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A PDF can display Arabic correctly yet fail to return the expected Arabic letters when you search or copy text. In a 2026 test using headless Chrome 135 and pdf.js 4.8, Amiri Regular and Amiri Bold returned most of the tested whole words; several other tested fonts returned none. That is a project author’s result for a specific setup—not proof that Amiri is the only searchable Arabic font in every PDF workflow.
What the 13-font test found
Mahmoud Qq2023 reports testing 13 fonts with headless Chrome 135 and pdf.js 4.8. In the displayed results, Amiri was the strongest performer for whole-word matching, but neither tested Amiri weight matched every word.
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| Font rows in the report | Reported whole-word matches | What the result means |
|---|---|---|
| Amiri Regular | 15/18 | 15 of the 18 tested words were returned as whole-word matches. |
| Amiri Bold | 16/18 | 16 of the 18 tested words were returned as whole-word matches. |
| IBM Plex Sans Arabic, Noto Sans Arabic, Arial (Windows), and Tahoma (Windows) | 0/18 for each listed row | The report says these rows stored presentation forms and did not return whole-word matches. |
These are the project author’s reported results, not an independent benchmark or a general ranking of font families. The report notes that some misses may arise when pdf.js inserts a space at a text-run boundary, even where the letters remain in order. A missed whole-word match therefore does not necessarily mean every character was mapped incorrectly. See the project comparison and test details.
Why a PDF can look right but search wrong
PDF display and text extraction use related but distinct information. A PDF can draw the shaped Arabic glyphs correctly while its character-to-Unicode mapping exposes a different string to search, copy, or extraction. In the project’s explanation, the tested Chrome output sometimes mapped glyphs to Arabic presentation-form code points—the shaped variants—rather than to the nominal Arabic letters a person expects to search.
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The PDF Reference describes a ToUnicode CMap as a way to map character codes to Unicode values for text extraction. That mapping is the document-level bridge between what a PDF encodes and the text an extractor can return. A suitable mapping is important for useful extraction, but the cited material does not establish that font choice alone determines the result; the generation pipeline matters too. Adobe’s PDF Reference provides the technical background.
Arabic’s right-to-left display is another issue, not a substitute for a correct text mapping. Unicode’s Bidirectional Algorithm governs visual ordering of right-to-left and mixed-direction text; a page that looks correctly ordered does not, by that fact alone, demonstrate that its characters will be searchable as the intended Unicode string. See the Unicode Bidirectional Algorithm.
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Arabic cases worth testing separately
Lam-alef ligatures
Arabic لا combines lam and alef, which may be shaped as a single glyph. The project reports reversed character order in some extracted mappings involving ligatures. Include words containing لا in a test document, then check both the extracted character order and whether the complete word can be found. Do not infer that a font or PDF handles all Arabic words correctly from a simpler sample. The project describes its lam-alef observations.
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The author reports that diacritics rendered but were extracted as U+0000 in the tested fonts. This is an observation from those runs, not a finding about every font or PDF generator. If copyable or searchable harakat matter, include marked words in the test and inspect the extracted text rather than relying on the page image.
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How to choose and validate a font for searchable Arabic PDFs
Based on its comparison, the project author recommends embedding Amiri, using a genuine bold font file when bold text must remain searchable, and testing words containing lam-alef. Treat that as a practical starting point from one reported configuration, not a universal guarantee.
- Record the setup. Note the browser or PDF-generation library and version, the exact font file and weight, and the PDF viewer or extraction tool. Results from headless Chrome 135 with pdf.js 4.8 should not be assumed to describe other combinations.
- Generate a representative PDF. Include ordinary Arabic words, words containing لا, any bold text you use, and diacritics if they are part of your content. Use the actual font files and styling intended for production.
- Check what the PDF exposes. Search for complete Arabic words and copy or extract sample text. Compare the returned characters with the intended base-letter string; correct-looking glyphs on the page are not enough.
- Test in the target reader. Record the PDF viewer or extraction utility, since the reported whole-word result involved pdf.js 4.8. If search or copying fails, compare another supported generation and reading combination before attributing the issue to the font alone.
When comparing candidate outputs, track whether extracted text uses base Arabic letters or presentation forms, whether lam-alef order survives, whether whole-word searches succeed, and whether marks remain in extracted text. TCPDF’s documentation offers an implementation example of Unicode mapping, but it does not establish that every PDF library behaves the same way. TCPDF documentation.
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What “only one” does—and does not—mean
The headline’s “only one” framing describes a particular test, not a universal rule. The reported table includes two Amiri weights, and both returned most of the tested words; Amiri Bold scored 16/18 while Amiri Regular scored 15/18. Other displayed rows scored 0/18. Those counts apply to the author’s 18-word test under headless Chrome 135 and pdf.js 4.8. They do not establish how all font files, PDF generators, browsers, or viewers will behave.
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