File size: 10,694 Bytes
0ec8fd6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 | #!/usr/bin/env python
"""Extract DOIs and reference-citation lines from two sources and aggregate
them into one record per unique DOI:
1. CMEMS EQC parsed markdown docs (store = CMEMS, source = eqc_refs)
2. CDS/ADS/EWDS per-collection reference blocks
(meta_harvest/cds_references.json; store = CDS|ADS|EWDS, source = cds_refs)
Outputs (in publications/registry/):
- unique_dois.jsonl one record per unique DOI aggregated across both sources
- no_doi_refs.jsonl {product_id|collection_id, ref_text} for DOI-less citations
- product_self_dois.json id -> list of its own catalogue DOIs (moi/mds/24381)
- extract_summary.json quick counts
"""
import json
import re
import sys
from collections import defaultdict
from pathlib import Path
from urllib.parse import unquote
BASE = Path("/Users/dmpantiu/copernicus_mcp")
CATALOG = BASE / "marine_rag" / "out" / "catalog.json"
CDS_REFS = BASE / "meta_harvest" / "cds_references.json"
OUT = BASE / "publications" / "registry"
OUT.mkdir(parents=True, exist_ok=True)
# --- DOI handling -----------------------------------------------------------
# allow one <...> segment (old AMS/Wiley SICI DOIs like 10.1175/...(1989)006<0599:x>2.0.co;2)
DOI_RE = re.compile(
r'10\.\d{4,9}/[^\s"\'<>\\]+(?:<\d[^\s<>]*>[^\s"\'<>\\]*)?', re.IGNORECASE)
YEAR_RE = re.compile(r'\b(19|20)\d{2}\b')
HEADING_RE = re.compile(r'^#{1,6}\s')
REF_HEADING_RE = re.compile(r'^#{1,6}\s.*(referen|bibliograph)', re.IGNORECASE)
TRAIL_CHARS = '.,;:!?"\'»›)]}>*_`|'
def clean_doi(raw: str):
"""Aggressively clean an OCR/markdown-noisy DOI match; return lowercase DOI or None."""
d = raw.strip()
# markdown / OCR artifacts
d = d.replace('**', '').replace('\\', '')
d = d.rstrip(' ')
# markdown link syntax: [doi](url) -> cut at first square bracket
d = re.split(r'[\[\]]', d, 1)[0]
# decode percent-encoding (handles %3c, %253c double-encoded) to canonical form
for _ in range(3):
if '%' not in d:
break
dec = unquote(d)
if dec == d:
break
d = dec
# OCR noise chars (negation sign, soft hyphen) and glued HTML tags
d = d.replace('¬', '').replace('', '')
d = re.split(r'<(?=[/a-zA-Z])', d, 1)[0]
# aggregate/collection URL DOIs glued with '@' (e.g. 10.1002/x@10.1002/(issn)...)
d = d.split('@', 1)[0]
# strip trailing punctuation, but keep balanced closing parens
while d and d[-1] in TRAIL_CHARS:
if d[-1] == ')' and d.count('(') >= d.count(')'):
break
d = d[:-1]
# cut at common junk that got glued on
for sep in ('http', ',last', 'available', 'ISSN', 'ISBN'):
i = d.lower().find(sep.lower(), 8)
if i > 0:
d = d[:i]
# re-strip
while d and d[-1] in TRAIL_CHARS:
if d[-1] == ')' and d.count('(') >= d.count(')'):
break
d = d[:-1]
d = d.lower()
# UUID-suffix DOIs with glued trailing text -> truncate to the UUID
m = re.match(r'(10\.\d{4,9}/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12})', d)
if m and len(d) > len(m.group(1)):
d = m.group(1)
# placeholder / template DOIs (e.g. 10.24381/XXXXXXXX)
if re.search(r'x{6,}', d):
return None
# validate (printable ASCII incl. <> for SICI DOIs)
if not re.fullmatch(r'10\.\d{4,9}/[!-~]{3,}', d):
return None
# angle brackets only allowed as one balanced <...> segment
if d.count('<') != d.count('>') or d.count('<') > 1:
return None
# suffix must contain an alnum
suffix = d.split('/', 1)[1]
if not re.search(r'[a-z0-9]', suffix):
return None
if len(d) > 120: # OCR runaway
return None
return d
def is_self_doi(doi: str, store: str) -> bool:
"""Catalogue self-DOIs: CMEMS uses 10.48670/moi|mds-*, CDS/ADS/EWDS use
the ECMWF DataCite prefix 10.24381/*."""
if store == "CMEMS":
return doi.startswith('10.48670/moi-') or doi.startswith('10.48670/mds-')
return doi.startswith('10.24381/')
# --- reference-section extraction (CMEMS markdown) --------------------------
def ref_section_lines(text: str):
"""Yield lines from all sections whose heading matches reference/bibliography."""
lines = text.splitlines()
in_ref = False
for ln in lines:
if HEADING_RE.match(ln):
in_ref = bool(REF_HEADING_RE.match(ln))
continue
if in_ref:
yield ln
def looks_like_citation(line: str) -> bool:
s = line.strip()
if len(s) <= 40:
return False
if not YEAR_RE.search(s):
return False
if s.startswith(('<table', '|', '![', '<tr', '<td', '#', '-', '*', '>', ' ')):
return False
# skip obvious CDS boilerplate / license / attribution lines
low = s.lower()
if any(b in low for b in (
'neither the european commission', 'responsible for any use',
'in addition to the requirements', 'clear and visible attribution',
'applicable license', 'cite the cds catalogue', 'contains modified')):
return False
return True
def line_has_doi(line: str) -> bool:
low = line.lower()
return bool(DOI_RE.search(line)) or 'doi.org' in low or 'doi:' in low
# --- aggregation containers -------------------------------------------------
class Agg:
def __init__(self):
self.doi_ids = defaultdict(set) # doi -> set(id)
self.doi_mentions = defaultdict(int) # doi -> int
self.doi_sources = defaultdict(set) # doi -> set(source)
self.id_store = {} # id -> store
self.self_dois = defaultdict(set) # id -> set(catalogue dois)
self.no_doi_refs = [] # list of dicts
self.id_meta = {} # id -> (domains, regions)
self.raw = 0
self.invalid = 0
def add_doi(self, doi, _id, store, source):
self.doi_ids[doi].add(_id)
self.doi_mentions[doi] += 1
self.doi_sources[doi].add(source)
self.id_store[_id] = store
def process_text(agg, _id, store, source, text, seen, id_key,
use_ref_section, join_linebreaks):
if join_linebreaks:
text = re.sub(r'(10\.\d{4,9}/[^\s"\'<>\\]*)-\s*\n\s*', r'\1', text)
text = re.sub(r'(10\.\d{4,9})/\s*\n\s*', r'\1/', text)
for m in DOI_RE.finditer(text):
agg.raw += 1
doi = clean_doi(m.group(0))
if doi is None:
agg.invalid += 1
continue
if is_self_doi(doi, store):
agg.self_dois[_id].add(doi)
agg.id_store[_id] = store
continue
agg.add_doi(doi, _id, store, source)
# citation text lines (no DOI in line)
line_iter = ref_section_lines(text) if use_ref_section else text.splitlines()
for ln in line_iter:
if not looks_like_citation(ln):
continue
if line_has_doi(ln):
continue
s = ' '.join(ln.split())
key = s.lower()
if key in seen:
continue
seen.add(key)
agg.no_doi_refs.append({id_key: _id, "ref_text": s})
# --- main --------------------------------------------------------------------
def main():
agg = Agg()
catalog = json.loads(CATALOG.read_text())
n_docs_read = n_docs_missing = 0
for prod in catalog:
pid = prod["product_id"]
agg.id_meta[pid] = (prod.get("domains") or [], prod.get("regions") or [])
seen = set()
for doc in prod.get("docs", []):
md_path = doc.get("md_path")
if not md_path:
continue
p = BASE / md_path
if not p.exists():
n_docs_missing += 1
continue
n_docs_read += 1
text = p.read_text(errors="replace")
process_text(agg, pid, "CMEMS", "eqc_refs", text, seen,
"product_id", use_ref_section=True, join_linebreaks=True)
# CDS / ADS / EWDS
cds = json.loads(CDS_REFS.read_text())
store_map = {"cds": "CDS", "ads": "ADS", "ewds": "EWDS"}
n_cds_coll = n_cds_blocks = 0
for store_key, colls in cds.items():
store = store_map.get(store_key, store_key.upper())
for cid, obj in colls.items():
n_cds_coll += 1
agg.id_meta.setdefault(cid, ([], []))
seen = set()
for ref in obj.get("references", []):
n_cds_blocks += 1
txt = ref.get("text") or ""
process_text(agg, cid, store, "cds_refs", txt, seen,
"collection_id", use_ref_section=False,
join_linebreaks=False)
# --- write unique_dois.jsonl ---
with open(OUT / "unique_dois.jsonl", "w") as f:
for doi in sorted(agg.doi_ids):
ids = sorted(agg.doi_ids[doi])
domains, regions = set(), set()
for i in ids:
d_, r_ = agg.id_meta.get(i, ([], []))
domains.update(d_)
regions.update(r_)
rec = {
"doi": doi,
"linked_products": ids,
"product_stores": {i: agg.id_store[i] for i in ids},
"n_mentions": agg.doi_mentions[doi],
"domains": sorted(domains),
"regions": sorted(regions),
"sources": sorted(agg.doi_sources[doi]),
}
f.write(json.dumps(rec, ensure_ascii=False) + "\n")
with open(OUT / "no_doi_refs.jsonl", "w") as f:
for rec in agg.no_doi_refs:
f.write(json.dumps(rec, ensure_ascii=False) + "\n")
with open(OUT / "product_self_dois.json", "w") as f:
json.dump({k: sorted(v) for k, v in sorted(agg.self_dois.items())},
f, indent=1)
linked_ids = {i for ids in agg.doi_ids.values() for i in ids}
by_store = defaultdict(int)
for i in linked_ids:
by_store[agg.id_store.get(i, "?")] += 1
summary = {
"cmems_docs_read": n_docs_read,
"cmems_docs_missing": n_docs_missing,
"cds_collections": n_cds_coll,
"cds_ref_blocks": n_cds_blocks,
"raw_doi_matches": agg.raw,
"invalid_after_clean": agg.invalid,
"unique_dois": len(agg.doi_ids),
"linked_ids_total": len(linked_ids),
"linked_ids_by_store": dict(by_store),
"ids_with_self_doi": len(agg.self_dois),
"no_doi_ref_lines": len(agg.no_doi_refs),
}
with open(OUT / "extract_summary.json", "w") as f:
json.dump(summary, f, indent=1)
print(json.dumps(summary, indent=1))
if __name__ == "__main__":
sys.exit(main())
|