mt_backtest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "54fb8f5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "from mt_data import download,data_global_set,data_init\n",
    "from mt_strategy import Order,Trade,Premium_only,Strategy_let_expire,Strategy_p_loss,Strategy_p_profit\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "from datetime import time\n",
    "from functools import reduce\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3eec73c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'ts': '2020-05-26T06:52:24', 'action': 'shorting', 'sym': 'ZM', 'spread_type': 'CALL', 'strike_date': '2020-05-29', 'strikes': [180.0, 185.0]}\n",
      "https://www.dropbox.com/s/ahlb9ldhnmemmwn/option_bars.json?dl=1\n",
      "prepare_options_cache Index(['symbol', 'type', 'expiry', 'strike', 'time', 'mid'], dtype='object')\n",
      "sorting options_cache\n",
      "finished\n",
      "after drop 865056\n",
      "https://www.dropbox.com/s/ll8xa6xb1xhrhv7/underlying_bars.json?dl=1\n",
      "prepare_underlying_cache Index(['symbol', 'time', 'close'], dtype='object')\n",
      "sorting underlying_cache\n",
      "finished\n",
      "after drop: 417290\n"
     ]
    }
   ],
   "source": [
    "actions = json.loads(download(\"https://www.dropbox.com/s/psgut932tw77b82/actions.json?dl=1\"))\n",
    "print(actions[0])\n",
    "\n",
    "#options_cache,underlying_cache = data_init()\n",
    "\n",
    "data_global_set(*data_init())\n",
    "\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e95d816",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                                                   premium    expire    2xLoss    2xGain\n",
      "0    2020-05-26 09:52:24    ZM       2020-05-29 CALL  180.0/ 185.0    179.48   0.72 /   0.35        0.38                              \n",
      "1         05-26 10:33:38    PYPL          05-29 CALL  155.0/ 160.0    156.00   0.83 /   0.26        0.57     -1.00     -1.21     -0.11\n",
      "2         05-26 10:41:19    HES           05-29 PUT    46.0/  44.0     46.58   0.39 /   0.25        0.14                         -0.03\n",
      "3         05-26 10:58:17    AAPL          05-29 PUT   315.0/ 310.0    316.35   1.32 /   0.54        0.78               -1.68     -0.20\n",
      "4         05-26 14:59:16    GS            05-29 PUT   185.0/ 180.0    193.49   0.74 /   0.29        0.45                         -0.06\n",
      "5         05-26 15:47:03    W             05-29 CALL  170.0/ 175.0    171.55   0.88 /   0.42        0.46     -1.55     -3.45          \n",
      "6         05-26 09:47:18    AMD           05-29 CALL   56.0/  58.0     53.10   0.35 /   0.17        0.19                         -0.05\n",
      "                            SPX      missing_data data\n",
      "                            SPX      missing_data data\n",
      "7         05-26 08:14:42    HES           05-29 PUT    46.0/  41.0     55.96   0.78 /   0.27        0.51                         -0.09\n",
      "8         05-26 08:57:49    MAR           05-29 PUT    94.0/  90.0    107.96   1.88 /   0.88        1.00               -2.30     -0.20\n",
      "9         05-26 10:07:58    BA            05-29 PUT   140.0/ 135.0    205.43   1.22 /   0.72        0.50               -1.33     -0.10\n",
      "10        05-26 08:13:30    DKNG          05-29 CALL   40.0/  45.0     39.34   1.65 /   0.78        0.87               -2.17     -0.05\n",
      "11   2020-05-29 10:12:18    COST     2020-06-05 CALL  315.0/ 320.0    302.24   1.47 /   0.71        0.76                         -0.21\n",
      "12        05-29 10:59:13    SBUX          06-05 CALL   80.0/  82.0     80.97   0.51 /   0.18        0.33     -0.97     -1.35     -0.97\n",
      "13        05-29 11:01:14    DKNG          06-05 CALL   42.0/  50.0     39.34   1.30 /   0.45        0.85               -2.17     -0.12\n",
      "14        05-29 11:20:26    SPY           06-05 PUT   299.0/ 289.0    299.52   0.40 /   0.01        0.38                         -0.02\n",
      "15        05-29 11:00:24    EA            06-05 PUT   118.0/ 114.0    118.02   0.45 /   0.21        0.24               -0.56     -0.01\n",
      "16        05-29 11:03:20    NFLX          06-05 PUT   400.0/ 390.0    419.60   1.97 /   1.15        0.82                         -0.21\n",
      "17        05-29 15:28:46    RCL           06-05 PUT    49.0/  47.0     69.44   0.48 /   0.27        0.21                         -0.06\n",
      "18        05-29 15:31:46    TSLA          06-05 PUT   820.0/ 810.0    885.66   3.35 /   2.44        0.91                         -0.13\n",
      "                            DKNG     missing_data data\n",
      "19        05-29 09:59:43    BYND          06-05 CALL  150.0/ 160.0    133.53   1.10 /   0.45        0.66                         -0.14\n",
      "20        05-29 10:03:59    SMH           06-05 PUT   137.0/ 133.0    151.64   0.56 /   0.18        0.38                         -0.01\n",
      "21        05-29 11:13:05    DKNG          06-05 CALL   45.0/  50.0     39.34   0.95 /   0.42        0.52                         -0.12\n",
      "22   2020-06-03 09:39:38    ZM       2020-06-05 CALL  225.0/ 235.0    207.60   1.45 /   0.62        0.82               -2.60     -0.20\n",
      "23        06-03 09:53:30    DAL           06-05 PUT    25.0/  23.0     30.43   0.39 /   0.12        0.26                         -0.06\n",
      "24        06-03 10:25:55    WYNN          06-05 PUT    80.0/  75.0     92.31   0.92 /   0.40        0.52                         -0.10\n",
      "25        06-03 10:33:38    LYFT          06-05 PUT    31.5/  28.5     36.89   0.42 /   0.13        0.29                         -0.04\n",
      "26        06-03 15:48:01    UAL           06-05 PUT    29.0/  26.0     39.66   0.44 /   0.14        0.30                         -0.08\n",
      "27        06-03 10:16:39    MU            06-05 PUT    48.0/  44.0     48.69   0.58 /   0.10        0.48                         -0.09\n",
      "28        06-03 10:48:23    ZM            06-05 CALL  225.0/ 235.0    207.60   1.10 /   0.30        0.80                         -0.20\n",
      "29        06-03 14:45:13    RAD           06-05 PUT    13.0/  11.0     13.17   0.43 /   0.06        0.37                         -0.07\n",
      "30        06-03 15:10:20    BA            06-05 CALL  195.0/ 205.0    205.43   0.77 /   0.39        0.38    -10.00     -4.90    -10.00\n",
      "31        06-03 15:24:55    WMT           06-05 CALL  125.0/ 129.0    116.34   0.55 /   0.10        0.45                         -0.12\n",
      "32        06-03 15:54:27    SPY           06-05 CALL  313.0/ 316.0    314.30   0.56 /   0.12        0.44     -1.30     -2.63     -1.30\n",
      "33   2020-06-04 19:21:24    AMD      2020-06-12 CALL   55.0/  60.0     53.50   0.62 /   0.10        0.52               -1.24     -0.10\n",
      "34        06-04 09:52:44    GRUB          06-12 PUT    55.0/  52.5     60.38   0.85 /   0.47        0.38               -0.90     -0.07\n",
      "35        06-04 15:14:42    RAD           06-12 PUT    13.0/  11.0     13.17   0.32 /   0.03        0.29                         -0.06\n",
      "36        06-04 10:08:54    SPY           06-12 CALL  322.0/ 326.0    318.10   0.26 /   0.01        0.24                              \n",
      "37        06-04 14:54:40    AMZN          06-12 PUT  2430.0/2420.0   2545.02   5.45 /   4.53        0.92                         -0.18\n",
      "38        06-04 07:44:16    AAPL          06-12 PUT   322.5/ 317.5    337.10   0.74 /   0.34        0.40                         -0.07\n",
      "39        06-04 09:37:57    GOOGL         06-12 PUT  1400.0/1390.0   1412.92   3.08 /   2.12        0.95               -2.50          \n",
      "40        06-04 10:59:11    NVDA          06-12 PUT   345.0/ 335.0    356.96   1.50 /   0.61        0.89                         -0.17\n",
      "41        06-04 14:19:57    W             06-12 PUT   170.0/ 165.0    184.76   1.20 /   0.75        0.45                          0.05\n",
      "42        06-04 10:38:30    MA            06-12 CALL  320.0/ 330.0    295.39   1.13 /   0.34        0.79                         -0.21\n",
      "43        06-04 11:01:03    FB            06-12 CALL  242.5/ 250.0    238.79   1.02 /   0.41        0.61                         -0.14\n",
      "44   2020-06-11 11:15:04    MKC      2020-06-19 CALL  175.0/ 180.0     84.91   1.38 /   0.38        1.00                         -0.15\n",
      "45        06-11 14:14:30    GOOGL         06-19 CALL 1460.0/1470.0   1412.92   1.65 /   0.90        0.75                         -0.05\n",
      "46        06-11 14:35:48    HD            06-19 CALL  255.0/ 265.0    242.51   0.99 /   0.23        0.77               -2.04     -0.14\n",
      "47        06-11 14:53:28    V             06-19 CALL  200.0/ 210.0    191.32   1.13 /   0.19        0.94                         -0.20\n",
      "48        06-11 09:56:37    SPY           06-19 CALL  312.0/ 317.0    299.41   0.28 /   0.03        0.26                         -0.03\n",
      "49        06-11 10:33:18    COST          06-19 CALL  312.5/ 317.5    290.49   1.20 /   0.57        0.63                         -0.14\n",
      "50        06-11 10:54:01    LULU          06-19 CALL  325.0/ 335.0    297.38   1.49 /   0.72        0.77                         -0.18\n",
      "51        06-11 14:53:57    BILL          06-19 PUT    65.0/  60.0     81.90   0.75 /   0.33        0.42                         -0.08\n",
      "52        06-11 10:20:08    QQQ           06-19 CALL  241.0/ 246.0    242.71   1.36 /   0.42        0.94     -1.71     -2.69     -1.71\n",
      "53        06-11 10:29:40    MRNA          06-19 PUT    59.0/  54.0     66.35   1.23 /   0.45        0.78                         -0.10\n",
      "54        06-11 11:28:12    DXCM          06-19 PUT   360.0/ 350.0    409.36   2.80 /   2.00        0.80                         -0.20\n",
      "55   2020-06-15 14:21:10    SPY      2020-06-17 PUT   298.0/ 293.0    306.74   0.85 /   0.40        0.46                         -0.06\n",
      "56        06-15 14:27:56    DDOG          06-17 PUT    75.0/  70.0     86.79   0.80 /   0.28        0.53                         -0.15\n",
      "57        06-15 14:42:00    COUP          06-17 PUT   220.0/ 215.0    258.86   1.45 /   0.90        0.55                         -0.08\n",
      "58        06-15 15:04:03    NVDA          06-17 PUT   345.0/ 340.0    370.10   1.78 /   1.20        0.58                         -0.14\n",
      "59        06-15 15:26:02    BYND          06-17 PUT   140.0/ 135.0    158.28   1.39 /   0.72        0.66                         -0.12\n",
      "60        06-15 08:59:34    BYND          06-17 PUT   140.0/ 135.0    158.28   0.94 /   0.52        0.42                         -0.09\n",
      "61        06-15 15:50:47    ROKU          06-17 PUT   108.0/ 102.0    128.50   0.58 /   0.21        0.38                         -0.04\n",
      "62        06-15 09:45:08    BYND          06-17 PUT   150.0/ 145.0    158.28   1.16 /   0.59        0.57                         -0.04\n",
      "63        06-15 09:39:38    ZS            06-17 PUT   105.0/ 100.0    108.57   0.42 /   0.10        0.32                         -0.07\n",
      "64        06-15 09:50:53    CRM           06-17 PUT   180.0/ 175.0    186.95   0.48 /   0.14        0.34                         -0.03\n",
      "65        06-15 09:53:30    DKNG          06-17 PUT    38.0/  34.0     33.34   1.05 /   0.35        0.70     -4.00     -1.62     -4.00\n",
      "66   2020-06-18 10:06:08    KR       2020-06-26 CALL   33.5/  35.5     32.16   0.36 /   0.13        0.23                         -0.07\n",
      "67        06-18 10:14:29    NCLH          06-26 PUT    17.5/  13.5     15.28   0.60 /   0.15        0.45     -2.22     -1.00     -2.22\n",
      "68        06-18 10:39:56    XOP           06-26 PUT    54.0/  49.0     48.88   0.94 /   0.26        0.68     -5.00     -1.50     -5.00\n",
      "69        06-18 09:50:57    NVDA          06-26 PUT   347.5/ 337.5    365.86   1.54 /   0.72        0.82                         -0.20\n",
      "70        06-18 10:04:02    BA            06-26 PUT   187.5/ 180.0    187.02   0.48 /   0.08        0.40     -0.48     -1.14     -0.48\n",
      "71        06-18 10:45:59    VXX           06-26 PUT    35.0/  33.0     36.89   0.30 /   0.01        0.29                         -0.05\n",
      "72        06-18 10:45:36    TEAM          06-26 PUT   172.5/ 165.0    181.01   1.23 /   0.45        0.78                         -0.12\n",
      "73        06-18 07:06:11    SPCE          06-26 PUT    15.0/  12.0     15.55   0.09 /   0.02        0.07               -0.17     -0.02\n",
      "74        06-18 08:19:25    SPCE          06-26 PUT    15.0/  12.0     16.25   0.33 /   0.06        0.28               -0.76     -0.07\n",
      "75        06-18 09:43:38    FB            06-26 PUT   232.5/ 222.5    233.42   2.13 /   0.68        1.46               -3.15     -0.11\n",
      "76        06-18 09:49:29    ACB           06-26 PUT    13.0/  10.0     12.27   0.49 /   0.07        0.42     -0.73     -0.90     -0.73\n",
      "77   2020-06-23 14:47:19    APT      2020-06-26 PUT    15.0/  13.0     17.55   0.33 /   0.07        0.26                         -0.07\n",
      "78        06-23 15:40:22    BYND          06-26 CALL  167.5/ 177.5    141.68   1.03 /   0.48        0.55                         -0.12\n",
      "                            FSLY     missing_data data\n",
      "79        06-23 09:00:20    MCD           06-26 CALL  192.5/ 197.5    180.26   0.81 /   0.29        0.52                         -0.09\n",
      "80        06-23 11:14:13    CVS           06-26 CALL   66.0/  68.0     63.24   0.34 /   0.12        0.21                         -0.03\n",
      "81        06-23 09:42:09    AMZN          06-26 CALL 2800.0/2810.0   2692.87   3.45 /   2.65        0.80                         -0.14\n",
      "82        06-23 09:57:00    RAD           06-26 PUT    14.0/  11.5     17.22   0.51 /   0.07        0.43                         -0.03\n",
      "                            MS       missing_data data\n",
      "83        06-23 10:07:14    GOOGL         06-26 CALL 1480.0/1490.0   1469.93   3.12 /   2.20        0.92               -4.30     -0.15\n",
      "84        06-23 10:24:35    NKE           06-26 CALL  102.0/ 105.0     97.82   0.51 /   0.17        0.34                         -0.08\n",
      "85        06-23 09:45:43    SQ            06-26 CALL  108.0/ 115.0    113.39   1.27 /   0.32        0.96     -5.39     -2.73     -5.39\n",
      "86        06-23 10:21:26    LULU          06-26 CALL  305.0/ 315.0    304.77   0.82 /   0.20        0.62               -5.75          \n",
      "87        06-23 14:25:57    BA            06-26 PUT   170.0/ 160.0    180.81   1.07 /   0.29        0.78                         -0.17\n",
      "88   2020-06-30 09:36:55    RAD      2020-07-10 PUT    15.0/  12.5     16.21   0.32 /   0.06        0.26                         -0.05\n",
      "89        06-30 09:05:26    UAL           07-10 PUT    33.0/  28.0     32.67   0.61 /   0.13        0.48     -0.33     -1.05     -0.33\n",
      "90        06-30 10:25:43    SPY           07-10 CALL  316.0/ 321.0    308.65   0.36 /   0.01        0.35                         -0.09\n",
      "91        06-30 10:36:25    TSLA          07-10 CALL 1240.0/1280.0   1208.66   0.57 /   0.31        0.26                              \n",
      "92        06-30 11:01:38    NVDA          07-10 PUT   375.0/ 365.0    418.78   1.15 /   0.42        0.73                         -0.17\n",
      "93        06-30 13:11:40    LLY           07-10 PUT   162.5/ 157.5    161.06   0.89 /   0.32        0.57     -1.44     -1.44     -1.44\n",
      "94        06-30 13:15:36    BURL          07-10 CALL  200.0/ 207.5    178.48   1.35 /   0.33        1.03                         -0.28\n",
      "95        06-30 09:47:57    DKNG          07-10 CALL   35.5/  38.5     32.43   0.10 /   0.07        0.03               -0.17          \n",
      "96        06-30 11:09:36    FB            07-10 PUT   235.0/ 230.0    245.07   0.87 /   0.44        0.43               -1.36     -0.05\n",
      "97        06-30 15:12:28    SPY           07-10 CALL  318.0/ 321.0    312.56   0.45 /   0.10        0.34                         -0.04\n",
      "98        06-30 08:33:25    XLE           07-10 CALL   38.0/  40.0     35.25   0.41 /   0.12        0.28                         -0.07\n",
      "99   2020-07-09 08:02:55    LULU     2020-07-10 PUT   302.5/ 297.5    314.39   1.12 /   0.54        0.58                         -0.12\n",
      "100       07-09 08:10:47    RCL           07-10 PUT    46.5/  35.0     53.16   1.05 /   0.20        0.85               -1.92     -0.16\n",
      "101       07-09 10:01:50    ROKU          07-10 PUT   128.0/ 118.0    148.36   1.78 /   0.59        1.19                         -0.29\n",
      "102       07-09 15:35:30    LULU          07-10 PUT   302.5/ 297.5    314.39   0.56 /   0.23        0.33                         -0.05\n",
      "103       07-09 08:59:30    CIEN          07-10 PUT    55.0/  50.0     54.60   0.88 /   0.17        0.71     -0.40     -2.00     -0.40\n",
      "104       07-09 09:47:20    DIS           07-10 PUT   112.0/ 107.0    118.64   0.73 /   0.25        0.48                         -0.05\n",
      "105       07-09 10:02:52    FB            07-10 CALL  245.0/ 250.0    245.07   0.34 /   0.04        0.29     -0.07     -0.07     -0.07\n",
      "106       07-09 15:04:46    XLF           07-10 PUT    22.5/  21.5     23.59   0.28 /   0.10        0.19                         -0.01\n",
      "107       07-09 09:33:35    IYT           07-10 PUT   160.0/ 152.0    174.38   0.88 /   0.15        0.72                         -0.05\n",
      "108       07-09 09:57:11    RCL           07-10 PUT    46.0/  41.0     53.16   0.83 /   0.23        0.60                         -0.12\n",
      "109       07-09 10:31:25    HD            07-10 PUT   245.0/ 240.0    256.00   0.94 /   0.52        0.43                         -0.08\n",
      "110  2020-07-13 10:44:51    LOW      2020-07-17 PUT   134.0/ 129.0    142.84   0.76 /   0.29        0.47                         -0.09\n",
      "111       07-13 12:40:49    DDOG          07-17 CALL  100.0/ 105.0     87.30   0.78 /   0.28        0.50                         -0.10\n",
      "112       07-13 15:51:36    INTC          07-17 PUT    57.5/  55.5     58.81   0.51 /   0.20        0.30                         -0.07\n",
      "113       07-13 09:57:21    NKE           07-17 CALL   99.0/ 104.0     97.82   0.96 /   0.18        0.78                         -0.21\n",
      "114       07-13 10:02:44    DOCU          07-17 CALL  220.0/ 230.0    190.95   1.74 /   0.96        0.77                         -0.12\n",
      "115       07-13 10:11:46    PTON          07-17 CALL   70.0/  80.0     61.82   0.93 /   0.22        0.71                         -0.18\n",
      "116       07-13 10:17:47    VXX           07-17 PUT    31.0/  27.0     30.17   0.56 /   0.04        0.53     -0.83     -1.16     -0.83\n",
      "117       07-13 10:41:27    XLI           07-17 PUT    68.0/  65.0     71.05   0.42 /   0.11        0.32                         -0.08\n",
      "118       07-13 10:43:46    IWM           07-17 PUT   138.0/ 128.0    144.80   1.15 /   0.27        0.88                         -0.23\n",
      "119       07-13 11:04:39    RCL           07-17 PUT    47.0/  40.0     50.85   1.03 /   0.28        0.76                         -0.17\n",
      "120       07-13 10:08:42    TWTR          07-17 CALL   36.0/  38.0     35.81   0.14 /   0.03        0.12               -0.29     -0.02\n",
      "121  2020-07-17 09:40:58    WORK     2020-07-24 PUT    30.0/  28.0     29.72   0.49 /   0.17        0.33     -0.28     -0.74     -0.04\n",
      "122       07-17 10:22:47    GOOGL         07-24 PUT  1470.0/1460.0   1508.21   4.45 /   3.45        1.00                         -0.28\n",
      "123       07-17 10:26:24    GOOGL         07-24 PUT  1470.0/1460.0   1508.21   4.00 /   3.15        0.85                         -0.18\n",
      "124       07-17 15:38:26    GOOGL         07-24 PUT  1470.0/1460.0   1508.21   1.98 /   1.52        0.45                         -0.10\n",
      "125       07-17 09:54:03    MCD           07-24 PUT   190.0/ 185.0    195.20   0.59 /   0.18        0.41                         -0.09\n",
      "126       07-17 11:26:52    XOP           07-24 PUT    50.0/  46.0     50.49   0.56 /   0.11        0.45                         -0.11\n",
      "127       07-17 09:56:52    WFC           07-24 PUT    24.5/  23.5     23.97   0.24 /   0.12        0.13     -0.53     -0.36     -0.03\n",
      "128       07-17 10:30:43    PLAY          07-24 PUT    12.0/  10.0     12.34   0.42 /   0.10        0.32                         -0.03\n",
      "129       07-17 10:37:34    CODX          07-24 PUT    18.0/  15.0     24.00   0.60 /   0.23        0.38                         -0.10\n",
      "130       07-17 10:55:59    AMZN          07-24 CALL 3280.0/3290.0   3008.91  15.97 /  15.07        0.90                         -0.09\n",
      "131       07-17 13:25:01    PENN          07-24 PUT    33.0/  29.0     33.85   0.68 /   0.14        0.55               -1.53     -0.14\n",
      "132  2020-07-23 12:53:34    MSFT     2020-07-31 CALL  215.0/ 220.0    203.51   1.04 /   0.53        0.52                         -0.12\n",
      "133       07-23 14:40:08    SQ            07-31 CALL  135.0/ 140.0    129.85   1.00 /   0.55        0.45                         -0.04\n",
      "134       07-23 14:43:33    QQQ           07-31 CALL  269.0/ 274.0    264.59   0.98 /   0.39        0.59                         -0.14\n",
      "135       07-23 14:59:26    NFLX          07-31 CALL  510.0/ 520.0    488.88   2.20 /   1.32        0.88                         -0.19\n",
      "136       07-23 09:06:29    BYND          07-31 CALL  137.0/ 142.0    125.90   1.27 /   0.77        0.51                         -0.04\n",
      "137       07-23 09:38:08    BYND          07-31 CALL  135.0/ 140.0    125.90   1.17 /   0.71        0.45                         -0.08\n",
      "138       07-23 09:51:53    DKNG          07-31 CALL   38.0/  43.0     33.38   0.70 /   0.15        0.55               -1.32     -0.10\n",
      "139       07-23 15:35:33    DIA           07-31 CALL  271.0/ 276.0    260.81   0.86 /   0.24        0.62                         -0.17\n",
      "140       07-23 10:30:09    RH            07-31 PUT   270.0/ 260.0    287.43   1.50 /   0.57        0.93                         -0.25\n",
      "141       07-23 15:05:34    RH            07-31 CALL  295.0/ 300.0    287.43   1.35 /   0.72        0.63                         -0.10\n",
      "142       07-23 09:38:32    SBUX          07-31 PUT    75.0/  70.0     75.11   0.61 /   0.12        0.49                         -0.08\n",
      "143  2020-07-29 10:10:50    BA       2020-07-31 CALL  175.0/ 182.5    158.00   1.30 /   0.48        0.82                         -0.15\n",
      "144       07-29 09:42:28    DIA           07-31 CALL  266.0/ 269.0    260.81   0.36 /   0.10        0.27                         -0.03\n",
      "145       07-29 10:46:16    AMZN          07-31 CALL 3250.0/3270.0   3164.68   2.31 /   1.44        0.88                         -0.12\n",
      "146       07-29 11:55:08    GOOGL         07-31 CALL 1550.0/1560.0   1498.37   3.55 /   2.85        0.70                         -0.18\n",
      "147       07-29 10:39:15    FB            07-31 CALL  260.0/ 265.0    268.50   1.03 /   0.49        0.54     -5.00     -2.16     -0.15\n",
      "148       07-29 14:44:37    TNA           07-31 PUT    27.5/  24.0     35.56   0.70 /   0.21        0.49                         -0.12\n",
      "149       07-29 10:47:58    TDOC          07-31 PUT   227.5/ 222.5    193.71   0.80 /   0.42        0.38     -5.00     -3.90     -5.00\n",
      "150       07-29 10:50:58    KMX           07-31 PUT    96.0/  91.0    104.35   1.07 /   0.47        0.60                         -0.18\n",
      "151       07-29 15:10:36    NEM           07-31 PUT    67.0/  62.0     62.57   0.81 /   0.15        0.66     -4.43     -2.79     -4.43\n",
      "                            NOC      missing_data data\n",
      "152       07-29 09:50:43    XOP           07-31 PUT    51.0/  47.0     55.19   0.51 /   0.06        0.45                         -0.08\n",
      "153       07-29 09:44:37    WYNN          07-31 PUT    69.0/  65.0     84.98   0.95 /   0.30        0.65                         -0.09\n",
      "154  2020-08-06 09:58:57    LULU     2020-08-14 PUT   322.5/ 312.5    349.12   1.79 /   0.72        1.07                         -0.30\n",
      "155       08-06 10:12:18    FB            08-14 PUT   247.5/ 242.5    268.50   0.60 /   0.15        0.45                         -0.06\n",
      "156       08-06 10:16:34    FB            08-14 PUT   247.5/ 242.5    268.50   0.64 /   0.17        0.46                         -0.06\n",
      "157       08-06 10:34:53    LVS           08-14 PUT    43.0/  41.0     48.37   0.44 /   0.12        0.32                         -0.04\n",
      "158       08-06 15:20:40    GD            08-14 PUT   148.0/ 143.0    154.15   0.65 /   0.15        0.50                         -0.10\n",
      "159       08-06 11:22:09    DRI           08-14 PUT    75.0/  70.0     82.25   0.80 /   0.33        0.48                         -0.13\n",
      "160       08-06 11:26:07    UAL           08-14 PUT    32.0/  29.0     33.04   0.47 /   0.17        0.30                         -0.04\n",
      "161       08-06 11:02:33    BA            08-14 PUT   170.0/ 162.5    167.50   1.48 /   0.56        0.92     -2.50     -2.12     -2.50\n",
      "162       08-06 11:10:37    QQQ           08-14 CALL  275.0/ 280.0    270.93   0.52 /   0.07        0.45               -0.96     -0.07\n",
      "163       08-06 10:22:45    AZN           08-14 PUT    55.0/  52.0     54.67   0.57 /   0.07        0.50     -0.33     -0.33     -0.12\n",
      "164       08-06 09:59:15    LUV           08-14 PUT    34.0/  30.0     34.69   0.55 /   0.10        0.44                         -0.04\n",
      "165  2020-08-13 10:02:48    JBLU     2020-08-21 PUT    11.0/   9.0     10.56   0.21 /   0.04        0.17     -0.44     -0.36     -0.44\n",
      "166       08-13 10:10:19    NKLA          08-21 PUT    39.0/  34.0     39.37   0.68 /   0.23        0.45                         -0.10\n",
      "167       08-13 10:29:24    GOOGL         08-21 PUT  1470.0/1460.0   1575.57   6.25 /   4.95        1.30                         -0.38\n",
      "168       08-13 15:29:05    DELL          08-21 CALL   62.5/  65.0     60.46   0.45 /   0.14        0.30                         -0.07\n",
      "169       08-13 09:45:13    IWM           08-21 CALL  160.0/ 163.0    153.25   0.73 /   0.27        0.46                         -0.09\n",
      "170       08-13 09:50:41    DKNG          08-21 CALL   38.0/  41.0     35.15   0.35 /   0.15        0.20               -0.42     -0.02\n",
      "171       08-13 09:59:48    AAPL          08-21 CALL  465.0/ 470.0    458.15   0.41 /   0.16        0.25                         -0.06\n",
      "172       08-13 10:38:49    XOP           08-21 PUT    53.5/  50.5     50.85   0.51 /   0.10        0.41     -2.65     -0.98     -2.65\n",
      "173       08-13 10:48:30    BLMN          08-21 PUT    12.5/  10.0     12.23   0.33 /   0.07        0.25     -0.27     -0.27     -0.27\n",
      "174       08-13 15:12:36    TWLO          08-21 CALL  255.0/ 265.0    251.26   1.72 /   0.68        1.04               -2.33     -0.15\n",
      "175       08-13 15:42:45    DOCU          08-21 CALL  210.0/ 215.0    210.18   1.86 /   1.14        0.73     -0.18     -1.48     -0.18\n",
      "176  2020-08-18 09:41:40    IWM      2020-08-21 CALL  160.0/ 163.0    153.25   0.39 /   0.07        0.31                         -0.07\n",
      "177       08-18 14:17:11    IWM           08-21 CALL  160.0/ 163.0    153.25   0.21 /   0.04        0.16                         -0.02\n",
      "178       08-18 09:41:16    TGT           08-21 CALL  155.0/ 165.0    152.46   1.21 /   0.37        0.84                         -0.24\n",
      "179       08-18 09:48:29    RCL           08-21 PUT    56.0/  52.0     70.13   0.67 /   0.23        0.44                         -0.12\n",
      "180       08-18 10:03:17    BYND          08-21 CALL  129.0/ 134.0    131.02   1.71 /   0.90        0.81     -2.02     -1.76     -2.02\n",
      "181       08-18 10:47:17    FB            08-21 PUT   257.5/ 252.5    267.01   0.72 /   0.34        0.38                         -0.05\n",
      "182       08-18 09:51:09    AMZN          08-21 PUT  3185.0/3175.0   3284.72   4.50 /   3.83        0.67                         -0.13\n",
      "183       08-18 11:55:51    YETI          08-21 PUT    49.0/  46.0     51.26   0.79 /   0.33        0.47                         -0.05\n",
      "184       08-18 10:15:12    IWM           08-21 CALL  159.0/ 163.0    155.74   0.56 /   0.14        0.42                         -0.09\n",
      "185       08-18 15:21:21    OSTK          08-21 CALL  140.0/ 150.0     96.93   1.85 /   1.00        0.85                         -0.20\n",
      "186       08-18 10:35:52    DKNG          08-21 PUT    35.5/  31.5     37.00   0.72 /   0.15        0.57               -1.32     -0.12\n",
      "187  2020-08-25 10:52:47    MTCH     2020-09-04 CALL  116.0/ 121.0    105.94   1.31 /   0.47        0.84               -1.91     -0.23\n",
      "188       08-25 15:17:57    AMZN          09-04 PUT  3240.0/3230.0   3401.80   9.28 /   8.07        1.20                         -0.26\n",
      "189       08-25 09:38:52    ROKU          09-04 PUT   144.0/ 135.0    159.91   2.17 /   0.79        1.39                         -0.21\n",
      "190       08-25 09:50:41    SHOP          09-04 PUT   950.0/ 940.0    973.02   4.65 /   3.85        0.80               -7.90     -0.15\n",
      "191       08-25 10:29:11    PTON          09-04 PUT    65.0/  60.0     80.63   0.72 /   0.23        0.49                         -0.12\n",
      "192       08-25 08:01:40    RCL           09-04 PUT    61.0/  56.0     71.92   0.63 /   0.16        0.47                         -0.12\n",
      "193       08-25 09:49:41    NKLA          09-04 PUT    38.5/  37.5     41.35   0.25 /   0.10        0.15                              \n",
      "194       08-25 10:58:51    SWK           09-04 PUT   157.5/ 152.5    158.93   0.97 /   0.35        0.62                         -0.08\n",
      "195       08-25 14:51:09    YUM           09-04 PUT    94.5/  92.0     94.34   0.65 /   0.30        0.35     -0.16     -0.16     -0.03\n",
      "196       08-25 14:52:46    YUM           09-04 PUT    94.0/  92.0     94.34   0.55 /   0.30        0.25                         -0.07\n",
      "                            TSLA     missing_data data\n",
      "                            TSLA     missing_data data\n",
      "197       08-25 15:30:39    WDAY          09-04 CALL  250.0/ 260.0    215.80   1.75 /   0.78        0.97                         -0.25\n",
      "198  2020-09-01 09:55:20    ADBE     2020-09-04 PUT   500.0/ 490.0    491.94   1.97 /   0.92        1.05     -8.06     -3.20     -0.24\n",
      "199       09-01 10:14:12    PLAY          09-04 PUT    16.5/  15.5     18.85   0.30 /   0.07        0.22                         -0.02\n",
      "                            PTON     missing_data data\n",
      "200       09-01 15:05:52    IWM           09-04 PUT   154.5/ 149.5    147.84   1.18 /   0.41        0.77     -5.00     -1.64     -5.00\n",
      "201       09-01 15:23:23    ANET          09-04 PUT   220.0/ 215.0    203.86   1.38 /   1.23        0.15     -5.00     -2.15     -5.00\n",
      "202       09-01 08:19:56    ANET          09-04 PUT   220.0/ 215.0    203.86   4.03 /   3.10        0.93     -5.00     -2.25     -5.00\n",
      "203       09-01 09:40:48    QQQ           09-04 CALL  304.0/ 314.0    269.23   2.50 /   0.62        1.88                         -0.46\n",
      "204       09-01 09:46:20    BYND          09-04 PUT   125.0/ 120.0    134.88   1.21 /   0.67        0.54               -1.19     -0.12\n",
      "205       09-01 09:48:53    BA            09-04 PUT   165.0/ 160.0    160.23   1.14 /   0.56        0.57     -4.77     -1.26     -4.77\n",
      "206       09-01 09:51:01    NKLA          09-04 PUT    35.0/  30.0     32.13   0.53 /   0.12        0.40     -2.87     -1.58     -0.10\n",
      "207       09-01 09:58:29    SPY           09-04 PUT   332.0/ 322.0    329.39   0.73 /   0.06        0.68     -2.61     -2.61     -0.10\n",
      "208       09-01 10:29:47    DAL           09-04 PUT    31.0/  28.0     31.70   0.45 /   0.06        0.39                         -0.08\n",
      "209  2020-09-09 07:57:31    UBER     2020-09-18 PUT    32.0/  29.0     37.12   0.39 /   0.09        0.30                         -0.08\n",
      "210       09-09 08:00:53    USO           09-18 PUT    26.0/  21.0     29.06   0.57 /   0.07        0.49                         -0.13\n",
      "211       09-09 08:16:16    DKNG          09-18 PUT    35.5/  30.0     55.39   1.25 /   0.20        1.05                         -0.20\n",
      "212       09-09 09:13:18    OSTK          09-18 PUT    60.0/  50.0     65.15   1.32 /   0.57        0.75                         -0.03\n",
      "213       09-09 09:51:48    SPY           09-18 PUT   334.0/ 326.0    335.90   0.68 /   0.07        0.61                         -0.18\n",
      "214       09-09 09:58:01    CAT           09-18 PUT   145.0/ 135.0    150.66   1.35 /   0.37        0.98                         -0.19\n",
      "215       09-09 10:00:16    MSFT          09-18 PUT   200.0/ 190.0    203.03   0.69 /   0.20        0.49                         -0.11\n",
      "216       09-09 10:06:59    OSTK          09-18 PUT    60.0/  50.0     65.15   1.12 /   0.17        0.95                         -0.03\n",
      "217       09-09 10:08:56    DKNG          09-18 PUT    35.0/  30.0     55.39   1.30 /   0.20        1.10                         -0.30\n",
      "218       09-09 10:35:59    QQQ           09-18 PUT   269.0/ 259.0    269.23   1.45 /   0.29        1.15                         -0.23\n",
      "219       09-09 11:07:01    FB            09-18 PUT   267.5/ 257.5    266.61   1.35 /   0.34        1.02     -0.89     -2.95     -0.89\n",
      "220  2020-09-09 14:38:41    GLD      2020-09-18 PUT   179.0/ 174.0    183.20   0.82 /   0.23        0.58                         -0.17\n",
      "221       09-09 15:25:40    WDAY          09-18 PUT   205.0/ 200.0    206.20   0.79 /   0.34        0.46               -2.06     -0.10\n",
      "222       09-09 15:26:39    GOOGL         09-18 PUT  1495.0/1485.0   1515.76   2.95 /   2.08        0.88               -3.75          \n",
      "223       09-09 08:11:30    OSTK          09-18 PUT    60.0/  50.0     75.04   1.38 /   0.28        1.10               -2.40     -0.33\n",
      "224       09-09 09:36:41    OSTK          09-18 PUT    60.0/  50.0     75.04   1.30 /   0.33        0.98               -2.45     -0.25\n",
      "                                                                                                  130.74    -95.40   -132.82    -94.81\n",
      "Strategy Premium only: trades = 225 average premium to strike_spread = 10.28 spread sum = 1344.5\n",
      "Strategy Let Expire summary. trades: 225  breaches: 38  breach ratio: 0.169 \n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "class Date_Reduce():\n",
    "    date = None\n",
    "    repeat = 0\n",
    "    count = 0\n",
    "    def __init__(self,repeat = 10):\n",
    "        self.repeat = repeat\n",
    "        \n",
    "    def reduce(self,new_date):\n",
    "        \n",
    "        if self.date == None or self.count == self.repeat:\n",
    "            self.date = new_date\n",
    "            self.count = 0\n",
    "            return str(new_date)\n",
    "        \n",
    "        if self.date.year != new_date.year:\n",
    "            self.date = new_date\n",
    "            self.count = 0\n",
    "            return str(new_date)\n",
    "        \n",
    "        self.count = self.count + 1\n",
    "        \n",
    "        return \" \" * 5 + \"{:02d}-{:02d}\".format(self.date.month,self.date.day)\n",
    "    \n",
    "class Date_Time_Reduce(Date_Reduce):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "    def reduce(self,new_date_time):\n",
    "        date_str = super().reduce(new_date_time.date())\n",
    "        return date_str + \" \" + str(new_date_time.time())\n",
    "    \n",
    "        \n",
    "events_breach = events_shorting = 0\n",
    "premium_sum = 0\n",
    "\n",
    "\n",
    "dr_ts = Date_Time_Reduce()\n",
    "\n",
    "\n",
    "\n",
    "strategies = [Premium_only(),Strategy_let_expire(),Strategy_p_loss(2),Strategy_p_profit(.3)]\n",
    "\n",
    "print(\" \" * 96,end = \"\")\n",
    "\n",
    "for i,strategy in enumerate(strategies):\n",
    "    results = '{:>10}'.format(strategy.column_title)\n",
    "    print(results,end=\"\")\n",
    "print()\n",
    "\n",
    "dr = Date_Reduce()\n",
    "\n",
    "\n",
    "trade_num = 0\n",
    "\n",
    "trades = []\n",
    "\n",
    "HOURS_TO_EST = 3\n",
    "\n",
    "for i,event in enumerate(actions):\n",
    "    \n",
    "    ts = datetime.strptime(event['ts'], '%Y-%m-%dT%H:%M:%S') + timedelta(hours=HOURS_TO_EST)\n",
    "    \n",
    "    if all(item in event.keys() for item in  ['action','sym','spread_type','strike_date','strikes']):\n",
    "            \n",
    "        \n",
    "        if event['action'] == 'shorting':\n",
    "            \n",
    "            events_shorting = events_shorting + 1\n",
    "            \n",
    "            orderx = Order(ts,event['sym'],event['spread_type'],event['strike_date'],event['strikes'])\n",
    "            trade = Trade(orderx)\n",
    "            \n",
    "            if not trade.has_data():\n",
    "                print(\" \"*28 + \"{:<8}\".format(orderx.symbol),\"missing_data data\")\n",
    "                continue\n",
    "                \n",
    "            trades.append(trade)\n",
    "                \n",
    "            trade.init_data()\n",
    "            \n",
    "            \n",
    "            order_str = \"{:<8} {:<10} {:<4} {:6.1f}/{:6.1f}\".format(orderx.symbol,dr.reduce(orderx.expiry.date()),orderx.spread_type,orderx.strike_sell,orderx.strike_buy)\n",
    "    \n",
    "            output_trade_details = \"{:<4} {}    {}  {:8.2f} {:6.2f} / {:6.2f}  \".format( trade_num, dr_ts.reduce(ts),order_str,trade.price_underlying_close,trade.price_sell,trade.price_buy )\n",
    "            \n",
    "            print(output_trade_details,end=\"\")\n",
    "            \n",
    "            \n",
    "            for strategy in strategies:\n",
    "                val = strategy.trade(trade)\n",
    "                \n",
    "                if val is None:\n",
    "                    print(\"val is none\")\n",
    "            \n",
    "                if val:\n",
    "                    output = \"{:10.2f}\".format(val)\n",
    "                else:\n",
    "                    output = \"{:<10}\".format(\"\")\n",
    "                    \n",
    "                print(output,end=\"\")\n",
    "            \n",
    "            \n",
    "            print()\n",
    "            \n",
    "            trade_num = trade_num + 1\n",
    "            \n",
    "            #break\n",
    "            \n",
    "            \n",
    "\n",
    "\n",
    "print(\" \" * 94,end = \"\")\n",
    "\n",
    "for i,strategy in enumerate(strategies):\n",
    "    results = '{:>10.2f}'.format(round(strategy.pnl,2))\n",
    "    print(results,end=\"\")\n",
    "    \n",
    "\n",
    "print()\n",
    "\n",
    "for strategy in strategies:\n",
    "    print(strategy.summary_results())\n",
    "\n",
    "\n",
    "                \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65a60e43",
   "metadata": {},
   "outputs": [],
   "source": [
    "d = datetime(year = 2020, month = 5, day = 6)\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e833339",
   "metadata": {},
   "outputs": [],
   "source": [
    "d.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63c78ad5",
   "metadata": {},
   "outputs": [],
   "source": [
    "trade.price_sell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c04f8641",
   "metadata": {},
   "outputs": [],
   "source": [
    "trade.bars_sell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0b393d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "trade.bars_buy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e64b7bcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import reduce\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56267f7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.intersect1d(trade.bars_buy.time,trade.bars_sell.time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01f041e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "trade.bars_buy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a2e0221",
   "metadata": {},
   "outputs": [],
   "source": [
    "trade.bars_sell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1eb733a",
   "metadata": {},
   "outputs": [],
   "source": [
    "len(trades)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91996dc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93227de1",
   "metadata": {},
   "outputs": [],
   "source": [
    "trades[0].bars_underlying"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8551177",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d48ef6c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = px.line(trades[2].bars_underlying,x='time',y='close')\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3110171",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "np.random.seed(1)\n",
    "\n",
    "work_week_40h = pd.date_range(start='2020-05-26', end='2020-05-30', freq=\"BM\")\n",
    "\n",
    "df = pd.DataFrame(dict(\n",
    "    date = work_week_40h,\n",
    "    value = np.cumsum(np.random.rand(len(work_week_40h))-0.5)\n",
    "))\n",
    "\n",
    "#df = trades[2].bars_underlying\n",
    "\n",
    "fig = px.scatter(df, x=\"date\", y=\"value\",\n",
    "#fig = px.line(df, x=\"time\", y=\"close\",\n",
    "                 title=\"Hide Non-Business Hour Gaps with rangebreaks\")\n",
    "fig.update_xaxes(\n",
    "    rangebreaks=[\n",
    "        dict(bounds=[17, 9], pattern=\"hour\"), #hide hours outside of 9am-5pm\n",
    "        #dict(bounds=[\"sat\", \"mon\"])\n",
    "        #dict(values=[\"2015-12-25\"])\n",
    "    ]\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d9d263f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "df = trades[2].bars_underlying.copy()\n",
    "\n",
    "df = df.set_index(\"time\",drop=True)\n",
    "\n",
    "df = df.resample(\"min\").max()\n",
    "#df_resample = df\n",
    "\n",
    "test = df['close'].isnull()\n",
    "print( True in test.values)\n",
    "\n",
    "\n",
    "df = df.where(pd.notnull(df),None)\n",
    "\n",
    "\n",
    "test = df['close'].apply(lambda x: False if x is None else math.isnan(x))\n",
    "#print(test.tolist())\n",
    "print('close1 test', True in test.values)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "fig = px.line(df, x=df.index, y=\"close\",\n",
    "                 title=\"Hide Non-Business Hour Gaps by filling empty Y values with None\")\n",
    "\n",
    "fig.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "140363dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(df_resample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "801ebcfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i,row in df_resample.iterrows():\n",
    "    print(i,row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96bf43e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame([1,np.nan])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3748e8b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be3739cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df.where(pd.notnull(df),None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f85c859e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34081ae0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#https://stackoverflow.com/questions/61346100/plotly-how-to-style-a-plotly-figure-so-that-it-doesnt-display-gaps-for-missing\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# sample data\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')\n",
    "\n",
    "print(df)\n",
    "\n",
    "# remove some dates to build a similar case as in the question\n",
    "df = df.drop(df.index[75:110])\n",
    "df = df.drop(df.index[210:250])\n",
    "df = df.drop(df.index[460:480])\n",
    "\n",
    "\n",
    "# build complete timepline from start date to end date\n",
    "dt_all = pd.date_range(start=df['Date'].iloc[0],end=df['Date'].iloc[-1])\n",
    "\n",
    "# retrieve the dates that ARE in the original datset\n",
    "dt_obs = [d.strftime(\"%Y-%m-%d\") for d in pd.to_datetime(df['Date'])]\n",
    "\n",
    "# define dates with missing values\n",
    "dt_breaks = [d for d in dt_all.strftime(\"%Y-%m-%d\").tolist() if not d in dt_obs]\n",
    "\n",
    "# make fiuge\n",
    "fig = go.Figure(data=[go.Candlestick(x=df['Date'],\n",
    "                open=df['AAPL.Open'], high=df['AAPL.High'],\n",
    "                low=df['AAPL.Low'], close=df['AAPL.Close'])\n",
    "                      ])\n",
    "\n",
    "# hide dates with no values\n",
    "fig.update_xaxes(rangebreaks=[dict(values=dt_breaks)])\n",
    "\n",
    "fig.update_layout(yaxis_title='AAPL Stock')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81d6159c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def every_n_df(df,n,title = 'none'):\n",
    "    print(\"title:\",title)\n",
    "    #df1 = df.reset_index()\n",
    "    c = 0\n",
    "    for i,row in df.iterrows():\n",
    "        c = c+1\n",
    "        if c==n:\n",
    "            print(i,row['time'])\n",
    "            c = 0\n",
    "            \n",
    "def every_n_list(l,n,title = 'none'):\n",
    "    print(\"title:\",title)\n",
    "    #df1 = df.reset_index()\n",
    "    c = 0\n",
    "    for i,val in enumerate(l):\n",
    "        c = c+1\n",
    "        if c==n:\n",
    "            print(i,val)\n",
    "            c = 0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc736cf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#https://stackoverflow.com/questions/61346100/plotly-how-to-style-a-plotly-figure-so-that-it-doesnt-display-gaps-for-missing\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# sample data\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')\n",
    "\n",
    "#print(df)\n",
    "\n",
    "# remove some dates to build a similar case as in the question\n",
    "df = df.drop(df.index[75:110])\n",
    "df = df.drop(df.index[210:250])\n",
    "df = df.drop(df.index[460:480])\n",
    "\n",
    "df = trades[2].bars_underlying.copy()\n",
    "\n",
    "\n",
    "\n",
    "# build complete timepline from start date to end date\n",
    "dt_all = pd.date_range(start=df['time'].iloc[0],end=df['time'].iloc[-1],freq='min')\n",
    "\n",
    "# retrieve the dates that ARE in the original datset\n",
    "dt_obs = [d.strftime(\"%Y-%m-%d %H:%M:%S\") for d in pd.to_datetime(df['time'])]\n",
    "\n",
    "#print(dt_obs)\n",
    "\n",
    "# define dates with missing values\n",
    "dt_breaks = [d for d in dt_all.strftime(\"%Y-%m-%d %H:%M:%S\").tolist() if not d in dt_obs]\n",
    "\n",
    "print(len(dt_breaks))\n",
    "\n",
    "\n",
    "\n",
    "# make fiuge\n",
    "fig = go.Figure(data=[go.Line(x=df['time'],y=df['close'])])\n",
    "                #open=df['close'], high=df['close'],\n",
    "                #low=df['close'], close=df['close'])\n",
    "                # $     ])\n",
    "\n",
    "# hide dates with no values\n",
    "fig.update_xaxes(rangebreaks=[dict(values=dt_breaks)])\n",
    "\n",
    "fig.update_layout(yaxis_title='AAPL Stock')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31ab21fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "time_range = pd.date_range(start='2020-05-26', end='2020-05-30', freq=\"min\")\n",
    "\n",
    "df = pd.DataFrame(dict(\n",
    "    time = time_range,\n",
    "    close = np.cumsum(np.random.rand(len(time_range))-0.5)\n",
    "))\n",
    "\n",
    "\n",
    "df = df.drop(df.index[200:1000]) # make a gap\n",
    "df = df.drop(df.index[2000:3000]) # make a gap\n",
    "\n",
    "\n",
    "\n",
    "dt_all = pd.date_range(start=df['time'].iloc[0],end=df['time'].iloc[-1],freq = 'min')\n",
    "dt_obs = [d for d in pd.to_datetime(df['time'])]\n",
    "dt_breaks = [d for d in dt_all.tolist() if not d in dt_obs]\n",
    "\n",
    "\n",
    "fig = go.Figure(data=[go.Line(x=df['time'],y=df['close'])\n",
    "                      ])\n",
    "\n",
    "fig.update_xaxes(rangebreaks=[dict(values=dt_breaks)])\n",
    "\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "411741a9",
   "metadata": {},
   "source": [
    "## Method: plot each day side by side\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c18fb1a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotly.subplots import make_subplots\n",
    "\n",
    "df = trades[2].bars_underlying.copy()\n",
    "\n",
    "dates = df['time'].apply(lambda x: x.date()).unique()\n",
    "\n",
    "fig = make_subplots(rows = 1,cols = len(dates),shared_yaxes=True,horizontal_spacing = 0)\n",
    "\n",
    "for i,date in enumerate(dates):\n",
    "    \n",
    "    df_date = df[df['time'].apply(lambda x: x.date() == date)]\n",
    "    \n",
    "    preamble_date_range = pd.date_range(start = datetime(date.year,date.month,date.day,hour = 9,minute = 31),\n",
    "                                        end = df_date['time'].iloc[0] - timedelta(minutes=1),\n",
    "                                        freq = 'min')\n",
    "    preamble_df = pd.DataFrame(({'time':  preamble_date_range}))\n",
    "    df_date = pd.concat([preamble_df,df_date])\n",
    "    \n",
    "    trace = go.Scatter(x=df_date['time'],y=df_date['close'],mode='lines',line_color = 'blue')\n",
    "    \n",
    "    fig.append_trace(trace,row = 1,col = i+1)\n",
    "    \n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c74e533",
   "metadata": {},
   "source": [
    "## Method: Replace timestamps with string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "042f66dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = trades[2].bars_underlying.copy()\n",
    "\n",
    "df['time'] = df['time'].astype(str)\n",
    "\n",
    "print(type(df['time'].iloc[0]))\n",
    "\n",
    "\n",
    "# make fiuge\n",
    "fig = go.Figure(data=[go.Line(x=df['time'],y=df['close'])])\n",
    "                #open=df['close'], high=df['close'],\n",
    "                #low=df['close'], close=df['close'])\n",
    "                # $     ])\n",
    "\n",
    "\n",
    "fig.update_layout(yaxis_title='AAPL Stock')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cb2fa67",
   "metadata": {},
   "source": [
    "## Method: Change time to integers, then provide custom axis labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88ee5d5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "MARKET_DAY_MINUTES = (6 * 60 + 30)\n",
    "MARKET_DAY_START = (9 * 60 + 30)\n",
    "TICK_SPACING = 30\n",
    "\n",
    "TICK_OFFSET = 0\n",
    "\n",
    "\n",
    "def show_graphs( dfs ):\n",
    "    \n",
    "    fig = make_subplots(rows = len(dfs),cols = 1,shared_xaxes=False)\n",
    "\n",
    "    hoverdata = []\n",
    "    \n",
    "    tickpos = []\n",
    "    ticktext = []\n",
    "    indexes = []\n",
    "    trace = []\n",
    "\n",
    "    \n",
    "    for plotnum,dfn in enumerate(dfs):\n",
    "        \n",
    "        \n",
    "        df = dfn.copy()\n",
    "        \n",
    "        col_name = df.columns[-1]\n",
    "\n",
    "\n",
    "        def convert_time_to_minute_index(df,date,day_num):\n",
    "    \n",
    "            day_base = day_num * MARKET_DAY_MINUTES \n",
    "    \n",
    "            df_date = df[df['time'].apply(lambda x: x.date() == date)].copy()\n",
    "    \n",
    "            df_date['time'] = df_date['time'].apply( lambda x: x.time().hour * 60 + x.time().minute)\n",
    "\n",
    "            df_date['time'] = df_date['time'] - MARKET_DAY_START + day_base\n",
    "    \n",
    "            return list(df_date['time'])\n",
    "\n",
    "        def get_axis_ticks(date,day_num,offset):\n",
    "    \n",
    "            tickpos = []\n",
    "            ticktext = []\n",
    "        \n",
    "            day_base = day_num * MARKET_DAY_MINUTES\n",
    "        \n",
    "            day_ticks = [ x for x in range(0,MARKET_DAY_MINUTES)]\n",
    "        \n",
    "            for i,day_tick in enumerate(day_ticks):\n",
    "                if not day_tick % TICK_SPACING:\n",
    "                    tickpos.append(i + day_base + TICK_OFFSET)\n",
    "                    day_minute = day_tick + MARKET_DAY_START\n",
    "                    hour = int(day_minute/60)\n",
    "                    t = time( hour,day_minute - hour*60)\n",
    "                    t = datetime.combine(date,t)\n",
    "                \n",
    "                    if not i:\n",
    "                        if not day_num:\n",
    "                            ticktext.append(t.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "                        else:\n",
    "                            ticktext.append(t.strftime(\"%m-%d %H:%M\"))\n",
    "                    else:\n",
    "                        ticktext.append(t.strftime(\"%H:%M\"))\n",
    "                    \n",
    "            return tickpos,ticktext\n",
    "\n",
    "        indexes.append([])\n",
    "        \n",
    "        tickpos.append([])\n",
    "        ticktext.append([])\n",
    "        hoverdata.append([])\n",
    "\n",
    "        hoverdata[plotnum].append(df['time'].apply(lambda x: x.strftime(\"%H:%M\")))\n",
    "        \n",
    "\n",
    "        offset_time = df['time'].iloc[0].time()\n",
    "        offset = offset_time.hour * 60 + offset_time.minute - MARKET_DAY_START\n",
    "\n",
    "        dates = df['time'].apply(lambda x: x.date()).unique()\n",
    "        for i,date in enumerate(dates):\n",
    "            minute_index = convert_time_to_minute_index(df,date,i)\n",
    "            indexes[plotnum].extend(minute_index)\n",
    "            pos,text = get_axis_ticks(date,i,offset)\n",
    "            tickpos[plotnum].extend(pos.copy())\n",
    "            ticktext[plotnum].extend(text.copy())\n",
    "    \n",
    "        df['time'] = indexes[plotnum]\n",
    "\n",
    "#        trace = go.Figure(data=[go.Scatter(x=df['time'],y=df['close'],\n",
    "#                                     #customdata=customdata,\n",
    "#                                     #hovertemplate='z1:%{customdata[0]:.3f}',\n",
    "#                                     hovertext = hoverdata,\n",
    "#                                     hoverlabel=dict(namelength=0),\n",
    "#                                     hovertemplate='%{hovertext}<br>%{x}<br>%{y:.2f}',\n",
    "#                                     #mode='lines',  # without mode, defaults to line+markers\n",
    "#                                     line_color = 'blue')])\n",
    "        \n",
    "        trace.append(go.Scatter(x=df['time'],y=df[col_name],\n",
    "                                     #customdata=customdata,\n",
    "                                     #hovertemplate='z1:%{customdata[0]:.3f}',\n",
    "                                     hovertext = hoverdata[plotnum],\n",
    "                                     hoverlabel=dict(namelength=0),\n",
    "                                     hovertemplate='%{hovertext[plotnum]}<br>%{x}<br>%{y:.2f}',\n",
    "                                     #mode='lines',  # without mode, defaults to line+markers\n",
    "                                     line_color = 'blue'))\n",
    "\n",
    "\n",
    "\n",
    "#        trace.update_layout(yaxis_title='AAPL Stock',\n",
    "#                     xaxis = dict(tickangle = 45,\n",
    "#                                 tickmode = 'array',\n",
    "#                                  tickvals = tickpos,\n",
    "#                                 ticktext = ticktext))\n",
    "        \n",
    "        fig.append_trace(trace[plotnum],row = plotnum+1,col =1)\n",
    "        \n",
    "        sym = df.iloc[0]['symbol']\n",
    "        \n",
    "        fig.update_layout(yaxis_title=sym,xaxis = dict(tickangle = 45,\n",
    "                        tickmode = 'array',\n",
    "                        tickvals = tickpos[plotnum],\n",
    "                        ticktext = ticktext[plotnum]))\n",
    "        \n",
    "        #trace.show()\n",
    "        \n",
    "\n",
    "    fig.show()\n",
    "    \n",
    "\n",
    "data = {'time':[datetime(2020,2,3,10,0),\n",
    "                datetime(2020,2,3,10,15),\n",
    "                datetime(2020,2,3,11,22),\n",
    "                datetime(2020,2,3,13,10),\n",
    "                \n",
    "                datetime(2020,2,4,9,31),\n",
    "                datetime(2020,2,4,13,30),\n",
    "                datetime(2020,2,4,14,24),\n",
    "                datetime(2020,2,4,16,0),\n",
    "                \n",
    "                datetime(2020,2,5,9,31),\n",
    "                datetime(2020,2,5,11,22),\n",
    "                datetime(2020,2,5,13,50),\n",
    "                datetime(2020,2,5,16,00)\n",
    "               ],\n",
    "        \n",
    "        'close':[1,2,3,4,5,6,7,8,9,10,11,12]}\n",
    "\n",
    "#df = pd.DataFrame(data)\n",
    "\n",
    "df = trades[190]\n",
    "\n",
    "\n",
    "\n",
    "show_graphs([df.bars_premium,df.bars_underlying])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "498fa901",
   "metadata": {},
   "outputs": [],
   "source": [
    "show_graphs([df.bars_underlying])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bad212d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "data = {'time':[datetime(2020,2,3,9,45),\n",
    "                datetime(2020,2,3,10,15),\n",
    "                datetime(2020,2,3,11,22),\n",
    "                datetime(2020,2,3,13,10),\n",
    "                datetime(2020,2,4,10,1),\n",
    "                datetime(2020,2,4,13,30),\n",
    "                datetime(2020,2,4,14,34),\n",
    "                datetime(2020,2,4,16,30),\n",
    "                datetime(2020,2,5,9,31),\n",
    "                datetime(2020,2,5,11,22),\n",
    "                datetime(2020,2,5,13,50),\n",
    "                datetime(2020,2,5,13,30)\n",
    "               ],\n",
    "        \n",
    "        'close':[1,2,3,4,5,6,7,8,9,10,11,12]}\n",
    "\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e94ecb08",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4330d1e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "time(4,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a0e6c9cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "datetime.combine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe64acd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = trades[2]\n",
    "df.bars_premium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79a83638",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.bars_underlying"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1fdb98c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "int_times = np.intersect1d(df.bars_buy.time,df.bars_sell.time)\n",
    "print(len(int_times))\n",
    "print(len(df.bars_buy))\n",
    "print(len(df.bars_sell))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02d5f3ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "common_buy = df.bars_buy[df.bars_buy['time'] == int_times]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "126e54ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "commen_sell = df.bars_sell[df.bars_sell['time'] == int_times]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da5aab6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = pd.merge(df.bars_sell,df.bars_buy, how='inner', on=['time'])\n",
    "s1.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5bfee5df",
   "metadata": {},
   "outputs": [],
   "source": [
    "frame = { 'time': s1['time'],'mid': s1['mid_x'] - s1['mid_y']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ea4cb14",
   "metadata": {},
   "outputs": [],
   "source": [
    "result = pd.DataFrame(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e8a89bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8392236a",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = pd.merge(df.bars_sell,df.bars_buy, how='inner', on=['time'])\n",
    "s1.dropna(inplace=True)\n",
    "frame = { 'time': s1['time'],'mid': s1['mid_x'] - s1['mid_y']}\n",
    "result = pd.DataFrame(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92bfc692",
   "metadata": {},
   "outputs": [],
   "source": [
    "trades[2].bars_premium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e033a46",
   "metadata": {},
   "outputs": [],
   "source": [
    "trades[3].bars_premium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79c94ae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"/home/cc/Dropbox/option_bars.json\",'r') as infile:\n",
    "    json.load(infile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e096ec53",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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