The Publication Extractor is a Python script designed to extract information from PDF documents related to publications, particularly Abstract Book from 5th World..... It utilizes the pdfplumber library for PDF text extraction and data manipulation, and the ExcelWriter module for exporting the extracted data to an Excel file.

• Introduction
• Features
• Usage
• Dependencies
• Installation
• Configuration
• License

• Extracts publication information from specified PDF files with same structure.
• Processes pages in the PDF document to extract relevant data.
• Handles different font sizes and styles to correctly identify and categorize information.
• Creates an Excel file with the extracted data for easy storage and analysis.

1. Place the PDF file containing the conference abstracts in the same directory as the script.
2. Modify the file_name variable in the script to match the name of your PDF file.
3. Run the script.
4. The extracted publication information will be stored in an Excel file named result.xlsx in the same directory.

• pdfplumber: A library for extracting text and metadata from PDF files.
• ExcelWriter (Custom module): A module for writing data to Excel files.

To get started with the Beetroot Scraping Test project, follow these steps to set up the required environment and run the main.py file on different systems. This guide assumes you have Python and Git already installed on your machine.

Open a terminal/command prompt and navigate to the directory where you want to store the project. Then, run the following command to clone the repository:

git clone https://github.com/NazikM/beetroot_scraping_test.git

It's a good practice to use a virtual environment to isolate project dependencies. Navigate into the project directory and create a virtual environment:

cd beetroot_scraping_test
python -m venv venv

Activate the virtual environment:

• On Windows (Command Prompt):

  venv\Scripts\activate

• On macOS and Linux:

  source venv/bin/activate

While in the project directory and with your virtual environment active, install the required packages using pip:

pip install -r requirements.txt

Now that the environment is set up and the dependencies are installed, you can run the main.py script:

python main.py

No additional configuration is required if using the provided ExcelWriter module. However, if you need to customize the output format or file naming, you may need to modify the save_to_excel() function or the ExcelWriter module.

This script is provided under the MIT License.