tzmerkle 0.1.2

A Merkle tree implementation for Tezos

tzmerkle

A Merkle tree implementation for Tezos blockchain applications.

Features

• 🔐 Multiple hash functions (SHA256, SHA512, SHA3, BLAKE2b, Keccak)
• 🎯 Tezos-native support with Michelson type encoding
• 🔗 SmartPy integration for on-chain verification
• 💾 Serialization support for tree persistence
• ✅ Fully typed with comprehensive type hints

Installation

pip install tzmerkle

For development:

pip install -e ".[dev]"

Quick Start

from tzmerkle import MerkleTree
from tzmerkle.hashes import sha256

# Create a tree for natural numbers
tree = MerkleTree("nat", hash_fn=sha256)

# Add leaves
tree.add_leaves([1, 2, 3, 4, 5])

# Build the tree
tree.build()

# Get the root hash
root = tree.merkle_root
print(f"Root: {root.hex()}")

# Generate a proof for a leaf
encoded_leaf = tree.encode_raw_leaf(3)
proof = tree.get_proof(encoded_leaf)
print(f"Proof length: {len(proof)}")

Usage Examples

Working with Different Types

from tzmerkle import MerkleTree

# String type
tree = MerkleTree("string")
tree.add_leaves(["alice", "bob", "charlie"])
tree.build()

# Complex types (pairs)
tree = MerkleTree("pair nat string")
tree.add_leaves([
    (1, "alice"),
    (2, "bob"),
    (3, "charlie")
])
tree.build()

Using Different Hash Functions

from tzmerkle import MerkleTree
from tzmerkle.hashes import blake2b, sha512, keccak

# BLAKE2b
tree = MerkleTree("nat", hash_fn=blake2b)

# SHA512
tree = MerkleTree("nat", hash_fn=sha512)

# Keccak (Ethereum-compatible)
tree = MerkleTree("nat", hash_fn=keccak)

Proof Generation and Verification

from tzmerkle import MerkleTree

tree = MerkleTree("nat")
tree.add_leaves(list(range(100)))
tree.build()

# Get proof for a specific leaf
leaf_value = 42
encoded_leaf = tree.encode_raw_leaf(leaf_value)
proof = tree.get_proof(encoded_leaf)

print(f"Proof size: {len(proof)} hashes")
print(f"Root: {tree.merkle_root.hex()}")

SmartPy Integration

import smartpy as sp
from tzmerkle import MerkleTree
from tzmerkle.hashes import sha256
from tzmerkle.smartpy.merkle_utils import verify_merkle_proof

# Use in SmartPy contract
@sp.module
def my_module():
    import verify_merkle_proof

    class MyContract(sp.Contract):
        def __init__(self, merkle_root):
            self.data.merkle_root = merkle_root

        @sp.entrypoint
        def verify(self, leaf: sp.bytes, proof: sp.list[sp.bytes]):
            assert self.data.merkle_root == verify_merkle_proof.sha256(sp.record(
                leaf=leaf,
                proof=proof
            ))

@sp.add_test()
def _():
    s = sp.test_scenario("/tmp/test")

    # Create and build tree
    tree = MerkleTree("nat", hash_fn=sha256)
    tree.add_leaves([1, 2, 3, 4])
    tree.build()

    c = my_module.MyContract(tree.merkle_root_spy)

    s += c

    leaf_raw = 1
    encoded_leaf = tree.encode_raw_leaf(leaf_raw)
    proof_spy = tree.get_proof_spy(encoded_leaf)
    c.verify(sp.record(leaf=tree.encode_raw_leaf_spy(leaf_raw), proof=proof_spy))

Serialization and Persistence

from tzmerkle import MerkleTree
from pathlib import Path

# Create and save tree
tree = MerkleTree("nat")
tree.add_leaves(range(1000))
tree.build()

# Save with tree structure for fast loading
tree.serialise("tree.json", include_tree=True, include_proofs=True)

# Load from file
loaded_tree = MerkleTree.from_file("tree.json")
print(f"Loaded {len(loaded_tree._leaves)} leaves")
print(f"Root matches: {loaded_tree.merkle_root == tree.merkle_root}")

Error Handling

from tzmerkle import (
    MerkleTree,
    EmptyTreeError,
    TreeNotBuiltError,
    LeafNotFoundError,
    InvalidLeafError
)

tree = MerkleTree("nat")

# Proper error handling
try:
    tree.build()
except EmptyTreeError:
    print("Add leaves before building!")

try:
    root = tree.merkle_root
except TreeNotBuiltError:
    print("Build tree first!")

tree.add_leaves([1, 2, 3])
tree.build()

try:
    encoded = tree.encode_raw_leaf(999)
    proof = tree.get_proof(encoded)
except LeafNotFoundError:
    print("Leaf not in tree!")

API Reference

MerkleTree

Constructor

MerkleTree(leaf_type: str, hash_fn: TezosHash = sha256)

Create a new Merkle tree.

• leaf_type: Michelson type string (e.g., "nat", "string", "pair nat string")
• hash_fn: Hash function from tzmerkle.hashes

Methods

• add_leaf(leaf) - Add a single leaf (auto-encoded)
• add_leaves(leaves) - Add multiple leaves (auto-encoded)
• add_encoded_leaf(leaf: bytes) - Add pre-encoded leaf
• add_encoded_leaves(leaves: List[bytes]) - Add pre-encoded leaves
• encode_raw_leaf(leaf) -> bytes - Encode a leaf to bytes
• build() - Build the Merkle tree
• get_proof(leaf: bytes) -> List[bytes] - Generate proof for a leaf
• serialise(path, include_tree=False, include_proofs=False) - Save to file
• from_file(path) -> MerkleTree - Load from file (class method)

Properties

• merkle_root: bytes - Get the root hash
• merkle_root_spy: sp.bytes - Get root for SmartPy

Hash Functions

All hash functions follow the same interface:

from tzmerkle.hashes import sha256, sha512, sha3, blake2b, keccak

# Use as function
digest = sha256(b"data")

# Get hex digest
hex_digest = sha256.hexdigest(b"data")

# Properties
print(sha256.name)          # "sha256"
print(sha256.digest_size)   # 32

Exceptions

• MerkleTreeError - Base exception
• EmptyTreeError - Tree has no leaves
• TreeNotBuiltError - Tree not calculated yet
• LeafNotFoundError - Leaf not in tree
• InvalidLeafError - Invalid leaf data or encoding

Development

Setup

# Clone the repository
git clone https://github.com/objkt-com/tzmerkle.git
cd tzmerkle

# Install with dev dependencies
pip install -e ".[dev]"

Running Tests

# Run all tests
pytest

# With coverage
pytest --cov=tzmerkle --cov-report=html

# Verbose output
pytest -v

Code Quality

# Format code
black tzmerkle tests

# Lint
flake8 tzmerkle tests

Performance

Benchmark results for various tree sizes:

Operation	100 leaves	1,000 leaves	10,000 leaves
Build tree	5ms	50ms	520ms
Get proof	<1ms	<1ms	<1ms
Verify proof	<1ms	<1ms	<1ms

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit a pull request

Credits

Developed by objkt.com for the Tezos ecosystem.

Links

• GitHub Repository
• Issue Tracker
• PyPI Package