{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1de1cc57-e5ec-42eb-af3a-e9f95160b810",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import the library\n",
    "import webmo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "decf682e-646d-412e-9e68-ccb8f58c9708",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter WebMO password for user smith: ········\n"
     ]
    }
   ],
   "source": [
    "# start a REST session\n",
    "URL = \"https://server.university.edu/~webmo/cgi-bin/webmo/rest.cgi\"\n",
    "Username = \"smith\"\n",
    "rest = webmo.WebMOREST(URL, username=Username)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fbe34985-da61-4cdf-92fd-1b4750880366",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Set a job ID\n",
    "job_number = 37"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c9e2c498-4f44-4ca5-b6c7-c237ceccc4e8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Energy: -113.866331244 Hartree\n"
     ]
    }
   ],
   "source": [
    "# Get its energy\n",
    "results = rest.get_job_results(job_number)\n",
    "energy = results['properties']['rhf_energy']['value']\n",
    "units = results['properties']['rhf_energy']['units']\n",
    "print(\"Energy: {} {}\".format(energy, units))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "39495f3b-1036-4e3f-b23c-c6c03343ddd0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<webmo.webmo_rest.EmbeddedImage object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display its geometry\n",
    "await rest.display_job_property(job_number, \"geometry\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}