added source code

README.md

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+Weather forecasting using machine learning

training/.dockerignore

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+.git

training/.gitignore

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+.python-version

training/data/weather-data.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8b8096982477f4058aee79f5b4b41f8dacf9e5bcda5d97434ccbf2a573189e14
-size 38169226

training/src/.ipynb_checkpoints/MSML-602-HW1-Q4-checkpoint.ipynb

@@ -0,0 +1,283 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "d10fb797-f9d4-40c7-ba48-08e4ece334f9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Data for sum\n",
+      "     x      P(X)  x * P(X)\n",
+      "0   10  0.125000  1.250000\n",
+      "1   11  0.125000  1.375000\n",
+      "2    9  0.115741  1.041667\n",
+      "3   12  0.115741  1.388889\n",
+      "4    8  0.097222  0.777778\n",
+      "5   13  0.097222  1.263889\n",
+      "6    7  0.069444  0.486111\n",
+      "7   14  0.069444  0.972222\n",
+      "8    6  0.046296  0.277778\n",
+      "9   15  0.046296  0.694444\n",
+      "10   5  0.027778  0.138889\n",
+      "11  16  0.027778  0.444444\n",
+      "12   4  0.013889  0.055556\n",
+      "13  17  0.013889  0.236111\n",
+      "14   3  0.004630  0.013889\n",
+      "15  18  0.004630  0.083333\n",
+      "\n",
+      "Expectation for sum: 10.5\n",
+      "\n",
+      "Data for product\n",
+      "      x      P(X)  x * P(X)\n",
+      "0    12  0.069444  0.833333\n",
+      "1    24  0.069444  1.666667\n",
+      "2    30  0.055556  1.666667\n",
+      "3    60  0.055556  3.333333\n",
+      "4    36  0.055556  2.000000\n",
+      "5    18  0.041667  0.750000\n",
+      "6    72  0.041667  3.000000\n",
+      "7     6  0.041667  0.250000\n",
+      "8    48  0.041667  2.000000\n",
+      "9    20  0.041667  0.833333\n",
+      "10    8  0.032407  0.259259\n",
+      "11   90  0.027778  2.500000\n",
+      "12   40  0.027778  1.111111\n",
+      "13   16  0.027778  0.444444\n",
+      "14   10  0.027778  0.277778\n",
+      "15    4  0.027778  0.111111\n",
+      "16   15  0.027778  0.416667\n",
+      "17  120  0.027778  3.333333\n",
+      "18   32  0.013889  0.444444\n",
+      "19   25  0.013889  0.347222\n",
+      "20  108  0.013889  1.500000\n",
+      "21  100  0.013889  1.388889\n",
+      "22   96  0.013889  1.333333\n",
+      "23    3  0.013889  0.041667\n",
+      "24   80  0.013889  1.111111\n",
+      "25   75  0.013889  1.041667\n",
+      "26  150  0.013889  2.083333\n",
+      "27  144  0.013889  2.000000\n",
+      "28    5  0.013889  0.069444\n",
+      "29  180  0.013889  2.500000\n",
+      "30   50  0.013889  0.694444\n",
+      "31    9  0.013889  0.125000\n",
+      "32   45  0.013889  0.625000\n",
+      "33    2  0.013889  0.027778\n",
+      "34   54  0.013889  0.750000\n",
+      "35    1  0.004630  0.004630\n",
+      "36  125  0.004630  0.578704\n",
+      "37   64  0.004630  0.296296\n",
+      "38   27  0.004630  0.125000\n",
+      "39  216  0.004630  1.000000\n",
+      "Expectation for product 42.875\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "    \n",
+    "dice1 = [1, 2, 3, 4, 5, 6]\n",
+    "dice2 = [1, 2, 3, 4, 5, 6]\n",
+    "dice3 = [1, 2, 3, 4, 5, 6]\n",
+    "\n",
+    "\n",
+    "data = [[d1, d2, d3, d1 + d2 + d3, d1 * d2 * d3] for d1 in dice1 for d2 in dice2 for d3 in dice3]\n",
+    "\n",
+    "df = pd.DataFrame(data, columns=[\"dice1\", \"dice2\", \"dice3\", \"sum_of_dots\", \"product_of_dots\"])\n",
+    "total_count = len(dice1) * len(dice2) * len(dice3)\n",
+    "\n",
+    "# Expectation of sum of number of dots on the three rolls\n",
+    "sum_pmf = [(x[0], count_x / (total_count * 1.0)) for x, count_x in df.value_counts([\"sum_of_dots\"]).items()]\n",
+    "sum_pmf_df = pd.DataFrame(sum_pmf, columns=[\"x\", \"P(X)\"])\n",
+    "sum_pmf_df[\"x * P(X)\"] = sum_pmf_df[\"x\"] *  sum_pmf_df[\"P(X)\"] \n",
+    "expectation_sum = sum_pmf_df[\"x * P(X)\"].sum()\n",
+    "\n",
+    "# Expectation of product of number of dots on the three rolls\n",
+    "product_pmf = [(x[0], count_x / (total_count * 1.0)) for x, count_x in df.value_counts([\"product_of_dots\"]).items()]\n",
+    "product_pmf_df = pd.DataFrame(product_pmf, columns=[\"x\", \"P(X)\"])\n",
+    "product_pmf_df[\"x * P(X)\"] = product_pmf_df[\"x\"] *  product_pmf_df[\"P(X)\"] \n",
+    "expectation_product = product_pmf_df[\"x * P(X)\"].sum()\n",
+    "\n",
+    "print(\"\\nData for sum\")\n",
+    "print(sum_pmf_df)\n",
+    "print(\"\\nExpectation for sum: {}\".format(expectation_sum))\n",
+    "\n",
+    "print(\"\\nData for product\")\n",
+    "print(product_pmf_df)\n",
+    "print(\"Expectation for product {}\".format(expectation_product))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "301ba7da-d523-48eb-8a6d-25e8d6fa5ffe",
+   "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>x</th>\n",
+       "      <th>P(X)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>10</td>\n",
+       "      <td>0.125000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11</td>\n",
+       "      <td>0.125000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>9</td>\n",
+       "      <td>0.115741</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12</td>\n",
+       "      <td>0.115741</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.097222</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    x      P(X)\n",
+       "0  10  0.125000\n",
+       "1  11  0.125000\n",
+       "2   9  0.115741\n",
+       "3  12  0.115741\n",
+       "4   8  0.097222"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "42954464-bab8-44fc-9087-8c4f07bac679",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<zip at 0x7f9ae912ac40>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "4de2391b-e130-405b-bc26-b04584b2ed9c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "56b9fd02-79ec-4c7d-9eca-17c04a7df44d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "09e2316e-e242-48ab-9803-ef9e9212ea94",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "45a28a91-dc74-469b-8a1c-caa43ed0b907",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2268\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(expectation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b4b63417-d541-44d1-98ad-2027865e1818",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

training/src/.ipynb_checkpoints/MSML602_Midterm_Karki-checkpoint.ipynb

@@ -0,0 +1,831 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 82,
+      "metadata": {
+        "cellView": "form",
+        "id": "AXI2uCSkxx7m"
+      },
+      "outputs": [],
+      "source": [
+        "#@title Setup\n",
+        "\n",
+        "%%capture\n",
+        "!pip install networkx pulp numpy pandas\n",
+        "\n",
+        "!rm -rf ./data/\n",
+        "!mkdir -p ./data/\n",
+        "!wget -c -O ./data/lastfm_asia.zip \"https://snap.stanford.edu/data/lastfm_asia.zip\"\n",
+        "!unzip -q ./data/lastfm_asia.zip -d ./data/"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Problem 3: Linear Programming\n",
+        "\n",
+        "\n",
+        "from pulp import *\n",
+        "from IPython.display import HTML, display\n",
+        "\n",
+        "def display_table(table):\n",
+        "    display(HTML(\n",
+        "       '<table><tr>{}</tr></table>'.format(\n",
+        "           '</tr><tr>'.join(\n",
+        "               '<td>{}</td>'.format('</td><td>'.join(str(_) for _ in row)) for row in table)\n",
+        "           )\n",
+        "    ))\n",
+        "\n",
+        "problem = LpProblem(\"MSML_602_Midterm_Q3\", LpMaximize)\n",
+        "\n",
+        "X = LpVariable(\"X\", cat=\"Integer\")\n",
+        "Y = LpVariable(\"Y\", cat=\"Integer\")\n",
+        "\n",
+        "problem += (5 * X) + (3 * Y), \"Objective\"\n",
+        "problem += X + (2 * Y) <= 14, \"Constraint 1\"\n",
+        "problem += (3* X) - Y >= 0, \"Constraint 2\"\n",
+        "problem += X - Y <= 2, \"Constraint 3\"\n",
+        "\n",
+        "problem.solve()\n",
+        "print(\"Solution:\\n\")\n",
+        "\n",
+        "data = [[\"Variable\", \"Value\"]] + [[v.name, v.varValue] for v in problem.variables()]\n",
+        "data += [[\"Max value for objective function: \", problem.objective.value()]]\n",
+        "display_table(data)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 140
+        },
+        "cellView": "form",
+        "id": "ALmlZnbcx-9e",
+        "outputId": "45e2c507-3265-4b22-e21a-2d6dbd72f05f"
+      },
+      "execution_count": 83,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Solution:\n",
+            "\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "<table><tr><td>Variable</td><td>Value</td></tr><tr><td>X</td><td>6.0</td></tr><tr><td>Y</td><td>4.0</td></tr><tr><td>Max value for objective function: </td><td>42.0</td></tr></table>"
+            ]
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Problem 5: Graph Metrics\n",
+        "\n",
+        "import pandas as pd \n",
+        "import networkx as nx\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "df = pd.read_csv(\"/content/data/lasftm_asia/lastfm_asia_edges.csv\")\n",
+        "G = nx.from_pandas_edgelist(df, source=\"node_1\", target=\"node_2\")\n",
+        "shortest_path = nx.shortest_path_length(G, 0)\n",
+        "del shortest_path[0]\n",
+        "num = len(shortest_path)\n",
+        "total_length = sum([shortest_path[k] for k in shortest_path])\n",
+        "avg_shortest_path = total_length / num\n",
+        "print(f\"The average shortest path length from node 0 to all other nodes is: {avg_shortest_path}\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "cellView": "form",
+        "id": "87mMC-B1yJoq",
+        "outputId": "83ff28ec-7d51-4f6a-ced6-358538a58f83"
+      },
+      "execution_count": 84,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "The average shortest path length from node 0 to all other nodes is: 5.651974288337925\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Problem 6: Extracting Webpage Data"
+      ],
+      "metadata": {
+        "id": "mAiJRhb5iW5O"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Scraping result\n",
+        "\n",
+        "import requests\n",
+        "from bs4 import BeautifulSoup\n",
+        "import pandas as pd \n",
+        "import numpy as np\n",
+        "\n",
+        "page = requests.get(\"https://www.worldometers.info/coronavirus/#countries\")\n",
+        "html = page.content\n",
+        "\n",
+        "soup = BeautifulSoup(html, 'html.parser')\n",
+        "table = soup.find(\"table\", {\"id\": \"main_table_countries_today\"})\n",
+        "\n",
+        "cols = [\n",
+        "    '#', 'Country', 'TotalCases', 'NewCases', 'TotalDeaths', 'NewDeaths', 'TotalRecovered',\n",
+        "    'NewRecovered','ActiveCases','Serious,Critical','TotalCases/1M pop','Deaths/1M pop', \n",
+        "    'TotalTests', 'Tests/1M pop', 'Population', 'Continent', '1 Case every X ppl', '1 Death every X ppl',\n",
+        "    '1 Test every X ppl', 'New Cases/1M pop', 'New Deaths/1M pop', 'Active Cases/1M pop'\n",
+        "]\n",
+        "\n",
+        "tbody = table.find(\"tbody\")\n",
+        "rows = tbody.find_all(\"tr\")\n",
+        "\n",
+        "data = []\n",
+        "for row in rows:\n",
+        "  cells = row.find_all(\"td\")\n",
+        "  values = [c.text for c in cells]\n",
+        "  data.append(values)\n",
+        "\n",
+        "def sanitize_country_number(row):\n",
+        "  val = row[\"#\"]\n",
+        "  if not val.strip():\n",
+        "    return np.NaN\n",
+        "  else:\n",
+        "    return val\n",
+        "\n",
+        "def fill_active_cases(row):\n",
+        "  val = row[\"ActiveCases\"]\n",
+        "  if not np.isnan(val):\n",
+        "    return val\n",
+        "  active_per_1_mil = row[\"Active Cases/1M pop\"]\n",
+        "  if np.isnan(active_per_1_mil):\n",
+        "    return np.nan\n",
+        "  population = row[\"Population\"]\n",
+        "  return (active_per_1_mil/1000000) * population\n",
+        "\n",
+        "def to_float(col):\n",
+        "  def mapper(row):\n",
+        "    if row[col] == \"N/A\":\n",
+        "      return np.NaN\n",
+        "    val = row[col]\n",
+        "    val = val.replace(\",\", \"\").strip()\n",
+        "    if not val:\n",
+        "      return np.NaN\n",
+        "    return float(val)\n",
+        "  return mapper \n",
+        "\n",
+        "df = pd.DataFrame(data, columns=cols)\n",
+        "df.replace(r\"\\n\", \"\", regex=True, inplace=True)\n",
+        "\n",
+        "df.head()\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 386
+        },
+        "cellView": "form",
+        "id": "Ay-ceRkkzcVg",
+        "outputId": "3b1e8535-f211-45ba-9b90-85c279e522ec"
+      },
+      "execution_count": 85,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "  #        Country   TotalCases  NewCases TotalDeaths NewDeaths  \\\n",
+              "0    North America  118,308,960   +16,354   1,557,219       +76   \n",
+              "1             Asia  195,343,819  +168,618   1,491,630      +230   \n",
+              "2           Europe  235,496,414   +41,389   1,948,669      +165   \n",
+              "3    South America   64,557,158   +10,126   1,333,737       +79   \n",
+              "4          Oceania   12,691,699    +3,057      21,779        +9   \n",
+              "\n",
+              "  TotalRecovered NewRecovered ActiveCases Serious,Critical  ... TotalTests  \\\n",
+              "0    113,762,872      +16,362   2,988,869            7,881  ...              \n",
+              "1    188,186,652      +78,736   5,665,537            9,159  ...              \n",
+              "2    229,427,346     +175,758   4,120,399            7,685  ...              \n",
+              "3     62,884,992       +7,699     338,429           10,119  ...              \n",
+              "4     12,512,305                  157,615               97  ...              \n",
+              "\n",
+              "  Tests/1M pop Population          Continent 1 Case every X ppl  \\\n",
+              "0                              North America                      \n",
+              "1                                       Asia                      \n",
+              "2                                     Europe                      \n",
+              "3                              South America                      \n",
+              "4                          Australia/Oceania                      \n",
+              "\n",
+              "  1 Death every X ppl 1 Test every X ppl New Cases/1M pop New Deaths/1M pop  \\\n",
+              "0                                                                             \n",
+              "1                                                                             \n",
+              "2                                                                             \n",
+              "3                                                                             \n",
+              "4                                                                             \n",
+              "\n",
+              "  Active Cases/1M pop  \n",
+              "0                      \n",
+              "1                      \n",
+              "2                      \n",
+              "3                      \n",
+              "4                      \n",
+              "\n",
+              "[5 rows x 22 columns]"
+            ],
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+              "\n",
+              "  <div id=\"df-ba4843e7-ab30-4f7d-ab50-7ddf8afb1bbb\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <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",
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+              "\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>#</th>\n",
+              "      <th>Country</th>\n",
+              "      <th>TotalCases</th>\n",
+              "      <th>NewCases</th>\n",
+              "      <th>TotalDeaths</th>\n",
+              "      <th>NewDeaths</th>\n",
+              "      <th>TotalRecovered</th>\n",
+              "      <th>NewRecovered</th>\n",
+              "      <th>ActiveCases</th>\n",
+              "      <th>Serious,Critical</th>\n",
+              "      <th>...</th>\n",
+              "      <th>TotalTests</th>\n",
+              "      <th>Tests/1M pop</th>\n",
+              "      <th>Population</th>\n",
+              "      <th>Continent</th>\n",
+              "      <th>1 Case every X ppl</th>\n",
+              "      <th>1 Death every X ppl</th>\n",
+              "      <th>1 Test every X ppl</th>\n",
+              "      <th>New Cases/1M pop</th>\n",
+              "      <th>New Deaths/1M pop</th>\n",
+              "      <th>Active Cases/1M pop</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td></td>\n",
+              "      <td>North America</td>\n",
+              "      <td>118,308,960</td>\n",
+              "      <td>+16,354</td>\n",
+              "      <td>1,557,219</td>\n",
+              "      <td>+76</td>\n",
+              "      <td>113,762,872</td>\n",
+              "      <td>+16,362</td>\n",
+              "      <td>2,988,869</td>\n",
+              "      <td>7,881</td>\n",
+              "      <td>...</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td>North America</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td></td>\n",
+              "      <td>Asia</td>\n",
+              "      <td>195,343,819</td>\n",
+              "      <td>+168,618</td>\n",
+              "      <td>1,491,630</td>\n",
+              "      <td>+230</td>\n",
+              "      <td>188,186,652</td>\n",
+              "      <td>+78,736</td>\n",
+              "      <td>5,665,537</td>\n",
+              "      <td>9,159</td>\n",
+              "      <td>...</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td>Asia</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td></td>\n",
+              "      <td>Europe</td>\n",
+              "      <td>235,496,414</td>\n",
+              "      <td>+41,389</td>\n",
+              "      <td>1,948,669</td>\n",
+              "      <td>+165</td>\n",
+              "      <td>229,427,346</td>\n",
+              "      <td>+175,758</td>\n",
+              "      <td>4,120,399</td>\n",
+              "      <td>7,685</td>\n",
+              "      <td>...</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td>Europe</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td></td>\n",
+              "      <td>South America</td>\n",
+              "      <td>64,557,158</td>\n",
+              "      <td>+10,126</td>\n",
+              "      <td>1,333,737</td>\n",
+              "      <td>+79</td>\n",
+              "      <td>62,884,992</td>\n",
+              "      <td>+7,699</td>\n",
+              "      <td>338,429</td>\n",
+              "      <td>10,119</td>\n",
+              "      <td>...</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td>South America</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td></td>\n",
+              "      <td>Oceania</td>\n",
+              "      <td>12,691,699</td>\n",
+              "      <td>+3,057</td>\n",
+              "      <td>21,779</td>\n",
+              "      <td>+9</td>\n",
+              "      <td>12,512,305</td>\n",
+              "      <td></td>\n",
+              "      <td>157,615</td>\n",
+              "      <td>97</td>\n",
+              "      <td>...</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td>Australia/Oceania</td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "      <td></td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 22 columns</p>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ba4843e7-ab30-4f7d-ab50-7ddf8afb1bbb')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-ba4843e7-ab30-4f7d-ab50-7ddf8afb1bbb button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-ba4843e7-ab30-4f7d-ab50-7ddf8afb1bbb');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 85
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Data sanitization / generation\n",
+        "\n",
+        "#@markdown Some of the countries (actually ships, in this case) did not have any population data, so I excluded those records from the dataset.\n",
+        "\n",
+        "#@markdown Some countries didn't have data for exact active cases, but had data for **active cases per 1 million population**. \n",
+        "#@markdown For these countries, I calculated their active cases by using the active cases per 1 million population data as follows: \n",
+        "\n",
+        "#@markdown ```Active Cases = (Active cases per 1 million population / 1,000,000) * Population```\n",
+        "\n",
+        "df[\"country_number\"] = df.apply(sanitize_country_number, axis=1)\n",
+        "\n",
+        "data_by_country = df[df[\"country_number\"].notna()].copy()\n",
+        "data_by_country[\"ActiveCases\"] = data_by_country.apply(to_float(\"ActiveCases\"), axis=1)\n",
+        "data_by_country[\"Active Cases/1M pop\"] = data_by_country.apply(to_float(\"Active Cases/1M pop\"), axis=1)\n",
+        "data_by_country[\"Population\"] = data_by_country.apply(to_float(\"Population\"), axis=1)\n",
+        "data_by_country[\"ActiveCases\"] = data_by_country.apply(fill_active_cases, axis=1)\n",
+        "data_by_country[data_by_country[\"ActiveCases\"] == \"N/A\"].head(20)\n",
+        "aggregated = data_by_country.groupby(\"Country\").agg({'ActiveCases':'mean', 'Population':'sum'}, as_index=False)\n",
+        "aggregated.reset_index(inplace=True)\n",
+        "dropped_countries = aggregated[aggregated[\"Population\"] == 0 ]\n",
+        "aggregated = aggregated[aggregated[\"Population\"] != 0 ]\n",
+        "aggregated[\"PercentageInfected\"] = aggregated.apply(lambda x: x[\"ActiveCases\"]/x[\"Population\"], axis=1)\n",
+        "aggregated.sort_values([\"PercentageInfected\"], ascending=False, inplace=True)\n",
+        "\n",
+        "print(\"These were the countries(ships) that didn't have population data:\\n\")\n",
+        "print(dropped_countries)\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "cellView": "form",
+        "id": "Roitzj22-VO5",
+        "outputId": "5dc61fa2-31c9-4fa4-828c-c9f88fb449e2"
+      },
+      "execution_count": 86,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "These were the countries(ships) that didn't have population data:\n",
+            "\n",
+            "              Country  ActiveCases  Population\n",
+            "56   Diamond Princess          0.0         0.0\n",
+            "120        MS Zaandam          0.0         0.0\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Average active cases & the proportion of the total population affected\n",
+        "\n",
+        "from IPython.display import HTML, display\n",
+        "\n",
+        "def display_table(table):\n",
+        "    display(HTML(\n",
+        "       '<table><tr>{}</tr></table>'.format(\n",
+        "           '</tr><tr>'.join(\n",
+        "               '<td>{}</td>'.format('</td><td>'.join(str(_) for _ in row)) for row in table)\n",
+        "           )\n",
+        "    ))\n",
+        "\n",
+        "avg_active_cases = aggregated[\"ActiveCases\"].mean()\n",
+        "\n",
+        "aggr = aggregated.agg({\"ActiveCases\": \"sum\",  \"Population\": \"sum\"}, as_index=False)\n",
+        "final_df = aggr.to_frame().T\n",
+        "final_df[\"PercentageInfected\"] = final_df.apply(lambda x: (x[\"ActiveCases\"]/x[\"Population\"]) * 100, axis=1)\n",
+        "percentage_infected = final_df[\"PercentageInfected\"].to_numpy()[0]\n",
+        "\n",
+        "display(HTML(\n",
+        "    \"\"\"\n",
+        "      <h3>Result:</h3>\n",
+        "      <br>\n",
+        "      <table border=\"1\">\n",
+        "        <tr>\n",
+        "          <th align=\"left\">Average active cases:</th>\n",
+        "          <td>{0:.2f}</td>\n",
+        "        </tr>\n",
+        "        <tr>\n",
+        "          <th align=\"left\">Proportion of total <br>population currently infected:</th>\n",
+        "          <td>{1:.2f}%</td>\n",
+        "        </tr>\n",
+        "      </table>\n",
+        "      <br>\n",
+        "    \"\"\".format(avg_active_cases, percentage_infected))\n",
+        ")\n",
+        "\n",
+        "\n",
+        "print(\"\"\"\n",
+        "I was unsure whether the problem wanted the percentage of the population\n",
+        "affected for each country, so I have included the percentage for each country \n",
+        "as well, just in case:\n",
+        "\"\"\")\n",
+        "aggregated.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 439
+        },
+        "cellView": "form",
+        "id": "lRtwSfqSAPAY",
+        "outputId": "a7037d5d-fbd6-48b3-e47b-32090720dfd1"
+      },
+      "execution_count": 87,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "\n",
+              "      <h3>Result:</h3>\n",
+              "      <br>\n",
+              "      <table border=\"1\">\n",
+              "        <tr>\n",
+              "          <th align=\"left\">Average active cases:</th>\n",
+              "          <td>60038.20</td>\n",
+              "        </tr>\n",
+              "        <tr>\n",
+              "          <th align=\"left\">Proportion of total <br>population currently infected:</th>\n",
+              "          <td>0.17%</td>\n",
+              "        </tr>\n",
+              "      </table>\n",
+              "      <br>\n",
+              "    "
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "I was unsure whether the problem wanted the percentage of the population\n",
+            "affected for each country, so I have included the percentage for each country \n",
+            "as well, just in case:\n",
+            "\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "            Country    ActiveCases  Population  PercentageInfected\n",
+              "129      Martinique  222576.901869    374087.0            0.594987\n",
+              "68   Faeroe Islands   26936.998989     49233.0            0.547133\n",
+              "195       St. Barth    4854.999825      9945.0            0.488185\n",
+              "84       Guadeloupe  193026.939904    399794.0            0.482816\n",
+              "93          Iceland  130899.111498    345393.0            0.378986"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-5b3415ae-443b-4212-be42-19efc6bff309\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <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>Country</th>\n",
+              "      <th>ActiveCases</th>\n",
+              "      <th>Population</th>\n",
+              "      <th>PercentageInfected</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>129</th>\n",
+              "      <td>Martinique</td>\n",
+              "      <td>222576.901869</td>\n",
+              "      <td>374087.0</td>\n",
+              "      <td>0.594987</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>68</th>\n",
+              "      <td>Faeroe Islands</td>\n",
+              "      <td>26936.998989</td>\n",
+              "      <td>49233.0</td>\n",
+              "      <td>0.547133</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>195</th>\n",
+              "      <td>St. Barth</td>\n",
+              "      <td>4854.999825</td>\n",
+              "      <td>9945.0</td>\n",
+              "      <td>0.488185</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>84</th>\n",
+              "      <td>Guadeloupe</td>\n",
+              "      <td>193026.939904</td>\n",
+              "      <td>399794.0</td>\n",
+              "      <td>0.482816</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>93</th>\n",
+              "      <td>Iceland</td>\n",
+              "      <td>130899.111498</td>\n",
+              "      <td>345393.0</td>\n",
+              "      <td>0.378986</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5b3415ae-443b-4212-be42-19efc6bff309')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-5b3415ae-443b-4212-be42-19efc6bff309 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-5b3415ae-443b-4212-be42-19efc6bff309');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 87
+        }
+      ]
+    }
+  ]
+}

web/.dockerignore

@@ -0,0 +1,2 @@
+.git
+node_modules

web/.gitignore

@@ -0,0 +1 @@
+.python-version

web/Dockerfile.backend

@@ -0,0 +1,11 @@
+FROM tensorflow/tensorflow:2.11.0
+
+WORKDIR /app
+
+COPY ./requirements.txt /app/requirements.txt
+
+RUN pip install -r requirements.txt
+
+COPY ./src /app
+
+CMD ["python3", "-m", "flask", "run", "--host=0.0.0.0"]

web/Dockerfile.frontend

@@ -0,0 +1,13 @@
+FROM node:18-alpine3.15
+
+WORKDIR /app
+
+COPY package.json ./
+
+COPY package-lock.json ./
+
+RUN npm update && npm install
+
+COPY . .
+
+CMD ["npm", "start"]

web/Makefile

@@ -0,0 +1,19 @@
+.PHONY: build-backend
+build-backend: ## Build backend services
+	docker build -f Dockerfile.backend -t pred-backend ./backend
+
+.PHONY: build-frontend
+build-frontend: ## Build frontend services
+	docker build -f Dockerfile.frontend -t pred-frontend ./frontend
+
+.PHONY: up-prod
+up-prod: ## Build backend services
+	docker build -f Dockerfile.backend -t pred-backend ./backend
+	docker build -f Dockerfile.frontend -t pred-frontend ./frontend
+	docker-compose -f docker-compose.yml -f docker-compose.prod.yml up -d 
+
+.PHONY: up-dev
+up-dev: ## Build backend services
+	docker build -f Dockerfile.backend -t pred-backend ./backend
+	docker build -f Dockerfile.frontend -t pred-frontend ./frontend
+	docker-compose up -d 

web/README.md

@@ -0,0 +1 @@
+MSML 602 Assignments/Projects

web/backend/.dockerignore

@@ -0,0 +1 @@
+.git

web/backend/.gitignore

@@ -0,0 +1,2 @@
+.python-version
+__pycache__

web/backend/README.md

@@ -0,0 +1 @@
+MSML 602 Assignments/Projects

web/backend/requirements.txt

@@ -0,0 +1,7 @@
+flask==2.2.2
+flask-cors==3.0.10
+pandas==1.5.0
+numpy==1.23.3
+scipy==1.9.1
+scikit-learn==1.1.2
+requests-cache==0.9.7

web/backend/src/app.py

@@ -0,0 +1,244 @@
+from flask import Flask, request
+import tensorflow as tf
+from datetime import datetime, timedelta
+import logging 
+import requests
+import requests_cache
+import pandas as pd
+import json
+import numpy as np
+import pickle
+import math
+import pytz
+
+from flask_cors import CORS, cross_origin
+
+
+session = requests_cache.CachedSession('requests-cache')
+
+app = Flask(__name__)
+cors = CORS(app)
+app.config['CORS_HEADERS'] = 'Content-Type'
+
+app.logger.setLevel(logging.INFO)
+DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
+API_KEY = "e1f10a1e78da46f5b10a1e78da96f525"
+BASE_URL = "https://api.weather.com/v1/location/KDCA:9:US/observations/historical.json?apiKey={api_key}&units=e&startDate={start_date}&endDate={end_date}"
+model = tf.keras.models.load_model('/app/model', compile=False)
+
+scaler = pickle.load(open('./model/scaler.pkl','rb'))
+cols_to_scale = ["pressure", "wspd","heat_index","dewPt", "rh",	"vis", "wc", "wdir_degree", "clds_ordinal",
+             "day_sin", "day_cos", "year_sin", "year_cos", "wdir_sin", "wdir_cos"]
+
+def get_NaN_counts(df):    
+    nan_counts = df.isna().sum()
+    return pd.concat([nan_counts, ((nan_counts/len(df))*100).round(2)], 
+                     axis=1, 
+                     keys=["NaN count", "Percentage"])
+
+def clds_to_ordinal(row):
+  mapping = {
+      "SKC": 0,
+      "CLR": 0,
+      "FEW": 1,
+      "SCT": 2,
+      "BKN": 3,
+      "OVC": 4,
+      "VV": 5
+  }
+  clds = row["clds"]
+  if pd.isnull(clds):
+      return np.NaN 
+  return mapping[clds]
+
+def clean_wspd(row):
+  if row["wdir_cardinal"] == "CALM":
+    return 0
+  return row["wspd"]
+
+def restrict_wspd(row):
+  if row["wspd"] < 0:
+    return 0
+  return row["wspd"]
+
+def restrict_rh(row):
+  if row["rh"] < 0:
+    return 0
+  if row["rh"] > 100:
+    return 100
+  return row["rh"]
+
+def clean_wdir(row):
+  if row["wdir_cardinal"] == "CALM":
+    return 0
+  return row["wdir"]
+
+def wdir_cardinal_to_deg(row):
+    wdir = row["wdir"]
+    if not pd.isnull(wdir):
+      return wdir 
+    cardinal_directions = {
+        'N': 0,
+        'NNE': 22.5,
+        'NE': 45,
+        'ENE': 67.5,
+        'E': 90,
+        'ESE': 112.5,
+        'SE': 135,
+        'SSE': 157.5,
+        'S': 180,
+        'SSW': 202.5,
+        'SW': 225,
+        'WSW': 247.5,
+        'W': 270,
+        'WNW': 292.5,
+        'NW': 315,
+        'NNW': 337.5,
+        'CALM': 0,
+        'VAR': -1
+    }
+    wdir_cardinal = row["wdir_cardinal"]
+   
+    return cardinal_directions[wdir_cardinal] if wdir_cardinal in cardinal_directions else np.NaN
+
+def prepare_dataframe(_df, start_timestamp, end_timestamp):
+  dates_df = pd.DataFrame()
+  dates_df["obs_timestamp"] = pd.date_range(start_timestamp, end_timestamp, freq="H")
+
+  _df = dates_df.merge(_df, how='left', on='obs_timestamp')
+  _df = _df.astype(
+      {
+          'temp': 'float',
+          'pressure': 'float',
+          'wspd': 'float',
+          'heat_index': 'float'
+      },
+  )
+
+  _df["wdir_cardinal"].fillna(method="bfill", inplace=True)
+  _df["wdir_degree"] = _df.apply(wdir_cardinal_to_deg, axis=1)
+  _df["clds_ordinal"] = _df.apply(clds_to_ordinal, axis=1)
+  _df["temp"].interpolate("polynomial", order=2, inplace=True)
+  _df["pressure"].interpolate("polynomial", order=2, inplace=True)
+  _df["heat_index"].interpolate("polynomial", order=2, inplace=True)
+  _df["wdir"].fillna(method="bfill", inplace=True)
+  _df["wdir"] = _df.apply(clean_wdir, axis=1)
+  _df["wspd"] = _df.apply(clean_wspd, axis=1)
+  _df["wspd"].interpolate("polynomial", order=2, inplace=True)
+  _df["wspd"] = _df.apply(restrict_wspd, axis=1)
+  _df["clds"].fillna(method="bfill", inplace=True)
+  _df["clds_ordinal"].interpolate("linear", inplace=True)
+  _df["dewPt"].interpolate("polynomial", order=2, inplace=True)
+  _df["rh"].interpolate("polynomial", order=2, inplace=True)
+  _df["rh"] = _df.apply(restrict_rh, axis=1)
+  _df["wc"].interpolate("polynomial", order=2, inplace=True)
+  _df["vis"].fillna(method="bfill", inplace=True)
+  _df.drop(["wdir", "wdir_cardinal", "clds"], axis=1, inplace=True)
+
+  _df = _df.dropna()
+
+  _df = _df.sort_values(by=['obs_timestamp'])
+  date_time = _df.pop('obs_timestamp')
+  timestamp_s = date_time.map(pd.Timestamp.timestamp)
+  day = 24*60*60
+  year = (365.2425)*day
+  
+  _df['day_sin'] = np.sin(timestamp_s * (2 * np.pi / day))
+  _df['day_cos'] = np.cos(timestamp_s * (2 * np.pi / day))
+  _df['year_sin'] = np.sin(timestamp_s * (2 * np.pi / year))
+  _df['year_cos'] = np.cos(timestamp_s * (2 * np.pi / year))
+  _df['wdir_sin'] = np.sin(_df["wdir_degree"])
+  _df['wdir_cos'] = np.cos(_df["wdir_degree"])
+
+  return _df, date_time
+
+
+def map_data_to_dataframe(data, target_date):
+    end_timestamp = target_date - timedelta(minutes=8)
+    start_timestamp = end_timestamp - timedelta(days=8) + timedelta(hours=1)
+    
+    df = pd.read_json(json.dumps(data))
+    df["obs_timestamp"] = df.apply(lambda x: datetime.fromtimestamp(x["valid_time_gmt"]).strftime(DATE_FORMAT), axis=1)
+    df = df.astype({'obs_timestamp': 'datetime64[ns]'})
+    initial_cols = ["temp", "obs_timestamp", "pressure", "wspd", "heat_index", "dewPt", "rh", "vis", "wc", "wdir", "wdir_cardinal", "clds" ]
+    df = df[initial_cols]
+    
+    df, _ = prepare_dataframe(df, start_timestamp.strftime(DATE_FORMAT), end_timestamp.strftime(DATE_FORMAT))
+    return df 
+
+
+def map_to_timestamp(predictions, target_date):
+  start = target_date + timedelta(hours=1)
+  end = start + timedelta(hours=23)
+  target_hours = [x.to_pydatetime().strftime(DATE_FORMAT) for x in pd.date_range(start, end, freq="H")]
+  return { h: predictions[idx] for idx, h in enumerate(target_hours)}
+
+def predict(df):
+    predict_df = df[-168:]
+    predict_df_features = predict_df[cols_to_scale]
+    predict_df_features = scaler.transform(predict_df_features.values)
+    predict_df[cols_to_scale] = predict_df_features
+    predictions = model(predict_df.to_numpy().reshape(1, 168, 16))
+    return predictions
+
+def predict_for_date(target_date):
+    date_format = "%Y%m%d"
+    start_date = target_date - timedelta(days=9)
+    res = session.get(BASE_URL.format(api_key=API_KEY, start_date=start_date.strftime(date_format), end_date=target_date.strftime(date_format)))
+    data = res.json()
+    df = map_data_to_dataframe(data["observations"], target_date)
+    predictions = predict(df)
+    flattened = list(map(lambda x: math.floor(x), predictions.numpy().flatten().tolist()))
+    return map_to_timestamp(flattened, target_date)
+
+def get_actual_temperatures(target_date):
+  date_format = "%Y%m%d"
+  start_date = target_date - timedelta(days=1)  #Because api uses utc
+  end_date = target_date + timedelta(days=1)
+  start_date_str = (start_date - timedelta(days=1)).strftime(date_format)
+  end_date_str = end_date.strftime(date_format)
+  today = datetime.today().astimezone(pytz.timezone("America/New_York")).date()
+  req_url = BASE_URL.format(api_key=API_KEY, start_date=start_date_str, end_date=end_date_str)
+  if target_date.date() < today:
+    res = session.get(req_url)
+  else:
+    res = requests.get(req_url)
+  start_timestamp = target_date + timedelta(minutes=52)
+  end_timestamp = end_date + timedelta(days=1) - timedelta(minutes=8)
+  
+
+  data = res.json()
+  df = pd.read_json(json.dumps(data["observations"]))
+  df["obs_timestamp"] = df.apply(lambda x: datetime.fromtimestamp(x["valid_time_gmt"]).astimezone(pytz.timezone("America/New_York")).strftime(DATE_FORMAT), axis=1)
+  df = df.astype({'obs_timestamp': 'datetime64[ns]'})
+  initial_cols = ["temp", "obs_timestamp"]
+  df = df[initial_cols]
+  dates_df = pd.DataFrame()
+  dates_df["obs_timestamp"] = pd.date_range(start_timestamp, end_timestamp, freq="H")
+  df = dates_df.merge(df, how='left', on='obs_timestamp')
+ 
+  df["obs_timestamp"] = df.apply(lambda x: (x["obs_timestamp"] + timedelta(minutes=8)).strftime(DATE_FORMAT), axis=1)
+  dicts =  df.to_dict("records")
+  reduced = { k["obs_timestamp"]: k["temp"] for k in dicts}
+  for k in reduced:
+    if np.isnan(reduced[k]): 
+      reduced[k] = None
+  return reduced
+
+@app.route("/predictions")
+@cross_origin()
+def get_predictions():
+    today = datetime.today().astimezone(pytz.timezone("America/New_York")).date()
+    target_date = datetime.strptime(request.args["target_date"], "%Y-%m-%d")
+    app.logger.info(today)
+    app.logger.info(target_date)
+    # target_dates = list(filter(lambda x: x < today, [x.to_pydatetime() for x in pd.date_range(start_date, end_date, freq="D").to_list()]))
+    predictions = predict_for_date(target_date)
+    actual_temp = get_actual_temperatures(target_date) if target_date.date() <= today else None
+
+    merged = { k: {"predicted": predictions[k], "actual": actual_temp[k] if actual_temp else None} for k in predictions}
+    response = app.response_class(response=json.dumps(merged),
+                                  status=200,
+                                  mimetype='application/json')
+    return response
+

web/backend/src/model/keras_metadata.pb

@@ -0,0 +1,8 @@
+
+�%root"_tf_keras_sequential*�%{"name": "sequential", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "must_restore_from_config": false, "class_name": "Sequential", "config": {"name": "sequential", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": {"class_name": "__tuple__", "items": [null, 168, 16]}, "dtype": "float32", "sparse": false, "ragged": false, "name": "lstm_input"}}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 12, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 24, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "Zeros", "config": {}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}, {"class_name": "Reshape", "config": {"name": "reshape", "trainable": true, "dtype": "float32", "target_shape": {"class_name": "__tuple__", "items": [24, 1]}}}]}, "shared_object_id": 10, "build_input_shape": {"class_name": "TensorShape", "items": [null, 168, 16]}, "is_graph_network": true, "full_save_spec": {"class_name": "__tuple__", "items": [[{"class_name": "TypeSpec", "type_spec": "tf.TensorSpec", "serialized": [{"class_name": "TensorShape", "items": [null, 168, 16]}, "float32", "lstm_input"]}], {}]}, "save_spec": {"class_name": "TypeSpec", "type_spec": "tf.TensorSpec", "serialized": [{"class_name": "TensorShape", "items": [null, 168, 16]}, "float32", "lstm_input"]}, "keras_version": "2.9.0", "backend": "tensorflow", "model_config": {"class_name": "Sequential", "config": {"name": "sequential", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": {"class_name": "__tuple__", "items": [null, 168, 16]}, "dtype": "float32", "sparse": false, "ragged": false, "name": "lstm_input"}, "shared_object_id": 0}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 12, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 5}, {"class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 24, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 6}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 7}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 8}, {"class_name": "Reshape", "config": {"name": "reshape", "trainable": true, "dtype": "float32", "target_shape": {"class_name": "__tuple__", "items": [24, 1]}}, "shared_object_id": 9}]}}, "training_config": {"loss": {"class_name": "MeanSquaredError", "config": {"reduction": "auto", "name": "mean_squared_error"}, "shared_object_id": 11}, "metrics": null, "weighted_metrics": null, "loss_weights": null, "optimizer_config": {"class_name": "Adam", "config": {"name": "Adam", "learning_rate": 0.0010000000474974513, "decay": 0.0, "beta_1": 0.8999999761581421, "beta_2": 0.9990000128746033, "epsilon": 1e-07, "amsgrad": false}}}}2

+�
root.layer_with_weights-0"_tf_keras_rnn_layer*�
+{"name": "lstm", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 12, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 5, "input_spec": [{"class_name": "InputSpec", "config": {"dtype": null, "shape": {"class_name": "__tuple__", "items": [null, null, 16]}, "ndim": 3, "max_ndim": null, "min_ndim": null, "axes": {}}, "shared_object_id": 12}], "build_input_shape": {"class_name": "TensorShape", "items": [null, 168, 16]}}2

+�root.layer_with_weights-1"_tf_keras_layer*�{"name": "dense", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 24, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 6}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 7}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 8, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 2, "axes": {"-1": 12}}, "shared_object_id": 13}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 12]}}2

+�root.layer-2"_tf_keras_layer*�{"name": "reshape", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "class_name": "Reshape", "config": {"name": "reshape", "trainable": true, "dtype": "float32", "target_shape": {"class_name": "__tuple__", "items": [24, 1]}}, "shared_object_id": 9}2

+�root.layer_with_weights-0.cell"_tf_keras_layer*�{"name": "lstm_cell", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "class_name": "LSTMCell", "config": {"name": "lstm_cell", "trainable": true, "dtype": "float32", "units": 12, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 4}2

+�
^root.keras_api.metrics.0"_tf_keras_metric*�
{"class_name": "Mean", "name": "loss", "dtype": "float32", "config": {"name": "loss", "dtype": "float32"}, "shared_object_id": 14}2

web/docker-compose.prod.yml

@@ -0,0 +1,10 @@
+version: "3.5"
+services:
+  pred-backend:
+    ports:
+      - "81:5000"
+    
+  pred-frontend:
+    command: npm start
+    ports:
+      - "80:4200"

web/docker-compose.yml

@@ -0,0 +1,34 @@
+version: "3.5"
+services:
+  pred-backend:
+    image: pred-backend:latest
+    ports:
+      - "3001:5000"
+    volumes:
+      - ./backend/src:/app
+    networks:
+      - prediction-project
+    logging:
+      driver: "json-file"
+      options:
+        max-size: "10m"
+  
+  pred-frontend:
+    image: pred-frontend:latest
+    command: npm run start-dev
+    ports:
+      - "4200:4200"
+    volumes:
+      - ./frontend/src:/app/src
+    networks:
+      - prediction-project
+    logging:
+      driver: "json-file"
+      options:
+        max-size: "10m"
+
+volumes:
+  db-volume:
+
+networks:
+  prediction-project:

web/frontend/.browserslistrc

@@ -0,0 +1,16 @@
+# This file is used by the build system to adjust CSS and JS output to support the specified browsers below.
+# For additional information regarding the format and rule options, please see:
+# https://github.com/browserslist/browserslist#queries
+
+# For the full list of supported browsers by the Angular framework, please see:
+# https://angular.io/guide/browser-support
+
+# You can see what browsers were selected by your queries by running:
+#   npx browserslist
+
+last 1 Chrome version
+last 1 Firefox version
+last 2 Edge major versions
+last 2 Safari major versions
+last 2 iOS major versions
+Firefox ESR

web/frontend/.dockerignore

@@ -0,0 +1,3 @@
+node_modules
+.github
+.angular

web/frontend/.editorconfig

@@ -0,0 +1,16 @@
+# Editor configuration, see https://editorconfig.org
+root = true
+
+[*]
+charset = utf-8
+indent_style = space
+indent_size = 2
+insert_final_newline = true
+trim_trailing_whitespace = true
+
+[*.ts]
+quote_type = single
+
+[*.md]
+max_line_length = off
+trim_trailing_whitespace = false

web/frontend/.github/CODE_OF_CONDUCT.md

@@ -0,0 +1,46 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at . The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version]
+
+[homepage]: http://contributor-covenant.org
+[version]: http://contributor-covenant.org/version/1/4/

web/frontend/.github/COMMIT_CONVENTION.md

@@ -0,0 +1,83 @@
+## Git Commit Message Convention
+
+> This is adapted from [Angular's commit convention](https://github.com/conventional-changelog/conventional-changelog/blob/master/packages/conventional-changelog-angular/convention.md).
+
+#### Examples
+
+Appears under "Features" header, `compiler` subheader:
+
+```
+feat(compiler): add 'comments' option
+```
+
+Appears under "Bug Fixes" header, `sidebar` subheader, with a link to issue #28:
+
+```
+fix(sidebar): handle events on blur
+
+close #28
+```
+
+Appears under "Performance Improvements" header, and under "Breaking Changes" with the breaking change explanation:
+
+```
+perf(core): improve vdom diffing by removing 'foo' option
+
+BREAKING CHANGE: The 'foo' option has been removed.
+```
+
+The following commit and commit `667ecc1` do not appear in the changelog if they are under the same release. If not, the revert commit appears under the "Reverts" header.
+
+```
+revert: feat(compiler): add 'comments' option
+
+This reverts commit 667ecc1654a317a13331b17617d973392f415f02.
+```
+
+### Full Message Format
+
+A commit message consists of a **header**, **body** and **footer**.  The header has a **type**, **scope** and **subject**:
+
+```
+<type>(<scope>): <subject>
+<BLANK LINE>
+<body>
+<BLANK LINE>
+<footer>
+```
+
+The **header** is mandatory and the **scope** of the header is optional.
+
+### Revert
+
+If the commit reverts a previous commit, it should begin with `revert: `, followed by the header of the reverted commit. In the body it should say: `This reverts commit <hash>.`, where the hash is the SHA of the commit being reverted.
+
+### Type
+
+If the prefix is `feat`, `fix` or `perf`, it will appear in the changelog. However if there is any [BREAKING CHANGE](#footer), the commit will always appear in the changelog.
+
+Other prefixes are up to your discretion. Suggested prefixes are `docs`, `chore`, `style`, `refactor`, and `test` for non-changelog related tasks.
+
+### Scope
+
+The scope could be anything specifying place of the commit change. For example `core`, `compiler`, `ssr`, `v-model`, `transition` etc...
+
+### Subject
+
+The subject contains succinct description of the change:
+
+* use the imperative, present tense: "change" not "changed" nor "changes"
+* don't capitalize first letter
+* no dot (.) at the end
+
+### Body
+
+Just as in the **subject**, use the imperative, present tense: "change" not "changed" nor "changes".
+The body should include the motivation for the change and contrast this with previous behavior.
+
+### Footer
+
+The footer should contain any information about **Breaking Changes** and is also the place to
+reference GitHub issues that this commit **Closes**.
+
+**Breaking Changes** should start with the word `BREAKING CHANGE:` with a space or two newlines. The rest of the commit message is then used for this.

web/frontend/.github/CONTRIBUTING.md

@@ -0,0 +1,178 @@
+# Contributing to CoreUI
+
+Looking to contribute something to CoreUI? **Here's how you can help.**
+
+Please take a moment to review this document in order to make the contribution process easy and effective for everyone involved.
+
+Following these guidelines helps to communicate that you respect the time of the developers managing and developing this open source project. In return, they should reciprocate that respect in addressing your issue or assessing
+patches and features.
+
+## Using the issue tracker
+
+The [issue tracker](https://github.com/coreui/coreui-free-angular-admin-template/issues) is
+the preferred channel for [bug reports](#bug-reports), [features requests](#feature-requests)
+and [submitting pull requests](#pull-requests), but please respect the following
+restrictions:
+
+* Please **do not** use the issue tracker for personal support requests.
+
+* Please **do not** post comments consisting solely of "+1" or ":thumbsup:".
+  Use [GitHub's "reactions" feature](https://github.blog/2016-03-10-add-reactions-to-pull-requests-issues-and-comments/)
+  instead.
+
+## Bug reports
+
+A bug is a _demonstrable problem_ that is caused by the code in the repository.
+Good bug reports are extremely helpful, so thanks!
+
+Guidelines for bug reports:
+
+0. **Validate and lint your code** — to ensure your problem isn't caused by a simple error in your own code.
+
+1. **Use the GitHub issue search** — check if the issue has already been reported.
+
+2. **Check if the issue has been fixed** — try to reproduce it using the latest `master` or development branch in the repository.
+
+3. **Isolate the problem** — ideally create a [reduced test case](https://css-tricks.com/reduced-test-cases/) and a live example. [This JS Bin](http://jsbin.com/lefey/1/edit?html,output) is a helpful template.
+
+
+A good bug report shouldn't leave others needing to chase you up for more
+information. Please try to be as detailed as possible in your report. What is
+your environment? What steps will reproduce the issue? What browser(s) and OS
+experience the problem? Do other browsers show the bug differently? What
+would you expect to be the outcome? All these details will help people to fix
+any potential bugs.
+
+Example:
+
+> Short and descriptive example bug report title
+>
+> A summary of the issue and the browser/OS environment in which it occurs. If
+> suitable, include the steps required to reproduce the bug.
+>
+> 1. This is the first step
+> 2. This is the second step
+> 3. Further steps, etc.
+>
+> `<url>` - a link to the reduced test case
+>
+> Any other information you want to share that is relevant to the issue being
+> reported. This might include the lines of code that you have identified as
+> causing the bug, and potential solutions (and your opinions on their
+> merits).
+
+## Feature requests
+
+Feature requests are welcome. Before opening a feature request, please take a
+moment to find out whether your idea fits with the scope and aims of the
+project. It's up to *you* to make a strong case to convince the project's
+developers of the merits of this feature. Please provide as much detail
+and context as possible.
+
+
+## Pull requests
+
+Good pull requests—patches, improvements, new features—are a fantastic
+help. They should remain focused in scope and avoid containing unrelated
+commits.
+
+**Please ask first** before embarking on any significant pull request (e.g.
+implementing features, refactoring code, porting to a different language),
+otherwise you risk spending a lot of time working on something that the
+project's developers might not want to merge into the project.
+
+Adhering to the following process is the best way to get your work
+included in the project:
+
+1. [Fork](https://help.github.com/fork-a-repo/) the project, clone your fork,
+   and configure the remotes:
+
+   ```bash
+   # Clone your fork of the repo into the current directory
+   git clone https://github.com/<your-username>/coreui-vue.git
+   # Navigate to the newly cloned directory
+   cd coreui
+   # Assign the original repo to a remote called "upstream"
+   git remote add upstream https://github.com/coreui/coreui-vue.git
+   ```
+
+2. If you cloned a while ago, get the latest changes from upstream:
+
+   ```bash
+   git checkout master
+   git pull upstream master
+   ```
+
+3. Create a new topic branch (off the main project development branch) to
+   contain your feature, change, or fix:
+
+   ```bash
+   git checkout -b <topic-branch-name>
+   ```
+
+4. Commit your changes in logical chunks. Please adhere to these [git commit
+   message guidelines](http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html)
+   or your code is unlikely to be merged into the main project. Use Git's
+   [interactive rebase](https://help.github.com/articles/interactive-rebase)
+   feature to tidy up your commits before making them public.
+
+5. Locally merge (or rebase) the upstream development branch into your topic branch:
+
+   ```bash
+   git pull [--rebase] upstream master
+   ```
+
+6. Push your topic branch up to your fork:
+
+   ```bash
+   git push origin <topic-branch-name>
+   ```
+
+7. [Open a Pull Request](https://help.github.com/articles/using-pull-requests/)
+    with a clear title and description against the `master` branch.
+
+**IMPORTANT**: By submitting a patch, you agree to allow the project owners to
+license your work under the terms of the [MIT License](LICENSE).
+
+### Semantic Git commit messages
+
+Inspired by Sparkbox's awesome article on
+[semantic commit messages](http://seesparkbox.com/foundry/semantic_commit_messages).
+Please use following commit message format.
+
+* chore (updating npm tasks etc; no production code change) -> ```git test -m 'chore: commit-message-here'```
+* docs (changes to documentation) -> ```git commit -m 'docs: commit-message-here'```
+* feat (new feature) -> ```git commit -m 'feat: commit-message-here'```
+* fix (bug fix) -> ```git commit -m 'fix: commit-message-here'```
+* refactor (refactoring production code) -> ```git commit -m 'refactor: commit-message-here'```
+* style (formatting, missing semi colons, etc; no code change) -> ```git commit -m 'style: commit-message-here'```
+* test (adding missing tests, refactoring tests; no production code change) -> ```git test -m 'refactor: commit-message-here'```
+
+## Code guidelines
+
+### HTML
+
+[Adhere to the Code Guide.](http://codeguide.co/#html)
+
+- Use tags and elements appropriate for an HTML5 doctype (e.g., self-closing tags).
+- Use CDNs and HTTPS for third-party JS when possible. We don't use protocol-relative URLs in this case because they break when viewing the page locally via `file://`.
+- Use [WAI-ARIA](https://developer.mozilla.org/en-US/docs/Web/Accessibility/ARIA) attributes in documentation examples to promote accessibility.
+
+### CSS
+
+[Adhere to the Code Guide.](http://codeguide.co/#css)
+
+- When feasible, default color palettes should comply with [WCAG color contrast guidelines](http://www.w3.org/TR/WCAG20/#visual-audio-contrast).
+- Except in rare cases, don't remove default `:focus` styles (via e.g. `outline: none;`) without providing alternative styles. See [this A11Y Project post](http://a11yproject.com/posts/never-remove-css-outlines) for more details.
+
+### JS
+
+- No semicolons (in client-side JS)
+- 2 spaces (no tabs)
+- strict mode
+- "Attractive"
+- Don't use [jQuery event alias convenience methods](https://github.com/jquery/jquery/blob/master/src/event/alias.js) (such as `$().focus()`). Instead, use [`$().trigger(eventType, ...)`](http://api.jquery.com/trigger/) or [`$().on(eventType, ...)`](http://api.jquery.com/on/), depending on whether you're firing an event or listening for an event. (For example, `$().trigger('focus')` or `$().on('focus', function (event) { /* handle focus event */ })`) We do this to be compatible with custom builds of jQuery where the event aliases module has been excluded.
+
+## License
+
+By contributing your code, you agree to license your contribution under the [MIT License](LICENSE).

web/frontend/.github/FUNDING.yml

@@ -0,0 +1,4 @@
+# These are supported funding model platforms
+
+custom: "https://coreui.io/pricing?support=angular"
+open_collective: coreui

web/frontend/.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,20 @@
+---
+name: Bug report
+about: Tell us about a bug you may have identified in CoreUI Free Angular Admin Template.
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+Before opening:
+
+- [Search for duplicate or closed issues](https://github.com/coreui/coreui-free-angular-admin-template/issues?utf8=%E2%9C%93&q=is%3Aissue)
+- [Validate](https://html5.validator.nu/) any HTML to avoid common problems
+- Read the [contributing guidelines](https://github.com/coreui/coreui-free-angular-admin-template/blob/v4-dev/.github/CONTRIBUTING.md)
+
+Bug reports must include:
+
+- Operating system and version (Windows, macOS, Android, iOS)
+- Browser and version (Chrome, Firefox, Safari, Microsoft Edge, Opera, Android Browser)
+- A [reduced test case](https://css-tricks.com/reduced-test-cases/) or suggested fix using [CodePen](https://codepen.io/) or [JS Bin](https://jsbin.com/)

web/frontend/.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,18 @@
+---
+name: Feature request
+about: Suggest an idea for a new feature in CoreUI Free Angular Admin Template.
+title: ''
+labels: feature
+assignees: ''
+
+---
+
+Before opening:
+
+- [Search for duplicate or closed issues](https://github.com/coreui/coreui-free-angular-admin-template/issues?utf8=%E2%9C%93&q=is%3Aissue)
+- Read the [contributing guidelines](https://github.com/coreui/coreui-free-angular-admin-template/blob/main/.github/CONTRIBUTING.md)
+
+Feature requests must include:
+
+- As much detail as possible for what we should add and why it's important to Bootstrap
+- Relevant links to prior art, screenshots, or live demos whenever possible

web/frontend/.github/SUPPORT.md

@@ -0,0 +1,9 @@
+### Bug reports
+
+See the [contributing guidelines](CONTRIBUTING.md) for sharing bug reports.
+
+### How-to
+
+For general troubleshooting or help getting started:
+
+- Go to [Discussions](https://github.com/coreui/coreui-free-angular-admin-template/discussions).

web/frontend/.github/workflows/build-check.yml

@@ -0,0 +1,39 @@
+name: Build Check
+
+on:
+  push:
+    branches-ignore:
+      - "dependabot/**"
+  pull_request:
+    branches:
+      - main
+      - v4
+  schedule:
+    - # build runs every weekday at 4:15AM UTC
+    - cron: '15 4 * * *'
+
+env:
+  FORCE_COLOR: 2
+  NODE: 16
+
+jobs:
+  build:
+    strategy:
+      matrix:
+        platform: [ubuntu-latest, windows-latest, macOS-latest]
+        node-version: [16.x, 18.x]
+    runs-on: ${{ matrix.platform }}
+    steps:
+      - name: Clone repository
+        uses: actions/checkout@v3
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version: ${{ env.node-version }}
+
+      - name: Install npm dependencies
+        run: npm install
+
+      - name: Run build
+        run: npm run build

web/frontend/.github/workflows/stale.yml

@@ -0,0 +1,27 @@
+# This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
+#
+# You can adjust the behavior by modifying this file.
+# For more information, see:
+# https://github.com/actions/stale
+name: Mark stale issues and pull requests
+
+on:
+  schedule:
+  - cron: '34 23 * * 0'
+
+jobs:
+  stale:
+
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+
+    steps:
+    - uses: actions/stale@v5
+      with:
+        repo-token: ${{ secrets.GITHUB_TOKEN }}
+        stale-issue-message: 'This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions'
+        stale-pr-message: 'This PR has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions'
+        stale-issue-label: 'no-issue-activity'
+        stale-pr-label: 'no-pr-activity'

web/frontend/.gitignore

@@ -0,0 +1,45 @@
+# See http://help.github.com/ignore-files/ for more about ignoring files.
+
+# Compiled output
+/dist
+/tmp
+/out-tsc
+/bazel-out
+
+# Node
+/node_modules
+npm-debug.log
+yarn-error.log
+
+# profiling files
+chrome-profiler-events*.json
+
+# IDEs and editors
+.idea/
+.project
+.classpath
+.c9/
+*.launch
+.settings/
+*.sublime-workspace
+
+# Visual Studio Code
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+.history/*
+
+# Miscellaneous
+/.angular/cache
+.sass-cache/
+/connect.lock
+/coverage
+/libpeerconnection.log
+testem.log
+/typings
+
+# System files
+.DS_Store
+Thumbs.db

web/frontend/README.md

@@ -0,0 +1,219 @@
+[![@coreui angular](https://img.shields.io/badge/@coreui%20-angular-lightgrey.svg?style=flat-square)](https://github.com/coreui/angular)
+[![npm-coreui-angular-next][npm-coreui-angular-badge-next]][npm-coreui-angular]
+[![NPM downloads][npm-coreui-angular-download]][npm-coreui-angular]  
+[![@coreui coreui](https://img.shields.io/badge/@coreui%20-coreui-lightgrey.svg?style=flat-square)](https://github.com/coreui/coreui)
+[![npm package][npm-coreui-badge]][npm-coreui]
+[![NPM downloads][npm-coreui-download]][npm-coreui]  
+![angular](https://img.shields.io/badge/angular-^14.2.0-lightgrey.svg?style=flat-square&logo=angular)
+
+[npm-coreui-angular]: https://www.npmjs.com/package/@coreui/angular
+[npm-coreui-angular-badge]: https://img.shields.io/npm/v/@coreui/angular.png?style=flat-square
+[npm-coreui-angular-badge-next]: https://img.shields.io/npm/v/@coreui/angular/next?style=flat-square&color=red
+[npm-coreui-angular-download]: https://img.shields.io/npm/dm/@coreui/angular.svg?style=flat-square
+[npm-coreui]: https://www.npmjs.com/package/@coreui/coreui
+[npm-coreui-badge]: https://img.shields.io/npm/v/@coreui/coreui.png?style=flat-square
+[npm-coreui-download]: https://img.shields.io/npm/dm/@coreui/coreui.svg?style=flat-square
+
+# CoreUI 4 Angular 14 Free Admin Template
+
+CoreUI is meant to be the UX game changer. Pure & transparent code is devoid of redundant components, so the app is light enough to offer ultimate user experience. This means mobile devices also, where the navigation is just as easy and intuitive as on a desktop or laptop. The CoreUI Layout API lets you customize your project for almost any device – be it Mobile, Web or WebApp – CoreUI covers them all!
+
+[CoreUI Angular Admin Template](https://coreui.io/angular)  
+[Demo](https://coreui.io/angular/demo/4.0/free/)
+
+## Table of Contents
+
+* [Versions](#versions)
+* [CoreUI Pro](#coreui-pro)
+* [Quick Start](#quick-start)
+* [Installation](#installation)
+* [Basic usage](#basic-usage)
+* [What's included](#whats-included)
+* [Documentation](#documentation)
+* [Versioning](#versioning)
+* [Creators](#creators)
+* [Community](#community)
+* [Copyright and License](#copyright-and-license)
+
+## Versions
+
+* [CoreUI Free Bootstrap Admin Template](https://github.com/coreui/coreui-free-bootstrap-admin-template)
+* [CoreUI Free Angular Admin Template](https://github.com/coreui/coreui-free-angular-admin-template)
+* [CoreUI Free React.js Admin Template](https://github.com/coreui/coreui-free-react-admin-template)
+* [CoreUI Free Vue.js Admin Template](https://github.com/coreui/coreui-free-vue-admin-template)
+
+## CoreUI Pro
+
+**Only customers with [Enterpise Membership Plan](https://coreui.io/pro/#buy) have access to private github CoreUI Pro repository.**
+
+* 💪  [CoreUI Pro Angular Admin Template](https://coreui.io/product/angular-dashboard-template/)
+* 💪  [CoreUI Pro Bootstrap Admin Template](https://coreui.io/product/bootstrap-dashboard-template/)
+* 💪  [CoreUI Pro React Admin Template](https://coreui.io/product/react-dashboard-template/)
+* 💪  [CoreUI Pro Vue Admin Template](https://coreui.io/product/vue-dashboard-template/)
+
+## Quick Start
+
+- [Download the latest release](https://github.com/coreui/coreui-free-angular-admin-template/)
+- Clone the repo: `git clone https://github.com/coreui/coreui-free-angular-admin-template.git`
+
+#### <i>Prerequisites</i>
+Before you begin, make sure your development environment includes `Node.js®` and an `npm` package manager.
+
+###### Node.js
+Angular 14 requires `Node.js` version `^14.15` or `^16.10`.
+
+- To check your version, run `node -v` in a terminal/console window.
+- To get `Node.js`, go to [nodejs.org](https://nodejs.org/).
+
+###### Angular CLI
+Install the Angular CLI globally using a terminal/console window.
+```bash
+npm install -g @angular/cli
+```
+
+### Installation
+
+``` bash
+$ npm install
+```
+
+### Basic usage
+
+``` bash
+# dev server with hot reload at http://localhost:4200
+$ npm start
+```
+
+Navigate to [http://localhost:4200](http://localhost:4200). The app will automatically reload if you change any of the source files.
+
+#### Build
+
+Run `build` to build the project. The build artifacts will be stored in the `dist/` directory.
+
+```bash
+# build for production with minification
+$ npm run build
+```
+## What's included
+
+Within the download you'll find the following directories and files, logically grouping common assets and providing both compiled and minified variations. You'll see something like this:
+
+```
+coreui-free-angular-admin-template
+├── src/                         # project root
+│   ├── app/                     # main app directory
+|   │   ├── containers/          # layout containers
+|   |   │   └── default-layout/  # layout containers
+|   |   |       └── _nav.js      # sidebar navigation config
+|   │   ├── icons/               # icons set for the app
+|   │   └── views/               # application views
+│   ├── assets/                  # images, icons, etc.
+��   ├── components/              # components for demo only
+│   ├── scss/                    # scss styles
+│   └── index.html               # html template
+│
+├── angular.json
+├── README.md
+└── package.json
+```
+
+## Documentation
+
+The documentation for the CoreUI Admin Template is hosted at our website [CoreUI for Angular](https://coreui.io/angular/)
+
+---
+
+This project was generated with [Angular CLI](https://github.com/angular/angular-cli) version 14.0.0.
+
+## Versioning
+
+For transparency into our release cycle and in striving to maintain backward compatibility, CoreUI Free Admin Template is maintained under [the Semantic Versioning guidelines](http://semver.org/).
+
+See [the Releases section of our project](https://github.com/coreui/coreui-free-angular-admin-template/releases) for changelogs for each release version.
+
+## Development server
+
+Run `ng serve` for a dev server. Navigate to `http://localhost:4200/`. The app will automatically reload if you change any of the source files.
+
+## Code scaffolding
+
+Run `ng generate component component-name` to generate a new component. You can also use `ng generate directive|pipe|service|class|guard|interface|enum|module`.
+
+## Build
+
+Run `ng build` to build the project. The build artifacts will be stored in the `dist/` directory.
+
+## Running unit tests
+
+Run `ng test` to execute the unit tests via [Karma](https://karma-runner.github.io).
+
+## Running end-to-end tests
+
+Run `ng e2e` to execute the end-to-end tests via a platform of your choice. To use this command, you need to first add a package that implements end-to-end testing capabilities.
+
+## Further help
+
+To get more help on the Angular CLI use `ng help` or go check out the [Angular CLI Overview and Command Reference](https://angular.io/cli) page.
+
+## Creators
+
+**Łukasz Holeczek**
+* <https://twitter.com/lukaszholeczek>
+* <https://github.com/mrholek>
+* <https://github.com/coreui>
+
+**CoreUI team**
+* https://github.com/orgs/coreui/people
+
+## Community
+
+Get updates on CoreUI's development and chat with the project maintainers and community members.
+
+- Follow [@core_ui on Twitter](https://twitter.com/core_ui).
+- Read and subscribe to [CoreUI Blog](https://coreui.io/blog/).
+
+## Support CoreUI Development
+
+CoreUI is an MIT-licensed open source project and is completely free to use. However, the amount of effort needed to maintain and develop new features for the project is not sustainable without proper financial backing. You can support development by buying the [CoreUI PRO](https://coreui.io/pricing/) or by becoming a sponsor via [Open Collective](https://opencollective.com/coreui/).
+
+<!--- StartOpenCollectiveBackers -->
+
+### Platinum Sponsors
+
+Support this project by [becoming a Platinum Sponsor](https://opencollective.com/coreui/contribute/platinum-sponsor-40959/). A large company logo will be added here with a link to your website.
+
+<a href="https://opencollective.com/coreui/contribute/platinum-sponsor-40959/checkout"><img src="https://opencollective.com/coreui/tiers/platinum-sponsor/0/avatar.svg?avatarHeight=100"></a>
+
+### Gold Sponsors
+
+Support this project by [becoming a Gold Sponsor](https://opencollective.com/coreui/contribute/gold-sponsor-40960/). A big company logo will be added here with a link to your website.
+
+<a href="https://opencollective.com/coreui/contribute/gold-sponsor-40960/checkout"><img src="https://opencollective.com/coreui/tiers/gold-sponsor/0/avatar.svg?avatarHeight=100"></a> 
+
+### Silver Sponsors
+
+Support this project by [becoming a Silver Sponsor](https://opencollective.com/coreui/contribute/silver-sponsor-40967/). A medium company logo will be added here with a link to your website.
+
+<a href="https://opencollective.com/coreui/contribute/silver-sponsor-40967/checkout"><img src="https://opencollective.com/coreui/tiers/gold-sponsor/0/avatar.svg?avatarHeight=100"></a>
+
+### Bronze Sponsors
+
+Support this project by [becoming a Bronze Sponsor](https://opencollective.com/coreui/contribute/bronze-sponsor-40966/). The company avatar will show up here with a link to your OpenCollective Profile.
+
+<a href="https://opencollective.com/coreui/contribute/bronze-sponsor-40966/checkout"><img src="https://opencollective.com/coreui/tiers/bronze-sponsor/0/avatar.svg?avatarHeight=100"></a> 
+
+### Backers
+
+Thanks to all the backers and sponsors! Support this project by [becoming a backer](https://opencollective.com/coreui/contribute/backer-40965/).
+
+<a href="https://opencollective.com/coreui/contribute/backer-40965/checkout" target="_blank" rel="noopener"><img src="https://opencollective.com/coreui/backers.svg?width=890"></a>
+
+<!--- EndOpenCollectiveBackers -->
+
+## Copyright and License
+
+copyright 2022 creativeLabs Łukasz Holeczek.   
+
+ 
+Code released under [the MIT license](https://github.com/coreui/coreui-free-react-admin-template/blob/master/LICENSE).
+There is only one limitation you can't re-distribute the CoreUI as stock. You can’t do this if you modify the CoreUI. In past we faced some problems with persons who tried to sell CoreUI based templates.

web/frontend/angular.json

@@ -0,0 +1,118 @@
+{
+  "$schema": "./node_modules/@angular/cli/lib/config/schema.json",
+  "cli": {
+    "analytics": false
+  },
+  "version": 1,
+  "newProjectRoot": "projects",
+  "projects": {
+    "weather-forecaster": {
+      "projectType": "application",
+      "schematics": {
+        "@schematics/angular:component": {
+          "style": "scss"
+        },
+        "@schematics/angular:application": {
+          "strict": true
+        }
+      },
+      "root": "",
+      "sourceRoot": "src",
+      "prefix": "app",
+      "architect": {
+        "build": {
+          "builder": "@angular-devkit/build-angular:browser",
+          "options": {
+            "outputPath": "dist/weather-forecaster",
+            "index": "src/index.html",
+            "main": "src/main.ts",
+            "polyfills": "src/polyfills.ts",
+            "tsConfig": "tsconfig.app.json",
+            "inlineStyleLanguage": "scss",
+            "preserveSymlinks": true,
+            "assets": [
+              "src/favicon.ico",
+              "src/assets"
+            ],
+            "styles": [
+              "src/scss/styles.scss"
+            ],
+            "scripts": [],
+            "allowedCommonJsDependencies": [
+              "chart.js",
+              "@coreui/chartjs/dist/js/coreui-chartjs.js"
+            ]
+          },
+          "configurations": {
+            "production": {
+              "budgets": [
+                {
+                  "type": "initial",
+                  "maximumWarning": "1500kb",
+                  "maximumError": "6mb"
+                },
+                {
+                  "type": "anyComponentStyle",
+                  "maximumWarning": "2kb",
+                  "maximumError": "4kb"
+                }
+              ],
+              "fileReplacements": [
+                {
+                  "replace": "src/environments/environment.ts",
+                  "with": "src/environments/environment.prod.ts"
+                }
+              ],
+              "outputHashing": "all"
+            },
+            "development": {
+              "buildOptimizer": false,
+              "optimization": false,
+              "vendorChunk": true,
+              "extractLicenses": false,
+              "sourceMap": true,
+              "namedChunks": true
+            }
+          },
+          "defaultConfiguration": "production"
+        },
+        "serve": {
+          "builder": "@angular-devkit/build-angular:dev-server",
+          "configurations": {
+            "production": {
+              "browserTarget": "weather-forecaster:build:production"
+            },
+            "development": {
+              "browserTarget": "weather-forecaster:build:development"
+            }
+          },
+          "defaultConfiguration": "development"
+        },
+        "extract-i18n": {
+          "builder": "@angular-devkit/build-angular:extract-i18n",
+          "options": {
+            "browserTarget": "weather-forecaster:build"
+          }
+        },
+        "test": {
+          "builder": "@angular-devkit/build-angular:karma",
+          "options": {
+            "main": "src/test.ts",
+            "polyfills": "src/polyfills.ts",
+            "tsConfig": "tsconfig.spec.json",
+            "karmaConfig": "karma.conf.js",
+            "inlineStyleLanguage": "scss",
+            "assets": [
+              "src/favicon.ico",
+              "src/assets"
+            ],
+            "styles": [
+              "src/scss/styles.scss"
+            ],
+            "scripts": []
+          }
+        }
+      }
+    }
+  }
+}