File size: 7,164 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 | #!/usr/bin/env python3
"""Code-preserving parse + dataset mapping for CopernicusMarineInsitu/INSTACTraining."""
import json, re, sys
from pathlib import Path
REPO = Path("/Users/dmpantiu/copernicus_mcp/notebook_harvest/repos/INSTACTraining")
OUT = Path("/Users/dmpantiu/copernicus_mcp/notebook_harvest/parsed/INSTACTraining")
CATALOG = Path("/Users/dmpantiu/copernicus_mcp/marine_rag/out/catalog.json")
DOWNLOAD_RE = re.compile(
r"cdsapi|\.retrieve\(|copernicusmarine|\bcm\.(subset|get|open_dataset)|"
r"motuclient|!?\bwget\b|!?\bcurl\b|urlretrieve|requests\.get|\bftplib\b|"
r"FTP\(|\.hda\b|urlopen|ftp://", re.I)
ANALYZE_RE = re.compile(
r"\bimport xarray|\bxr\.|\.open_dataset|\.open_mfdataset|\bimport pandas|\bpd\.|"
r"\bimport numpy|\bnp\.|\bnetCDF4|\bDataset\(|\bscipy|\.groupby\(|\.resample\(|"
r"\.mean\(|\.sel\(|\.isel\(", re.I)
PLOT_RE = re.compile(
r"\bmatplotlib|\bplt\.|\bcartopy|\bccrs\b|\bcmocean|\.plot\(|\.plot\.|seaborn|"
r"\bsns\.|\bfolium\b|basemap|\bBasemap\b", re.I)
# product id patterns (legacy + current)
PID_RE = re.compile(r"INSITU_[A-Z]+_[A-Z_]*?OBSERVATIONS_0\d\d_\d\d\d(?:_[a-z])?|"
r"INSITU_[A-Z]+_[A-Z_]+_0\d\d_\d\d\d", re.I)
DSID_RE = re.compile(r"cmems_obs-ins_[a-z0-9_-]+", re.I)
SUFFIX_RE = re.compile(r"(0\d\d_\d\d\d)")
# CMEMS INSTAC platform-file naming convention: <REGION>_<DATATYPE>_<PLATFORM>_<id>.nc
# region prefix (first token) -> regional DISCRETE_MYNRT product numeric suffix
REGION2SUFFIX = {"GL": "013_030", "AR": "013_031", "BO": "013_032", "BS": "013_034",
"IR": "013_033", "IB": "013_033", "MO": "013_035", "NO": "013_036"}
FILENAME_RE = re.compile(
r"\b(GL|AR|BO|BS|IR|IB|MO|NO)_(TS|PR|WS|CT|GL|TG|SF|WV|RF|HF)_[A-Z]{2}_[A-Za-z0-9_]+\.nc")
def _src(cell):
s = cell.get("source", "")
return "".join(s) if isinstance(s, list) else s
def code_line_count(code):
return sum(1 for ln in code.splitlines()
if ln.strip() and not ln.strip().startswith("#"))
def text_outputs(cell):
out = []
for o in cell.get("outputs", []):
ot = o.get("output_type"); s = None
if ot == "stream":
t = o.get("text", ""); s = "".join(t) if isinstance(t, list) else t
elif ot in ("execute_result", "display_data"):
tp = (o.get("data") or {}).get("text/plain")
if tp is not None:
s = "".join(tp) if isinstance(tp, list) else tp
if not s:
continue
s = s.strip()
if not s or re.fullmatch(r"<[^>]+>", s) or s.startswith("<Figure"):
continue
lines = [ln for ln in s.splitlines()
if "%|" not in ln and "it/s]" not in ln and "B/s]" not in ln]
s = "\n".join(lines).strip()
if len(s) >= 8:
out.append(s[:1500])
return out
def classify(code):
kinds = []
if DOWNLOAD_RE.search(code): kinds.append("download")
if ANALYZE_RE.search(code): kinds.append("analyze")
if PLOT_RE.search(code): kinds.append("plot")
return kinds or ["other"]
def slug(path):
rel = path.relative_to(REPO).with_suffix("")
return "__".join(rel.parts).replace(" ", "_")
def extract_notebook(path):
nb = json.loads(path.read_text(encoding="utf-8", errors="replace"))
parts, n_code_cells, n_code_lines = [], 0, 0
kinds, title = set(), ""
raw_all = []
for cell in nb.get("cells", []):
ct = cell.get("cell_type")
if ct == "markdown":
txt = _src(cell).strip()
if txt:
parts.append(txt); raw_all.append(txt)
if not title:
for ln in txt.splitlines():
if ln.startswith("# "):
title = ln[2:].strip(); break
elif ct == "code":
src = _src(cell).rstrip()
if not src.strip():
continue
n_code_cells += 1
n_code_lines += code_line_count(src)
kinds.update(classify(src))
raw_all.append(src)
parts.append("```python\n" + src + "\n```")
for to in text_outputs(cell):
parts.append("```text\n" + to + "\n```")
raw_all.append(to)
return {
"content_md": "\n\n".join(parts).strip(),
"title": title or path.stem,
"n_code_cells": n_code_cells,
"n_code_lines": n_code_lines,
"recipe_kinds": sorted(kinds),
"raw": "\n".join(raw_all),
}
def main():
OUT.mkdir(parents=True, exist_ok=True)
catalog = json.load(open(CATALOG))
suffix2pid = {}
valid_pids = set()
dsid2pid = {}
for e in catalog:
pid = e.get("product_id")
if not pid:
continue
valid_pids.add(pid)
m = SUFFIX_RE.search(pid)
if m:
suffix2pid.setdefault(m.group(1), pid)
for ds in (e.get("dataset_ids") or []):
dsid2pid[ds] = pid
records = []
nbs = sorted(p for p in REPO.rglob("*.ipynb")
if ".ipynb_checkpoints" not in p.parts)
for nb in nbs:
ex = extract_notebook(nb)
nid = slug(nb)
if ex["n_code_cells"] == 0:
print(f"SKIP prose-only: {nid}", file=sys.stderr)
continue
(OUT / f"{nid}.md").write_text(ex["content_md"], encoding="utf-8")
raw = ex["raw"]
found_pids = set()
raw_ids = set()
for m in PID_RE.findall(raw):
raw_ids.add(m)
sm = SUFFIX_RE.search(m)
if sm and sm.group(1) in suffix2pid:
found_pids.add(suffix2pid[sm.group(1)])
for m in DSID_RE.findall(raw):
raw_ids.add(m)
if m in dsid2pid:
found_pids.add(dsid2pid[m])
# fallback: infer product from INSTAC platform-file naming convention
if not found_pids:
for region, dtype in FILENAME_RE.findall(raw):
suf = REGION2SUFFIX.get(region.upper())
if suf and suf in suffix2pid:
found_pids.add(suffix2pid[suf])
fm = FILENAME_RE.search(raw)
if fm:
raw_ids.add("file:" + fm.group(0))
matched = sorted(found_pids)
scope = "dataset" if matched else "generic"
records.append({
"notebook_id": nid,
"title": ex["title"],
"matched_dataset_ids": matched,
"raw_ids": sorted(raw_ids),
"store": "CMEMS in-situ",
"scope": scope,
"source_repo": "CopernicusMarineInsitu/INSTACTraining",
"license": "MIT",
"src_path": str(nb.relative_to(REPO)),
"md_path": f"notebook_harvest/parsed/INSTACTraining/{nid}.md",
"n_code_cells": ex["n_code_cells"],
"n_code_lines": ex["n_code_lines"],
"recipe_kinds": ex["recipe_kinds"],
})
print(json.dumps(records, indent=2))
tot_lines = sum(r["n_code_lines"] for r in records)
print(f"\nNOTEBOOKS={len(records)} TOTAL_CODE_LINES={tot_lines}", file=sys.stderr)
if __name__ == "__main__":
main()
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