{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyN7KrJ5aFUDzz8ZbDcCHGEo",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/inigmat/exupery/blob/main/XER_reading.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Intro\n",
        "\n",
        "This notebook demonstrates an example of how to use [the Primavera P6 xer files reader](https://pypi.org/project/xerparser/0.10.3/) library for data preparation.\n",
        "\n",
        "\n",
        "The XER file contains the same data presented in the [notebook](https://nbviewer.org/github/inigmat/exupery/blob/main/Schedule_CPLEX.ipynb) which is shown in the [\"Optimizing Project Planning and Material transportation\"](https://inigmat.github.io/home/2023/11/29/Transport-and-Resources.html) post.\n",
        "\n",
        "By obtaining the file via URL link, the required data—task names, durations, precedences, and release dates (intervals between each house's earliest starting date)—is transformed into Python objects.\n"
      ],
      "metadata": {
        "id": "BhG4x-GqoR_3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Installing xerparser\n"
      ],
      "metadata": {
        "id": "EYEH5p-0oF4Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import importlib\n",
        "\n",
        "# Check if xerparser is already installed\n",
        "try:\n",
        "    importlib.import_module('xerparser')\n",
        "    print(\"xerparser is already installed.\")\n",
        "except ImportError:\n",
        "    try:\n",
        "        # Attempt installation\n",
        "        %pip install xerparser\n",
        "    except Exception as e:\n",
        "        print(\"An error occurred while installing xerparser:\", e)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gbiCgG_RUiY0",
        "outputId": "bb1d4cc0-73ad-410f-ee4c-0fe89d11d7a2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "xerparser is already installed.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Getting the XER file"
      ],
      "metadata": {
        "id": "sya1fu_QqTgW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "\n",
        "url = \"https://raw.githubusercontent.com/inigmat/exupery/main/files/schedule/MDL4D.xer\"\n",
        "\n",
        "try:\n",
        "    response = requests.get(url)\n",
        "    if response.status_code == 200:\n",
        "        print(\"Request successful!\")\n",
        "    else:\n",
        "        print(f\"Failed to retrieve data. Status code: {response.status_code}\")\n",
        "except requests.exceptions.RequestException as e:\n",
        "    print(f\"An error occurred: {e}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sjlr83pETrsi",
        "outputId": "9559e561-2f45-496c-9ab3-a0276502c925"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Request successful!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Read the downloaded file with checking for errors"
      ],
      "metadata": {
        "id": "9nLeMn863_fl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from xerparser import Xer, CorruptXerFile\n",
        "\n",
        "try:\n",
        "    xer = Xer(response.text)\n",
        "except CorruptXerFile as e:\n",
        "    for error in e.errors:\n",
        "        print(error)"
      ],
      "metadata": {
        "id": "-G_0Dr4lJhul"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Getting the project data"
      ],
      "metadata": {
        "id": "2qKhVOAF37Yl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "project = list(xer.projects.values())[0]"
      ],
      "metadata": {
        "id": "q1zW1dI7fxJT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "We have to get the following data\n",
        "\n",
        "```\n",
        "NbWorkers = 3\n",
        "NbHouses  = 5\n",
        "\n",
        "TaskNames = (\"masonry\",\"carpentry\",\"plumbing\",\n",
        "             \"ceiling\",\"roofing\",\"painting\",\n",
        "             \"windows\",\"facade\",\"garden\",\"moving\")\n",
        "\n",
        "Duration =  [35, 15, 40, 15, 5, 10, 5, 10, 5, 5]\n",
        "\n",
        "ReleaseDate = [31, 0, 90, 120, 90]\n",
        "\n",
        "Precedences = [(\"masonry\", \"carpentry\"), (\"masonry\", \"plumbing\"), (\"masonry\", \"ceiling\"),\n",
        "               (\"carpentry\", \"roofing\"), (\"ceiling\", \"painting\"), (\"roofing\", \"windows\"),\n",
        "               (\"roofing\", \"facade\"), (\"plumbing\", \"facade\"), (\"roofing\", \"garden\"),\n",
        "               (\"plumbing\", \"garden\"), (\"windows\", \"moving\"), (\"facade\", \"moving\"),\n",
        "               (\"garden\", \"moving\"), (\"painting\", \"moving\")]\n",
        "```\n",
        "\n"
      ],
      "metadata": {
        "id": "WwED080mhUzT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Start with getting the WBS (house numbers)\n",
        "\n",
        "We skip the first two levels using WBS_LVL variable"
      ],
      "metadata": {
        "id": "9ECY5LtO4l-F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "WBS_LVL = 2\n",
        "houses = [obj.name for obj in project.wbs_nodes[WBS_LVL:]]\n",
        "NbHouses= len(houses)\n",
        "houses"
      ],
      "metadata": {
        "id": "h_slxPqjRvWH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2db66196-9c1f-4646-e4e4-a9f8791ea424"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['House 1', 'House 2', 'House 3', 'House 4', 'House 5']"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Obtain the labor resources of the project to get the number of workers"
      ],
      "metadata": {
        "id": "mnuxHbRR5mqB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "workers = {}\n",
        "for res in project.resources:\n",
        "  if res.rsrc_type == \"RT_Labor\":\n",
        "    workers[res.rsrc_id] = res.resource.name\n",
        "NbWorkers = len(workers)"
      ],
      "metadata": {
        "id": "spxHZUTpareG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Prepare pandas dataframe to check out the tasks data such as 'TASK ID','Name','Type', 'WBS ID', 'Duration', 'Successors (ID, Link, Lag)'"
      ],
      "metadata": {
        "id": "RFsILb_753_3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "tasks_df = pd.DataFrame(columns=['TASK ID','Name','Type', 'WBS ID', 'Duration', 'Successors (ID, Link, Lag)'])\n",
        "\n",
        "for task in project.tasks:\n",
        "    task_sucs = []\n",
        "    for pred_link in task.successors:\n",
        "        task_suc = pred_link.task.uid\n",
        "        task_link = pred_link.link\n",
        "        task_lag = pred_link.lag\n",
        "        task_sucs.append((task_suc, task_link, task_lag))\n",
        "\n",
        "    tasks_df = pd.concat([tasks_df, pd.DataFrame(\n",
        "        {'TASK ID': [task.uid],\n",
        "         'Name': [task.name],\n",
        "         'Type': [task.type],\n",
        "         'WBS ID': [task.wbs_id],\n",
        "         'Duration': [task.duration],\n",
        "         'Successors (ID, Link, Lag)': [task_sucs],\n",
        "         })], ignore_index=True)"
      ],
      "metadata": {
        "id": "SdzXOiYMmBiK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tasks_df.head(15)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "dAkhLXxm5ph6",
        "outputId": "36199cdb-a44e-4d67-d913-35478941617c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   TASK ID           Name              Type WBS ID Duration  \\\n",
              "0   104836  House 1 Start  TaskType.TT_Mile  26152        0   \n",
              "1   104837        Masonry  TaskType.TT_Task  26154       35   \n",
              "2   104838      Carpentry  TaskType.TT_Task  26154       15   \n",
              "3   104839       Plumbing  TaskType.TT_Task  26154       40   \n",
              "4   104840        Ceiling  TaskType.TT_Task  26154       15   \n",
              "5   104841        Roofing  TaskType.TT_Task  26154        5   \n",
              "6   104842       Painting  TaskType.TT_Task  26154       10   \n",
              "7   104843        Windows  TaskType.TT_Task  26154        5   \n",
              "8   104844         Facade  TaskType.TT_Task  26154       10   \n",
              "9   104845         Garden  TaskType.TT_Task  26154        5   \n",
              "10  104846         Moving  TaskType.TT_Rsrc  26154        5   \n",
              "11  104847  House 2 Start  TaskType.TT_Mile  26152        0   \n",
              "12  104848        Masonry  TaskType.TT_Task  26155       35   \n",
              "13  104849      Carpentry  TaskType.TT_Task  26155       15   \n",
              "14  104850       Plumbing  TaskType.TT_Task  26155       40   \n",
              "\n",
              "                           Successors (ID, Link, Lag)  \n",
              "0                                                  []  \n",
              "1   [(104838, FS, 0), (104839, FS, 0), (104840, FS...  \n",
              "2                                   [(104841, FS, 0)]  \n",
              "3                  [(104844, FS, 0), (104845, FS, 0)]  \n",
              "4                                   [(104842, FS, 0)]  \n",
              "5   [(104843, FS, 0), (104844, FS, 0), (104845, FS...  \n",
              "6                                   [(104846, FS, 0)]  \n",
              "7                                   [(104846, FS, 0)]  \n",
              "8                                   [(104846, FS, 0)]  \n",
              "9                                   [(104846, FS, 0)]  \n",
              "10                                  [(104883, FF, 0)]  \n",
              "11                                                 []  \n",
              "12  [(104849, FS, 0), (104850, FS, 0), (104851, FS...  \n",
              "13                                  [(104852, FS, 0)]  \n",
              "14                 [(104855, FS, 0), (104856, FS, 0)]  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-11e5c0b1-13df-42bc-980f-216548301c26\" 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>TASK ID</th>\n",
              "      <th>Name</th>\n",
              "      <th>Type</th>\n",
              "      <th>WBS ID</th>\n",
              "      <th>Duration</th>\n",
              "      <th>Successors (ID, Link, Lag)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>104836</td>\n",
              "      <td>House 1 Start</td>\n",
              "      <td>TaskType.TT_Mile</td>\n",
              "      <td>26152</td>\n",
              "      <td>0</td>\n",
              "      <td>[]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>104837</td>\n",
              "      <td>Masonry</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>35</td>\n",
              "      <td>[(104838, FS, 0), (104839, FS, 0), (104840, FS...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>104838</td>\n",
              "      <td>Carpentry</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>15</td>\n",
              "      <td>[(104841, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>104839</td>\n",
              "      <td>Plumbing</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>40</td>\n",
              "      <td>[(104844, FS, 0), (104845, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>104840</td>\n",
              "      <td>Ceiling</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>15</td>\n",
              "      <td>[(104842, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>104841</td>\n",
              "      <td>Roofing</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>5</td>\n",
              "      <td>[(104843, FS, 0), (104844, FS, 0), (104845, FS...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>104842</td>\n",
              "      <td>Painting</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>10</td>\n",
              "      <td>[(104846, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>104843</td>\n",
              "      <td>Windows</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>5</td>\n",
              "      <td>[(104846, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>104844</td>\n",
              "      <td>Facade</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>10</td>\n",
              "      <td>[(104846, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>104845</td>\n",
              "      <td>Garden</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26154</td>\n",
              "      <td>5</td>\n",
              "      <td>[(104846, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>104846</td>\n",
              "      <td>Moving</td>\n",
              "      <td>TaskType.TT_Rsrc</td>\n",
              "      <td>26154</td>\n",
              "      <td>5</td>\n",
              "      <td>[(104883, FF, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>104847</td>\n",
              "      <td>House 2 Start</td>\n",
              "      <td>TaskType.TT_Mile</td>\n",
              "      <td>26152</td>\n",
              "      <td>0</td>\n",
              "      <td>[]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>104848</td>\n",
              "      <td>Masonry</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26155</td>\n",
              "      <td>35</td>\n",
              "      <td>[(104849, FS, 0), (104850, FS, 0), (104851, FS...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>104849</td>\n",
              "      <td>Carpentry</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26155</td>\n",
              "      <td>15</td>\n",
              "      <td>[(104852, FS, 0)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>104850</td>\n",
              "      <td>Plumbing</td>\n",
              "      <td>TaskType.TT_Task</td>\n",
              "      <td>26155</td>\n",
              "      <td>40</td>\n",
              "      <td>[(104855, FS, 0), (104856, FS, 0)]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-11e5c0b1-13df-42bc-980f-216548301c26')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-11e5c0b1-13df-42bc-980f-216548301c26 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-11e5c0b1-13df-42bc-980f-216548301c26');\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",
              "\n",
              "\n",
              "<div id=\"df-f88aaf74-ee16-4e74-a1c1-3d3afd25655b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f88aaf74-ee16-4e74-a1c1-3d3afd25655b')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f88aaf74-ee16-4e74-a1c1-3d3afd25655b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "tasks_df",
              "repr_error": "'str' object has no attribute 'empty'"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Get the list of task names. Filter by wbs_id due to the repeating structure of activities on each house"
      ],
      "metadata": {
        "id": "-1uKFFLf6XkD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def get_task_dict_by_wbs_id(df, wbs_id):\n",
        "    filtered_df = df[df['WBS ID'] == wbs_id]\n",
        "    task_dict = dict(zip(filtered_df['TASK ID'], filtered_df['Name']))\n",
        "    return task_dict\n",
        "\n",
        "wbs_id = '26154' # wbs_id of activites on House 1 (taken from the dataframe above)\n",
        "task_dict = get_task_dict_by_wbs_id(tasks_df, wbs_id)\n",
        "TaskNames = tuple(task_dict.values())"
      ],
      "metadata": {
        "id": "z7wTzw6lwNgf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Get the tasks duration"
      ],
      "metadata": {
        "id": "xroCud946zAJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "durations = {task_id: tasks_df.loc[tasks_df['TASK ID'] == task_id, 'Duration'].values[0] for task_id in task_dict.keys()}\n",
        "Duration =  list(durations.values())"
      ],
      "metadata": {
        "id": "-2B234fTxuY7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Get the precedences of the tasks"
      ],
      "metadata": {
        "id": "jJgBMctH7HBQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prec = []\n",
        "for task in project.tasks:\n",
        "  if task.uid in task_dict:\n",
        "    for pred_link in task.successors:\n",
        "      suc_uid = pred_link.task.uid\n",
        "      if suc_uid in task_dict:\n",
        "        suc_name = pred_link.task.name\n",
        "        prec.append((task.name,suc_name))\n",
        "Precedences = prec"
      ],
      "metadata": {
        "id": "DPSmJMX1ytUt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Get the release dates. Dates ordered by the house number"
      ],
      "metadata": {
        "id": "VD3uCInt7T9f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lags = {}\n",
        "for rel in project.relationships:\n",
        "    if str(rel.predecessor.type) == 'TaskType.TT_Mile':\n",
        "      lags[rel.successor.wbs.name] = rel.lag\n",
        "lags"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vn_Kgd9W8pND",
        "outputId": "1154f128-88b1-48b6-f551-6afcccc4f76c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'House 2': 0, 'House 1': 31, 'House 3': 90, 'House 4': 120, 'House 5': 90}"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ReleaseDate_dict = {key: lags.get(key) for key in sorted(lags)}\n",
        "ReleaseDate = list(ReleaseDate_dict.values())"
      ],
      "metadata": {
        "id": "kTx8RVxqnOZ8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Finally obtain the project data"
      ],
      "metadata": {
        "id": "V4e2bEzQ7sgp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"NbWorkers =\", NbWorkers, \"\\n\")\n",
        "print(\"NbHouses =\", NbHouses, \"\\n\")\n",
        "print(\"TaskNames =\", TaskNames, \"\\n\")\n",
        "print(\"Duration =\", Duration, \"\\n\")\n",
        "print(\"ReleaseDate =\", ReleaseDate, \"\\n\")\n",
        "print(\"Precedences =\", Precedences, \"\\n\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p7aKiCvMNF8Z",
        "outputId": "2d0f3c82-6208-4328-ffd2-c5c30868fd2b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "NbWorkers = 3 \n",
            "\n",
            "NbHouses = 5 \n",
            "\n",
            "TaskNames = ('Masonry', 'Carpentry', 'Plumbing', 'Ceiling', 'Roofing', 'Painting', 'Windows', 'Facade', 'Garden', 'Moving') \n",
            "\n",
            "Duration = [35, 15, 40, 15, 5, 10, 5, 10, 5, 5] \n",
            "\n",
            "ReleaseDate = [31, 0, 90, 120, 90] \n",
            "\n",
            "Precedences = [('Masonry', 'Carpentry'), ('Masonry', 'Plumbing'), ('Masonry', 'Ceiling'), ('Carpentry', 'Roofing'), ('Plumbing', 'Facade'), ('Plumbing', 'Garden'), ('Ceiling', 'Painting'), ('Roofing', 'Windows'), ('Roofing', 'Facade'), ('Roofing', 'Garden'), ('Painting', 'Moving'), ('Windows', 'Moving'), ('Facade', 'Moving'), ('Garden', 'Moving')] \n",
            "\n"
          ]
        }
      ]
    }
  ]
}