            0   \n",
       "4  2022-07-18T11:41:51.824Z          20000000000            0   \n",
       "\n",
       "                                      makerAllowance  \\\n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "1  1157920892373161954235709850086879078532699846...   \n",
       "2  1157920892373161954235709850086879078532699846...   \n",
       "3  1157920892373161954235709850086879078532699846...   \n",
       "4  1157920892373161954235709850086879078532699846...   \n",
       "\n",
       "                                                data  \\\n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...   \n",
       "1  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...   \n",
       "2  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...   \n",
       "3  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...   \n",
       "4  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...   \n",
       "\n",
       "                           makerRate             takerRate  isMakerContract  \\\n",
       "0             971.032267288250000000  0.001029831895074554            False   \n",
       "1   7301768985380.116959064300000000           1.36953E-13            False   \n",
       "2     21783782711.421098517850000000         4.5905709E-11            False   \n",
       "3   2376688557322.414778137450000000           4.20753E-13            False   \n",
       "4  24005864980732.177263969150000000            4.1656E-14            False   \n",
       "\n",
       "                                   makerAsset  \\\n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "1  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "2  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "3  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "4  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "\n",
       "                                   takerAsset  \n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b  \n",
       "1  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b  \n",
       "2  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b  \n",
       "3  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b  \n",
       "4  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# all = all['data']\n",
    "# all.head()\n",
    "import requests\n",
    "import json\n",
    "import pandas as pd\n",
    "all = requests.get('https://limit-orders.1inch.io/v2.0/1/limit-order/all?page=1&limit=10&statuses=%5B1%2C2%2C3%5D').json()\n",
    "# all = all['data']\n",
    "all = pd.DataFrame(all)\n",
    "\n",
    "# all = all['data']\n",
    "all['makerAsset'] = all['data'][0]['makerAsset']\n",
    "all['takerAsset'] = all['data'][0]['takerAsset']\n",
    "\n",
    "# d = {[all[0]['makerAsset']]\n",
    "# ,[all[0]['takerAsset']]}\n",
    "# simple_df = pd.DataFrame(data=d,columns=['makerAsset', 'takerAsset'])\n",
    "# simple_df = simple_df.append(\n",
    "# )\n",
    "# # all[0]['makerAsset']\n",
    "# # all[0]['takerAsset']\n",
    "# # for row, data in all.i\n",
    "all.head()\n",
    "# terrows:\n",
    "#     print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "ruby"
    }
   },
   "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>signature</th>\n",
       "      <th>orderHash</th>\n",
       "      <th>createDateTime</th>\n",
       "      <th>remainingMakerAmount</th>\n",
       "      <th>makerBalance</th>\n",
       "      <th>makerAllowance</th>\n",
       "      <th>data</th>\n",
       "      <th>makerRate</th>\n",
       "      <th>takerRate</th>\n",
       "      <th>isMakerContract</th>\n",
       "      <th>makerAsset</th>\n",
       "      <th>takerAsset</th>\n",
       "      <th>symbol_x</th>\n",
       "      <th>symbol_y</th>\n",
       "      <th>maker_symbol</th>\n",
       "      <th>makerAsset_symbol</th>\n",
       "      <th>takerAsset_symbol</th>\n",
       "      <th>makerAsset_decimals</th>\n",
       "      <th>takerAsset_decimals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...</td>\n",
       "      <td>0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...</td>\n",
       "      <td>2022-07-18T11:41:52.975Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>971.032267288250000000</td>\n",
       "      <td>0.001029831895074554</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "      <td>USDC</td>\n",
       "      <td>USDC</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>USDC</td>\n",
       "      <td>CRO</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...</td>\n",
       "      <td>0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...</td>\n",
       "      <td>2022-07-18T11:41:52.975Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>971.032267288250000000</td>\n",
       "      <td>0.001029831895074554</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "      <td>USDC</td>\n",
       "      <td>USDC</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>USDC</td>\n",
       "      <td>CRO</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...</td>\n",
       "      <td>0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...</td>\n",
       "      <td>2022-07-18T11:41:52.975Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>971.032267288250000000</td>\n",
       "      <td>0.001029831895074554</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "      <td>USDC</td>\n",
       "      <td>USDC</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>USDC</td>\n",
       "      <td>CRO</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...</td>\n",
       "      <td>0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...</td>\n",
       "      <td>2022-07-18T11:41:52.975Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>971.032267288250000000</td>\n",
       "      <td>0.001029831895074554</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "      <td>USDC</td>\n",
       "      <td>USDC</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>USDC</td>\n",
       "      <td>CRO</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...</td>\n",
       "      <td>0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...</td>\n",
       "      <td>2022-07-18T11:41:52.975Z</td>\n",
       "      <td>20000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1157920892373161954235709850086879078532699846...</td>\n",
       "      <td>{'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...</td>\n",
       "      <td>971.032267288250000000</td>\n",
       "      <td>0.001029831895074554</td>\n",
       "      <td>False</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b</td>\n",
       "      <td>USDC</td>\n",
       "      <td>USDC</td>\n",
       "      <td>0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48</td>\n",
       "      <td>USDC</td>\n",
       "      <td>CRO</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           signature  \\\n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "0  0x3103ca9e44dc0d71acdc159c209bcafaa7848ca7e348...   \n",
       "\n",
       "                                           orderHash  \\\n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "0  0xa38cfb28ac4c752e8daa21120064b318013f5de7e303...   \n",
       "\n",
       "             createDateTime remainingMakerAmount makerBalance  \\\n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "0  2022-07-18T11:41:52.975Z          20000000000            0   \n",
       "\n",
       "                                      makerAllowance  \\\n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "\n",
       "                                                data               makerRate  \\\n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...  971.032267288250000000   \n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...  971.032267288250000000   \n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...  971.032267288250000000   \n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...  971.032267288250000000   \n",
       "0  {'makerAsset': '0xa0b86991c6218b36c1d19d4a2e9e...  971.032267288250000000   \n",
       "\n",
       "              takerRate  isMakerContract  \\\n",
       "0  0.001029831895074554            False   \n",
       "0  0.001029831895074554            False   \n",
       "0  0.001029831895074554            False   \n",
       "0  0.001029831895074554            False   \n",
       "0  0.001029831895074554            False   \n",
       "\n",
       "                                   makerAsset  \\\n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "\n",
       "                                   takerAsset symbol_x symbol_y  \\\n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b     USDC     USDC   \n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b     USDC     USDC   \n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b     USDC     USDC   \n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b     USDC     USDC   \n",
       "0  0xa0b73e1ff0b80914ab6fe0444e65848c4c34450b     USDC     USDC   \n",
       "\n",
       "                                 maker_symbol makerAsset_symbol  \\\n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48              USDC   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48              USDC   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48              USDC   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48              USDC   \n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48              USDC   \n",
       "\n",
       "  takerAsset_symbol  makerAsset_decimals  takerAsset_decimals  \n",
       "0               CRO                    6                    8  \n",
       "0               CRO                    6                    8  \n",
       "0               CRO                    6                    8  \n",
       "0               CRO                    6                    8  \n",
       "0               CRO                    6                    8  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokens_list = requests.get(f\"https://api.1inch.io/v4.0/1/tokens\")\n",
    "tokens_list = json.loads(tokens_list.text)\n",
    "tokens_list = [tokens_list[\"tokens\"][x] for x in tokens_list[\"tokens\"]]\n",
    "# symbol_list = [elem[\"symbol\"] for elem in tokens_list]\n",
    "# print(\"Tokens List\")\n",
    "# print(\"Great!\")\n",
    "tokens_list = pd.DataFrame(tokens_list)\n",
    "# print(tokens_list)\n",
    "'''find the symbol for each maker asset by looking in the tokens list and matching the symbol with the maker asset'''\n",
    "all['makerAsset_symbol'] = all['makerAsset'].apply(lambda x: tokens_list[tokens_list['address'] == x]['symbol'].values[0])\n",
    "all['takerAsset_symbol'] = all['takerAsset'].apply(lambda x: tokens_list[tokens_list['address'] == x]['symbol'].values[0])\n",
    "all['makerAsset_decimals'] = all['makerAsset'].apply(lambda x: tokens_list[tokens_list['address'] == x]['decimals'].values[0])\n",
    "all['takerAsset_decimals'] = all['takerAsset'].apply(lambda x: tokens_list[tokens_list['address'] == x]['decimals'].values[0])\n",
    "all.head()\n",
    "     \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# all['maker_symbol']\n",
    "# # tokenIN = st.selectbox(\"tokenIN\", tokens_list['symbol'], index=103)\n",
    "# address_of_said_tokenIN = (tokens_list.loc['makerAsset'])\n",
    "# print(address_of_said_tokenIN)\n",
    "# address_of_said_tokenIN = pd.DataFrame(address_of_said_tokenIN)\n",
    "# print(address_of_said_tokenIN)# print(address_of_said_tokenIN)\n",
    "\n",
    "# all = all.merge(address_of_said_tokenIN, left_on='makerAsset', right_index=True)\n",
    "# all['maker_symbol'] = address_of_said_tokenIN\n",
    "# # all.head()\n",
    "# decimal_of_said_tokenIN = tokens_list.set_index(\"address\").loc[all['makerAsset']][\"decimals\"]\n",
    "# # all = all.merge(decimal_of_said_tokenIN, left_on='makerAsset', right_index=True)\n",
    "\n",
    "# # print(decimal_of_said_tokenIN)\n",
    "\n",
    "# # # tokenOUT = st.selectbox(\"tokenOUT\", tokens_list['symbol'], index=146)\n",
    "# address_of_said_tokenOUT = tokens_list.set_index(\"address\").loc[all['takerAsset']][\"symbol\"]\n",
    "# # all = all.merge(address_of_said_tokenOUT, left_on='takerAsset', right_index=True)\n",
    "\n",
    "# # print(address_of_said_tokenOUT)\n",
    "\n",
    "# decimal_of_said_tokenOUT = tokens_list.set_index(\"address\").loc[all['takerAsset']][\"decimals\"]\n",
    "# # all = all.merge(decimal_of_said_tokenOUT, left_on='takerAsset', right_index=True)\n",
    "# # all.head()\n",
    "\n",
    "# # print(decimal_of_said_tokenOUT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "ruby"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "      <th>f</th>\n",
       "      <th>token1</th>\n",
       "      <th>token2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0xf01a670973edc81865ebb9f68b10c47c31afc133</td>\n",
       "      <td>0xae7ab96520de3a18e5e111b5eaab095312d7fe84</td>\n",
       "      <td>0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0</td>\n",
       "      <td>0xf01a670973edc81865ebb9f68b10c47c31afc133</td>\n",
       "      <td>340000000000000000</td>\n",
       "      <td>564397840925300413418</td>\n",
       "      <td>stETH</td>\n",
       "      <td>MATIC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0xf01a670973edc81865ebb9f68b10c47c31afc133</td>\n",
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       "      <td>0xf01a670973edc81865ebb9f68b10c47c31afc133</td>\n",
       "      <td>340000000000000000</td>\n",
       "      <td>564397840925300413418</td>\n",
       "      <td>stETH</td>\n",
       "      <td>MATIC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            a  \\\n",
       "0  0xf01a670973edc81865ebb9f68b10c47c31afc133   \n",
       "1  0xf01a670973edc81865ebb9f68b10c47c31afc133   \n",
       "\n",
       "                                            b  \\\n",
       "0  0xae7ab96520de3a18e5e111b5eaab095312d7fe84   \n",
       "1  0xae7ab96520de3a18e5e111b5eaab095312d7fe84   \n",
       "\n",
       "                                            c  \\\n",
       "0  0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0   \n",
       "1  0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0   \n",
       "\n",
       "                                            d                   e  \\\n",
       "0  0xf01a670973edc81865ebb9f68b10c47c31afc133  340000000000000000   \n",
       "1  0xf01a670973edc81865ebb9f68b10c47c31afc133  340000000000000000   \n",
       "\n",
       "                       f token1 token2  \n",
       "0  564397840925300413418  stETH  MATIC  \n",
       "1  564397840925300413418  stETH  MATIC  "
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokens_list = requests.get(f\"https://api.1inch.io/v4.0/1/tokens\")\n",
    "tokens_list = json.loads(tokens_list.text)\n",
    "tokens_list = tokens_list[\"tokens\"]\n",
    "tokens_list = pd.DataFrame(tokens_list)\n",
    "tokens_list = tokens_list.T\n",
    "tokens_list = tokens_list.reset_index()\n",
    "tokens_list = tokens_list.drop(columns=['index','logoURI', 'tags', 'eip2612', 'isFoT', 'synth', 'displayedSymbol'])\n",
    "\n",
    "(tokens_list).head()\n",
    "ls = ['0xf01a670973edc81865ebb9f68b10c47c31afc133', '0xae7ab96520de3a18e5e111b5eaab095312d7fe84', '0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0', '0xf01a670973edc81865ebb9f68b10c47c31afc133', 340000000000000000, 564397840925300413418]\n",
    "ls2 = ['0xf01a670973edc81865ebb9f68b10c47c31afc133', '0xae7ab96520de3a18e5e111b5eaab095312d7fe84', '0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0', '0xf01a670973edc81865ebb9f68b10c47c31afc133', 340000000000000000, 564397840925300413418]\n",
    "from datetime import datetime\n",
    "now = datetime.now()\n",
    "\n",
    "ls = pd.DataFrame([ls], columns=['a', 'b', 'c', 'd', 'e', 'f'])\n",
    "ls2 = pd.DataFrame([ls2], columns=['a', 'b', 'c', 'd', 'e', 'f'])\n",
    "ls = ls.append(ls2, ignore_index=True)\n",
    "ls['token1'] = [tokens_list.loc[tokens_list['address'] == b, 'symbol'].values[0] for b in ls['b']]\n",
    "ls['token2'] = [tokens_list.loc[tokens_list['address'] == b, 'symbol'].values[0] for b in ls['c']]\n",
    "ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>createDateTime</th>\n",
       "      <th>remainingMakerAmount</th>\n",
       "      <th>makerBalance</th>\n",
       "      <th>makerAllowance</th>\n",
       "      <th>makerRate</th>\n",
       "      <th>takerRate</th>\n",
       "      <th>isMakerContract</th>\n",
       "      <th>maker_asset</th>\n",
       "      <th>taker_asset</th>\n",
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       "      <td>60898095123177.476118652550000000</td>\n",
       "      <td>1.6420E-14</td>\n",
       "      <td>False</td>\n",
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      "text/plain": [
       "             createDateTime remainingMakerAmount makerBalance  \\\n",
       "0  2022-07-19T12:32:10.864Z          20000000000            0   \n",
       "1  2022-07-19T12:32:10.169Z          20000000000            0   \n",
       "2  2022-07-19T12:32:04.067Z          20000000000            0   \n",
       "3  2022-07-19T12:32:03.648Z          20000000000            0   \n",
       "4  2022-07-19T12:32:00.896Z          20000000000            0   \n",
       "\n",
       "                                      makerAllowance  \\\n",
       "0  1157920892373161954235709850086879078532699846...   \n",
       "1  1157920892373161954235709850086879078532699846...   \n",
       "2  1157920892373161954235709850086879078532699846...   \n",
       "3  1157920892373161954235709850086879078532699846...   \n",
       "4  1157920892373161954235709850086879078532699846...   \n",
       "\n",
       "                           makerRate       takerRate  isMakerContract  \\\n",
       "0   1250125012501.250125012500000000     7.99920E-13            False   \n",
       "1  42158516020236.087689713300000000      2.3720E-14            False   \n",
       "2   6018997354085.603112840450000000     1.66140E-13            False   \n",
       "3      1145047822.557181337800000000  8.73325969E-10            False   \n",
       "4  60898095123177.476118652550000000      1.6420E-14            False   \n",
       "\n",
       "                                  maker_asset  \\\n",
       "0  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "1  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "2  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "3  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "4  0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48   \n",
       "\n",
       "                                  taker_asset  \n",
       "0  0x6b175474e89094c44da98b954eedeac495271d0f  \n",
       "1  0x6b175474e89094c44da98b954eedeac495271d0f  \n",
       "2  0x6b175474e89094c44da98b954eedeac495271d0f  \n",
       "3  0x6b175474e89094c44da98b954eedeac495271d0f  \n",
       "4  0x6b175474e89094c44da98b954eedeac495271d0f  "
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chainId = 1\n",
    "page = 1 #  page -Pagination step, default: 1 (page = offset / limit)\n",
    "limit = 100 #  limit -Number of limit orders to receive (default: 100, max: 500)\n",
    "status = \"%5B1%5D&\"\n",
    "sortBy = 'createDateTime'\n",
    "url = f'https://limit-orders.1inch.io/v2.0/{chainId}/limit-order/all?page={page}&limit={limit}&statuses={status}sortBy={sortBy}'\n",
    "ping_limit_orders = requests.get(url).json()\n",
    "ping_limit_orders = pd.DataFrame(ping_limit_orders)\n",
    "ping_limit_orders['maker_asset'] = ping_limit_orders['data'][0]['makerAsset']\n",
    "ping_limit_orders['taker_asset'] = ping_limit_orders['data'][0]['takerAsset']\n",
    "ping_limit_orders = ping_limit_orders.drop(columns=['data', 'signature','orderHash'])\n",
    "ping_limit_orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'requests' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mc:\\Users\\massn\\21\\21\\1inchparser.ipynb Cell 10\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000009?line=0'>1</a>\u001b[0m \u001b[39m# chainId = 1\u001b[39;00m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000009?line=1'>2</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mmath\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000009?line=2'>3</a>\u001b[0m tokens_list \u001b[39m=\u001b[39m requests\u001b[39m.\u001b[39mget(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhttps://api.1inch.io/v4.0/\u001b[39m\u001b[39m{\u001b[39;00mchainId\u001b[39m}\u001b[39;00m\u001b[39m/tokens\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000009?line=3'>4</a>\u001b[0m tokens_list \u001b[39m=\u001b[39m json\u001b[39m.\u001b[39mloads(tokens_list\u001b[39m.\u001b[39mtext)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/massn/21/21/1inchparser.ipynb#ch0000009?line=4'>5</a>\u001b[0m tokens_list \u001b[39m=\u001b[39m tokens_list[\u001b[39m\"\u001b[39m\u001b[39mtokens\u001b[39m\u001b[39m\"\u001b[39m]\n",
      "\u001b[1;31mNameError\u001b[0m: name 'requests' is not defined"
     ]
    }
   ],
   "source": [
    "# chainId = 1\n",
    "import math\n",
    "tokens_list = requests.get(f\"https://api.1inch.io/v4.0/{chainId}/tokens\")\n",
    "tokens_list = json.loads(tokens_list.text)\n",
    "tokens_list = tokens_list[\"tokens\"]\n",
    "tokens_list = pd.DataFrame(tokens_list)\n",
    "tokens_list = tokens_list.T\n",
    "tokens_list = tokens_list.reset_index()\n",
    "tokens_list = tokens_list.drop(columns=['index','logoURI', 'tags', 'eip2612', 'isFoT', 'synth', 'displayedSymbol'])\n",
    "# print(tokens_list)\n",
    "\n",
    "\n",
    "\n",
    "ping_limit_orders['maker_asset_addy'] = ping_limit_orders['maker_asset']\n",
    "ping_limit_orders['taker_asset_addy'] = ping_limit_orders['taker_asset']\n",
    "ping_limit_orders['maker_asset_decimalz'] = ping_limit_orders['maker_asset']\n",
    "ping_limit_orders['taker_asset_decimalz'] = ping_limit_orders['taker_asset']\n",
    "ping_limit_orders['maker_asset_decimalz'] = [tokens_list.loc[tokens_list['address'] == b, 'decimals'].values[0] for b in ping_limit_orders['maker_asset_decimalz']]\n",
    "ping_limit_orders['taker_asset_decimalz'] = [tokens_list.loc[tokens_list['address'] == b, 'decimals'].values[0] for b in ping_limit_orders['taker_asset_decimalz']]\n",
    "ping_limit_orders['maker_asset'] = [tokens_list.loc[tokens_list['address'] == b, 'symbol'].values[0] for b in ping_limit_orders['maker_asset']]\n",
    "ping_limit_orders['taker_asset'] = [tokens_list.loc[tokens_list['address'] == b, 'symbol'].values[0] for b in ping_limit_orders['taker_asset']]\n",
    "ping_limit_orders['maker_amount_fixed'] = ping_limit_orders['remainingMakerAmount'] / math.pow(10, ping_limit_orders['maker_asset_decimalz'])\n",
    "# makerRate\t\n",
    "# takerRate\n",
    "ping_limit_orders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"singular value decomposition of a matrix\"\"\"\n",
    "import numpy as np\n",
    "def svd(A):\n",
    "    \"\"\"Singular Value Decomposition\n",
    "\n",
    "    Factorizes the matrix A into U*S*V such that U*S*V = A, where S is a diagonal matrix of singular values and V is a column matrix of eigenvectors.\n",
    "    \"\"\"\n",
    "    U, s, V = np.linalg.svd(A)\n",
    "    return U, s, V\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.1.2 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\massn\\.virtualenvs\\eAEDQwed\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: torch in c:\\users\\massn\\.virtualenvs\\eaedqwed\\lib\\site-packages (1.12.0)\n",
      "Requirement already satisfied: typing-extensions in c:\\users\\massn\\.virtualenvs\\eaedqwed\\lib\\site-packages (from torch) (4.3.0)\n"
     ]
    }
   ],
   "source": [
    "\"\"\"fully connected deep neural network\"\"\"\n",
    "# !pip install torch\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import torch \n",
    "# import tensorflow as tf\n",
    "# from tensorflow.keras.models import Sequential\n",
    "# from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, MaxPooling2D\n",
    "# from tensorflow.keras.callbacks import TensorBoard\n",
    "# from tensorflow.keras.optimizers import Adam\n",
    "# from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "# from tensorflow.keras.utils import to_categorical\n",
    "# from tensorflow.keras.preprocessing import image\n",
    "# from tensorflow.keras.applications.vgg16 import VGG16\n",
    "\n",
    "\n",
    "class Samnet\n",
    "    \"\"\"inherit from\"\"\"\n",
    "    def __init__(self, input_size, hidden_size, output_size):\n",
    "        self.input_size = input_size\n",
    "        self.hidden_size = hidden_size\n",
    "        self.output_size = output_size\n",
    "        self.W1 = torch.randn(self.input_size, self.hidden_size)\n",
    "        self.W2 = torch.randn(self.hidden_size, self.output_size)\n",
    "        self.b1 = torch.randn(1, self.hidden_size)\n",
    "        self.b2 = torch.randn(1, self.output_size)\n",
    "        self.learning_rate = 0.001\n",
    "        self.loss_list = []\n",
    "        self.accuracy_list = []\n",
    "        self.epoch_list = []\n",
    "        self.batch_size = 100\n",
    "        self.epochs = 100\n",
    "        self.X = None\n",
    "        self.Y = None\n",
    "        self.Y_hat = None\n",
    "        self.Y_hat_one_hot = None\n",
    "        self.Y_one_hot = None\n",
    "        self.Y_one_hot_hat = None\n",
    "        self.Y_hat_one_hot_hat = None\n",
    "        self.loss = None\n",
    "        self.accuracy = None\n",
    "        self.epoch = None\n",
    "        self.batch = None\n",
    "        self.batch_size = None\n",
    "        self.epochs = None\n",
    "        self.X = None\n",
    "        self.Y = None\n",
    "        self.Y_hat = None\n",
    "        self.Y_hat_one_hot = None\n",
    "        self.Y_one_hot = None\n",
    "        self.Y_one_hot_hat = None\n",
    "        self.Y_hat_one_hot_hat = None\n",
    "        self.loss = None\n",
    "        self.accuracy = None\n",
    "        self.epoch = None\n",
    "        self.batch = None\n",
    "        self.batch_size = None\n",
    "        self.epochs = None\n",
    "        self.X = None\n",
    "        self.Y = None\n",
    "        self.Y_hat = None\n",
    "        self.Y_hat_one_hot = None\n",
    "        self.Y_one_hot = None\n",
    "        self.Y_one\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"fully connected deep neural network\"\"\"\n",
    "# !pip install tensorflow\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, MaxPooling2D\n"
   ]
  }
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