story-to-pack: add the corpora and the catalogue v2/v3

Fourteen corpora split and classified: aesop, bierce, chekhov, holmes, keefe, lawson, lorimer, maupassant, nobody, plaintales, poe, torchy, wallingford and winesburg, each with its splitter and the hand-written groups and pages; catalogue v2 and v3; and the shared splitters gutenberg_chunks.py, se_split.py and se_build.py. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019rwKTmug58sEsJ72AuWsEi
2026-10-07 06:05:51 -04:00
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+"""Split the Project Gutenberg plain text of Anton Chekhov, *The Schoolmistress, and Other Stories*
+(Constance Garnett translation, "Tales of Chekhov, Volume 9", eBook #1732), into stories, then cut
+scenes with the same rule as ../chunk.py, ../jacobs/split_se.py and ../wharton/split_gutenberg.py
+(paragraph boundaries, ~320 words, tail >= 80).
+Deterministic: titles are the 21 contents entries, matched as whole upper-case lines after the
+contents; roman-numeral section headings and the "A Wayfarer's Story" subtitle inside Champagne are
+dropped; the Gutenberg licence after END is dropped."""
+import json, pathlib, re
+
+TITLES = ['The Schoolmistress', 'A Nervous Breakdown', 'Misery', 'Champagne', 'After the Theatre',
+          "A Lady's Story", 'In Exile', 'The Cattle-Dealers', 'Sorrow', 'On Official Duty',
+          'The First-Class Passenger', 'A Tragic Actor', 'A Transgression', 'Small Fry',
+          'The Requiem', 'In the Coach-House', 'Panic Fears', 'The Bet',
+          "The Head-Gardener's Story", 'The Beauties', 'The Shoemaker and the Devil']
+TARGET = 320
+VOLUME = 'The Schoolmistress, and Other Stories (Anton Chekhov, tr. Constance Garnett, 1918)'
+
+
+def norm(s):
+    return s.replace('’', "'").strip()
+
+
+raw = pathlib.Path('corpus/schoolmistress-and-other-stories.txt').read_text(encoding='utf-8').replace('\r', '')
+raw = raw[:raw.index('*** END OF THE PROJECT GUTENBERG')]
+lines = raw.split('\n')
+start = next(i for i, l in enumerate(lines) if norm(l) == 'CONTENTS')
+heads = []
+for t in TITLES:
+    hits = [i for i, l in enumerate(lines) if i > start + 22 and norm(l) == t.upper()]
+    assert len(hits) == 1, (t, hits)
+    heads.append(hits[0])
+assert heads == sorted(heads)
+
+stories = []
+for n, (t, a) in enumerate(zip(TITLES, heads)):
+    b = heads[n + 1] if n + 1 < len(heads) else len(lines)
+    body = '\n'.join(lines[a + 1:b])
+    paras = []
+    for p in re.split(r'\n\s*\n', body):
+        p = re.sub(r'\s+', ' ', p).strip()
+        if not p or re.fullmatch(r'[IVX]+\.?', p): continue
+        if norm(p).upper() == "A WAYFARER'S STORY": continue
+        paras.append(p)
+    stories.append({'volume': VOLUME, 'title': t, 'words': sum(len(p.split()) for p in paras),
+                    'text': '\n\n'.join(paras)})
+
+chunks = []
+for si, s in enumerate(stories):
+    buf, n = [], 0
+    for p in s['text'].split('\n\n'):
+        w = len(p.split())
+        if n + w > TARGET and buf:
+            chunks.append({'story': si, 'title': s['title'], 'volume': s['volume'], 'text': ' '.join(buf), 'words': n})
+            buf, n = [], 0
+        buf.append(p); n += w
+    if buf and n >= 80:
+        chunks.append({'story': si, 'title': s['title'], 'volume': s['volume'], 'text': ' '.join(buf), 'words': n})
+    elif buf:
+        # tail too short to stand alone: fold into the previous scene rather than drop it
+        if chunks and chunks[-1]['story'] == si:
+            chunks[-1]['text'] += ' ' + ' '.join(buf)
+            chunks[-1]['words'] += n
+        else:
+            chunks.append({'story': si, 'title': s['title'], 'volume': s['volume'], 'text': ' '.join(buf), 'words': n})
+
+pathlib.Path('stories.json').write_text(json.dumps(stories, indent=1, ensure_ascii=False), encoding='utf-8')
+pathlib.Path('chunks.json').write_text(json.dumps(chunks, ensure_ascii=False), encoding='utf-8')
+for si, s in enumerate(stories):
+    print(f"{si:2} {s['title']:28} {s['words']:6} words  {sum(c['story']==si for c in chunks):3} scenes")
+ws = sorted(c['words'] for c in chunks)
+print(f'stories {len(stories)}  scenes {len(chunks)}  words/scene min {ws[0]} median {ws[len(ws)//2]} max {ws[-1]}  total {sum(ws):,}')