"""Analyze a WizTree CSV for VWP app-modernization source-code hunting.

Single streaming pass. Emits:
  - per-category file lists (vb6-source, access-db, crystal-reports, installshield,
    vm-images, source-archives, rar/zip near Darv)
  - all paths whose terminal segment matches Darv/Source/Orders/VWP/Denali
  - a summary table

Run:
  py analyze_wiztree.py <wiztree.csv> <output-dir>
"""
from __future__ import annotations
import csv, os, re, sys
from collections import defaultdict
from pathlib import Path

EXT_CATEGORIES = {
    # VB6 source
    '.vbp': 'vb6-project', '.vbg': 'vb6-project-group', '.vbw': 'vb6-workspace',
    '.frm': 'vb6-form', '.bas': 'vb6-module', '.cls': 'vb6-class',
    '.ctl': 'vb6-usercontrol', '.frx': 'vb6-form-resource', '.ctx': 'vb6-usercontrol-resource',
    # Access
    '.mdb': 'access-mdb', '.accdb': 'access-accdb', '.mde': 'access-mde', '.accde': 'access-accde',
    # Crystal Reports
    '.rpt': 'crystal-report',
    # InstallShield / installers
    '.ism': 'installshield-project', '.isproj': 'installshield-project',
    '.msi': 'installer', '.iss': 'inno-setup-script',
    # VMs
    '.vdi': 'vm-image-vbox', '.vmdk': 'vm-image-vmware', '.vhd': 'vm-image-vhd',
    '.vhdx': 'vm-image-vhdx', '.ova': 'vm-image-ova', '.vbox': 'vm-config-vbox',
    # Archives (interesting near Darv only — handled separately)
    '.zip': 'archive', '.rar': 'archive', '.7z': 'archive', '.tar': 'archive',
    '.gz': 'archive', '.cab': 'archive',
}

# Folder leaf name keywords (lower-case substring match)
FOLDER_KEYWORDS = ('darv', 'source', 'orders', 'vwp', 'denali')

# Archives outside Darv/Source/Orders/VWP context are noise — filter
ARCHIVE_INTEREST_RE = re.compile(r'\\(darv|source|orders|vwp|denali)\\', re.IGNORECASE)


def categorize(path: str) -> str | None:
    p = path.lower()
    # Last char '\' means folder row — handle separately
    if p.endswith('\\'):
        return None
    ext = os.path.splitext(p)[1]
    cat = EXT_CATEGORIES.get(ext)
    if cat is None:
        return None
    if cat == 'archive':
        # Archives only interesting if path contains Darv/Source/Orders/VWP/Denali
        if not ARCHIVE_INTEREST_RE.search(path):
            return None
        return 'archive-near-darv'
    return cat


def is_folder_row(path: str) -> bool:
    return path.endswith('\\')


def folder_keyword_match(path: str) -> str | None:
    # Get terminal segment (strip trailing \, then take last component)
    p = path.rstrip('\\')
    leaf = p.rsplit('\\', 1)[-1].lower()
    for kw in FOLDER_KEYWORDS:
        if kw in leaf:
            return kw
    return None


def main(csv_path: str, out_dir: str) -> int:
    out = Path(out_dir)
    out.mkdir(parents=True, exist_ok=True)

    cat_files: dict[str, list[tuple[int, str, str]]] = defaultdict(list)  # cat -> [(size, modified, path)]
    folder_matches: dict[str, list[tuple[int, int, int, str, str]]] = defaultdict(list)
    # ^ keyword -> [(size_bytes, files, folders, modified, path)]

    seen_rows = 0
    seen_files = 0
    seen_folders = 0

    with open(csv_path, 'r', encoding='utf-8-sig', errors='replace', newline='') as fh:
        reader = csv.reader(fh)
        header_seen = False
        for row in reader:
            seen_rows += 1
            if not row:
                continue
            # Skip donation/banner line if it's not a CSV row
            if len(row) < 2:
                continue
            if not header_seen:
                if row[0].strip().lower().startswith('file name') or row[0].strip().lower() == 'file name':
                    header_seen = True
                    continue
                if row[0].startswith('Generated by'):
                    continue
                # Defensive: maybe first row IS data
                header_seen = True

            path = row[0]
            try:
                size = int(row[1]) if row[1].strip() else 0
            except (ValueError, IndexError):
                size = 0
            modified = row[3] if len(row) > 3 else ''

            if is_folder_row(path):
                seen_folders += 1
                kw = folder_keyword_match(path)
                if kw:
                    try:
                        files = int(row[5]) if len(row) > 5 and row[5].strip() else 0
                        folders = int(row[6]) if len(row) > 6 and row[6].strip() else 0
                    except (ValueError, IndexError):
                        files, folders = 0, 0
                    folder_matches[kw].append((size, files, folders, modified, path))
            else:
                seen_files += 1
                cat = categorize(path)
                if cat:
                    cat_files[cat].append((size, modified, path))

    # Write per-category CSVs
    summary_lines = []
    summary_lines.append(f"# WizTree analysis — {csv_path}")
    summary_lines.append(f"")
    summary_lines.append(f"Rows: {seen_rows:,}  Files: {seen_files:,}  Folders: {seen_folders:,}")
    summary_lines.append(f"")
    summary_lines.append(f"## File matches by category")
    summary_lines.append(f"")
    summary_lines.append(f"| Category | Count | Total MB |")
    summary_lines.append(f"|---|---|---|")
    for cat in sorted(cat_files.keys()):
        rows = cat_files[cat]
        total_mb = sum(r[0] for r in rows) / 1024 / 1024
        summary_lines.append(f"| `{cat}` | {len(rows):,} | {total_mb:,.1f} |")
        # Sort by size descending, write CSV
        rows.sort(key=lambda r: -r[0])
        csv_out = out / f"cat_{cat}.csv"
        with open(csv_out, 'w', encoding='utf-8', newline='') as fout:
            w = csv.writer(fout)
            w.writerow(['size_bytes', 'size_mb', 'modified', 'path'])
            for size, mod, path in rows:
                w.writerow([size, f"{size/1024/1024:.2f}", mod, path])

    summary_lines.append("")
    summary_lines.append(f"## Folder name matches")
    summary_lines.append(f"")
    summary_lines.append(f"| Keyword | Matching folders | Total GB | Total files inside |")
    summary_lines.append(f"|---|---|---|---|")
    for kw in sorted(folder_matches.keys()):
        rows = folder_matches[kw]
        total_gb = sum(r[0] for r in rows) / 1024 / 1024 / 1024
        total_files = sum(r[1] for r in rows)
        summary_lines.append(f"| `{kw}` | {len(rows):,} | {total_gb:,.1f} | {total_files:,} |")
        # Sort by size descending, write CSV
        rows.sort(key=lambda r: -r[0])
        csv_out = out / f"folder_{kw}.csv"
        with open(csv_out, 'w', encoding='utf-8', newline='') as fout:
            w = csv.writer(fout)
            w.writerow(['size_bytes', 'size_gb', 'files_inside', 'folders_inside', 'modified', 'path'])
            for size, files, folders, mod, path in rows:
                w.writerow([size, f"{size/1024/1024/1024:.2f}", files, folders, mod, path])

    summary_path = out / 'SUMMARY.md'
    summary_path.write_text('\n'.join(summary_lines), encoding='utf-8')
    print(summary_path.read_text(encoding='utf-8'))
    print(f"\n[OK] Per-category and per-keyword CSVs written to: {out}")
    return 0


if __name__ == '__main__':
    if len(sys.argv) < 3:
        print("Usage: py analyze_wiztree.py <wiztree.csv> <output-dir>", file=sys.stderr)
        sys.exit(2)
    sys.exit(main(sys.argv[1], sys.argv[2]))