"""
Generate realistic typo-based misspellings from words.txt → misspellings.txt

Colab version
Place words.txt in /content/ before running
"""

import os
import time

# Optional: mount Google Drive if your file is there
# from google.colab import drive
# drive.mount('/content/drive')
# words_path = '/content/drive/MyDrive/words.txt'

words_path = '/content/words.txt'
output_path = '/content/misspellings.txt'

KEYBOARD_NEIGHBORS = {
    'q': 'wa', 'w': 'qeas', 'e': 'wrds', 'r': 'etfs', 't': 'rygs',
    'y': 'tuhs', 'u': 'yijs', 'i': 'uoks', 'o': 'ipls', 'p': 'o',
    'a': 'qwsz', 's': 'awedxz', 'd': 'serfcx', 'f': 'drtgvc',
    'g': 'ftyhbv', 'h': 'gyujnb', 'j': 'huikmn', 'k': 'jiolm',
    'l': 'kop', 'z': 'asx', 'x': 'zsdc', 'c': 'xdfv', 'v': 'cfgb',
    'b': 'vghn', 'n': 'bhjm', 'm': 'njk',
}

def generate_adjacent_swaps(word):
    typos = []
    for i in range(len(word) - 1):
        chars = list(word)
        chars[i], chars[i + 1] = chars[i + 1], chars[i]
        typo = ''.join(chars)
        if typo != word:
            typos.append(typo)
    return typos

def generate_deletions(word):
    typos = []
    for i in range(len(word)):
        typo = word[:i] + word[i + 1:]
        if len(typo) >= 2:
            typos.append(typo)
    return typos

def generate_duplications(word):
    typos = []
    for i in range(len(word)):
        typo = word[:i] + word[i] + word[i:]
        if typo != word:
            typos.append(typo)
    return typos

def generate_nearby_key_subs(word):
    typos = []
    lower = word.lower()
    for i in range(len(word)):
        ch = lower[i]
        if ch in KEYBOARD_NEIGHBORS:
            for neighbor in KEYBOARD_NEIGHBORS[ch]:
                typo = lower[:i] + neighbor + lower[i + 1:]
                if typo != lower:
                    typos.append(typo)
    return typos

def generate_all_typos(word):
    typos = set()
    typos.update(generate_adjacent_swaps(word))
    typos.update(generate_deletions(word))
    typos.update(generate_duplications(word))
    typos.update(generate_nearby_key_subs(word))
    typos.discard(word)
    typos.discard(word.lower())
    return typos

def is_pure_alpha(word):
    return word.isalpha()

# ── Check file ──────────────────────────────────────────────
if not os.path.exists(words_path):
    raise FileNotFoundError(f"{words_path} not found. Upload it to /content/ first.")

print(f"Reading words from: {words_path}")

with open(words_path, 'r', encoding='utf-8', errors='replace') as f:
    raw_words = [line.strip() for line in f if line.strip()]

print(f"Total raw entries: {len(raw_words):,}")

words = [w for w in raw_words if is_pure_alpha(w) and len(w) >= 3]
print(f"Filtered to {len(words):,} alphabetical words (len >= 3)")

start = time.time()
total_typos = 0
batch_size = 10_000

print(f"Generating typos → {output_path}")

with open(output_path, 'w', encoding='utf-8', newline='\n') as out:
    out.write("# Auto-generated misspellings database\n")
    out.write("# Format: misspelling=correction\n\n")

    for idx, word in enumerate(words):
        correction = word
        typos = generate_all_typos(word.lower())

        for typo in sorted(typos):
            out.write(f"{typo}={correction}\n")
            total_typos += 1

        if (idx + 1) % batch_size == 0:
            elapsed = time.time() - start
            pct = (idx + 1) / len(words) * 100
            rate = (idx + 1) / elapsed if elapsed > 0 else 0
            print(f"[{pct:5.1f}%] {idx + 1:,}/{len(words):,} words | "
                  f"{total_typos:,} typos | {rate:.0f} words/sec")

elapsed = time.time() - start
file_size_mb = os.path.getsize(output_path) / (1024 * 1024)

print("\n" + "=" * 60)
print(f"Done in {elapsed:.1f}s")
print(f"Words processed : {len(words):,}")
print(f"Typos generated : {total_typos:,}")
print(f"Output file     : {output_path}")
print(f"File size       : {file_size_mb:.1f} MB")
print("=" * 60)