import sys, os
sys.stdout.reconfigure(encoding='utf-8')
sys.stderr.reconfigure(encoding='utf-8')
from huggingface_hub import HfApi
from pathlib import Path

api = HfApi()
repo = "Nacryos/ancient-scripts-datasets"
local_base = Path("C:/Users/alvin/hf-ancient-scripts")

checks = [
    ("docs", 20),
    ("scripts", 37),
    ("cognate_pipeline", 91),
    ("data/validation", 58),
    ("data/training/validation", 53),
    ("data/training/audit_trails", 27),
    ("data/training/language_profiles", 1110),
    ("data/training/raw", 14),
    ("data/cited_sources", 5),
]

all_pass = True
for path, expected in checks:
    local_dir = local_base / path
    # Count local files (exclude __pycache__, .pyc, .git)
    local_count = 0
    local_names = set()
    for root, dirs, files in os.walk(local_dir):
        dirs[:] = [d for d in dirs if d not in ('__pycache__', '.git')]
        for f in files:
            if not f.endswith('.pyc'):
                local_count += 1
                rel = os.path.relpath(os.path.join(root, f), local_dir).replace("\\", "/")
                local_names.add(rel)

    # Count HF files
    try:
        hf_items = list(api.list_repo_tree(repo, path_in_repo=path, repo_type="dataset", recursive=True))
        hf_names = set()
        for item in hf_items:
            if hasattr(item, 'size'):
                rel = item.path.replace(path + "/", "", 1)
                hf_names.add(rel)
        hf_count = len(hf_names)
    except Exception as e:
        hf_count = 0
        hf_names = set()
        print(f"ERROR listing {path}: {e}")

    missing = local_names - hf_names
    extra = hf_names - local_names
    status = "PASS" if local_count == hf_count and not missing else "FAIL"
    if status == "FAIL":
        all_pass = False

    print(f"{path:40s} local={local_count:5d}  hf={hf_count:5d}  expected={expected:5d}  {status}")
    if missing and len(missing) <= 10:
        for f in sorted(missing):
            print(f"  MISSING on HF: {f}")
    elif missing:
        print(f"  MISSING on HF: {len(missing)} files (too many to list)")
    if extra and len(extra) <= 10:
        for f in sorted(extra):
            print(f"  EXTRA on HF: {f}")
    elif extra:
        print(f"  EXTRA on HF: {len(extra)} files")

# Verify Source column in languages.tsv metadata
print(f"\n{'='*60}")
print("METADATA PROVENANCE CHECK:")
from huggingface_hub import hf_hub_download
lang_path = hf_hub_download(repo_id=repo, filename="data/training/metadata/languages.tsv", repo_type="dataset")
with open(lang_path, "r", encoding="utf-8") as f:
    lines = f.readlines()
header = lines[0].strip().split("\t")
print(f"  languages.tsv columns: {header}")
print(f"  languages.tsv entries: {len(lines)-1}")
# Check that Sources column exists
if "Sources" in header:
    src_idx = header.index("Sources")
    sources_present = sum(1 for line in lines[1:] if line.strip().split("\t")[src_idx].strip())
    print(f"  Entries with Sources: {sources_present}/{len(lines)-1}")
    if sources_present > 0:
        print(f"  STATUS: PASS")
    else:
        print(f"  STATUS: FAIL - no source data")
else:
    print(f"  STATUS: FAIL - no Sources column")

# Also check Source column in a sample lexicon
print(f"\n{'='*60}")
print("LEXICON PROVENANCE CHECK (Source column in TSVs):")
for iso in ["hit", "ave", "ine-pro", "xlc", "txb"]:
    lex_path = hf_hub_download(repo_id=repo, filename=f"data/training/lexicons/{iso}.tsv", repo_type="dataset")
    with open(lex_path, "r", encoding="utf-8") as f:
        lex_lines = f.readlines()
    lex_header = lex_lines[0].strip().split("\t")
    if "Source" in lex_header:
        src_idx = lex_header.index("Source")
        sources = set()
        for line in lex_lines[1:]:
            parts = line.strip().split("\t")
            if len(parts) > src_idx:
                sources.add(parts[src_idx])
        print(f"  {iso:10s} entries={len(lex_lines)-1:5d}  sources={sources}")
    else:
        print(f"  {iso:10s} FAIL - no Source column")

print(f"\n{'='*60}")
if all_pass:
    print("OVERALL: PASS")
else:
    print("OVERALL: FAIL")