notebooks/2023_11_07_Firebase_Interface.ipynb

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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/michaelachmann/social-media-lab/blob/main/notebooks/2023_11_07_Firebase_Interface.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Firebase Interace Notebook [![DOI](https://zenodo.org/badge/660157642.svg)](https://zenodo.org/doi/10.5281/zenodo.8199901)\n",
        "\n",
        "![Notes on (Computational) Social Media Research Banner](https://raw.githubusercontent.com/michaelachmann/social-media-lab/main/images/banner.png)\n",
        "\n",
        "## Overview\n",
        "\n",
        "This Jupyter notebook is a part of the social-media-lab.net project, which is a work-in-progress textbook on computational social media analysis. The notebook is intended for use in my classes.\n",
        "\n",
        "The **Firebase Interace Notebook** Notebook provides an interface for the backend, to create projects and export data from firebase.\n",
        "\n",
        "\n",
        "### Project Information\n",
        "\n",
        "- Project Website: [social-media-lab.net](https://social-media-lab.net/)\n",
        "- GitHub Repository: [https://github.com/michaelachmann/social-media-lab](https://github.com/michaelachmann/social-media-lab)\n",
        "\n",
        "## License Information\n",
        "\n",
        "This notebook, along with all other notebooks in the project, is licensed under the following terms:\n",
        "\n",
        "- License: [GNU General Public License version 3.0 (GPL-3.0)](https://www.gnu.org/licenses/gpl-3.0.de.html)\n",
        "- License File: [LICENSE.md](https://github.com/michaelachmann/social-media-lab/blob/main/LICENSE.md)\n",
        "\n",
        "\n",
        "## Citation\n",
        "\n",
        "If you use or reference this notebook in your work, please cite it appropriately. Here is an example of the citation:\n",
        "\n",
        "```\n",
        "Michael Achmann. (2023). michaelachmann/social-media-lab: 2023-11-09 (v0.0.4). Zenodo. https://doi.org/10.5281/zenodo.8199901\n",
        "```"
      ],
      "metadata": {
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    },
    {
      "cell_type": "code",
      "source": [
        "!pip -q install firebase-admin"
      ],
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      "outputs": []
    },
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      "execution_count": 1,
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        "id": "vXVRVTOVjPo2",
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      "source": [
        "# @title Connecting to Firebase\n",
        "# @markdown Please provide the path to your credentials file\n",
        "\n",
        "import firebase_admin\n",
        "from firebase_admin import credentials, firestore\n",
        "\n",
        "credentials_path = '/content/XXXX-firebase-adminsdk-ZZZ-YYYYY.json'  # @param {type: \"string\"}\n",
        "\n",
        "cred = credentials.Certificate(credentials_path)\n",
        "firebase_admin.initialize_app(cred)\n",
        "db = firestore.client()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Project Creation\n",
        "# @markdown Please fill in the following form in order to create a new project on the backend.\n",
        "\n",
        "from IPython.display import display, Markdown\n",
        "import pandas as pd\n",
        "\n",
        "alert_email = 'michael@achmann.me'  # @param {type: \"string\"}\n",
        "project_name = 'Forschungsseminar23 Test'  # @param {type: \"string\"}\n",
        "\n",
        "# Create Project\n",
        "import uuid\n",
        "\n",
        "# Generate a UUID for the document\n",
        "project_id = str(uuid.uuid4())\n",
        "api_key = str(uuid.uuid4())\n",
        "\n",
        "# Your data\n",
        "data = {\n",
        "    \"api_key\": api_key,\n",
        "    \"email\": alert_email,\n",
        "    \"name\": project_name\n",
        "}\n",
        "\n",
        "# Add a new document with a UUID as the document name (ID)\n",
        "doc_ref = db.collection('projects').document(project_id)\n",
        "doc_ref.set(data)\n",
        "\n",
        "display(Markdown(\"### Project Created:\"))\n",
        "display(Markdown(f\"**Project Name:** {project_name}\"))\n",
        "display(Markdown(f\"**Alert Email:** {alert_email}\"))\n",
        "display(Markdown(f\"**Project ID:** {project_id}\"))\n",
        "display(Markdown(f\"**API-Key:** {api_key}\"))"
      ],
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        "outputId": "b7c520af-4dc7-4534-fe0d-fdb162c13ea6",
        "cellView": "form"
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      "execution_count": 10,
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "### Project Created:"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
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            "text/markdown": "**Project ID:** 959466fe-4088-4099-a6b2-3cbe058889d3"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
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            "text/markdown": "**API-Key:** 554fbce8-fb15-44f1-bb4d-54cdc57554f2"
          },
          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Project Export\n",
        "# @markdown Please fill in project ID and export path to download all JSON files and store them locally.\n",
        "\n",
        "from tqdm.auto import tqdm\n",
        "import os\n",
        "import json\n",
        "\n",
        "PROJECT_ID = '959466fe-4088-4099-a6b2-3cbe058889d3'  # @param {type: \"string\"}\n",
        "export_path = '/content/export'  # @param {type: \"string\"}\n",
        "\n",
        "\n",
        "def fetch_stories(project_id):\n",
        "    stories_ref = db.collection('projects').document(project_id).collection('stories')\n",
        "    docs = stories_ref.stream()\n",
        "\n",
        "    stories = []\n",
        "    for doc in docs:\n",
        "        stories.append(doc.to_dict())\n",
        "\n",
        "    return stories\n",
        "\n",
        "db = fetch_stories(PROJECT_ID)\n",
        "\n",
        "if not os.path.exists('export'):\n",
        "    os.makedirs('export')\n",
        "\n",
        "# Iterate over each element in the database\n",
        "for element in tqdm(db, desc='Exporting elements'):\n",
        "    # Serialize the element to JSON\n",
        "    element_json = json.dumps(element, indent=4)\n",
        "\n",
        "    # Write to a file named {id}.json\n",
        "    with open(os.path.join('export', f\"{element['id']}.json\"), 'w') as f:\n",
        "        f.write(element_json)"
      ],
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      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Exporting elements:   0%|          | 0/22 [00:00<?, ?it/s]"
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    {
      "cell_type": "code",
      "source": [
        "# @title Convert to DataFrame\n",
        "# @markdown After running the above cell, you may conver the data to a pandas DataFrame.\n",
        "\n",
        "import pandas as pd\n",
        "from datetime import datetime, timedelta\n",
        "\n",
        "\n",
        "df_export_path = '/content/2022-11-09-Stories-Exported.csv'  # @param {type: \"string\"}\n",
        "\n",
        "def process_instagram_story(data):\n",
        "\n",
        "    # Extract relevant information\n",
        "    story_info = {\n",
        "        'ID': data.get(\"id\"),\n",
        "        'Time of Posting': datetime.utcfromtimestamp(data['taken_at']).strftime('%Y-%m-%d %H:%M:%S'),\n",
        "        'Type of Content': 'Video' if 'video_duration' in data else 'Image',\n",
        "        'video_url': None,\n",
        "        'image_url': None,\n",
        "        'Username': data['user']['username'],\n",
        "        'Video Length (s)': data.get('video_duration', None),\n",
        "        'Expiration': (datetime.utcfromtimestamp(data['taken_at']) + timedelta(hours=24)).strftime('%Y-%m-%d %H:%M:%S'),\n",
        "        'Caption': data.get('caption', None),\n",
        "        'Is Verified': data['user']['is_verified'],\n",
        "        'Stickers': data.get('story_bloks_stickers', []),\n",
        "        'Accessibility Caption': data.get('accessibility_caption', ''),\n",
        "        'Attribution URL': data.get('attribution_content_url', '')\n",
        "    }\n",
        "\n",
        "    return story_info\n",
        "\n",
        "rows = []\n",
        "for element in db:\n",
        "  rows.append(process_instagram_story(element))\n",
        "\n",
        "df = pd.DataFrame(rows)\n",
        "df.to_csv(df_export_path)\n",
        "print(f\"Successfully exported {len(df)} rows as CSV.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "id": "8eQAv1xHgzqI",
        "outputId": "057f4830-e99e-44c5-f218-10d4fec18b8b"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Successfully exported 22 rows as CSV.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "Lg1dWwn1kCrh",
        "outputId": "8ccc4395-6dd8-4ae1-e723-7c45fc147171"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               ID      Time of Posting Type of Content  \\\n",
              "0  3231585718932790545_1483455177  2023-11-08 14:50:59           Image   \n",
              "1  3231585778860997221_1483455177  2023-11-08 14:51:06           Image   \n",
              "2  3231750838597692854_1349651722  2023-11-08 20:19:00           Video   \n",
              "3  3231750989408058657_1349651722  2023-11-08 20:19:18           Video   \n",
              "4  3231751135118088390_1349651722  2023-11-08 20:19:35           Video   \n",
              "\n",
              "                                           video_url  \\\n",
              "0                                               <NA>   \n",
              "1                                               <NA>   \n",
              "2  https://storage.googleapis.com/zeeschuimer-fb-...   \n",
              "3  https://storage.googleapis.com/zeeschuimer-fb-...   \n",
              "4  https://storage.googleapis.com/zeeschuimer-fb-...   \n",
              "\n",
              "                                           image_url    Username  \\\n",
              "0  https://storage.googleapis.com/zeeschuimer-fb-...    rmf24.pl   \n",
              "1  https://storage.googleapis.com/zeeschuimer-fb-...    rmf24.pl   \n",
              "2                                               <NA>  tagesschau   \n",
              "3                                               <NA>  tagesschau   \n",
              "4                                               <NA>  tagesschau   \n",
              "\n",
              "   Video Length (s)           Expiration Caption  Is Verified Stickers  \\\n",
              "0               NaN  2023-11-09 14:50:59    None        False       []   \n",
              "1               NaN  2023-11-09 14:51:06    None        False       []   \n",
              "2            13.300  2023-11-09 20:19:00    None         True       []   \n",
              "3            15.267  2023-11-09 20:19:18    None         True       []   \n",
              "4            17.000  2023-11-09 20:19:35    None         True       []   \n",
              "\n",
              "                               Accessibility Caption Attribution URL  \n",
              "0  Photo by Fakty RMF FM | Rozmowy | Podcasty on ...                  \n",
              "1  Photo by Fakty RMF FM | Rozmowy | Podcasty on ...                  \n",
              "2                                                                     \n",
              "3                                                                     \n",
              "4                                                                     "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3348bb22-61ce-44bf-a90a-e5fabf1016fd\" 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>ID</th>\n",
              "      <th>Time of Posting</th>\n",
              "      <th>Type of Content</th>\n",
              "      <th>video_url</th>\n",
              "      <th>image_url</th>\n",
              "      <th>Username</th>\n",
              "      <th>Video Length (s)</th>\n",
              "      <th>Expiration</th>\n",
              "      <th>Caption</th>\n",
              "      <th>Is Verified</th>\n",
              "      <th>Stickers</th>\n",
              "      <th>Accessibility Caption</th>\n",
              "      <th>Attribution URL</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3231585718932790545_1483455177</td>\n",
              "      <td>2023-11-08 14:50:59</td>\n",
              "      <td>Image</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>https://storage.googleapis.com/zeeschuimer-fb-...</td>\n",
              "      <td>rmf24.pl</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2023-11-09 14:50:59</td>\n",
              "      <td>None</td>\n",
              "      <td>False</td>\n",
              "      <td>[]</td>\n",
              "      <td>Photo by Fakty RMF FM | Rozmowy | Podcasty on ...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3231585778860997221_1483455177</td>\n",
              "      <td>2023-11-08 14:51:06</td>\n",
              "      <td>Image</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>https://storage.googleapis.com/zeeschuimer-fb-...</td>\n",
              "      <td>rmf24.pl</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2023-11-09 14:51:06</td>\n",
              "      <td>None</td>\n",
              "      <td>False</td>\n",
              "      <td>[]</td>\n",
              "      <td>Photo by Fakty RMF FM | Rozmowy | Podcasty on ...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3231750838597692854_1349651722</td>\n",
              "      <td>2023-11-08 20:19:00</td>\n",
              "      <td>Video</td>\n",
              "      <td>https://storage.googleapis.com/zeeschuimer-fb-...</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>tagesschau</td>\n",
              "      <td>13.300</td>\n",
              "      <td>2023-11-09 20:19:00</td>\n",
              "      <td>None</td>\n",
              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3231750989408058657_1349651722</td>\n",
              "      <td>2023-11-08 20:19:18</td>\n",
              "      <td>Video</td>\n",
              "      <td>https://storage.googleapis.com/zeeschuimer-fb-...</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>tagesschau</td>\n",
              "      <td>15.267</td>\n",
              "      <td>2023-11-09 20:19:18</td>\n",
              "      <td>None</td>\n",
              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3231751135118088390_1349651722</td>\n",
              "      <td>2023-11-08 20:19:35</td>\n",
              "      <td>Video</td>\n",
              "      <td>https://storage.googleapis.com/zeeschuimer-fb-...</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>tagesschau</td>\n",
              "      <td>17.000</td>\n",
              "      <td>2023-11-09 20:19:35</td>\n",
              "      <td>None</td>\n",
              "      <td>True</td>\n",
              "      <td>[]</td>\n",
              "      <td></td>\n",
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              "  </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-3348bb22-61ce-44bf-a90a-e5fabf1016fd')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </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",
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              "      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-3348bb22-61ce-44bf-a90a-e5fabf1016fd 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-3348bb22-61ce-44bf-a90a-e5fabf1016fd');\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-92ff8e8c-3998-45f8-a0cc-02327a4be17d\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-92ff8e8c-3998-45f8-a0cc-02327a4be17d')\"\n",
              "            title=\"Suggest charts\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </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",
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              "    }\n",
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              "    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-92ff8e8c-3998-45f8-a0cc-02327a4be17d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Download Images and Videos\n",
        "# @markdown Once the data has been converted to a DataFrame, you may download the images and videos.\n",
        "\n",
        "storage_bucket = \"XXX.appspot.com\"  # @param {type: \"string\"}\n",
        "media_export_path =  '/content/media/'  # @param {type: \"string\"}\n",
        "\n",
        "from firebase_admin import storage\n",
        "import os\n",
        "import requests\n",
        "\n",
        "bucket = storage.bucket(storage_bucket)\n",
        "\n",
        "def generate_signed_url(username, content_id, file_type):\n",
        "    if file_type not in ['images', 'videos']:\n",
        "        raise ValueError(\"Invalid file type specified\")\n",
        "\n",
        "    ext = 'jpeg' if file_type == 'images' else 'mp4'\n",
        "    blob_path = f\"projects/{PROJECT_ID}/stories/{file_type}/{username}/{content_id}.{ext}\"\n",
        "    blob = bucket.blob(blob_path)\n",
        "    # Set the expiration of the link. Here, it's set to 24 hours.\n",
        "    return blob.generate_signed_url(expiration=timedelta(hours=24), method='GET')\n",
        "\n",
        "# Create a function to be applied across DataFrame rows\n",
        "def apply_generate_signed_url(row):\n",
        "    image_url = generate_signed_url(row['Username'], row['ID'], 'images')\n",
        "    video_url = generate_signed_url(row['Username'], row['ID'], 'videos') if row['Type of Content'] == 'Video' else pd.NA\n",
        "    return pd.Series({'image_url': image_url, 'video_url': video_url})\n",
        "\n",
        "# Apply the function along the axis=1 (row-wise)\n",
        "df[['image_url', 'video_url']] = df.apply(apply_generate_signed_url, axis=1)\n",
        "\n",
        "# Now, creating the lists for images and videos can be done more efficiently\n",
        "data_images = df.loc[df['image_url'].notna(), ['ID', 'image_url', 'Username', 'Time of Posting']] \\\n",
        "               .rename(columns={'image_url': 'url', 'Time of Posting': 'datetime'}) \\\n",
        "               .to_dict('records')\n",
        "\n",
        "data_videos = df.loc[df['video_url'].notna(), ['ID', 'video_url', 'Username', 'Time of Posting']] \\\n",
        "               .rename(columns={'video_url': 'url', 'Time of Posting': 'datetime'}) \\\n",
        "               .to_dict('records')\n",
        "\n",
        "\n",
        "def create_directories(base_path, entries, subdir):\n",
        "    usernames = set(entry['Username'] for entry in entries)\n",
        "    for username in usernames:\n",
        "        os.makedirs(os.path.join(base_path, subdir, username), exist_ok=True)\n",
        "\n",
        "def download_file(entry, media_type, media_export_path, session):\n",
        "    directory = os.path.join(media_export_path, media_type, entry['Username'])\n",
        "    ext = 'jpg' if media_type == 'images' else 'mp4'\n",
        "    filename = os.path.join(directory, f\"{entry['ID']}.{ext}\")\n",
        "\n",
        "    with session.get(entry['url'], stream=True) as response:\n",
        "        if response.status_code == 200:\n",
        "            with open(filename, 'wb') as file:\n",
        "                for chunk in response.iter_content(8192):\n",
        "                    file.write(chunk)\n",
        "        else:\n",
        "            print(f\"Failed to download {entry['url']}. Status code: {response.status_code}\")\n",
        "\n",
        "session = requests.Session()\n",
        "# Pre-create directories\n",
        "create_directories(media_export_path, data_images, 'images')\n",
        "create_directories(media_export_path, data_videos, 'videos')\n",
        "\n",
        "# Download images\n",
        "for entry in tqdm(data_images, desc=\"Downloading Images\", unit=\"file\"):\n",
        "    download_file(entry, 'images', media_export_path, session)\n",
        "\n",
        "# Download videos\n",
        "for entry in tqdm(data_videos, desc=\"Downloading Videos\", unit=\"file\"):\n",
        "    download_file(entry, 'videos', media_export_path, session)\n",
        "\n",
        "print(\"Download complete!\")\n"
      ],
      "metadata": {
        "id": "OCJDVKW8mv81",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98,
          "referenced_widgets": [
            "f8502a9e0bf749aebd6bcacda092b805",
            "869711b71fdd4f2a878340e5b1c85ff5",
            "184363b3492e4ace894031ae0685be7b",
            "0c6aac41577243a2b23bc15fe7e1e5cf",
            "c9cfa7c858774a37befb6ab4e276f4ee",
            "ab5d3c1ee82f4d358a1b526bc6a9a0ee",
            "dc00f6dfaac941a3b87eeb10fe2f508e",
            "b6fa24189ea84be1b50f3c2f76efe7db",
            "ea11138c71074eff9e6ef81548b0f363",
            "cbb4ec36e918414a8fc44d21ed189ba4",
            "e9cc889c01954ab0aaf6fbe0060fcb54",
            "e9d19af8d51740a1b73403c5db49265e",
            "8acd1b4b6cf14abbab3de578217a6c2a",
            "c59dd8e1d7194e7c92871739b2c8bf29",
            "34cf2cc0fb3f460baa50eb22000a53e3",
            "dc31ad5b72a74999965be8592851b92e",
            "d09f05d6d79b4283ad4cb3c067619275",
            "4cdceda16b1147c7bfabe2e42337079a",
            "5072419cabcd42cca4136fd368c46830",
            "e31bbbc4fb564eb4a2eb7aff7b3d85db",
            "7cc2c5b606304d98acae77f5006d194f",
            "6c7906ded84243c1a17af53fc840b917"
          ]
        },
        "cellView": "form",
        "outputId": "11209e58-556f-4abd-8fe2-93f751ba4729"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading Images:   0%|          | 0/22 [00:00<?, ?file/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f8502a9e0bf749aebd6bcacda092b805"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading Videos:   0%|          | 0/11 [00:00<?, ?file/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e9d19af8d51740a1b73403c5db49265e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Download complete!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Prepare Downloadable ZIP\n",
        "Run the following to ZIP all files. *Optionally* copy them to Google Drive."
      ],
      "metadata": {
        "id": "OyhZKJu_k-uh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!zip -r 2023-11-09-Story-Media-Export.zip media/*"
      ],
      "metadata": {
        "id": "bB-MLrifeLUQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!cp 2023-11-09-Story-Media-Export.zip /content/drive/MyDrive/"
      ],
      "metadata": {
        "id": "XBZ2ZoFpfEnU"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}