Alvin
Add complete dataset: all sources, metadata, scripts, docs, and phylo enrichment
26786e3
#!/usr/bin/env python3
"""Parser for the Oracc (Open Richly Annotated Cuneiform Corpus) API.
Fetches lemma data from Oracc project JSON endpoints. Oracc hosts
multiple cuneiform language corpora; the project identifier determines
the language:
- "ecut" -> Urartian
- "dcclt" -> Sumerian lexical texts
- "saao/saa01" -> Neo-Assyrian
Endpoint pattern: http://oracc.museum.upenn.edu/{project}/json
Reference: http://oracc.museum.upenn.edu/doc/opendata/
"""
from __future__ import annotations
import json
import logging
import urllib.request
import urllib.error
from typing import Any
logger = logging.getLogger(__name__)
def _extract_lemmas_from_catalog(data: dict) -> list[dict]:
"""Extract lemmas from the catalogue/index JSON structure."""
entries: list[dict] = []
# Oracc JSON has nested structure:
# {"members": {"P123456": {"cdl": [...]}}}
# or {"index": {"cat": {...}, "lem": {...}}}
# or {"glossary": {"entries": [...]}}
# Strategy 1: glossary format
if "glossary" in data:
glossary = data["glossary"]
glo_entries = glossary.get("entries", [])
if isinstance(glo_entries, list):
for entry in glo_entries:
cf = entry.get("cf", "") # citation form
gw = entry.get("gw", "") # guide word (gloss)
form_list = entry.get("forms", [])
if cf and gw:
translit = cf
# If forms are available, use the first one
if form_list and isinstance(form_list, list):
first_form = form_list[0] if form_list else {}
if isinstance(first_form, dict):
translit = first_form.get("n", cf)
entries.append({
"word": cf,
"transliteration": translit,
"gloss": gw,
})
elif isinstance(glo_entries, dict):
for key, entry in glo_entries.items():
if isinstance(entry, dict):
cf = entry.get("cf", key)
gw = entry.get("gw", "")
if cf and gw:
entries.append({
"word": cf,
"transliteration": cf,
"gloss": gw,
})
# Strategy 2: index/lem format
if not entries and "index" in data:
index = data["index"]
lem_data = index.get("lem", {})
if isinstance(lem_data, dict):
for lemma_key, lemma_info in lem_data.items():
# lemma_key format: "cf[gw]POS" e.g. "šarru[king]N"
import re
m = re.match(r"^(.+?)\[(.+?)\]", lemma_key)
if m:
entries.append({
"word": m.group(1),
"transliteration": m.group(1),
"gloss": m.group(2),
})
# Strategy 3: members/cdl format (text corpus)
if not entries and "members" in data:
members = data["members"]
if isinstance(members, dict):
for text_id, text_data in members.items():
if not isinstance(text_data, dict):
continue
_extract_cdl_lemmas(text_data.get("cdl", []), entries)
return entries
def _extract_cdl_lemmas(cdl_list: list, entries: list[dict]) -> None:
"""Recursively extract lemmas from CDL (Corpus Description Language) nodes."""
if not isinstance(cdl_list, list):
return
for node in cdl_list:
if not isinstance(node, dict):
continue
# Leaf node with lemma
if "f" in node:
f = node["f"]
if isinstance(f, dict):
cf = f.get("cf", "")
gw = f.get("gw", "")
form = f.get("form", cf)
if cf and gw:
entries.append({
"word": cf,
"transliteration": form if form else cf,
"gloss": gw,
})
# Recurse into children
if "cdl" in node:
_extract_cdl_lemmas(node["cdl"], entries)
def parse(url: str, **kwargs: Any) -> list[dict]:
"""Fetch and parse lemma data from an Oracc project JSON endpoint.
Args:
url: Oracc URL. Can be:
- Direct JSON: http://oracc.museum.upenn.edu/ecut/json
- Project page: http://oracc.museum.upenn.edu/ecut
The parser will append /json if needed.
**kwargs:
project: Override project name (e.g., "ecut", "dcclt")
Returns:
List of dicts with keys: word, transliteration, gloss.
Returns empty list if URL is unreachable.
"""
# Normalize URL to JSON endpoint
json_url = url.rstrip("/")
if not json_url.endswith("/json"):
json_url += "/json"
logger.info("Oracc: downloading %s", json_url)
try:
req = urllib.request.Request(json_url, headers={"User-Agent": "PhaiPhon/1.0"})
with urllib.request.urlopen(req, timeout=60) as resp:
raw = resp.read().decode("utf-8", errors="replace")
except (urllib.error.URLError, urllib.error.HTTPError, OSError) as exc:
logger.warning("Oracc: failed to download %s: %s", json_url, exc)
return []
try:
data = json.loads(raw)
except json.JSONDecodeError as exc:
logger.warning("Oracc: invalid JSON from %s: %s", json_url, exc)
return []
entries = _extract_lemmas_from_catalog(data)
# Deduplicate by (word, gloss)
seen: set[tuple[str, str]] = set()
unique: list[dict] = []
for e in entries:
key = (e["word"], e["gloss"])
if key not in seen:
seen.add(key)
unique.append(e)
logger.info("Oracc: extracted %d unique entries from %s", len(unique), json_url)
return unique
if __name__ == "__main__":
import sys
logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
test_url = (
sys.argv[1] if len(sys.argv) > 1
else "http://oracc.museum.upenn.edu/ecut/json"
)
results = parse(test_url)
print(f"\nExtracted {len(results)} entries:")
for entry in results[:15]:
print(f" {entry['word']:20s} {entry['transliteration']:20s} {entry['gloss']}")
if len(results) > 15:
print(f" ... and {len(results) - 15} more")