"""Match unmatched Blue Guide controls against the English PDF."""
import os
import re
import json
import unicodedata
import psycopg2
import urllib.parse

try:
    import fitz
except ImportError:
    print("ERROR: PyMuPDF (fitz) not installed")
    exit(1)

PDF_PATH = os.path.expanduser("~/rag-ingestion/pdfs/blue_guide_2022_en.pdf")

def normalize(s):
    s = s.replace('\u00ad', '').replace('\xad', '')
    s = s.replace('\u200b', '').replace('\u00a0', ' ')
    s = s.replace('\ufb01', 'fi').replace('\ufb02', 'fl')
    s = s.replace('\ufb00', 'ff').replace('\ufb03', 'ffi').replace('\ufb04', 'ffl')
    s = s.replace('\u2019', "'").replace('\u2018', "'")
    s = s.replace('\u201c', '"').replace('\u201d', '"')
    s = s.replace('\u2013', '-').replace('\u2014', '-')
    s = s.replace('\u2022', '-').replace('\u00b7', '-')
    s = re.sub(r'[\x00-\x08\x0b\x0c\x0e-\x1f]', '', s)
    s = unicodedata.normalize('NFC', s)
    s = re.sub(r'\s+', ' ', s)
    return s.strip()

# Read EN PDF
print(f"Reading {PDF_PATH}...")
doc = fitz.open(PDF_PATH)
text = ""
for page in doc:
    text += page.get_text() + "\n"
doc.close()
print(f"  {len(text):,} chars")

text_norm = normalize(text)

# Build article index for EN Blue Guide
# EN Blue Guide uses "Article N" headings (not "Artikel N")
items = []

# Find where "Article 1" starts — content before is preamble/intro
art1_match = re.search(r'\nArticle\s+1\s*\n', text)
if not art1_match:
    # Try section-based structure instead
    print("  No 'Article N' headings found, trying section-based index...")
    for m in re.finditer(r'(?:^|\n)\s*(\d+(?:\.\d+)*)\.\s+[A-Z]', text, re.MULTILINE):
        items.append((m.start(), f"Section {m.group(1)}", "section"))
else:
    art1_pos = art1_match.start()
    # Article headings
    for m in re.finditer(r'(?:^|\n)\s*Article\s+(\d+[a-z]?)\s*\n', text, re.MULTILINE):
        art_num = int(re.match(r'(\d+)', m.group(1)).group(1))
        items.append((m.start(), f"Article {m.group(1)}", "article"))

    # Annex markers
    for m in re.finditer(r'(?:^|\n)\s*ANNEX\s+([IVXLC]+[a-z]?)\b', text, re.MULTILINE):
        items.append((m.start(), f"Annex {m.group(1)}", "annex"))

# Also try numbered section headings as fallback
for m in re.finditer(r'(?:^|\n)\s*(\d+\.\d+(?:\.\d+)?)\s+[A-Z]', text, re.MULTILINE):
    items.append((m.start(), f"Section {m.group(1)}", "section"))

items.sort(key=lambda x: x[0])
seen = set()
unique = []
for pos, label, typ in items:
    if label not in seen:
        seen.add(label)
        unique.append((pos, label, typ))

print(f"  Index: {len(unique)} sections")
if unique[:5]:
    for pos, label, typ in unique[:5]:
        print(f"    {label} [{typ}] @ pos {pos}")

# Precompute normalized positions
index_norm = []
for pos, label, typ in unique:
    norm_pos = len(normalize(text[:pos]))
    index_norm.append((norm_pos, label, typ))

# Connect to DB
db_url = os.environ['DATABASE_URL']
parsed = urllib.parse.urlparse(db_url)
conn = psycopg2.connect(
    host=parsed.hostname, port=parsed.port or 5432,
    user=parsed.username, password=parsed.password,
    dbname=parsed.path.lstrip('/'),
    options="-c search_path=compliance,public"
)
cur = conn.cursor()

# Get Blue Guide controls without article_type (unmatched)
cur.execute("""
    SELECT id, control_id, title, source_original_text,
           source_citation->>'article' as existing_article,
           source_citation->>'article_type' as existing_type,
           release_state
    FROM compliance.canonical_controls
    WHERE source_citation->>'source' = 'EU Blue Guide 2022'
    AND source_original_text IS NOT NULL
    AND length(source_original_text) > 50
    AND (source_citation->>'article_type' IS NULL)
    ORDER BY control_id
""")
controls = cur.fetchall()
print(f"\nUnmatched Blue Guide controls: {len(controls)}")

# Match each control
results = []
found = 0
not_found = 0

for ctrl in controls:
    ctrl_id, control_id, title, orig_text, existing_art, existing_type, state = ctrl
    orig_norm = normalize(orig_text)
    if len(orig_norm) < 30:
        not_found += 1
        continue

    matched = False
    for start_frac in [0.25, 0.1, 0.5, 0.0, 0.75]:
        for length in [80, 60, 40, 30, 20]:
            start = max(0, int(len(orig_norm) * start_frac))
            snippet = orig_norm[start:start+length]
            if not snippet or len(snippet) < 15:
                continue
            pos = text_norm.find(snippet)
            if pos >= 0:
                # Find section
                label = "Unknown"
                typ = "unknown"
                for h_pos, h_label, h_type in reversed(index_norm):
                    if h_pos <= pos:
                        label = h_label
                        typ = h_type
                        break
                results.append({
                    "ctrl_id": str(ctrl_id),
                    "control_id": control_id,
                    "source": "EU Blue Guide 2022",
                    "article_label": label,
                    "article_type": typ,
                })
                found += 1
                is_active = "" if state not in ('duplicate', 'too_close') else " [DUP]"
                print(f"  {control_id:10s}: {label:25s} [{typ:8s}]{is_active}")
                matched = True
                break
        if matched:
            break

    if not matched:
        not_found += 1
        print(f"  {control_id:10s}: NOT FOUND  {title[:50]}")

print(f"\n{'='*50}")
print(f"Results: {found} matched, {not_found} not found out of {len(controls)}")

# Save results
out_path = "/tmp/blue_guide_en_results.json"
with open(out_path, 'w') as f:
    json.dump(results, f, indent=2, ensure_ascii=False)
print(f"Saved to {out_path}")

# Apply results to DB
if results:
    print(f"\nApplying {len(results)} results to DB...")
    applied = 0
    for r in results:
        cur.execute("""
            UPDATE compliance.canonical_controls
            SET source_citation = source_citation ||
                jsonb_build_object('article', %s, 'article_type', %s)
            WHERE id = %s::uuid
            AND (source_citation->>'article' IS DISTINCT FROM %s
                 OR source_citation->>'article_type' IS DISTINCT FROM %s)
        """, (r["article_label"], r["article_type"],
              r["ctrl_id"], r["article_label"], r["article_type"]))
        if cur.rowcount > 0:
            applied += 1
    conn.commit()
    print(f"  Applied: {applied} controls updated")

# Show type distribution
type_counts = {}
for r in results:
    t = r["article_type"]
    type_counts[t] = type_counts.get(t, 0) + 1
if type_counts:
    print(f"\nArticle type distribution:")
    for t, c in sorted(type_counts.items(), key=lambda x: -x[1]):
        print(f"  {t:12s}: {c:5d}")

conn.close()