Before compressing the PDF, first determine whether you can accept image loss.

This paper uses synthetic samples to demonstrate the processing method. The code has been verified using examples in an isolated environment; this does not guarantee effectiveness for all real-world files or products. Before processing important files, please retain the original copies and verify them against the boundaries and acceptance criteria outlined in this document. Which problem does this paper address first? below only checks lossless compression of the content stream: the decoded bytes before and after compression should be identical to the extracted text. It does not guarantee that every PDF will become smaller, nor does it equate lossless stream compression with JPEG’s lossy re-encoding. self-contained synthetic example dependencies are listed in the import section. The code constructs inputs in memory; runtime logs are provided separately and do not constitute a guarantee for all real-world files. from io import BytesIO import pymupdf from pypdf import PdfReader, PdfWriter with pymupdf.open() as source: page = source.new_page() page.insert_text((50, 50), "Compression sample") raw = source.tobytes() writer = PdfWriter(clone_from=BytesIO(raw)) before = writer.pages[0].get_contents().get_data() writer.pages[0].compress_content_streams() out = BytesIO() writer.write(out) out.seek(0) reader = PdfReader(out) assert reader.pages[0].get_contents().get_data() == before assert "Compression sample" in reader.pages[0].extract_text() assert len(reader.pages) == 1 The key point is: no matter how the content stream is compressed, the text vector paths, font embeddings, and the original pixel data of images will remain unchanged. This means you can safely perform this step during the translation preprocessing phase as part of the standardization process, without worrying about compromising the original text’s readability. However, be sure to note that compress_content_streams does not accept compression level parameters and uses the default zlib configuration internally. image replacement is a lossy operation and is irreversible Furthermore, remove_images() is a complete deletion rather than compression. Unless you explicitly know that the target scenario does not require images (such as plain text extraction), it should not be used during the translation preparation stage. Many users mistakenly believe that “compressing images” is equivalent to “intelligent optimization”; in reality, pypdf only performs mechanical re-encoding and lacks the ability to perceive the semantic content. synthesis example demonstrates the differences between two compression paths The following code constructs a PDF containing repeated images and multi-page content, demonstrating the effects of lossless structural compression and lossy image processing, respectively. Note: This is instructional code that has been verified using synthetic samples, intended solely to illustrate API behavior boundaries. Please verify it in your local environment before actual use. References and Next Steps The specific handling decision for the exception observation What should be done should not infer decoding stream variation is determined to not meet the lossless requirements of this case retains the original volume has not decreased faithfully records does not guarantee that all PDFs will be successfully compressed text read-back consistency completes an inspection Complex rendering still requires comparison with uses this checklist for document translation file splitting, encryption, or attachment processing are part of delivery preparation; translation cannot replace these checks. Retain the original documents and the processing checklist, then reassess the translated manuscript’s page order, hyperlinks, and content integrity. OmniDoc (Product Entry) provides an entry point for translating multi-format documents, and the official website highlights its OCR, terminology database, and bilingual alignment features. For teams that wish to start processing directly from files, this is a path worth evaluating with real-world samples. Please use de-identified files that you are authorized to upload, and verify the results against the checklist provided in this document; we do not claim that OmniDoc utilizes the open-source libraries or internal algorithms referenced herein, nor do we substitute examples for formal product performance testing. Original manufacturer interface based on: pypdf document 。 - 1 -