Books — capture <li> vocab bullets the extractor was silently dropping

extract_epub.py was walking <p> only, but every "Vocabulario" section in
the Olly Richards EPUB lives inside <ul><li>...</li></ul>. That meant
the heading made it through but the entries didn't — 680 vocab lines
across 24 sections in this book were missing from the bundled JSON.

Audit (text-node owner by closest block ancestor) confirmed <li> is the
only silent drop: 5,260 nodes in <p>, 1,960 in <li>, 0 anywhere else.
No <h1>-<h6>, tables, or blockquotes in this EPUB at all.

Fix: walk find_all(["p", "li"]) in document order so bullet entries
slot in right after their "Vocabulario" / list heading. Re-extracted
(2,646 → 3,326 paragraphs), re-translated all 118 jobs in parallel
Claude Code subagents. translate_chapters.py prompt template now tells
subagents to keep bilingual `palabra = meaning` lines verbatim — both
sides already coexist on the line.

Bumped bookDataVersion to 2 so refreshBooksDataIfNeeded re-seeds.
Verified in simulator: all 13 chapter row sizes grew (e.g. ch6
18,295→20,951 chars).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Conjuga/Conjuga/Services/DataLoader.swift

@@ -9,7 +9,7 @@ actor DataLoader {
     static let textbookDataVersion = 14
     static let textbookDataKey = "textbookDataVersion"
 
-    static let bookDataVersion = 1
+    static let bookDataVersion = 2  // bump: vocab <li> bullets now extracted
     static let bookDataKey = "bookDataVersion"
 
     /// Quick check: does the DB need seeding or course data refresh?

Conjuga/Scripts/books/extract_epub.py

@@ -141,14 +141,13 @@ def _extract_paragraphs(zf: zipfile.ZipFile, zip_path: str) -> list[str]:
         return []
     soup = BeautifulSoup(html, "lxml")
     paragraphs: list[str] = []
-    for p in soup.find_all("p"):
+    # Walk <p> and <li> in document order so vocab bullets (rendered as
-        # Drop nav-anchor wrappers that contain no real text.
+    # <ul><li>...</li></ul> in this EPUB family) are kept alongside narrative
-        text = _normalise(p.get_text(" ", strip=True))
+    # paragraphs. `<li>` rolls up its inline <b>/<span> children via get_text.
+    for el in soup.find_all(["p", "li"]):
+        text = _normalise(el.get_text(" ", strip=True))
         if not text:
             continue
-        # Drop chapter-heading paragraphs that only echo the title — handled
-        # separately by the TOC. Heuristic: very short paragraph that's just
-        # numbers + the chapter title pattern. Keep everything else.
         paragraphs.append(text)
     return paragraphs
 

Conjuga/Scripts/books/translate_chapters.py

@@ -57,6 +57,10 @@ Notes for translation quality:
   ONLY if it reads more naturally; otherwise keep them as em-dashes.
 - Do NOT add explanatory parentheticals; the in-app dictionary handles
   per-word lookup.
+- Some paragraphs are vocabulary entries shaped like `palabra = meaning`
+  (e.g. `alto = tall`, `el dueño = owner`). Keep these verbatim — both the
+  Spanish word and its English gloss already coexist on the line, and the
+  bilingual reader UI shows the same line in both views.
 
 Write the output as JSON with shape:
     {{"jobId": "<the jobId from the input>", "paragraphsEN": [...]}}