{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "59d19f73",
   "metadata": {},
   "source": [
    "# US Arb Freight Breakevens vs Spot Freight Rates\n",
    "\n",
    "This script is used to compare the US Arb Freight Breakevens with Spark30S Spot Freight Rates.\n",
    "\n",
    "For a full explanation of how to import our Arb Breakevens or Spark30S data, please refer to our Python Jupyter Notebook Code Samples:\n",
    "\n",
    "https://www.sparkcommodities.com/api/code-examples/jupyter.html\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a05be4",
   "metadata": {},
   "source": [
    "### Have any questions?\n",
    "\n",
    "If you have any questions regarding our API, or need help accessing specific datasets, please contact us at:\n",
    "\n",
    "__data@sparkcommodities.com__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e00ae34",
   "metadata": {},
   "source": [
    "## 1. Importing Data\n",
    "\n",
    "Here we define the functions that allow us to retrieve the valid credentials to access the Spark API.\n",
    "\n",
    "__This section can remain unchanged for most Spark API users.__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "705cbb25",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries for calling the API\n",
    "import json\n",
    "import os\n",
    "import sys\n",
    "import pandas as pd\n",
    "from base64 import b64encode\n",
    "from urllib.parse import urljoin\n",
    "\n",
    "\n",
    "try:\n",
    "    from urllib import request, parse\n",
    "    from urllib.error import HTTPError\n",
    "except ImportError:\n",
    "    raise RuntimeError(\"Python 3 required\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1161e807",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining functions for API request\n",
    "\n",
    "API_BASE_URL = \"https://api.sparkcommodities.com\"\n",
    "\n",
    "\n",
    "def retrieve_credentials(file_path=None):\n",
    "    \"\"\"\n",
    "    Find credentials either by reading the client_credentials file or reading\n",
    "    environment variables\n",
    "    \"\"\"\n",
    "    if file_path is None:\n",
    "        client_id = os.getenv(\"SPARK_CLIENT_ID\")\n",
    "        client_secret = os.getenv(\"SPARK_CLIENT_SECRET\")\n",
    "        if not client_id or not client_secret:\n",
    "            raise RuntimeError(\n",
    "                \"SPARK_CLIENT_ID and SPARK_CLIENT_SECRET environment vars required\"\n",
    "            )\n",
    "    else:\n",
    "        # Parse the file\n",
    "        if not os.path.isfile(file_path):\n",
    "            raise RuntimeError(\"The file {} doesn't exist\".format(file_path))\n",
    "\n",
    "        with open(file_path) as fp:\n",
    "            lines = [l.replace(\"\\n\", \"\") for l in fp.readlines()]\n",
    "\n",
    "        if lines[0] in (\"clientId,clientSecret\", \"client_id,client_secret\"):\n",
    "            client_id, client_secret = lines[1].split(\",\")\n",
    "        else:\n",
    "            print(\"First line read: '{}'\".format(lines[0]))\n",
    "            raise RuntimeError(\n",
    "                \"The specified file {} doesn't look like to be a Spark API client \"\n",
    "                \"credentials file\".format(file_path)\n",
    "            )\n",
    "\n",
    "    print(\">>>> Found credentials!\")\n",
    "    print(\n",
    "        \">>>> Client_id={}, client_secret={}****\".format(client_id, client_secret[:5])\n",
    "    )\n",
    "\n",
    "    return client_id, client_secret\n",
    "\n",
    "\n",
    "def do_api_post_query(uri, body, headers):\n",
    "    \"\"\"\n",
    "    OAuth2 authentication requires a POST request with client credentials before accessing the API. \n",
    "    This POST request will return an Access Token which will be used for the API GET request.\n",
    "    \"\"\"\n",
    "    url = urljoin(API_BASE_URL, uri)\n",
    "\n",
    "    data = json.dumps(body).encode(\"utf-8\")\n",
    "\n",
    "    # HTTP POST request\n",
    "    req = request.Request(url, data=data, headers=headers)\n",
    "    try:\n",
    "        response = request.urlopen(req)\n",
    "    except HTTPError as e:\n",
    "        print(\"HTTP Error: \", e.code)\n",
    "        print(e.read())\n",
    "        sys.exit(1)\n",
    "\n",
    "    resp_content = response.read()\n",
    "\n",
    "    # The server must return HTTP 201. Raise an error if this is not the case\n",
    "    assert response.status == 201, resp_content\n",
    "\n",
    "    # The server returned a JSON response\n",
    "    content = json.loads(resp_content)\n",
    "\n",
    "    return content\n",
    "\n",
    "\n",
    "def do_api_get_query(uri, access_token, format='json'):\n",
    "    \"\"\"\n",
    "    After receiving an Access Token, we can request information from the API.\n",
    "    \"\"\"\n",
    "    url = urljoin(API_BASE_URL, uri)\n",
    "\n",
    "    if format == 'json':\n",
    "        headers = {\n",
    "            \"Authorization\": \"Bearer {}\".format(access_token),\n",
    "            \"Accept\": \"application/json\",\n",
    "        }\n",
    "    elif format == 'csv':\n",
    "        headers = {\n",
    "            \"Authorization\": \"Bearer {}\".format(access_token),\n",
    "            \"Accept\": \"text/csv\"\n",
    "        }\n",
    "\n",
    "    #headers = {\n",
    "    #    \"Authorization\": \"Bearer {}\".format(access_token),\n",
    "    #    \"Accept\": \"application/json\",\n",
    "    #}\n",
    "\n",
    "    # HTTP POST request\n",
    "    req = request.Request(url, headers=headers)\n",
    "    try:\n",
    "        response = request.urlopen(req)\n",
    "    except HTTPError as e:\n",
    "        print(\"HTTP Error: \", e.code)\n",
    "        print(e.read())\n",
    "        sys.exit(1)\n",
    "\n",
    "    resp_content = response.read()\n",
    "\n",
    "    # The server must return HTTP 201. Raise an error if this is not the case\n",
    "    assert response.status == 200, resp_content\n",
    "\n",
    "    # Storing response based on requested format\n",
    "    if format == 'json':\n",
    "        content = json.loads(resp_content)\n",
    "    elif format == 'csv':\n",
    "        content = resp_content\n",
    "\n",
    "    return content\n",
    "\n",
    "\n",
    "def get_access_token(client_id, client_secret):\n",
    "    \"\"\"\n",
    "    Get a new access_token. Access tokens are the thing that applications use to make\n",
    "    API requests. Access tokens must be kept confidential in storage.\n",
    "\n",
    "    # Procedure:\n",
    "\n",
    "    Do a POST query with `grantType` and `scopes` in the body. A basic authorization\n",
    "    HTTP header is required. The \"Basic\" HTTP authentication scheme is defined in\n",
    "    RFC 7617, which transmits credentials as `clientId:clientSecret` pairs, encoded\n",
    "    using base64.\n",
    "    \"\"\"\n",
    "\n",
    "    # Note: for the sake of this example, we choose to use the Python urllib from the\n",
    "    # standard lib. One should consider using https://requests.readthedocs.io/\n",
    "\n",
    "    payload = \"{}:{}\".format(client_id, client_secret).encode()\n",
    "    headers = {\n",
    "        \"Authorization\": b64encode(payload).decode(),\n",
    "        \"Accept\": \"application/json\",\n",
    "        \"Content-Type\": \"application/json\",\n",
    "    }\n",
    "    body = {\n",
    "        \"grantType\": \"clientCredentials\",\n",
    "        \"scopes\": \"read:netbacks,read:access,read:prices,read:routes\",\n",
    "    }\n",
    "\n",
    "    content = do_api_post_query(uri=\"/oauth/token/\", body=body, headers=headers)\n",
    "\n",
    "    print(\n",
    "        \">>>> Successfully fetched an access token {}****, valid {} seconds.\".format(\n",
    "            content[\"accessToken\"][:5], content[\"expiresIn\"]\n",
    "        )\n",
    "    )\n",
    "\n",
    "    return content[\"accessToken\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ada4f167",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the function for listing all netbacks\n",
    "def list_netbacks(access_token):\n",
    "\n",
    "    content = do_api_get_query(\n",
    "        uri=\"/v1.0/netbacks/reference-data/\", access_token=access_token\n",
    "    )\n",
    "\n",
    "    print(\">>>> All the routes you can fetch\")\n",
    "    tickers = []\n",
    "    fobPort_names = []\n",
    "\n",
    "    availablevia = []\n",
    "\n",
    "    for contract in content[\"data\"][\"staticData\"][\"fobPorts\"]:\n",
    "        tickers.append(contract[\"uuid\"])\n",
    "        fobPort_names.append(contract[\"name\"])\n",
    "\n",
    "        availablevia.append(contract[\"availableViaPoints\"])\n",
    "\n",
    "    reldates = content[\"data\"][\"staticData\"][\"sparkReleases\"]\n",
    "\n",
    "    dicto1 = content[\"data\"]\n",
    "\n",
    "    return tickers, fobPort_names, availablevia, reldates, dicto1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b46f962b",
   "metadata": {},
   "source": [
    "## N.B. Credentials\n",
    "\n",
    "Here we call the above functions, and input the file path to our credentials.\n",
    "\n",
    "N.B. You must have downloaded your client credentials CSV file before proceeding. Please refer to the API documentation if you have not dowloaded them already.  Instructions for downloading your credentials can be found here:\n",
    "\n",
    "https://api.sparkcommodities.com/redoc#section/Authentication/Create-an-Oauth2-Client\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3acdfe86",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>> Found credentials!\n",
      ">>>> Client_id=01c23590-ef6c-4a36-8237-c89c3f1a3b2a, client_secret=80763****\n",
      ">>>> Successfully fetched an access token eyJhb****, valid 604799 seconds.\n",
      "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ0eXBlIjoiYWNjZXNzVG9rZW4iLCJzdWIiOiIwMWMyMzU5MC1lZjZjLTRhMzYtODIzNy1jODljM2YxYTNiMmEiLCJzdWJUeXBlIjoib2F1dGgtY2xpZW50IiwiZXhwIjoxNzQ0MTE0MTI5LCJoYXNoZWRTZWNyZXQiOiJwYmtkZjJfc2hhMjU2JDYwMDAwMCRoTXRMNDlrMUZUaVVzTE42Njlqc2pPJHVCSXNxcml5b1NHVzJTS1AvaHVLNHh3eTZ4d3VDN001aUdGRm43N2l4S1U9Iiwib3JnVXVpZCI6IjQ5MzhiMGJiLTVmMjctNDE2NC04OTM4LTUyNTdmYmQzNTNmZiIsInNjb3BlcyI6WyJyZWFkOmFjY2VzcyIsInJlYWQ6cHJpY2VzIiwicmVhZDpyb3V0ZXMiLCJyZWFkOm5ldGJhY2tzIl0sImNsaWVudFR5cGUiOiJvYXV0aC1jbGllbnQifQ.29Nt_huWq6oV-H7R5j5aWpqgCdjP4COb-h3qqG2P6Mk\n"
     ]
    }
   ],
   "source": [
    "# Input the path to your client credentials here\n",
    "client_id, client_secret = retrieve_credentials(file_path=\"/tmp/client_credentials.csv\")\n",
    "\n",
    "# Authenticate:\n",
    "access_token = get_access_token(client_id, client_secret)\n",
    "print(access_token)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7adcc5ed",
   "metadata": {},
   "source": [
    "### Fetching Netbacks reference data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "aaefce45",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>> All the routes you can fetch\n"
     ]
    }
   ],
   "source": [
    "# Fetch all contracts:\n",
    "tickers, fobPort_names, availablevia, reldates, dicto1 = list_netbacks(access_token)\n",
    "\n",
    "# Define formatting data function\n",
    "def format_store(available_via, fob_names, tickrs):\n",
    "    dict_store = {\n",
    "        \"Index\": [],\n",
    "        \"Ports\": [],\n",
    "        \"Ticker\": [],\n",
    "        \"Available Via\": []\n",
    "    }\n",
    "    \n",
    "    c = 0\n",
    "    for a in available_via:\n",
    "        ## Check which routes have non-empty Netbacks data and save indices\n",
    "        if len(a) != 0:\n",
    "            dict_store['Index'].append(c)\n",
    "\n",
    "            # Use these indices to retrive the corresponding Netbacks info\n",
    "            dict_store['Ports'].append(fob_names[c])\n",
    "            dict_store['Ticker'].append(tickrs[c])\n",
    "            dict_store['Available Via'].append(available_via[c])\n",
    "        c += 1\n",
    "    # Show available Netbacks ports in a DataFrame (with corresponding indices)\n",
    "    dict_df = pd.DataFrame(dict_store)\n",
    "    return dict_df\n",
    "\n",
    "# Run formatting data function\n",
    "available_df = format_store(availablevia,fobPort_names,tickers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e447d6b2",
   "metadata": {},
   "source": [
    "## Fetching Netback UUID for an individual port"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "a4480909",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "003dec0a-ce8f-41db-8c24-4d7ef6addf70\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Qasim\\AppData\\Local\\Temp\\ipykernel_15628\\3472757705.py:5: FutureWarning: Calling int on a single element Series is deprecated and will raise a TypeError in the future. Use int(ser.iloc[0]) instead\n",
      "  ti = int(available_df[available_df[\"Ports\"] == port][\"Index\"])\n"
     ]
    }
   ],
   "source": [
    "# Choose route ID and price release date\n",
    "\n",
    "# Here we define which port we want\n",
    "port = \"Sabine Pass\"\n",
    "ti = int(available_df[available_df[\"Ports\"] == port][\"Index\"])\n",
    "my_ticker = tickers[ti]\n",
    "my_via = 'cogh'\n",
    "\n",
    "print(my_ticker)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d1bf4c0",
   "metadata": {},
   "source": [
    "## Data Import \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "eb563eb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Defining the function\n",
    "from io import StringIO\n",
    "\n",
    "def fetch_breakevens(access_token, ticker, nea_via=None, nwe_via=None, format='json'):\n",
    "    \n",
    "    query_params = \"?fob-port={}\".format(ticker)\n",
    "    if nea_via is not None:\n",
    "        query_params += \"&nea-via-point={}\".format(nea_via)\n",
    "    if nwe_via is not None:\n",
    "        query_params += \"&nwe-via-point={}\".format(nwe_via)\n",
    "    \n",
    "    \n",
    "    content = do_api_get_query(\n",
    "        uri=\"/beta/netbacks/arb-breakevens/{}\".format(query_params),\n",
    "        access_token=access_token, format=format,\n",
    "    )\n",
    "    \n",
    "    if format == 'json':\n",
    "        my_dict = content['data']\n",
    "    else:\n",
    "        my_dict = content.decode('utf-8')\n",
    "        my_dict = pd.read_csv(StringIO(my_dict))\n",
    "\n",
    "    return my_dict\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "30d317eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fetching data in CSV format\n",
    "\n",
    "break_df = fetch_breakevens(access_token, my_ticker, nea_via=my_via, format='csv')\n",
    "\n",
    "break_df['ReleaseDate'] = pd.to_datetime(break_df['ReleaseDate'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "a3336112",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
       "columns": [
        {
         "name": "index",
         "rawType": "int64",
         "type": "integer"
        },
        {
         "name": "FobPortSlug",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "NEAViaPoint",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "NWEViaPoint",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "ReleaseDate",
         "rawType": "datetime64[ns]",
         "type": "datetime"
        },
        {
         "name": "LoadMonthIndex",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "LoadMonthStartDate",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "LoadingDate",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "NEADeliveryDate",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "NWEDeliveryDate",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "ArbUSDPerMBBtu",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "FreightBreakevenUSDPerDay",
         "rawType": "int64",
         "type": "integer"
        },
        {
         "name": "JKMTTFSpreadBreakevenUSDPerMBBtu",
         "rawType": "float64",
         "type": "float"
        },
        {
         "name": "FobPortUUID",
         "rawType": "object",
         "type": "string"
        }
       ],
       "conversionMethod": "pd.DataFrame",
       "ref": "5be1471b-6751-4821-9ac6-910496232f48",
       "rows": [
        [
         "0",
         "sabine-pass",
         "cogh",
         null,
         "2025-03-31 00:00:00",
         "M+1",
         "2025-05",
         "2025-05-15",
         "2025-06-28",
         "2025-06-01",
         "-0.426",
         "-2000",
         "0.087",
         "003dec0a-ce8f-41db-8c24-4d7ef6addf70"
        ],
        [
         "1",
         "sabine-pass",
         "cogh",
         null,
         "2025-03-31 00:00:00",
         "M+2",
         "2025-06",
         "2025-06-15",
         "2025-07-29",
         "2025-07-02",
         "-0.393",
         "2000",
         "0.218",
         "003dec0a-ce8f-41db-8c24-4d7ef6addf70"
        ],
        [
         "2",
         "sabine-pass",
         "cogh",
         null,
         "2025-03-31 00:00:00",
         "M+3",
         "2025-07",
         "2025-07-15",
         "2025-08-28",
         "2025-08-01",
         "-0.441",
         "-750",
         "0.441",
         "003dec0a-ce8f-41db-8c24-4d7ef6addf70"
        ]
       ],
       "shape": {
        "columns": 13,
        "rows": 3
       }
      },
      "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>FobPortSlug</th>\n",
       "      <th>NEAViaPoint</th>\n",
       "      <th>NWEViaPoint</th>\n",
       "      <th>ReleaseDate</th>\n",
       "      <th>LoadMonthIndex</th>\n",
       "      <th>LoadMonthStartDate</th>\n",
       "      <th>LoadingDate</th>\n",
       "      <th>NEADeliveryDate</th>\n",
       "      <th>NWEDeliveryDate</th>\n",
       "      <th>ArbUSDPerMBBtu</th>\n",
       "      <th>FreightBreakevenUSDPerDay</th>\n",
       "      <th>JKMTTFSpreadBreakevenUSDPerMBBtu</th>\n",
       "      <th>FobPortUUID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sabine-pass</td>\n",
       "      <td>cogh</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-03-31</td>\n",
       "      <td>M+1</td>\n",
       "      <td>2025-05</td>\n",
       "      <td>2025-05-15</td>\n",
       "      <td>2025-06-28</td>\n",
       "      <td>2025-06-01</td>\n",
       "      <td>-0.426</td>\n",
       "      <td>-2000</td>\n",
       "      <td>0.087</td>\n",
       "      <td>003dec0a-ce8f-41db-8c24-4d7ef6addf70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sabine-pass</td>\n",
       "      <td>cogh</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-03-31</td>\n",
       "      <td>M+2</td>\n",
       "      <td>2025-06</td>\n",
       "      <td>2025-06-15</td>\n",
       "      <td>2025-07-29</td>\n",
       "      <td>2025-07-02</td>\n",
       "      <td>-0.393</td>\n",
       "      <td>2000</td>\n",
       "      <td>0.218</td>\n",
       "      <td>003dec0a-ce8f-41db-8c24-4d7ef6addf70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sabine-pass</td>\n",
       "      <td>cogh</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-03-31</td>\n",
       "      <td>M+3</td>\n",
       "      <td>2025-07</td>\n",
       "      <td>2025-07-15</td>\n",
       "      <td>2025-08-28</td>\n",
       "      <td>2025-08-01</td>\n",
       "      <td>-0.441</td>\n",
       "      <td>-750</td>\n",
       "      <td>0.441</td>\n",
       "      <td>003dec0a-ce8f-41db-8c24-4d7ef6addf70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   FobPortSlug NEAViaPoint  NWEViaPoint ReleaseDate LoadMonthIndex  \\\n",
       "0  sabine-pass        cogh          NaN  2025-03-31            M+1   \n",
       "1  sabine-pass        cogh          NaN  2025-03-31            M+2   \n",
       "2  sabine-pass        cogh          NaN  2025-03-31            M+3   \n",
       "\n",
       "  LoadMonthStartDate LoadingDate NEADeliveryDate NWEDeliveryDate  \\\n",
       "0            2025-05  2025-05-15      2025-06-28      2025-06-01   \n",
       "1            2025-06  2025-06-15      2025-07-29      2025-07-02   \n",
       "2            2025-07  2025-07-15      2025-08-28      2025-08-01   \n",
       "\n",
       "   ArbUSDPerMBBtu  FreightBreakevenUSDPerDay  \\\n",
       "0          -0.426                      -2000   \n",
       "1          -0.393                       2000   \n",
       "2          -0.441                       -750   \n",
       "\n",
       "   JKMTTFSpreadBreakevenUSDPerMBBtu                           FobPortUUID  \n",
       "0                             0.087  003dec0a-ce8f-41db-8c24-4d7ef6addf70  \n",
       "1                             0.218  003dec0a-ce8f-41db-8c24-4d7ef6addf70  \n",
       "2                             0.441  003dec0a-ce8f-41db-8c24-4d7ef6addf70  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "break_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "7a80e89c",
   "metadata": {},
   "outputs": [],
   "source": [
    "length = len(break_df['ReleaseDate'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de4957ed",
   "metadata": {},
   "source": [
    "# Fetching Spot Freight Prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "08ec1036",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_historical_price_releases(access_token, ticker, limit=4, offset=None, vessel=None):\n",
    "\n",
    "    query_params = \"?limit={}\".format(limit)\n",
    "    if offset is not None:\n",
    "        query_params += \"&offset={}\".format(offset)\n",
    "    \n",
    "    # '174-2stroke' or '160-tfde'\n",
    "    if vessel is not None:\n",
    "        query_params += \"&vessel-type={}\".format(vessel)\n",
    "        \n",
    "    print(\"/v1.0/contracts/{}/price-releases/{}\".format(ticker, query_params))\n",
    "        \n",
    "    content = do_api_get_query(\n",
    "        uri=\"/v1.0/contracts/{}/price-releases/{}\".format(ticker, query_params),\n",
    "        access_token=access_token,\n",
    "    )\n",
    "\n",
    "    my_dict = content['data']\n",
    "    \n",
    "    return my_dict\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "64897525",
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "def fetch_prices(ticker, my_lim, my_vessel=None):\n",
    "    my_dict_hist = fetch_historical_price_releases(access_token, ticker, limit=my_lim, vessel=my_vessel)\n",
    "    \n",
    "    release_dates = []\n",
    "    period_start = []\n",
    "    ticker = []\n",
    "    usd_day = []\n",
    "    usd_mmbtu = []\n",
    "\n",
    "    day_min = []\n",
    "    day_max = []\n",
    "    cal_month = []\n",
    "\n",
    "    for release in my_dict_hist:\n",
    "            release_date = release[\"releaseDate\"]\n",
    "            ticker.append(release['contractId'])\n",
    "\n",
    "            release_dates.append(release_date)\n",
    "\n",
    "            data_points = release[\"data\"][0][\"dataPoints\"]\n",
    "\n",
    "            for data_point in data_points:\n",
    "                period_start_at = data_point[\"deliveryPeriod\"][\"startAt\"]\n",
    "                period_start.append(period_start_at)\n",
    "\n",
    "                usd_day.append(data_point['derivedPrices']['usdPerDay']['spark'])\n",
    "                day_min.append(data_point['derivedPrices']['usdPerDay']['sparkMin'])\n",
    "                day_max.append(data_point['derivedPrices']['usdPerDay']['sparkMax'])\n",
    "\n",
    "                usd_mmbtu.append(data_point['derivedPrices']['usdPerMMBtu']['spark'])\n",
    "                cal_month.append(datetime.datetime.strptime(period_start_at, '%Y-%m-%d').strftime('%b-%Y'))\n",
    "\n",
    "\n",
    "\n",
    "    ## Storing values in a Pandas DataFrame\n",
    "\n",
    "    historical_df = pd.DataFrame({\n",
    "        'ticker': ticker,\n",
    "        'Period Start': period_start,\n",
    "        'USDperday': usd_day,\n",
    "        'USDperdayMax': day_max,\n",
    "        'USDperdayMin': day_min,\n",
    "        'USDperMMBtu': usd_mmbtu,\n",
    "        'Release Date': release_dates})\n",
    "\n",
    "    historical_df['USDperday'] = pd.to_numeric(historical_df['USDperday'])\n",
    "    historical_df['USDperdayMax'] = pd.to_numeric(historical_df['USDperdayMax'])\n",
    "    historical_df['USDperdayMin'] = pd.to_numeric(historical_df['USDperdayMin'])\n",
    "    historical_df['USDperMMBtu'] = pd.to_numeric(historical_df['USDperMMBtu'])\n",
    "\n",
    "    historical_df['Release Datetime'] = pd.to_datetime(historical_df['Release Date'])\n",
    "    \n",
    "    return historical_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "efcb7515",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/v1.0/contracts/spark30s/price-releases/?limit=902&vessel-type=174-2stroke\n"
     ]
    }
   ],
   "source": [
    "spark30_174 = fetch_prices('spark30s', length, my_vessel='174-2stroke')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3567b011",
   "metadata": {},
   "source": [
    "# Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "1fd3546a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fetch front month breakevens only\n",
    "front_df = break_df[break_df['LoadMonthIndex']==\"M+1\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "6c736ee6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e55e1653d0>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "ax.plot(spark30_174['Release Datetime'],spark30_174['USDperday'], color = '#48C38D', linewidth=2.5, label='Spark30S (Atlantic)')\n",
    "ax.plot(front_df['ReleaseDate'],front_df['FreightBreakevenUSDPerDay'], color='#4F41F4', linewidth=2, label='US Arb [M+1] Freight Breakeven Level')\n",
    "\n",
    "ax.set_xlim(datetime.datetime.today() - datetime.timedelta(days=380), datetime.datetime.today())\n",
    "ax.set_ylim(-100000, 120000)\n",
    "\n",
    "plt.title('Spark30S (Atlantic) vs. US Arb [M+1] Freight Breakeven Level')\n",
    "\n",
    "sns.despine(left=True, bottom=True)\n",
    "plt.grid(True)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5002787",
   "metadata": {},
   "source": [
    "## Plotting with Conditional Shading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "76361e74",
   "metadata": {},
   "outputs": [],
   "source": [
    "spark30_174['Release Date'] = pd.to_datetime(spark30_174['Release Date'])\n",
    "merge_df = pd.merge(spark30_174, front_df, left_on='Release Date', right_on='ReleaseDate', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "328faa9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e55da18cd0>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2, ax2 = plt.subplots(figsize=(15,7))\n",
    "\n",
    "ax2.plot(merge_df['Release Date'],merge_df['USDperday'], color = '#48C38D', linewidth=2.5, label='Spark30S (Atlantic)')\n",
    "ax2.plot(merge_df['Release Date'],merge_df['FreightBreakevenUSDPerDay'], color='#4F41F4', linewidth=2, label='US Arb [M+1] Freight Breakeven Level')\n",
    "\n",
    "ax2.fill_between(merge_df['Release Date'], merge_df['USDperday'], merge_df['FreightBreakevenUSDPerDay'], \\\n",
    "                where=merge_df['USDperday']>merge_df['FreightBreakevenUSDPerDay'], facecolor='red', interpolate=True, alpha=0.05)\n",
    "\n",
    "ax2.fill_between(merge_df['Release Date'], merge_df['USDperday'], merge_df['FreightBreakevenUSDPerDay'], \\\n",
    "                where=merge_df['USDperday']<merge_df['FreightBreakevenUSDPerDay'], facecolor='green', interpolate=True, alpha=0.05)\n",
    "\n",
    "ax2.set_xlim(datetime.datetime.today() - datetime.timedelta(days=380), datetime.datetime.today())\n",
    "ax2.set_ylim(-100000, 120000)\n",
    "\n",
    "plt.title('Spark30S (Atlantic) vs. US Arb [M+1] Freight Breakeven Level')\n",
    "\n",
    "sns.despine(left=True, bottom=True)\n",
    "plt.grid(True)\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}