Update app.py

app.py

@@ -1,45 +1,130 @@
-# debug_which.py
+import itertools
+import math
+import time
+import os
+from multiprocessing import Pool
 from mnemonic import Mnemonic
 from eth_account import Account
-from eth_utils import keccak, to_checksum_address
-import coincurve, hmac, hashlib
 
 Account.enable_unaudited_hdwallet_features()
-phrase = "lesson cushion crane affair federal decline limb spend reunion chief cart zebra"
-TARGET = "0x3f0482fc3e9132c3d3acb5f588e980d7b3a5af07"
-
-# --- Manual BIP32 ---
-_N = 0xFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFEBAAEDCE6AF48A03BBFD25E8CD0364141
-_H = 0x80000000
-def _child(priv, chain, i):
-    if i >= _H:
-        data = b'\x00' + priv + i.to_bytes(4, 'big')
-    else:
-        pub = coincurve.PrivateKey(priv).public_key.format(compressed=True)
-        data = pub + i.to_bytes(4, 'big')
-    I = hmac.new(chain, data, hashlib.sha512).digest()
-    ki = (int.from_bytes(I[:32], 'big') + int.from_bytes(priv, 'big')) % _N
-    return ki.to_bytes(32, 'big'), I[32:]
-
-def seed_to_privkey_hd(seed, idx=0):
-    I = hmac.new(b"Bitcoin seed", seed, hashlib.sha512).digest()
-    key, chain = I[:32], I[32:]
-    for i in [44+_H, 60+_H, _H, 0, idx]:
-        key, chain = _child(key, chain, i)
-    return key
-
-# Test 1: Python mnemonic + manual BIP32
-seed_py = Mnemonic("english").to_seed(phrase, "")
-priv_py = seed_to_privkey_hd(seed_py, 0)
-pub = coincurve.PrivateKey(priv_py).public_key.format(compressed=False)[1:]
-addr_manual = to_checksum_address(keccak(pub)[-20:])
-
-# Test 2: eth_account
-acct = Account.from_mnemonic(phrase, account_path="m/44'/60'/0'/0/0")
-
-print(f"Manual BIP32: {addr_manual}")
-print(f"eth_account:  {acct.address}")
-print(f"Target:       {TARGET}")
-print(f"Manual == Target: {addr_manual.lower() == TARGET}")
-print(f"eth_account == Target: {acct.address.lower() == TARGET}")
-print(f"Manual == eth_account: {addr_manual.lower() == acct.address.lower()}")
+
+# ============================================================
+words = [
+    "lesson", "cushion", "crane", "affair", "federal",
+    "decline", "limb", "spend", "reunion", "chief", "cart", "zebra"
+]
+
+ADDRESSES_FILE = "12730802_addresses.csv"
+NUM_WORKERS = 48
+BATCH_SIZE = 2000
+CHECKSUM_PREFILTER = True    # True = checksum verify (fast filter), False = skip
+# ============================================================
+
+_MNEMONIC = None
+
+def get_mnemonic():
+    global _MNEMONIC
+    if _MNEMONIC is None:
+        _MNEMONIC = Mnemonic("english")
+    return _MNEMONIC
+
+
+def load_addresses(path):
+    """Lowercase, 0x ke baghair, 40-char addresses ka set."""
+    s = set()
+    with open(path, "r", encoding="utf-8") as f:
+        for line in f:
+            a = line.strip().strip('"').strip("'").lstrip("\ufeff").lower()
+            if a.startswith("0x"):
+                a = a[2:]
+            if a and len(a) == 40:
+                s.add(a)
+    return frozenset(s)
+
+
+def normalize(addr):
+    a = addr.strip().lower()
+    if a.startswith("0x"):
+        a = a[2:]
+    return a
+
+
+_KNOWN = None
+
+def init_worker(known):
+    global _KNOWN
+    _KNOWN = known
+    get_mnemonic()       # warm-up
+
+
+def process_batch(batch):
+    hits = []
+    known = _KNOWN
+    mnemo = get_mnemonic()
+    for phrase in batch:
+        if CHECKSUM_PREFILTER and not mnemo.check(phrase):
+            continue
+        try:
+            acct = Account.from_mnemonic(phrase)
+        except Exception:
+            continue
+        if normalize(acct.address) in known:
+            hits.append((phrase, acct.address, acct.key.hex()))
+    return hits
+
+
+def batch_generator():
+    batch = []
+    for perm in itertools.permutations(words):
+        batch.append(" ".join(perm))
+        if len(batch) >= BATCH_SIZE:
+            yield batch
+            batch = []
+    if batch:
+        yield batch
+
+
+def main():
+    if not os.path.exists(ADDRESSES_FILE):
+        raise SystemExit(f"File nahi mili: {ADDRESSES_FILE}")
+
+    total = math.factorial(len(words))   # 479,001,600
+    print(f"\nMode: order (permutations) | Total: {total:,} | Workers: {NUM_WORKERS}")
+    print(f"Batch size: {BATCH_SIZE} | Checksum prefilter: {CHECKSUM_PREFILTER}\n")
+
+    print("Addresses load ho rahe hain...")
+    known = load_addresses(ADDRESSES_FILE)
+    print(f"Loaded {len(known):,} addresses\n")
+
+    matches = []
+    done = 0
+    start = time.time()
+    last_log = start
+
+    with Pool(processes=NUM_WORKERS,
+              initializer=init_worker,
+              initargs=(known,)) as pool:
+        for hits in pool.imap_unordered(process_batch, batch_generator(), chunksize=4):
+            done += BATCH_SIZE
+            for phrase, addr, key in hits:
+                print(f"\n🎉 MATCH FOUND!")
+                print(f"Phrase : {phrase}")
+                print(f"Address: {addr}")
+                print(f"Key    : {key}\n")
+                matches.append((phrase, addr, key))
+
+            now = time.time()
+            if now - last_log >= 5:
+                elapsed = now - start
+                rate = done / elapsed if elapsed else 0
+                eta = (total - done) / rate if rate else 0
+                print(f"  ...{done:,}/{total:,} ({100*done/total:.1f}%)  "
+                      f"{rate:,.0f}/s  ETA {eta/60:.1f}min")
+                last_log = now
+
+    elapsed = time.time() - start
+    print(f"\nDone {elapsed/60:.1f} min. {len(matches)} match(es).")
+
+
+if __name__ == "__main__":
+    main()