| |
| """ |
| Validate Interslavic MT corpus format. |
| - Monolingual: id, sentence, source; no duplicate ids. |
| - Parallel: id, isv, target, translator, method, review_status; ids exist in monolingual; isv matches. |
| Exits 0 on success, 1 on validation failure. |
| """ |
| from pathlib import Path |
| import os |
| import sys |
|
|
| try: |
| import pandas as pd |
| except ImportError: |
| print("Requires pandas and pyarrow. Install with: pip install -r requirements.txt", file=sys.stderr) |
| sys.exit(2) |
|
|
| REPO_ROOT = Path(__file__).resolve().parent.parent |
| MONOLINGUAL_PATH = REPO_ROOT / "monolingual" / "isv_sentences.parquet" |
| PARALLEL_DIR = REPO_ROOT / "parallel" |
|
|
| MONO_COLUMNS = {"id", "sentence", "source"} |
| PARALLEL_COLUMNS = {"id", "isv", "target", "translator", "method", "review_status"} |
| METHOD_VALUES = {"human", "machine_raw", "machine_postedited"} |
|
|
|
|
| def main() -> None: |
| errors: list[str] = [] |
| ci_mode = os.environ.get("GITHUB_ACTIONS", "").lower() in ("true", "1") |
|
|
| |
| df_mono = None |
| mono_ids: set[str] = set() |
| mono_id_to_sentence: dict[str, str] = {} |
|
|
| if not MONOLINGUAL_PATH.exists(): |
| errors.append(f"Missing monolingual file: {MONOLINGUAL_PATH}") |
| else: |
| df_mono = pd.read_parquet(MONOLINGUAL_PATH) |
| cols = set(df_mono.columns) |
| if cols != MONO_COLUMNS: |
| missing = MONO_COLUMNS - cols |
| extra = cols - MONO_COLUMNS |
| if missing: |
| errors.append(f"monolingual: missing columns: {missing}") |
| if extra: |
| errors.append(f"monolingual: unexpected columns: {extra}") |
| if df_mono["id"].duplicated().any(): |
| dupes = df_mono[df_mono["id"].duplicated(keep=False)]["id"].unique().tolist() |
| errors.append(f"monolingual: duplicate ids: {dupes}") |
| if df_mono["id"].isna().any() or df_mono["sentence"].isna().any() or df_mono["source"].isna().any(): |
| errors.append("monolingual: null values in id, sentence, or source") |
| mono_ids = set(df_mono["id"].astype(str)) |
| mono_id_to_sentence = dict(zip(df_mono["id"].astype(str), df_mono["sentence"].astype(str))) |
|
|
| |
| for path in sorted(PARALLEL_DIR.glob("*.parquet")): |
| name = path.name |
| df = pd.read_parquet(path) |
| cols = set(df.columns) |
| if cols != PARALLEL_COLUMNS: |
| missing = PARALLEL_COLUMNS - cols |
| extra = cols - PARALLEL_COLUMNS |
| if missing: |
| errors.append(f"{name}: missing columns: {missing}") |
| if extra: |
| errors.append(f"{name}: unexpected columns: {extra}") |
| if "id" in df.columns and "isv" in df.columns and mono_id_to_sentence: |
| missing_ids = set(df["id"].astype(str)) - mono_ids |
| if missing_ids: |
| errors.append(f"{name}: ids not in monolingual: {list(missing_ids)[:10]}{'...' if len(missing_ids) > 10 else ''}") |
| |
| df_ids = df["id"].astype(str) |
| df_isv = df["isv"].astype(str).str.strip() |
| expected = df_ids.map(mono_id_to_sentence.get) |
| in_mono = df_ids.isin(mono_ids) |
| mismatch = in_mono & (df_isv != expected.str.strip()) |
| if mismatch.any(): |
| bad_ids = df.loc[mismatch, "id"].astype(str).tolist() |
| if ci_mode: |
| errors.append(f"{name}: id {bad_ids[0]} has isv text that does not match monolingual sentence") |
| else: |
| for rid in bad_ids: |
| errors.append(f"{name}: id {rid} has isv text that does not match monolingual sentence") |
| if "method" in df.columns and not set(df["method"].dropna().unique()).issubset(METHOD_VALUES): |
| bad = set(df["method"].dropna().unique()) - METHOD_VALUES |
| errors.append(f"{name}: invalid method values: {bad}") |
|
|
| if errors: |
| for e in errors: |
| print(e, file=sys.stderr) |
| sys.exit(1) |
| print("Validation passed.") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
