PDFMiner is a Python library for extracting text, images, and other information from PDF documents. It provides tools to parse and analyze PDF files, making it easier to work with PDF content programmatically. PDFMiner is widely used for various tasks, including text extraction, data mining, and information retrieval from PDF files.

Here are some key features of PDFMiner:

1. Text Extraction: PDFMiner allows you to extract text from PDF files, preserving the layout and formatting information.

2. PDF Parsing: The library provides a parser to navigate through the internal structure of PDF documents, which is useful for accessing various elements like images, annotations, and metadata.

3. Layout Analysis: PDFMiner can analyze the layout of the PDF pages, such as determining the coordinates of text and images, enabling you to preserve the visual structure.

4. Unicode Support: It handles Unicode characters, ensuring that text extraction from PDFs in various languages works seamlessly.

5. PDF-to-Text Conversion: With PDFMiner, you can convert PDF documents into plain text or HTML format, making it easier to process the content.

6. Command-line Tools: PDFMiner comes with command-line tools like “pdf2txt.py” and “dumppdf.py” that facilitate text extraction and document analysis from the terminal.

PDFMiner is available as an open-source library and can be installed using pip. To use it, you typically need to import the necessary modules, open the PDF file, and then process the content using the provided API.

Here’s a basic example of how to extract text from a PDF using PDFMiner:

Keep in mind that the quality of text extraction heavily depends on the structure and encoding of the PDF document. Some PDFs may have complex layouts or use non-standard fonts, which can affect the accuracy of the extracted text.

Before using PDFMiner or any other library for PDF processing, ensure you comply with copyright and licensing laws, as extracting content from PDF files may be subject to legal restrictions.