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| from typing import Protocol, runtime_checkable
from abc import ABC, abstractmethod
import pickle
from pathlib import Path
@runtime_checkable
class MerkleProtocol(Protocol):
"""Protocol defining Merkle Tree interface"""
@abstractmethod
def root(self) -> bytes:
"""Get root hash"""
pass
@abstractmethod
def insert(self, data: bytes) -> int:
"""Insert data and return index"""
pass
@abstractmethod
def get_proof(self, index: int) -> List[bytes]:
"""Get inclusion proof for index"""
pass
@abstractmethod
def verify(self, data: bytes, proof: List[bytes]) -> bool:
"""Verify data with proof"""
pass
class ProductionMerkleSystem:
"""
Production-ready Merkle Tree system with:
- Persistence
- Cache
- Monitoring
- Fault tolerance
"""
def __init__(self,
storage_path: Path,
cache_size: int = 10000,
backup_interval: int = 3600):
self.storage_path = storage_path
self.cache = LRUCache(cache_size)
self.backup_interval = backup_interval
self.metrics = {
'inserts': 0,
'proofs_generated': 0,
'verifications': 0,
'cache_hits': 0,
'cache_misses': 0
}
storage_path.mkdir(parents=True, exist_ok=True)
self.tree = self._load_or_create_tree()
self._start_backup_scheduler()
def _load_or_create_tree(self) -> MerkleTree:
"""Load existing tree or create new one"""
tree_file = self.storage_path / 'tree_state.pkl'
if tree_file.exists():
try:
with open(tree_file, 'rb') as f:
return pickle.load(f)
except Exception as e:
print(f"Failed to load tree: {e}. Creating new tree.")
return MerkleTree([b'initial'])
def _start_backup_scheduler(self):
"""Start periodic backup"""
import threading
def backup_task():
while True:
time.sleep(self.backup_interval)
self._backup_tree()
thread = threading.Thread(target=backup_task, daemon=True)
thread.start()
def _backup_tree(self):
"""Backup tree state"""
backup_file = self.storage_path / f'backup_{int(time.time())}.pkl'
try:
with open(backup_file, 'wb') as f:
pickle.dump(self.tree, f)
backups = sorted(self.storage_path.glob('backup_*.pkl'))
for old_backup in backups[:-10]:
old_backup.unlink()
except Exception as e:
print(f"Backup failed: {e}")
def insert_data(self, data: bytes) -> Dict[str, Any]:
"""Insert data with monitoring and caching"""
start_time = time.time()
current_leaves = self.tree.leaves.copy()
current_leaves.append(data)
new_tree = MerkleTree([leaf.data for leaf in current_leaves if leaf.data])
old_root = self.tree.root.hash
self.tree = new_tree
new_index = len(current_leaves) - 1
proof = self.tree.get_proof(new_index)
self.cache[new_index] = {
'data': data,
'proof': proof,
'timestamp': time.time()
}
self.metrics['inserts'] += 1
return {
'index': new_index,
'root': self.tree.root.hash.hex(),
'old_root': old_root.hex(),
'proof': proof,
'processing_time': time.time() - start_time
}
def get_proof_cached(self, index: int) -> Optional[Dict]:
"""Get proof with cache lookup"""
self.metrics['proofs_generated'] += 1
if index in self.cache:
self.metrics['cache_hits'] += 1
return self.cache[index]
self.metrics['cache_misses'] += 1
if 0 <= index < len(self.tree.leaves):
proof = self.tree.get_proof(index)
result = {
'data': self.tree.leaves[index].data,
'proof': proof,
'timestamp': time.time()
}
self.cache[index] = result
return result
return None
def get_metrics(self) -> Dict:
"""Get system metrics"""
return {
**self.metrics,
'tree_size': len(self.tree.leaves),
'cache_size': len(self.cache),
'storage_path': str(self.storage_path)
}
def verify_data(self, data: bytes, proof: List[bytes],
expected_root: bytes = None) -> bool:
"""Verify data with proof"""
self.metrics['verifications'] += 1
if expected_root is None:
expected_root = self.tree.root.hash
leaf_hash = sha256(data).digest()
return MerkleTree.verify_proof(
leaf_hash,
[(h, 'right') for h in proof],
expected_root,
sha256
)
if __name__ == "__main__":
system = ProductionMerkleSystem(Path('./merkle_storage'))
for i in range(100):
data = f"Transaction {i}: {random.randint(1, 1000)}".encode()
result = system.insert_data(data)
print(f"Inserted: {result['index']}, Root: {result['root'][:16]}...")
proof_data = system.get_proof_cached(42)
if proof_data:
print(f"Data: {proof_data['data'][:50]}...")
print(f"Proof length: {len(proof_data['proof'])} hashes")
is_valid = system.verify_data(
proof_data['data'],
proof_data['proof']
)
print(f"Verification: {'PASS' if is_valid else 'FAIL'}")
metrics = system.get_metrics()
print(f"\nSystem Metrics:")
for key, value in metrics.items():
print(f" {key}: {value}")
|