How to Extract Specific Text From PDF in Python

IronPDF Features

• With IronPDF, PDF files may be created from a variety of sources, including HTML, HTML5, ASPX, and Razor/MVC View. It offers the ability to convert HTML pages and images into PDF files.
• Creating interactive PDFs, completing and submitting interactive forms, splitting and combining PDF files, extracting text and images, searching text within PDF files, rasterizing PDFs to images, changing font sizes, natural language processing using ChatGPT, and converting PDF pages property are just a few of the activities that the IronPDF toolkit can help with.
• IronPDF offers HTML login form validation with support for user-agents, proxies, cookies, HTTP headers, and form variables.
• IronPDF uses usernames and passwords to provide users access to protected documents.
• With just a few lines of code, IronPDF can print a PDF file from a variety of sources, including a string, stream, or URL.

Environment Configuration

Make sure Python is set up on your computer. To download and install the most recent version of Python compatible with your operating system, go to the official Python website. Create a virtual environment once Python is installed to separate the needs for your project. Create and manage virtual environments with the venv module to give your conversion project a tidy, separate workplace.

New Initiative in PyCharm

For this demonstration, PyCharm is recommended as an IDE for developing Python code.

After starting the PyCharm IDE, select "New Project".

PyCharm

A new window will open when you choose "New Project", allowing you to set the project's location and environment. This might be seen in the image below.

New Project

After choosing the project location and environment path, click the Create button to begin a new project. The program can then be created in a new window that will open as a result. For this lesson, Python 3.9 is being used.

Create Python Project

IronPDF Library Requirement

The Python library IronPDF largely uses .NET 6.0. As a result, the .NET 6.0 runtime must be installed on your computer in order to use IronPDF for Python. It might be necessary to install .NET before this Python module can be used by Linux and Mac users. Visit this download page from Microsoft to get the needed runtime environment.

IronPDF Library Setup

To generate, modify, and open files with the ".pdf" extension, the "ironpdf" package must be installed. Open a terminal window and enter the following command to install the package in PyCharm:

pip install ironpdf

pip install ironpdf

The installation of the ironpdf package is shown in the screenshot below.

Install IronPDF

Page-by-Page Extraction from the PDF

The example code supplied below shows how to obtain data from a PDF file using the page number.

from ironpdf import PdfDocument

# Load the PDF file
pdf = PdfDocument.FromFile('F:\\PDF\\Extract.pdf')
# Extract text from the first page of the PDF document
all_text = pdf.ExtractTextFromPage(0)
# Iterate over each line in the extracted text
for line in all_text.split('\n'):
    # Check if the line contains the keyword "Name"
    if 'Name' in line:
        # Print the line if it contains the keyword
        print(line)

from ironpdf import PdfDocument

# Load the PDF file
pdf = PdfDocument.FromFile('F:\\PDF\\Extract.pdf')
# Extract text from the first page of the PDF document
all_text = pdf.ExtractTextFromPage(0)
# Iterate over each line in the extracted text
for line in all_text.split('\n'):
    # Check if the line contains the keyword "Name"
    if 'Name' in line:
        # Print the line if it contains the keyword
        print(line)

The code snippet shows how to read a PDF file and build a PDF object using the FromFile function. This object can be used to access the PDF's text and images. By passing the page number as a parameter to the ExtractTextFromPage function, the text can be retrieved from a specific page. A string containing all the words on the chosen page will be returned by this method. Then, use the split function in Python to split all the new lines from the extracted text. After that, check whether each line in the extracted text contains the required keywords. If the keyword matches, it will display the specific line in the command prompt. Otherwise, it will ignore that line and move on to the next line. The output for text extraction will appear as shown below.