ORPA-pyOpenRPA/Tools/Jupyter-notebooks/Quickstart/.ipynb_checkpoints/Robot-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Робот: быстрый запуск (quickstart) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Уважаемый пользователь! Данный файл содержит набор преднастроенных команд для ускоренной проверки гипотез роботизации. В"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Box(left=550, top=244, width=29, height=29), Box(left=550, top=298, width=29, height=29), Box(left=550, top=352, width=29, height=29), Box(left=550, top=406, width=29, height=29), Box(left=550, top=460, width=29, height=29), Box(left=550, top=514, width=29, height=29), Box(left=550, top=568, width=29, height=29), Box(left=550, top=622, width=29, height=29), Box(left=550, top=676, width=29, height=29), Box(left=550, top=730, width=29, height=29), Box(left=550, top=784, width=29, height=29), Box(left=550, top=838, width=29, height=29)]\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import os\n",
    "sys.path.insert(0, os.path.abspath(\"..\\\\..\\\\Sources\"))\n",
    "sys.path.insert(0, os.path.abspath(\"..\\\\..\\\\..\\\\KPI_Effect\\\\packages\"))\n",
    "import time\n",
    "from pyOpenRPA.Robot import Keyboard\n",
    "\n",
    "# Screen: Взаимодействие с объектами экрана\n",
    "from pyOpenRPA.Robot import Screen\n",
    "lBoxList = Screen.ImageLocateAll(inImgPathStr=\"screencontact.PNG\",inConfidenceFloat=0.9)\n",
    "print(lBoxList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ИМПОРТ ДИРЕКТОРИИ\n",
    "import sys\n",
    "import os\n",
    "sys.path.insert(0, os.path.abspath(\"..\\\\..\\\\..\\\\KPI_Effect\\\\packages\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Box(left=500, top=244, width=29, height=29), Box(left=500, top=298, width=29, height=29), Box(left=500, top=352, width=29, height=29), Box(left=500, top=406, width=29, height=29), Box(left=500, top=460, width=29, height=29), Box(left=500, top=514, width=29, height=29), Box(left=500, top=568, width=29, height=29), Box(left=500, top=622, width=29, height=29), Box(left=500, top=676, width=29, height=29), Box(left=500, top=730, width=29, height=29), Box(left=500, top=784, width=29, height=29), Box(left=500, top=838, width=29, height=29)]\n"
     ]
    }
   ],
   "source": [
    "lBox2List = Screen.BoxMoveTo(inBox=lBoxList,inDXInt=-50)\n",
    "print(lBox2List)\n",
    "Screen.BoxDraw(inBox = lBox2List)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "lPoint = Screen.BoxGetPoint(lBox2List[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Screen.PointClick(lPoint)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Box(left=489, top=243, width=46, height=32)]\n"
     ]
    }
   ],
   "source": [
    "lBoxList = Screen.ImageLocateAll(inImgPathStr=\"sendmessage.PNG\",inConfidenceFloat=0.9)\n",
    "print(lBoxList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Screen.PointClick(Screen.BoxGetPoint(Screen.ImageLocateAll(inImgPathStr=\"sendmessage.PNG\",inConfidenceFloat=0.9)[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Box(left=169, top=193, width=409, height=687)]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Screen.ImageLocateAll(inImgPathStr=\"emptytray.PNG\",inConfidenceFloat=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import importlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "123\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<module 'pak.test' from 'C:\\\\Abs\\\\Archive\\\\scopeSrcUL\\\\pyOpenRPA\\\\Tools\\\\Jupyter-notebooks\\\\pak\\\\test.py'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importlib.import_module(\".test\",\"pak\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'pak' (namespace)>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sys.modules[\"pak\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2022, 9, 26, 20, 58, 26, 931399)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.datetime.now()+datetime.timedelta(hours=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.timedelta(seconds=10800)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.timedelta(hours=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2022-09-26 17:59:17'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g_datetime_format_str = '%Y-%m-%d %H:%M:%S'\n",
    "(datetime.datetime.now()).strftime(g_datetime_format_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2022, 9, 26, 18, 1, 58, 924492)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.datetime.fromtimestamp(time.time())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\".endswith(\"/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "cannot import name 'kpi_client' from '__main__' (unknown location)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-15-2f86ae4ce68c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mkpi_client\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m: cannot import name 'kpi_client' from '__main__' (unknown location)"
     ]
    }
   ],
   "source": [
    "from . import kpi_client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ИМПОРТ ДИРЕКТОРИИ\n",
    "import sys\n",
    "import os\n",
    "sys.path.insert(0, os.path.abspath(\"..\\\\..\\\\..\\\\KPI_Effect\\\\packages\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import kpi_client\n",
    "kpi_client.init(\"http://localhost:1024\", \"1992-04-03-0643-ru-b4ff-openrpa52zzz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------START-----------\n",
      "POST http://localhost:1024/orpa/api/activity-list-execute\r\n",
      "Content-Type: application/x-www-form-urlencoded; charset=UTF-8\r\n",
      "Cookie: AuthToken=1992-04-03-0643-ru-b4ff-openrpa52zzz\r\n",
      "Content-Length: 466\r\n",
      "\r\n",
      "b'[{\"Def\": \"kpi_control_panel.actions.log\", \"ArgList\": [], \"ArgDict\": {\"in_code_str\": \"asd\", \"in_group_str\": \"\\\\u041f\\\\u0440\\\\u0438\\\\u0432\\\\u0435\\\\u0442!\", \"in_manual_operation_float\": 190, \"in_auto_operation_float\": 88, \"in_start_time_float\": 123124, \"in_comment_str\": \"-\", \"in_count_int\": 1, \"in_sla_percent_float\": 1.0, \"in_dev_next_mvp_float\": 1.0, \"in_revenue_float\": 0.0, \"in_fine_float\": 0.0, \"in_reputation_str\": \"-\"}, \"ArgGSettingsStr\": null, \"ArgLoggerStr\": null}]'\n"
     ]
    }
   ],
   "source": [
    "kpi_client.log(in_code_str=\"asd\",in_group_str=\"Привет!\",in_manual_operation_float=190, in_auto_operation_float=88, in_start_time_float=123124)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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