#!/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: ___.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("= 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()