NEVI Plan Keyword Search Tool

A Python-based tool to help analysts and researchers search through state NEVI plans for structured answers to key questions. The tool uses logic-based keyword matching to find pages that discuss specific topics in uploaded PDF documents.

Originally developed for a WPI undergraduate research initiative, sponsored by Atlas Public Policy.

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📄 What It Does

• Load any state NEVI plan (PDF)
• Choose a category (e.g., Equity, Buildout, Maintenance)
• Choose a question
• Search for structured keyword matches
• View matching pages in a built-in reader with highlights
• Edit the term sets with an easy-to-use term editor

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🧱 Project Structure

.
├── main.py                   # Entry point
├── data/
│   └── terms.json             # Questions and keyword groups
├── assets/
│   └── wpi_logo.ico           # App icon
├── gui/
│   ├── main_window.py         # Main application UI
│   ├── reader_window.py       # Highlighted PDF reader
│   └── term_editor_window.py  # JSON term editor
├── logic/
│   ├── search_engine.py       # Whole-word search engine
│   ├── term_loader.py         # Resource path handling
│   └── settings.py            # (reserved for future)
└── README.md

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⚙️ Installation (Run Locally)

Requirements

• Python 3.7+
• PyQt5
• pypdf

Install dependencies:

pip install PyQt5 pypdf

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▶️ Running the App

From the project root:

python main.py

1. Load a PDF
2. Select a category and question
3. Click "Run Search"
4. Review matching pages with highlighted keywords

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🧠 JSON Term Structure

Each question has grouped terms. A page matches if at least one word from each group appears on it.

Example:

{
  "Equity": {
    "How does the state identify disadvantaged communities?": [
      ["underserved", "disadvantaged", "DAC", "marginalized"],
      ["define", "identify", "locate"],
      ["engagement", "collaboration", "mapping tool"]
    ]
  }
}

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🧑‍💻 Background

This project was originally developed as part of a WPI undergraduate research initiative in response to the National Electric Vehicle Infrastructure (NEVI) program.

The research and tool development were sponsored by Atlas Public Policy to assist in accelerating EV adoption and infrastructure analysis.

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✍️ Authors

Developed by Nicholas Borrello
Supported by WPI faculty and advisors
Sponsored by Atlas Public Policy