{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# European Regas Slots Availability vs US Front Month Arb\n",
    "\n",
    "This script allows you to plot European terminal slot availability levels against the Front Month US Arb, utilising Spark Access and Spark Cargo data.\n",
    "\n",
    "This script uses elements from our API code samples. If you'd like a more basic and informative example of how to pull data via the Spark API, please visit our Github or API website:\n",
    "\n",
    "- Github: https://github.com/spark-commodities/api-code-samples/blob/master/jupyter_notebooks/\n",
    "- API Website: https://www.sparkcommodities.com/api/code-examples/jupyter.html\n",
    "\n",
    "\n",
    "### 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__\n",
    "\n",
    "or refer to our API website for more information about this endpoint:\n",
    "https://www.sparkcommodities.com/api/request/access.html\n",
    "\n",
    "__N.B. This script requires both Cargo and Access subscriptions__"
   ]
  },
  {
   "cell_type": "markdown",
   "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": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries for importing data\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",
    "from pprint import pprint\n",
    "import requests\n",
    "from io import StringIO\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "try:\n",
    "    from urllib import request, parse\n",
    "    from urllib.error import HTTPError\n",
    "except ImportError:\n",
    "    raise RuntimeError(\"Python 3 required\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "\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(\n",
    "            client_id[:5], client_secret[:5]\n",
    "        )\n",
    "    )\n",
    "\n",
    "    return client_id, client_secret\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",
    "def do_api_get_query(uri, access_token):\n",
    "    url = urljoin(API_BASE_URL, uri)\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",
    "    # The server returned a JSON response\n",
    "    content = json.loads(resp_content)\n",
    "\n",
    "    return content\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\"]\n",
    "\n",
    "def list_netbacks(access_token):\n",
    "    \"\"\"\n",
    "    Fetch available routes. Return contract ticker symbols\n",
    "\n",
    "    # Procedure:\n",
    "\n",
    "    Do a GET query to /v1.0/routes/ with a Bearer token authorization HTTP header.\n",
    "    \"\"\"\n",
    "    content = do_api_get_query(uri=\"/v1.0/netbacks/reference-data/\", access_token=access_token)\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",
    "        \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\n",
    "    #return dicto1\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### N.B. 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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>> Found credentials!\n",
      ">>>> Client_id=875f4****, client_secret=6cdf8****\n",
      ">>>> Successfully fetched an access token eyJhb****, valid 604799 seconds.\n"
     ]
    }
   ],
   "source": [
    "# Insert file 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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Slots Data\n",
    "Importing historical slot data from the Spark API. For more information on pulling our regas slot data, please refer to our Spark API website: \n",
    "\n",
    "https://www.sparkcommodities.com/api/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to get the list of terminals and their uuids (as well as their start and latest release date)\n",
    "def get_terminal_list():\n",
    "    uri = urljoin(API_BASE_URL,'beta/terminal-slots/terminals/')\n",
    "    headers = {\n",
    "            \"Authorization\": \"Bearer {}\".format(access_token),\n",
    "            \"accept\": \"text/csv\"\n",
    "        }\n",
    "    response = requests.get(uri, headers=headers)\n",
    "    if response.status_code == 200:\n",
    "        df = response.content.decode('utf-8')\n",
    "        df = pd.read_csv(StringIO(df))\n",
    "    else:\n",
    "        print('Bad Request')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>TerminalUUID</th>\n",
       "      <th>TerminalCode</th>\n",
       "      <th>TerminalName</th>\n",
       "      <th>firstAvailableRelease</th>\n",
       "      <th>latestAvailableRelease</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00317185-978a-4df5-970c-2c28d3ab893c</td>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0031994e-f370-4927-ba88-a4e7a78c42db</td>\n",
       "      <td>zeebrugge</td>\n",
       "      <td>Zeebrugge</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00338f3f-8875-435d-87a9-f83d9a5c5241</td>\n",
       "      <td>dunkerque</td>\n",
       "      <td>Dunkerque</td>\n",
       "      <td>2024-11-15</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00344dd2-5608-4413-a2f4-c52c747a286a</td>\n",
       "      <td>dragon</td>\n",
       "      <td>Dragon</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>003497c6-ed32-412f-95ef-c3b1f962464e</td>\n",
       "      <td>brunsbuttel</td>\n",
       "      <td>Brunsbuttel</td>\n",
       "      <td>2024-05-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>00355021-dc45-4aaa-8178-a6dc360c07b9</td>\n",
       "      <td>olt-toscana</td>\n",
       "      <td>OLT Toscana</td>\n",
       "      <td>2024-10-02</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>00361ab8-f70d-4a08-8e45-e6eb5a0b8b2f</td>\n",
       "      <td>le-havre-fsru</td>\n",
       "      <td>Le Havre</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>003660ee-567d-4d23-9e43-2891509b7bfb</td>\n",
       "      <td>piombino-fsru</td>\n",
       "      <td>Piombino</td>\n",
       "      <td>2023-12-18</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0037d9e4-cf09-4f26-8934-f1e038e185ea</td>\n",
       "      <td>eems-energy-terminal</td>\n",
       "      <td>EemsEnergyTerminal</td>\n",
       "      <td>2024-09-05</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0038a35c-253f-44f5-a4e5-d5240d98039a</td>\n",
       "      <td>adriatic</td>\n",
       "      <td>Adriatic</td>\n",
       "      <td>2024-10-02</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>003b1adb-f810-443c-a971-c2a6b28cb5dc</td>\n",
       "      <td>fos-cavaou</td>\n",
       "      <td>Fos Cavaou</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>003b1d25-f4bd-43bf-9cf6-9bd38216fe0f</td>\n",
       "      <td>montoir</td>\n",
       "      <td>Montoir</td>\n",
       "      <td>2023-01-01</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>003b1d36-d72b-4331-888f-22b3f84c1cce</td>\n",
       "      <td>wilhelmshaven</td>\n",
       "      <td>Wilhelmshaven 1</td>\n",
       "      <td>2024-05-30</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>003bf9ab-2829-40a1-a83d-c32b764f21fd</td>\n",
       "      <td>south-hook</td>\n",
       "      <td>South Hook</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>003d153e-282a-47a1-bb0c-b4fe0bc62d38</td>\n",
       "      <td>inkoo</td>\n",
       "      <td>Inkoo</td>\n",
       "      <td>2024-04-19</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>003e3e70-3626-4124-8ee9-d3ec39678e8c</td>\n",
       "      <td>deutsche-ostsee</td>\n",
       "      <td>Deutsche Ostsee</td>\n",
       "      <td>2024-06-21</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>003f55df-08c7-4b6a-8597-fbe9e3f398f8</td>\n",
       "      <td>klaipeda</td>\n",
       "      <td>Klaipeda</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>003f577c-7058-4b50-9c94-c499c07ca080</td>\n",
       "      <td>gate</td>\n",
       "      <td>Gate</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>2025-01-15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            TerminalUUID          TerminalCode  \\\n",
       "0   00317185-978a-4df5-970c-2c28d3ab893c             grain-lng   \n",
       "1   0031994e-f370-4927-ba88-a4e7a78c42db             zeebrugge   \n",
       "2   00338f3f-8875-435d-87a9-f83d9a5c5241             dunkerque   \n",
       "3   00344dd2-5608-4413-a2f4-c52c747a286a                dragon   \n",
       "4   003497c6-ed32-412f-95ef-c3b1f962464e           brunsbuttel   \n",
       "5   00355021-dc45-4aaa-8178-a6dc360c07b9           olt-toscana   \n",
       "6   00361ab8-f70d-4a08-8e45-e6eb5a0b8b2f         le-havre-fsru   \n",
       "7   003660ee-567d-4d23-9e43-2891509b7bfb         piombino-fsru   \n",
       "8   0037d9e4-cf09-4f26-8934-f1e038e185ea  eems-energy-terminal   \n",
       "9   0038a35c-253f-44f5-a4e5-d5240d98039a              adriatic   \n",
       "10  003b1adb-f810-443c-a971-c2a6b28cb5dc            fos-cavaou   \n",
       "11  003b1d25-f4bd-43bf-9cf6-9bd38216fe0f               montoir   \n",
       "12  003b1d36-d72b-4331-888f-22b3f84c1cce         wilhelmshaven   \n",
       "13  003bf9ab-2829-40a1-a83d-c32b764f21fd            south-hook   \n",
       "14  003d153e-282a-47a1-bb0c-b4fe0bc62d38                 inkoo   \n",
       "15  003e3e70-3626-4124-8ee9-d3ec39678e8c       deutsche-ostsee   \n",
       "16  003f55df-08c7-4b6a-8597-fbe9e3f398f8              klaipeda   \n",
       "17  003f577c-7058-4b50-9c94-c499c07ca080                  gate   \n",
       "\n",
       "          TerminalName firstAvailableRelease latestAvailableRelease  \n",
       "0        Isle of Grain            2023-11-28             2025-01-15  \n",
       "1            Zeebrugge            2023-11-28             2025-01-15  \n",
       "2            Dunkerque            2024-11-15             2025-01-15  \n",
       "3               Dragon            2023-11-28             2025-01-15  \n",
       "4          Brunsbuttel            2024-05-28             2025-01-15  \n",
       "5          OLT Toscana            2024-10-02             2025-01-15  \n",
       "6             Le Havre            2023-11-28             2025-01-15  \n",
       "7             Piombino            2023-12-18             2025-01-15  \n",
       "8   EemsEnergyTerminal            2024-09-05             2025-01-15  \n",
       "9             Adriatic            2024-10-02             2025-01-15  \n",
       "10          Fos Cavaou            2023-11-28             2025-01-15  \n",
       "11             Montoir            2023-01-01             2025-01-15  \n",
       "12     Wilhelmshaven 1            2024-05-30             2025-01-15  \n",
       "13          South Hook            2023-11-28             2025-01-15  \n",
       "14               Inkoo            2024-04-19             2025-01-15  \n",
       "15     Deutsche Ostsee            2024-06-21             2025-01-15  \n",
       "16            Klaipeda            2023-11-28             2025-01-15  \n",
       "17                Gate            2023-11-28             2025-01-15  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Call terminal list function\n",
    "terminal_list = get_terminal_list()\n",
    "terminal_list.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to collect and store historical slots for one specific terminal\n",
    "def get_individual_terminal(terminal_uuid):\n",
    "    uri = urljoin(API_BASE_URL, f'/beta/terminal-slots/terminals/{terminal_uuid}/')\n",
    "    headers = {\n",
    "            \"Authorization\": \"Bearer {}\".format(access_token),\n",
    "            \"accept\": \"text/csv\"\n",
    "        }\n",
    "    response = requests.get(uri, headers=headers)\n",
    "    if response.status_code == 200:\n",
    "        df = response.content.decode('utf-8')\n",
    "        df = pd.read_csv(StringIO(df))\n",
    "        return df\n",
    "\n",
    "    elif response.content == b'{\"errors\":[{\"code\":\"object_not_found\",\"detail\":\"Object not found\"}]}':\n",
    "        print('Bad Terminal Request')\n",
    "        return None\n",
    "    else:\n",
    "        print('Bad Request')\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to collect and store each terminal's historical slots data\n",
    "def get_all_terminal_data(terminal_list):\n",
    "    terminals_all = pd.DataFrame()\n",
    "    for i in range(len(terminal_list)):\n",
    "        terminal_df = get_individual_terminal(terminal_list['TerminalUUID'].loc[i])\n",
    "        time.sleep(0.1)\n",
    "        terminals_all = pd.concat([terminals_all,terminal_df])\n",
    "    return terminals_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>TerminalCode</th>\n",
       "      <th>TerminalName</th>\n",
       "      <th>ReleaseDate</th>\n",
       "      <th>Total</th>\n",
       "      <th>M+0</th>\n",
       "      <th>M+1</th>\n",
       "      <th>M+2</th>\n",
       "      <th>M+3</th>\n",
       "      <th>M+4</th>\n",
       "      <th>M+5</th>\n",
       "      <th>...</th>\n",
       "      <th>M+4StartDate</th>\n",
       "      <th>M+5StartDate</th>\n",
       "      <th>M+6StartDate</th>\n",
       "      <th>M+7StartDate</th>\n",
       "      <th>M+8StartDate</th>\n",
       "      <th>M+9StartDate</th>\n",
       "      <th>M+10StartDate</th>\n",
       "      <th>M+11StartDate</th>\n",
       "      <th>M+12StartDate</th>\n",
       "      <th>M&gt;12StartDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-11-28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-03-01</td>\n",
       "      <td>2024-04-01</td>\n",
       "      <td>2024-05-01</td>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>2024-07-01</td>\n",
       "      <td>2024-08-01</td>\n",
       "      <td>2024-09-01</td>\n",
       "      <td>2024-10-01</td>\n",
       "      <td>2024-11-01</td>\n",
       "      <td>2024-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-11-29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-03-01</td>\n",
       "      <td>2024-04-01</td>\n",
       "      <td>2024-05-01</td>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>2024-07-01</td>\n",
       "      <td>2024-08-01</td>\n",
       "      <td>2024-09-01</td>\n",
       "      <td>2024-10-01</td>\n",
       "      <td>2024-11-01</td>\n",
       "      <td>2024-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-04-01</td>\n",
       "      <td>2024-05-01</td>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>2024-07-01</td>\n",
       "      <td>2024-08-01</td>\n",
       "      <td>2024-09-01</td>\n",
       "      <td>2024-10-01</td>\n",
       "      <td>2024-11-01</td>\n",
       "      <td>2024-12-01</td>\n",
       "      <td>2025-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-04-01</td>\n",
       "      <td>2024-05-01</td>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>2024-07-01</td>\n",
       "      <td>2024-08-01</td>\n",
       "      <td>2024-09-01</td>\n",
       "      <td>2024-10-01</td>\n",
       "      <td>2024-11-01</td>\n",
       "      <td>2024-12-01</td>\n",
       "      <td>2025-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>grain-lng</td>\n",
       "      <td>Isle of Grain</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-04-01</td>\n",
       "      <td>2024-05-01</td>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>2024-07-01</td>\n",
       "      <td>2024-08-01</td>\n",
       "      <td>2024-09-01</td>\n",
       "      <td>2024-10-01</td>\n",
       "      <td>2024-11-01</td>\n",
       "      <td>2024-12-01</td>\n",
       "      <td>2025-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  TerminalCode   TerminalName ReleaseDate  Total  M+0  M+1  M+2  M+3  M+4  \\\n",
       "0    grain-lng  Isle of Grain  2023-11-28      1    0    1    0    0    0   \n",
       "1    grain-lng  Isle of Grain  2023-11-29      1    0    1    0    0    0   \n",
       "2    grain-lng  Isle of Grain  2023-11-30      2    2    0    0    0    0   \n",
       "3    grain-lng  Isle of Grain  2023-12-01      2    2    0    0    0    0   \n",
       "4    grain-lng  Isle of Grain  2023-12-04      2    2    0    0    0    0   \n",
       "\n",
       "   M+5  ...  M+4StartDate  M+5StartDate  M+6StartDate  M+7StartDate  \\\n",
       "0    0  ...    2024-03-01    2024-04-01    2024-05-01    2024-06-01   \n",
       "1    0  ...    2024-03-01    2024-04-01    2024-05-01    2024-06-01   \n",
       "2    0  ...    2024-04-01    2024-05-01    2024-06-01    2024-07-01   \n",
       "3    0  ...    2024-04-01    2024-05-01    2024-06-01    2024-07-01   \n",
       "4    0  ...    2024-04-01    2024-05-01    2024-06-01    2024-07-01   \n",
       "\n",
       "   M+8StartDate  M+9StartDate  M+10StartDate  M+11StartDate M+12StartDate  \\\n",
       "0    2024-07-01    2024-08-01     2024-09-01     2024-10-01    2024-11-01   \n",
       "1    2024-07-01    2024-08-01     2024-09-01     2024-10-01    2024-11-01   \n",
       "2    2024-08-01    2024-09-01     2024-10-01     2024-11-01    2024-12-01   \n",
       "3    2024-08-01    2024-09-01     2024-10-01     2024-11-01    2024-12-01   \n",
       "4    2024-08-01    2024-09-01     2024-10-01     2024-11-01    2024-12-01   \n",
       "\n",
       "  M>12StartDate  \n",
       "0    2024-12-01  \n",
       "1    2024-12-01  \n",
       "2    2025-01-01  \n",
       "3    2025-01-01  \n",
       "4    2025-01-01  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calling all terminal data function\n",
    "all_terminal_historical = get_all_terminal_data(terminal_list)\n",
    "all_terminal_historical.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defining which terminal slots to sum up\n",
    "\n",
    "Here we define which terminals we're interested in ('termlist'). We iterate through each release date, and sum up the total [M+0, M+1, M+2, M+3] slots for all chosen terminals, to gauge the overall demand for regasification slots in NWE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to define terminals and to sum the slot count\n",
    "\n",
    "def select_and_sum_terminals(termlist, historical_terminals_data):\n",
    "\n",
    "    # Unique release dates\n",
    "    termrels = pd.Series(historical_terminals_data['ReleaseDate'].unique()).sort_values().to_list()[::-1]\n",
    "    term_groups = historical_terminals_data.groupby('ReleaseDate')    \n",
    "\n",
    "    slots = []\n",
    "\n",
    "    for t in termrels:\n",
    "        df = term_groups.get_group(t)\n",
    "        \n",
    "        df1 = df[df['TerminalName'].isin(termlist)]\n",
    "        slots.append(df1['M+0'].sum() + df1['M+1'].sum() + df1['M+2'].sum() + df1['M+3'].sum())\n",
    "    return slots\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define terminals of interest\n",
    "\n",
    "termlist = ['Gate', 'Zeebrugge', 'Dunkerque', 'Fos Cavaou']\n",
    "\n",
    "\n",
    "# Call the function\n",
    "slots = select_and_sum_terminals(termlist, all_terminal_historical)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Importing Spark Netbacks - US Arb data \n",
    "\n",
    "Importing historical US front month arb data from the Spark API. For more information on pulling our netbacks data, please refer to our Spark API website: \n",
    "\n",
    "https://www.sparkcommodities.com/api/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>>> All the routes you can fetch\n"
     ]
    }
   ],
   "source": [
    "# List all netbacks available\n",
    "\n",
    "tickers, fobPort_names, availablevia, reldates, dicto1 = list_netbacks(access_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Defining the function\n",
    "\n",
    "def fetch_netback(access_token, ticker, release, via=None, laden=None, ballast=None):\n",
    "    \n",
    "    query_params = \"?fob-port={}\".format(ticker)\n",
    "    if release is not None:\n",
    "        query_params += \"&release-date={}\".format(release)\n",
    "    if via is not None:\n",
    "        query_params += \"&via-point={}\".format(via)\n",
    "    if laden is not None:\n",
    "        query_params += \"&laden-congestion-days={}\".format(laden)\n",
    "    if ballast is not None:\n",
    "        query_params += \"&ballast-congestion-days={}\".format(ballast)\n",
    "\n",
    "    \n",
    "    content = do_api_get_query(\n",
    "        uri=\"/v1.0/netbacks/{}\".format(query_params),\n",
    "        access_token=access_token,\n",
    "    )\n",
    "    \n",
    "    my_dict = content['data']\n",
    "\n",
    "    return my_dict\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Netbacks Historical Data Function\n",
    "\n",
    "Here we define a function to fetch the historical netbacks data from the Spark API. \n",
    "\n",
    "__N.B. This function takes a \"month\" parameter - this parameter is defined as the month up until which you would like to sum the arb data.__\n",
    "\n",
    "E.g. :\n",
    "- \"month=1\" will provide the M+1 US arb data\n",
    "- \"month=2\" will provide the mean value of the M+1 and M+2 US arb\n",
    "- \"month=3\" will provide the mean value of the [M+1, M+2, M+3] US arb\n",
    "- and so on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "\n",
    "def netbacks_history(tick, reldates, month=1, my_via=None, laden =None, ballast=None):\n",
    "\n",
    "    delta_outrights = []\n",
    "    release_date = []\n",
    "    \n",
    "    port = []\n",
    "\n",
    "    for r in reldates:\n",
    "        try:\n",
    "            my_dict = fetch_netback(access_token, tickers[tick], release=r, via=my_via, laden=laden, ballast=ballast)\n",
    "\n",
    "            dtemp = []\n",
    "            for m in my_dict['netbacks'][0:month]:\n",
    "                dtemp.append(float(m['neaMinusNwe']['outright']['usdPerMMBtu']))\n",
    "            delta_outrights.append(np.mean(dtemp))\n",
    "\n",
    "            release_date.append(my_dict['releaseDate'])\n",
    "            port.append(fobPort_names[tick])\n",
    "\n",
    "        except:\n",
    "            print('Bad Date: ' + r)\n",
    "        \n",
    "        time.sleep(0.5)\n",
    "        \n",
    "    historical_df = pd.DataFrame({\n",
    "                'Release Date': release_date,\n",
    "                'FoB Port': port,\n",
    "                'Delta Outrights': delta_outrights,\n",
    "                })\n",
    "    \n",
    "\n",
    "    historical_df['Release Date'] = pd.to_datetime(historical_df['Release Date'])\n",
    "    \n",
    "    return historical_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calling the function and importing the US arb data\n",
    "\n",
    "via ='cogh'\n",
    "my_t = 'Sabine Pass'\n",
    "t = fobPort_names.index(my_t)\n",
    "my_date = reldates.index('2024-01-05')\n",
    "\n",
    "my_rels = reldates[:my_date]\n",
    "\n",
    "df_cogh = netbacks_history(t, my_rels, month=3, my_via='cogh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combine Datasets and Final Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Release Date</th>\n",
       "      <th>Arb</th>\n",
       "      <th>Slots</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025-01-15</td>\n",
       "      <td>-0.769000</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025-01-14</td>\n",
       "      <td>-0.726333</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025-01-13</td>\n",
       "      <td>-0.658000</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025-01-10</td>\n",
       "      <td>-0.574000</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025-01-09</td>\n",
       "      <td>-0.606333</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Release Date       Arb  Slots\n",
       "0   2025-01-15 -0.769000      8\n",
       "1   2025-01-14 -0.726333     10\n",
       "2   2025-01-13 -0.658000     10\n",
       "3   2025-01-10 -0.574000     11\n",
       "4   2025-01-09 -0.606333     13"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combining Slots and US arb data into one single DataFrame\n",
    "\n",
    "slots_df = pd.DataFrame({\n",
    "    'Release Date': df_cogh['Release Date'],\n",
    "    'Arb' : df_cogh['Delta Outrights'],\n",
    "    'Slots' : slots[:my_date]\n",
    "})\n",
    "\n",
    "\n",
    "# Displaying Slots data\n",
    "\n",
    "slots_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Plotting\n",
    "\n",
    "### Daily Slots Data vs US Arb Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x114e6f3b0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "\n",
    "ax.plot(slots_df['Release Date'], slots_df['Arb'], label='US Arb')\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(slots_df['Release Date'], slots_df['Slots'], 'r--', label='Daily Slots Available')\n",
    "\n",
    "ax2.grid(False)\n",
    "\n",
    "fig.legend(loc = 'center', bbox_to_anchor=(0.5, 0.85))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Month Average Slots vs US Arb Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating the average slots per month from the daily data\n",
    "\n",
    "def calculate_average_slots_per_month(slots_df):\n",
    "    # Retrieving the months\n",
    "    month_times = []\n",
    "    for t in slots_df['Release Date'].to_list():\n",
    "        month_times.append(t.strftime(\"%b-%Y\"))\n",
    "\n",
    "    slots_df['Release Month'] = month_times\n",
    "\n",
    "\n",
    "    # Averaging over each month\n",
    "    month_groups = slots_df.groupby('Release Month')\n",
    "\n",
    "    m_aves_raw = []\n",
    "\n",
    "    for m in list(np.unique(month_times)):\n",
    "        mdf = month_groups.get_group(m)\n",
    "        m_aves_raw.append(mdf['Slots'].mean())\n",
    "    \n",
    "    # Storing in one \"Monthly\" DataFrame\n",
    "    monthly_slots = pd.DataFrame({\n",
    "        \"Month\": list(np.unique(month_times)),\n",
    "        \"Slots\": m_aves_raw\n",
    "    })\n",
    "\n",
    "    monthly_slots['Month'] = pd.to_datetime(monthly_slots['Month'])\n",
    "\n",
    "    return monthly_slots, slots_df\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calling the function\n",
    "\n",
    "monthly_slots, slots_df = calculate_average_slots_per_month(slots_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x114e88410>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "\n",
    "ax.plot(slots_df['Release Date'], slots_df['Arb'], color='#4F41F4', label='US Arb [M+1, M+2, M+3]', linewidth=4)\n",
    "plt.axhline(0, color='grey')\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.bar(monthly_slots['Month'], monthly_slots['Slots'], width=15.0, color='darkred', alpha=0.6, label='Monthly Ave Slots')\n",
    "\n",
    "ax.set_ylim(-1,0.5)\n",
    "\n",
    "ax2.grid(False)\n",
    "\n",
    "plt.title('')\n",
    "\n",
    "fig.legend(loc = 'center', bbox_to_anchor=(0.5, 0.85))"
   ]
  }
 ],
 "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": "3.12.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}