{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fugitive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Table of contents**\n",
    "- Overview\n",
    "- Setup\n",
    "  - Authentication Token\n",
    "- Query\n",
    "  - Output Description\n",
    "- Related Links"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Scope 1 emissions are calculations of direct greenhouse gas emissions that can be directly controlled by an organization. The source of the emissions is owned by the organization, for example, fossil fuels.\n",
    "\n",
    "Use the Fugitive API to calculate emissions leaks of greenhouse gasses from refrigeration or air conditioning units.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ensure that Python 3+ is installed on your system.\n",
    "\n",
    "\n",
    "<b>Note:</b> To run this notebook, you must first add your credentials to `'../../../auth/secrets.ini'` in the following format:\n",
    "\n",
    "```\n",
    "[EAPI]\n",
    "api.api_key = <Your Emissions API Key>\n",
    "api.tenant_id = <Your Emissions API Tenant Id>\n",
    "api.org_id = <Your Emissions API Org Id>\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install the prerequisite Python packages\n",
    "%pip install pandas configparser IPython requests matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import configparser\n",
    "import requests\n",
    "import json\n",
    "from IPython.display import display as display_summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Authorization Token"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the following code snippet to generate a Bearer Token by using your api_key configured in secrets.ini."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Authentication Success\n"
     ]
    }
   ],
   "source": [
    "config = configparser.RawConfigParser()\n",
    "config.read(['../../../auth/secrets.ini','../../../auth/config.ini'])\n",
    "\n",
    "EAPI_API_KEY        = config.get('EAPI', 'api.api_key')\n",
    "EAPI_TENANT_ID      = config.get('EAPI', 'api.tenant_id')\n",
    "EAPI_CLIENT_ID      = 'ghgemissions-' + EAPI_TENANT_ID\n",
    "EAPI_ORG_ID         = config.get('EAPI', 'api.org_id')\n",
    "\n",
    "EAPI_AUTH_CLIENT_ID = 'saascore-' + EAPI_TENANT_ID\n",
    "EAPI_AUTH_ENDPOINT  = config.get('EAPI', 'api.auth_endpoint')\n",
    "\n",
    "EAPI_BASE_URL       = config.get('EAPI', 'api.base_url')\n",
    "EAPI_ENDPOINT       = f\"{EAPI_BASE_URL}/fugitive\"\n",
    "\n",
    "auth_request_headers: dict = {}\n",
    "auth_request_headers[\"X-IBM-Client-Id\"] = EAPI_AUTH_CLIENT_ID\n",
    "auth_request_headers[\"X-API-Key\"] = EAPI_API_KEY\n",
    "\n",
    "verify = True\n",
    "\n",
    "auth_url = f\"{EAPI_AUTH_ENDPOINT}?orgId={EAPI_ORG_ID}\"\n",
    "              \n",
    "response = requests.get(url = auth_url,\n",
    "                        headers = auth_request_headers,\n",
    "                        verify  = verify\n",
    "                       )\n",
    "if response.status_code == 200:\n",
    "    jwt_token = response.text\n",
    "    print(\"Authentication Success\")\n",
    "else:     \n",
    "    print(\"Authentication Failed\")\n",
    "    print(response.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Query"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The example request payload (below) queries IBM Envizi - Emissions API for 1 kilogram (kg) of leaked R-404A in the state of New York, United States of America for 2025-01-01:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "payload = {\n",
    "  \"activity\": {\n",
    "    \"type\": \"R-404A\",\n",
    "    \"value\": 1,\n",
    "    \"unit\": \"kg\"\n",
    "  },\n",
    "  \"location\": {\n",
    "    \"country\": \"USA\",\n",
    "    \"stateProvince\": \"New York\"\n",
    "  },\n",
    "  \"time\": {\n",
    "    \"date\": \"2025-01-01\"\n",
    "  }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the query headers\n",
    "request_headers: dict = {}\n",
    "request_headers[\"Content-Type\"] = \"application/json\"\n",
    "request_headers[\"x-ibm-client-id\"] = EAPI_CLIENT_ID\n",
    "request_headers[\"Authorization\"] = \"Bearer \" + jwt_token\n",
    "\n",
    "# Submit the request\n",
    "response = requests.post(EAPI_ENDPOINT, \n",
    "                         headers = request_headers, \n",
    "                         data = json.dumps(payload))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more information about allowable parameters for the payload, please see [Emissions API Developer Guide]()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>transactionId</th>\n",
       "      <th>totalCO2e</th>\n",
       "      <th>HFC</th>\n",
       "      <th>unit</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bf34f5f0-fb11-4264-883c-3dccc57be7a5</td>\n",
       "      <td>4728</td>\n",
       "      <td>4728</td>\n",
       "      <td>kgCO2e</td>\n",
       "      <td>The R-404A emissions factor used to calculate this result was obtained from the  GHG - AR6 factor set for the area Earth.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "                          transactionId  totalCO2e   HFC    unit  \\\n",
       "0  bf34f5f0-fb11-4264-883c-3dccc57be7a5       4728  4728  kgCO2e   \n",
       "\n",
       "                                                                                                                 description  \n",
       "0  The R-404A emissions factor used to calculate this result was obtained from the  GHG - AR6 factor set for the area Earth.  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if response.text != \"\":\n",
    "    # Get the response as json\n",
    "    response_json = response.json()\n",
    "    \n",
    "    # Get json and convert to dataframe\n",
    "    json_str = json.dumps(response_json)\n",
    "    dict = json.loads(json_str)\n",
    "    dataframe = pd.json_normalize(dict) \n",
    "    \n",
    "    # display\n",
    "    print(\"\\n\\n\")\n",
    "    pd.set_option('display.max_colwidth', None)\n",
    "    display( dataframe) \n",
    "else:\n",
    "    print(\"Empty Response\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Output Explanation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>transactionId</b> - An Emissions API transaction id.\n",
    "\n",
    "<b>totalCO2e</b>     - The total emissions as CO<sub>2</sub> equivalent (CO<sub>2</sub>e)\n",
    "\n",
    "<b>co2</b>           - The amount of CO<sub>2</sub> (Carbon Dioxide) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>ch4</b>           - The amount of CH<sub>4</sub> (Methane) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>n2O</b>           - The amount of N<sub>2</sub>O (Nitrous Oxide) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>hfc</b>           - The amount of HFCs (Hydrofluorocarbons) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>pfc</b>           - The amount of PFCs (Perfluorocarbons) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>sf6</b>           - The amount of SF<sub>6</sub> (Sulphur Hexafluoride) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>nf3</b>           - The amount of NF<sub>3</sub> (Nitrogen Trifluoride) in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>bioCo2</b>        - The amount of bio CO<sub>2</sub> in the CO<sub>2</sub> value.\n",
    "\n",
    "<b>indirectCo2e</b>  - The amount of CO<sub>2</sub>e that is indirect in the CO<sub>2</sub>e value.\n",
    "\n",
    "<b>unit</b>          - The unit of measure of the values.\n",
    "\n",
    "<b>description</b>   - A description of the source factor set of the factor used in the calculation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Related Links"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Emissions API Developer Guide]()"
   ]
  }
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