SL_09_Regular_Expression_for_Coach.ipynb

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    "colab": {
      "name": "SL-09 Regular Expression - for Coach.ipynb",
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      "name": "python3",
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      "name": "python"
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        "<a href=\"https://colab.research.google.com/github/riskydav/Belajar-Python/blob/main/SL_09_Regular_Expression_for_Coach.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "## Regular Expression (Regex)\n",
        "> Library untuk pengenalan dan pengelolaan pola pada teks\n",
        "> \n",
        "\n",
        "Contoh implementasi:\n",
        "- Pola Email\n",
        "- Pola Nomor telepon\n",
        "- Pola url\n",
        "- Pola Nomor plat kendaraan bermotor \n",
        "- Menghilangkan karakter khusus pada teks\n",
        "- dll."
      ]
    },
    {
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      "source": [
        "## Disclaimer\n",
        "> Pada modul ini akan dipelajari **penggunaan regex untuk mengelola pola tertentu pada teks**. Detail mengenai syntax regex tidak dipelajari secara mendalam. Namun apabila tertarik untuk eksplorasi lebih jauh, dapat menggunakan resourse berikut untuk bahan belajar tambahan\n",
        "\n",
        "- [Python Tutorial: re Module - How to Write and Match Regular Expressions (Regex)](https://www.youtube.com/watch?v=K8L6KVGG-7o)\n",
        "- [Python Regex Cheat Sheet](https://www.geeksforgeeks.org/python-regex-cheat-sheet/)\n",
        "- Online Regex Debugger: [Regex Visualizer (Debuggex)](https://www.debuggex.com)\n",
        "\n",
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G0BL3jxVVM7m"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cckM0ieQI6_p"
      },
      "source": [
        "# Import Library Regex (re)\n",
        "import re\n",
        "\n",
        "# Pola Email\n",
        "email_pattern = re.compile(r'[\\w._%+-]+@[\\w\\.-]+\\.[a-zA-Z]{2,4}')\n",
        "\n",
        "txt = 'Contact kami di admin@thenextyunikorn.id, sales@yunikornbaru.com, atau hrd@yunikornindo.id'"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-vfDDYYyXzjB"
      },
      "source": [
        "### Pola Email"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eHLVDWodMsfQ",
        "outputId": "fd6dfd1b-7bf7-4576-e541-c7f229b44306"
      },
      "source": [
        "# Menghapus Email dalam teks\n",
        "print( re.sub(email_pattern, ' ', txt))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Contact kami di  ,  , atau  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dgmUPJv2Mp_T",
        "outputId": "4d64f67a-7d2d-4352-fd86-88d015f76f05"
      },
      "source": [
        "# Mengambil email dari teks berdasarkan pola regex yang ditentukan\n",
        "emails = re.findall(email_pattern, txt)\n",
        "print( 'Email yang ditemukan: ', emails)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Email yang ditemukan:  ['admin@thenextyunikorn.id', 'sales@yunikornbaru.com', 'hrd@yunikornindo.id']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oW4i5z3qX2jk"
      },
      "source": [
        "### Pola Nomor Telepon"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n6bvuA4QSOCh"
      },
      "source": [
        "# Pola telephone : \\d penanda angka di reguler Expression, \\s spasi, dan \"|\" adalah \"atau\"\n",
        "# \"?\" menyatakan pilihan (optional)\n",
        "phone_pattern = re.compile(r'(\\d{3}[-\\.\\s]??\\d{3}[-\\.\\s]??\\d{4,6}|\\(\\d{3}\\)\\s*\\d{3}[-\\.\\s]??\\d{4,6}|\\d{3,4}[-\\.\\s]??\\d{4,6})')\n",
        "txt = 'Contact kami di 021-7632456 atau 021-443-4162 atau 021 797 4524 atau 0822959020 atau +628199258643'"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FInY3LDaMDxn",
        "outputId": "b1df6770-6322-43f4-9f4b-57b281d3e402"
      },
      "source": [
        "# Sensor *** untuk pola Nomor Telepon\n",
        "print(re.sub(phone_pattern,'***',txt))"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Contact kami di *** atau *** atau *** atau *** atau +***\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eRAXR0apSsqN",
        "outputId": "384b4165-6606-4667-deab-d621b9019767"
      },
      "source": [
        "# Mengambil nomor telepon dari teks berdasarkan pola regex yang telah ditentukan\n",
        "phone_numbers = re.findall(phone_pattern,txt)\n",
        "print('Nomer telephone yang ditemukan: ', str(phone_numbers))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Nomer telephone yang ditemukan:  ['021-7632456', '021-443-4162', '021 797 4524', '0822959020', '628199258643']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ncMVez6hX5U6"
      },
      "source": [
        "Pola URL atau Link"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dvzYKfUtTJBt"
      },
      "source": [
        "# Website URL http(s)\n",
        "url_pattern = re.compile(r'www|http:|https:+[^\\s]+[\\w]')\n",
        "txt = 'Teman teman dapat mengunjungi link berikut untuk sumber belajar: https://www.regular-expressions.info/ atau https://www.towardsdatascience.com atau https://wikipedia.org'\n"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P-qHHhJVY4Ns",
        "outputId": "0032e8c9-96b8-4d85-b883-23ec1415ac6a"
      },
      "source": [
        "# Menghapus url pada teks\n",
        "print(re.sub(url_pattern,' ',txt))"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Teman teman dapat mengunjungi link berikut untuk sumber belajar:  / atau   atau  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NpUs-ZGbYpsQ",
        "outputId": "bddc0ee8-a367-40bf-8eaf-3e40f9169650"
      },
      "source": [
        "# Mengambil url dari teks berdasarkan pola regex yang telah ditentukan\n",
        "urls = re.findall(url_pattern,txt)# get urls\n",
        "print('URL yang ditemukan: ',str(urls))"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "URL yang ditemukan:  ['https://www.regular-expressions.info', 'https://www.towardsdatascience.com', 'https://wikipedia.org']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xHzYEMeZiYPf"
      },
      "source": [
        "### Pola Plat Kendaraan Bermotor"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DdEdAhAZZIPv"
      },
      "source": [
        "plat_pattern = re.compile(r'[A-Z]{1,2}\\s\\d{1,4}\\s[A-Z]{1,3}')\n",
        "text = \"Mr.X punya 2 motor dan 1 mobil. Adapun plat nomornya yaitu B 234 AA, C 3244 YGS, dan D 3 S.\""
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "idDWbJVTjC5u",
        "outputId": "5414f95e-1150-403b-9506-19a959d79de6"
      },
      "source": [
        "# Menghapus plat kendaraan pada teks\n",
        "print(re.sub(plat_pattern, ' ', text))"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mr.X punya 2 motor dan 1 mobil. Adapun plat nomornya yaitu  ,  , dan  .\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QpvW1tBCjkYZ",
        "outputId": "48af3abf-819a-44e4-f416-be94c65f77bd"
      },
      "source": [
        "kumpulan_plat_kendaraan = re.findall(plat_pattern, text)\n",
        "print(kumpulan_plat_kendaraan)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['B 234 AA', 'C 3244 YGS', 'D 3 S']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bmPJi8RXmYrS"
      },
      "source": [
        "### Menghilangkan Karakter Khusus"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wr_Y9lvTjtrj",
        "outputId": "eaffb2c7-b3a5-4141-9390-40c131e2f2df"
      },
      "source": [
        "text = \"Halo @Hyeri, apa kabar? #SapaKawan.\"\n",
        "result = re.sub(r'[@,.?#]', '', text)\n",
        "print(result)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Halo Hyeri apa kabar SapaKawan\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4vo0N0iKp32y"
      },
      "source": [
        "## Activity\n",
        "**TEXT:**\n",
        "> Halo semua, namaku Andy Joe. Kemarin smartphoneku mendapat SMS tagihan Pinjaman Online dari nomor 08004398499. Selain itu emailku juga mendapatkan pesan serupa dari debtcollector@pinjolninuninu.com. Ternyata salah satu temanku menjadikan nomor telepon dan emailku sebagai penanggungjawab pinjaman onlinenya :(. Tak lama sosok pria berbadan bongsor datang ke rumahku dengan menggunakan mogenya. Ia menanyakan keberadaan temanku yang meminjam uang di perusahaan Pinjol tersebut. Aku yang tak tahu keberadaannya pun menjawab apa adanya. Tak lama kemudian pria tersebut pergi dan segera kuambil gambar mogenya dengan  plat PO 3030 AY. Setelah itu aku menghubungi temanku dan meminta penjelasan kepadanya.\n",
        ">\n",
        "---\n",
        "### 1. Buatlah format pesan kepada teman Andy Joe untuk meminta penjelasan terkait dengan situasi yang sedang terjadi. (ganti teks yang cetak miring dan tebal menjadi nomor debtcollector, email debtcollector dan plat nomor)\n",
        ">\n",
        "\n",
        "**Format Pesan:**\n",
        "> \"*Halo xxxxx, Aku tadi habis didatangi debtcollector. Dia mengirimiku pesan lewat nomornya yaitu **nomor_debtcollector** dan email **email_debtcollector**. Dia bilang kamu jadiin nomorku dan emailku sebagai penanggungjawab. Bisa tolong jelasin? Terus aku tadi juga sempet foto motor yg dipake mas debtcollector. Plat nomornya **plat_nomor_debtcollector**.*\"\n",
        "\n",
        "\n",
        "### 2. Buatlah preprocessing sederhana dengan menghilangkan karakter titik, koma dan tanda tanya dari format pesan yang sudah dibuat (Di nomor 1)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IGWvnlpwoP8f"
      },
      "source": [
        "text = \"Halo semua, namaku Andy Joe. Kemarin smartphoneku mendapat SMS tagihan Pinjaman Online dari nomor 08004398499. Selain itu emailku juga mendapatkan pesan serupa dari debtcollector@pinjolninuninu.com. Ternyata salah satu temanku menjadikan nomor telepon dan emailku sebagai penanggungjawab pinjaman onlinenya :(. Tak lama sosok pria berbadan bongsor datang ke rumahku dengan menggunakan mogenya. Ia menanyakan keberadaan temanku yang meminjam uang di perusahaan Pinjol tersebut. Aku yang tak tahu keberadaannya pun menjawab apa adanya. Tak lama kemudian pria tersebut pergi dan segera kuambil gambar mogenya dengan plat PO 3030 AY. Setelah itu aku menghubungi temanku dan meminta penjelasan kepadanya.\""
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zaHCCY6RsvqU",
        "outputId": "b90a5e0c-cd59-4336-d7d8-f67a737cf92b"
      },
      "source": [
        "# Jawaban Nomor 1\n",
        "nomor_debtcollector = re.findall(phone_pattern, text)[0]\n",
        "email_debtcollector = re.findall(email_pattern, text)[0]\n",
        "plat_debtcollector = re.findall(plat_pattern, text)[0]\n",
        "\n",
        "\n",
        "format_pesan = f\"Halo xxxxx, Aku tadi habis didatangi debtcollector. Dia mengirimiku pesan lewat nomornya yaitu {nomor_debtcollector} dan email {email_debtcollector}. Dia bilang kamu jadiin nomorku dan emailku sebagai penanggungjawab. Bisa tolong jelasin? Terus aku tadi juga sempet foto motor yg dipake mas debtcollector. Plat nomornya {plat_debtcollector}.\"\n",
        "print(format_pesan)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Halo xxxxx, Aku tadi habis didatangi debtcollector. Dia mengirimiku pesan lewat nomornya yaitu 08004398499 dan email debtcollector@pinjolninuninu.com. Dia bilang kamu jadiin nomorku dan emailku sebagai penanggungjawab. Bisa tolong jelasin? Terus aku tadi juga sempet foto motor yg dipake mas debtcollector. Plat nomornya PO 3030 AY.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "da6pqZ6s3B7_",
        "outputId": "d149686f-73a0-451b-952b-87337bc4da79"
      },
      "source": [
        "# Jawaban Nomor 2\n",
        "result = re.sub(r'[.,?]', '', format_pesan)\n",
        "print(result)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Halo xxxxx Aku tadi habis didatangi debtcollector Dia mengirimiku pesan lewat nomornya yaitu 08004398499 dan email debtcollector@pinjolninuninucom Dia bilang kamu jadiin nomorku dan emailku sebagai penanggungjawab Bisa tolong jelasin Terus aku tadi juga sempet foto motor yg dipake mas debtcollector Plat nomornya PO 3030 AY\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TsPheuYCojsk"
      },
      "source": [
        ""
      ]
    }
  ]
}