Simple_Resume_Analyzer.ipynb

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    "# Simple Resume Analyzer\n",
    "\n",
    "This notebook helps recruiters and hiring managers to detect the best resumes very quickly based on their custom keywords. This code can accelerate finding a matched employee.\n",
    "\n",
    "This notebook is developed by Melanee on this repository: https://github.com/Melanee-Melanee/Simple_Resume_Analyzer"
   ]
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    "## Usage\n",
    "1- Install PyPDF2: ``` !pip install PyPDF2 ```\n",
    "\n",
    "2- Move all the resumes in a same directory and define your directory path in: ``` directory_path ```\n",
    "\n",
    "3- Replace your custom keywords in: ``` keywords ```\n",
    "\n",
    "4- Run the cell"
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      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: PyPDF2 in /home/melanee/.local/lib/python3.10/site-packages (3.0.1)\n",
      "\u001b[33mWARNING: Error parsing dependencies of send2trash: Expected matching RIGHT_PARENTHESIS for LEFT_PARENTHESIS, after version specifier\n",
      "    sys-platform (==\"darwin\") ; extra == 'objc'\n",
      "                 ~^\u001b[0m\u001b[33m\n",
      "\u001b[0m"
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   "source": [
    "!pip install PyPDF2 "
   ]
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     "text": [
      " PDF: /home/melanee/Resume_2.pdf (Total Keywords: 19)\n",
      "python : 7\n",
      "data : 2\n",
      "science : 3\n",
      "AI : 6\n",
      "machine learning : 1\n",
      " PDF: /home/melanee/Resume_1.pdf (Total Keywords: 14)\n",
      "python : 4\n",
      "data : 1\n",
      "science : 1\n",
      "AI : 6\n",
      "machine learning : 2\n",
      " PDF: /home/melanee/Resume_3.pdf (Total Keywords: 10)\n",
      "python : 0\n",
      "data : 2\n",
      "science : 3\n",
      "AI : 2\n",
      "machine learning : 3\n"
     ]
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   "source": [
    "#count function in the strings for some keywords in multiple PDFs and sort them\n",
    "\n",
    "import os\n",
    "import PyPDF2\n",
    "\n",
    "def count_keywords_in_pdf(pdf_path, keywords):\n",
    "    \n",
    "    keyword_counts = {keyword: 0 for keyword in keywords}\n",
    "\n",
    "    with open(pdf_path, 'rb') as file:\n",
    "        \n",
    "        reader = PyPDF2.PdfReader(file)\n",
    "        for page in reader.pages:\n",
    "            \n",
    "            text = page.extract_text()\n",
    "            if text: # Check if text extraction was successful\n",
    "                \n",
    "                text = text.lower() # Convert to lower case for case-insensitive matching\n",
    "                for keyword in keywords:\n",
    "                    \n",
    "                    keyword_lower = keyword.lower()\n",
    "                    keyword_counts[keyword] += text.count(keyword_lower)\n",
    "\n",
    "    return keyword_counts\n",
    "\n",
    "def count_keywords_in_directory(directory, keywords):\n",
    "    \n",
    "    pdf_keyword_counts = []\n",
    "    \n",
    "    for filename in os.listdir(directory):\n",
    "        \n",
    "        if filename.endswith('.pdf'):\n",
    "                \n",
    "            pdf_path = os.path.join(directory, filename)\n",
    "            counts = count_keywords_in_pdf(pdf_path, keywords)\n",
    "            total_count = sum(counts.values())\n",
    "            pdf_keyword_counts.append((pdf_path, counts, total_count))\n",
    "            \n",
    "    pdf_keyword_counts.sort(key=lambda x: x[2], reverse=True)\n",
    "    \n",
    "    # Print sorted results\n",
    "    for pdf_path, counts, total_count in pdf_keyword_counts:\n",
    "           \n",
    "        print(f\" PDF: {pdf_path} (Total Keywords: {total_count})\")\n",
    "        for keyword, count in counts.items():\n",
    "            print(keyword, \":\", count)\n",
    "\n",
    "\n",
    "# Example usage\n",
    "directory_path = '/home/melanee/' # Change this to your PDF directory\n",
    "\n",
    "keywords = ['python', 'data', 'science', 'AI', 'machine learning'] # Replace with your custom keywords\n",
    "\n",
    "count_keywords_in_directory(directory_path, keywords)"
   ]
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   "source": [
    "## Warning\n",
    "This notebook is under license and any publishing without referring to my repository is prohibited!\n",
    "\n",
    "Developer: [Melanee](https://github.com/Melanee-Melanee/Simple_Resume_Analyzer)"
   ]
  }
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