Focuses on what an object does rather than what it is . Decoupling: Allows for easier mocking and testing. 2. Dependency Injection
In the sprawling landscape of data processing, the Portable Document Format (PDF) remains an immovable cornerstone. Despite the rise of markdown, cloud-native documents, and structured data formats, the PDF endures as the standard for contracts, reports, and official communication. For the Python developer, this makes PDF manipulation a necessary—and often frustrating—rite of passage. But with the maturity of modern libraries, working with PDFs is no longer a chore. At the heart of this evolution is (formerly PyPDF2), a pure-Python library that has grown from a basic toolkit into a powerful, secure, and performant engine. Focuses on what an object does rather than what it is
When contributing to pypdf , the development team insists on an . For a PDF library, this means two things: Dependency Injection In the sprawling landscape of data
Using Python's advanced tools for powerful patterns of code reuse . Book Availability & Editions But with the maturity of modern libraries, working
Modern Python applications require architectures that separate business logic from external frameworks, databases, and user interfaces. Implementing structural design patterns ensures your codebase remains testable and maintainable as it grows. The Dependency Injection Pattern
from pathlib import Path from pypdf import PdfReader
: The AnnotationBuilder has since been deprecated in favor of the more declarative pypdf.annotations module, which uses separate classes for each annotation type. This shift moves away from a single builder to a more specialized, class-based strategy, reducing complexity and making the code more explicit.