Before handing over the PDF translation task, first check the fonts instead of rushing to change them.

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 files or products. Before processing important files, please retain the original copies and verify them against the boundaries and acceptance criteria specified in the text. Which problem does this paper address first ’s default font list differs in length from the tuple returned when full=True. Below, read the first six items, then check whether the font bytes returned by extract_font are empty. A Base14 font reference does not equate to the font program being embedded; nor should subset fonts be categorically deemed errors. 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. import pymupdf with pymupdf.open() as doc: page = doc.new_page() page.insert_text((72, 72), "Font sample", fontname="helv") fonts = doc.get_page_fonts(0, full=True) assert fonts report = [] for item in fonts: xref, ext, kind, basefont, name, encoding = item[:6] extracted_name, extracted_ext, extracted_type, data = doc.extract_font(xref) report.append({"name": basefont, "font_program_present": bool(data), "xref": xref, "encoding": encoding}) assert report[0]["name"] == "Helvetica" assert report[0]["font_program_present"] is False assert report[0]["xref"] > 0 receives a PDF to be translated, and the most hazardous instinctive reaction is to perform a global replacement with Source Han Sans or Arial. This approach often reveals problems only at delivery: mathematical symbols in the original text turn into squares, table numbers lose their proportional alignment, or, due to embedded restricted fonts, the translation becomes unreadable on certain readers. Before initiating any text extraction or typesetting reorganization, it is essential to first conduct a font inventory of the document. This is not for legal compliance auditing, but rather to ensure technical editability and rendering stability. get_page_fonts() is a low-level probe provided by PyMuPDF; it tells you which font resources each page actually references, whether they are fully embedded, and their encoding types. This information determines whether the subsequent translation process should proceed via OCR, direct replacement, or manual re-layout. Synthesis Test: Memory Construction and Assertion Verification To meet the requirements for isolated execution and to verify the revised logic described above, we constructed a fully self-contained test case. This script does not rely on external files; instead, it dynamically creates a PDF containing standard fonts in memory using PyMuPDF, followed immediately by an inventory analysis of the document. This approach ensures the reproducibility of the example while avoiding copyright and privacy risks. Note that, since we cannot construct “corrupted” or “non-embedded” synthetic font objects in memory without introducing external font files, this test focuses on verifying the accuracy of parsing normally embedded fonts and the function’s defensive handling of invalid page numbers. This aligns with the engineering practice of “first ensuring correctness along the normal path, then separately testing exceptional branches.” Acceptance Criteria and Manual Review Boundary The “safe” or “warning” messages generated by the code are merely technical indicators and should not be directly equated with translation feasibility. The table below summarizes the mapping between technical checks and production decisions, clarifying the limitations of automated tools and the triggers for human intervention. This table distinguishes between “code demonstration” and “end-to-end performance.” While scripts can accurately report embedding status, they cannot determine whether the font has a corresponding glyph in the target language or assess whether the license permits modifications to the embedded font. Such decisions must be made by humans in conjunction with the project context. Reference and Next Step PyMuPDF Document.get_page_fonts Official documentation: https://pymupdf.readthedocs.io/en/latest/document.html#Document.get_page_fonts PyMuPDF Homepage and Downloads: https://pymupdf.io The decision on handling the specific exception observation What should be done should not infer font program is empty record not extracted to the embedding program Base14 reference is not equal to embedded subset font retains the font identifier does not directly determine damage list is empty Confirm page content may be an image or another drawing path uses this checklist for document translation first ensures that the page order, source locations, and text integrity have been thoroughly checked, then submits the same de-identified sample to the translation process. After translation, it is still necessary to verify that the headings, body text, and figure captions correspond correctly; one should not rely solely on whether the text flows smoothly. 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 product performance testing. - 1 -