resume_parser (1).ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zCbr6_eQwip_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a16e953b-5c5b-4916-eded-27d84bf0c6a0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: resume-parser in /usr/local/lib/python3.8/dist-packages (0.8.4)\n",
            "Requirement already satisfied: numpy>=1.19.1 in /usr/local/lib/python3.8/dist-packages (from resume-parser) (1.21.6)\n",
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            "Requirement already satisfied: pandas>=1.1.0 in /usr/local/lib/python3.8/dist-packages (from resume-parser) (1.3.5)\n",
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            "Requirement already satisfied: click in /usr/local/lib/python3.8/dist-packages (from nltk>=3.5->resume-parser) (7.1.2)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.3.2->resume-parser) (2022.9.24)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.3.2->resume-parser) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.3.2->resume-parser) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.3.2->resume-parser) (1.24.3)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "!pip install resume-parser"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4dSUhbkzyvcK",
        "outputId": "b8fd802a-65fd-4edf-f3d8-f26c9d55b892"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "Requirement already satisfied: click in /usr/local/lib/python3.8/dist-packages (from nltk) (7.1.2)\n",
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            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting spacy==2.3.5\n",
            "  Using cached spacy-2.3.5-cp38-cp38-manylinux2014_x86_64.whl (10.5 MB)\n",
            "Requirement already satisfied: wasabi<1.1.0,>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from spacy==2.3.5) (0.10.1)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy==2.3.5) (2022.9.24)\n",
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            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Installing collected packages: spacy\n",
            "  Attempting uninstall: spacy\n",
            "\u001b[33m    WARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "    Found existing installation: spacy 2.3.8\n",
            "    Uninstalling spacy-2.3.8:\n",
            "      Successfully uninstalled spacy-2.3.8\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Successfully installed spacy-2.3.5\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz\n",
            "  Using cached https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz (12.0 MB)\n",
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            "Requirement already satisfied: catalogue<1.1.0,>=0.0.7 in /usr/local/lib/python3.8/dist-packages (from spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (1.0.2)\n",
            "Requirement already satisfied: wasabi<1.1.0,>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (0.10.1)\n",
            "Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.8/dist-packages (from spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (1.21.6)\n",
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            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.8/dist-packages (from spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (1.0.9)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (2.0.7)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (2022.9.24)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests<3.0.0,>=2.13.0->spacy<2.4.0,>=2.3.0->en-core-web-sm==2.3.1) (1.24.3)\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[33mWARNING: Ignoring invalid distribution -atalogue (/usr/local/lib/python3.8/dist-packages)\u001b[0m\n",
            "\u001b[31mERROR: Invalid requirement: 'pyresparser!'\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "!pip install nltk\n",
        "\n",
        "!pip install spacy==2.3.5\n",
        "\n",
        "!pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz\n",
        "\n",
        "!pip install pyresparser!"
      ]
    },
    {
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        "colab": {
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        "id": "B8rhBFRc0PFW",
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              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
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              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving Elena Turing Resume.docx (1).pdf to Elena Turing Resume.docx (1) (1).pdf\n"
          ]
        }
      ],
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bb4MevX2wpJQ",
        "outputId": "a5e9546d-79f8-4ddd-e80d-3edc53577f21"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'email': 'eturing_sample@ucsd.edu', 'phone': '(555) 555-5555', 'name': 'Elena Turing', 'total_exp': 5, 'university': ['university of california, san diego'], 'designition': ['junior data analyst', 'data analyst', 'change management', 'science intern', 'market research intern', 'research intern'], 'degree': [], 'skills': ['▪  (plug in your own): Python', ' Java', ' C++', ' SQL', ' MATLAB', ' Numpy', ' Pandas', ' Matplotlib', ' Keras', ' Tensorflow', ' Scikit-learn', '', 'NLP', ' Computer Vision', ' Statistics', ' Multivariable calculus', ' revenue modeling & forecasting; retail partnerships', ' sales', ' &', 'distro; crowdfunding; copywriting; content marketing; brand marketing; DTC; Shopify; supply chain management;', 'Keynote / PPT presentation'], 'Companies worked at': []}\n"
          ]
        }
      ],
      "source": [
        "from resume_parser import resumeparse\n",
        "\n",
        "#replace with file path of resume\n",
        "data = resumeparse.read_file('/content/Elena Turing Resume.docx.pdf')\n",
        "\n",
        "print(data)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4qLPerCJ0z0n",
        "outputId": "3fa45017-2339-4373-85f0-89aacd5856c5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'Companies worked at': [],\n",
            " 'degree': [],\n",
            " 'designition': ['junior data analyst',\n",
            "                 'data analyst',\n",
            "                 'change management',\n",
            "                 'science intern',\n",
            "                 'market research intern',\n",
            "                 'research intern'],\n",
            " 'email': 'eturing_sample@ucsd.edu',\n",
            " 'name': 'Elena Turing',\n",
            " 'phone': '(555) 555-5555',\n",
            " 'skills': ['▪  (plug in your own): Python',\n",
            "            ' Java',\n",
            "            ' C++',\n",
            "            ' SQL',\n",
            "            ' MATLAB',\n",
            "            ' Numpy',\n",
            "            ' Pandas',\n",
            "            ' Matplotlib',\n",
            "            ' Keras',\n",
            "            ' Tensorflow',\n",
            "            ' Scikit-learn',\n",
            "            '',\n",
            "            'NLP',\n",
            "            ' Computer Vision',\n",
            "            ' Statistics',\n",
            "            ' Multivariable calculus',\n",
            "            ' revenue modeling & forecasting; retail partnerships',\n",
            "            ' sales',\n",
            "            ' &',\n",
            "            'distro; crowdfunding; copywriting; content marketing; brand '\n",
            "            'marketing; DTC; Shopify; supply chain management;',\n",
            "            'Keynote / PPT presentation'],\n",
            " 'total_exp': 5,\n",
            " 'university': ['university of california, san diego']}\n"
          ]
        }
      ],
      "source": [
        "import pprint\n",
        "\n",
        "# Prints the nicely formatted dictionary\n",
        "pprint.pprint(data)\n",
        "\n",
        "# Sets 'pretty_dict_str' to the formatted string value\n",
        "#pretty_dict_str = pprint.pformat(dictionary)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "F3aW79iKlmP9"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}