Web_Scraping_from_TrustPilot v2.ipynb

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        "<a href=\"https://colab.research.google.com/github/analyticswithadam/Python/blob/main/Web_Scraping_from_TrustPilot%20v2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "120 138 120 120 120\n"
          ]
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      ],
      "source": [
        "from time import sleep\n",
        "import requests\n",
        "from google.colab import files\n",
        "import pandas as pd\n",
        "from bs4 import BeautifulSoup\n",
        "\n",
        "def soup2list(src, list_, attr=None):\n",
        "    if attr:\n",
        "        for val in src:\n",
        "            list_.append(val[attr])\n",
        "    else:\n",
        "        for val in src:\n",
        "            list_.append(val.get_text())\n",
        "\n",
        "users = []\n",
        "#userReviewNum = []\n",
        "ratings = []\n",
        "locations = []\n",
        "dates = []\n",
        "reviews = []\n",
        "\n",
        "from_page = 1\n",
        "to_page = 6\n",
        "company = 'www.pearsonvue.co.uk'\n",
        "\n",
        "for i in range(from_page, to_page+1):\n",
        "\n",
        "   result = requests.get(fr\"https://www.trustpilot.com/review/{company}?page={i}\")\n",
        "   soup = BeautifulSoup(result.content)\n",
        "\n",
        "   # Trust Pilot was setup in a way that's not friendly to scraping, so this hacky method will do.\n",
        "   soup2list(soup.find_all('span', {'class','typography_heading-xxs__QKBS8 typography_appearance-default__AAY17'}), users)\n",
        "   soup2list(soup.find_all('div', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l styles_detailsIcon__Fo_ua'}), locations)\n",
        "   #soup2list(soup.find_all('span', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l'}), userReviewNum)\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), dates)\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), ratings, attr='data-service-review-rating')\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewContent__0Q2Tg'}), reviews)\n",
        "\n",
        "   # To avoid throttling\n",
        "   sleep(1)\n",
        "\n",
        "\n",
        "\n",
        "review_data = pd.DataFrame(\n",
        "{\n",
        "   'Username':users,\n",
        "   #'Total reviews':userReviewNum,\n",
        "   'location':locations,\n",
        "   'date':dates,\n",
        "   'content':reviews,\n",
        "   'Rating': ratings\n",
        "})\n"
      ]
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        "review_data"
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        "outputId": "7d30a9fc-8a24-4db6-b421-75ed92010547"
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      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    Username location          date  \\\n",
              "0               Alex Schwarz       DE    4 days ago   \n",
              "1    Constantine Constantine       GB    4 days ago   \n",
              "2                      Amber       CA    6 days ago   \n",
              "3                     A. Aza       NL    4 days ago   \n",
              "4                     Taylor       US  Apr 29, 2024   \n",
              "..                       ...      ...           ...   \n",
              "115           Oscar Madrigal       US   Sep 8, 2023   \n",
              "116              Pete Dupree       GB  Sep 30, 2023   \n",
              "117          Sanjeev Chauhan       IN  Dec 30, 2023   \n",
              "118                     Liam       GB   Feb 5, 2024   \n",
              "119                Hakan Car       GB  Oct 25, 2023   \n",
              "\n",
              "                                               content Rating  \n",
              "0    suspicion of manipulation of answersWhen takin...      1  \n",
              "1    Absolutely Horrendous Experience - A Nightmare...      1  \n",
              "2    Complete s***show!!…I am surprised tech giants...      1  \n",
              "3    Everything was tested goodEverything was teste...      1  \n",
              "4    Online Proctoring - STAY AWAYOnline proctoring...      1  \n",
              "..                                                 ...    ...  \n",
              "115  Karan from Pearson Vue, a robotic proctorI was...      1  \n",
              "116  Don't use themWow, I queued for 90 minutes for...      1  \n",
              "117  Horrible experience with Pearson Vue and their...      1  \n",
              "118  Pearson awful customer serviceI booked Pearson...      1  \n",
              "119  70 alexandra road, manchesterI had my aws saa ...      1  \n",
              "\n",
              "[120 rows x 5 columns]"
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              "      <td>Alex Schwarz</td>\n",
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              "      <td>suspicion of manipulation of answersWhen takin...</td>\n",
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              "      <td>Constantine Constantine</td>\n",
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              "      <td>4 days ago</td>\n",
              "      <td>Absolutely Horrendous Experience - A Nightmare...</td>\n",
              "      <td>1</td>\n",
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              "      <th>2</th>\n",
              "      <td>Amber</td>\n",
              "      <td>CA</td>\n",
              "      <td>6 days ago</td>\n",
              "      <td>Complete s***show!!…I am surprised tech giants...</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A. Aza</td>\n",
              "      <td>NL</td>\n",
              "      <td>4 days ago</td>\n",
              "      <td>Everything was tested goodEverything was teste...</td>\n",
              "      <td>1</td>\n",
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              "      <td>Apr 29, 2024</td>\n",
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              "      <td>US</td>\n",
              "      <td>Sep 8, 2023</td>\n",
              "      <td>Karan from Pearson Vue, a robotic proctorI was...</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>Pete Dupree</td>\n",
              "      <td>GB</td>\n",
              "      <td>Sep 30, 2023</td>\n",
              "      <td>Don't use themWow, I queued for 90 minutes for...</td>\n",
              "      <td>1</td>\n",
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              "      <th>117</th>\n",
              "      <td>Sanjeev Chauhan</td>\n",
              "      <td>IN</td>\n",
              "      <td>Dec 30, 2023</td>\n",
              "      <td>Horrible experience with Pearson Vue and their...</td>\n",
              "      <td>1</td>\n",
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              "      <th>118</th>\n",
              "      <td>Liam</td>\n",
              "      <td>GB</td>\n",
              "      <td>Feb 5, 2024</td>\n",
              "      <td>Pearson awful customer serviceI booked Pearson...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>Hakan Car</td>\n",
              "      <td>GB</td>\n",
              "      <td>Oct 25, 2023</td>\n",
              "      <td>70 alexandra road, manchesterI had my aws saa ...</td>\n",
              "      <td>1</td>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "review_data",
              "summary": "{\n  \"name\": \"review_data\",\n  \"rows\": 120,\n  \"fields\": [\n    {\n      \"column\": \"Username\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 120,\n        \"samples\": [\n          \"Guido Ricciardi\",\n          \"si ferg\",\n          \"Taylor\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"location\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"DE\",\n          \"NZ\",\n          \"PL\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 94,\n        \"samples\": [\n          \"Mar 21, 2024\",\n          \"Mar 18, 2024\",\n          \"Mar 5, 2024\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 120,\n        \"samples\": [\n          \"Just a scam company!They own a scam company called Mindhub, where I bought a voucher to do an exam. I never received any voucher. I contacted the company per email and got no reply. There is no phone number to contact customer service. It is really frutrasting when you get scammed by such big companies, which are not able to do the very basics. I am also disappointed from Microsoft for partnering with these scammers!Date of experience: February 15, 2024\",\n          \"The worst service I think I have ever\\u2026The worst service I think I have ever experienced. Initially was fine with a headset, then couldn't have noise cancelling. Changed headset to cable and then they didn't like this. Suggested I use a different device for the test and then they said I was out of time! No email / correspondence about rescheduling etc. This was the same experience last time I used them as well. Absolutely shocking!Date of experience: February 16, 2024\",\n          \"Online Proctoring - STAY AWAYOnline proctoring failed at was stuck at the \\\"we're checking for open applications\\\" screen. Never even got to take my IAPP AIGP exam. Go in-person to avoid this type of mess. What a train wreck. Calling customer support was worthless other than to get a ticket started for a refund and to re-take in person. They just tell you to restart your computer.Date of experience: April 29, 2024\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"1\",\n          \"5\",\n          \"3\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
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          "metadata": {},
          "execution_count": 8
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    {
      "cell_type": "code",
      "source": [
        "# Convert the DataFrame to a CSV file and download it\n",
        "review_data.to_csv('reviews.csv', index=False)\n",
        "files.download('reviews.csv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "XfeWnNaSVd02",
        "outputId": "680e8a17-e0fd-4873-deb5-355d38772162"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_9c6b9184-994b-440a-9e86-267dc193321c\", \"reviews.csv\", 32399)"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}