⚡️ Speed up method Transaction.output_value by 6%

[codeflash-ai]

📄 6% (0.06x) speedup for Transaction.output_value in electrum/transaction.py

⏱️ Runtime : 189 microseconds → 178 microseconds (best of 9 runs)

📝 Explanation and details

The optimized code implements two key optimizations that provide a 6% performance improvement:

1. Local Variable Caching in outputs() Method
The original code directly returns self._outputs after checking if it's None and deserializing if needed. The optimized version caches self._outputs in a local variable outputs, checks the local copy, and returns the local reference. This eliminates redundant attribute lookups on self._outputs, which in Python involve dictionary lookups that are more expensive than local variable access.

2. Memory-Efficient Hex Conversion
In the constructor, when handling bytes or bytearray input, the original code calls .hex() directly on the raw bytes. The optimized version wraps the bytes in a memoryview() before calling .hex(), which creates a zero-copy view of the data and can be more memory-efficient for large byte arrays.

Performance Analysis from Test Results:
The optimizations show consistent improvements across all test cases:

• Single output cases: 6-13% faster
• Multiple outputs: 5-17% faster
• Large-scale tests (1000 outputs): 3-7% faster
• Edge cases with special values: 5-13% faster

The local variable optimization is particularly effective because outputs() is called frequently in Bitcoin transaction processing, and each call previously required multiple attribute lookups. The test results show that even simple cases like single outputs benefit significantly (13% improvement), while complex scenarios with many outputs still see meaningful gains (3-7%).

These micro-optimizations are valuable in cryptocurrency applications where transaction processing performance directly impacts user experience, especially when handling large transaction volumes or complex multi-output transactions.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 44 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from typing import List, Optional, Sequence

# imports
import pytest
from electrum.transaction import Transaction


# Minimal stubs for dependencies
class SerializationError(Exception):
    pass

# ----------- UNIT TESTS ------------

# Helper to construct a serialized transaction hex string for testing
def make_tx_hex(version, n_inputs, n_outputs, output_values, locktime=0):
    # version (4 bytes LE)
    parts = [version.to_bytes(4, 'little')]
    # n_inputs (1 byte)
    parts.append(n_inputs.to_bytes(1, 'little'))
    # For each input: just 1 byte dummy (not parsed)
    for _ in range(n_inputs):
        parts.append(b'\x00')
    # n_outputs (1 byte)
    parts.append(n_outputs.to_bytes(1, 'little'))
    # For each output: value (8 bytes LE)
    for v in output_values:
        parts.append(v.to_bytes(8, 'little'))
    # locktime (4 bytes LE)
    parts.append(locktime.to_bytes(4, 'little'))
    # Concatenate and return hex string
    return b''.join(parts).hex()

# ----------- BASIC TEST CASES ------------

def test_single_output():
    # Test with one output of value 5000
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=1, output_values=[5000])
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()  # Should match the single output value

def test_multiple_outputs():
    # Test with three outputs
    values = [100, 200, 300]
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=3, output_values=values)
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()  # Should sum all output values

def test_zero_output_value():
    # Test with an output value of zero
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=2, output_values=[0, 1234])
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()  # Should sum correctly even with zero

def test_all_zero_outputs():
    # Test with all outputs having value zero
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=3, output_values=[0, 0, 0])
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()  # Should be zero

# ----------- EDGE TEST CASES ------------

def test_maximum_output_value():
    # Test with maximum 64-bit unsigned integer value
    max_val = 2**64 - 1
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=1, output_values=[max_val])
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()

def test_large_output_values_sum():
    # Test with two large values that sum to less than 2**64
    v1 = 2**63
    v2 = 2**63 - 1
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=2, output_values=[v1, v2])
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value()

def test_no_outputs_raises():
    # Test with zero outputs (should raise SerializationError)
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=0, output_values=[])
    tx = Transaction(tx_hex)
    with pytest.raises(SerializationError):
        tx.output_value()

def test_no_inputs_raises():
    # Test with zero inputs (should raise SerializationError)
    tx_hex = make_tx_hex(version=2, n_inputs=0, n_outputs=1, output_values=[123])
    tx = Transaction(tx_hex)
    with pytest.raises(SerializationError):
        tx.output_value()

def test_invalid_hex_string_raises():
    # Test with invalid hex string (should raise AssertionError)
    with pytest.raises(AssertionError):
        Transaction("nothexstring")

def test_none_raw_transaction():
    # Test with None as raw transaction (should return 0)
    tx = Transaction(None)
    codeflash_output = tx.output_value()  # No outputs

def test_bytes_raw_transaction():
    # Test with bytes input
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=2, output_values=[10, 20])
    tx_bytes = bytes.fromhex(tx_hex)
    tx = Transaction(tx_bytes)
    codeflash_output = tx.output_value()

def test_extra_junk_raises():
    # Test with extra bytes at the end (should raise SerializationError)
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=1, output_values=[1])
    tx_hex_junk = tx_hex + "abcd"  # Add extra junk
    tx = Transaction(tx_hex_junk)
    with pytest.raises(SerializationError):
        tx.output_value()

def test_negative_output_value():
    # Test with negative output value (should handle as unsigned, so negative not possible)
    # But our stub does not allow negative values in bytes
    pass  # Not applicable with our stub; in real code, negative values would not be possible

def test_empty_string_raw_transaction():
    # Test with empty string as raw transaction (should raise AssertionError)
    with pytest.raises(AssertionError):
        Transaction("")

# ----------- LARGE SCALE TEST CASES ------------




def test_outputs_called_twice_consistent():
    # Test that calling output_value twice returns the same result
    values = [100, 200, 300]
    tx_hex = make_tx_hex(version=2, n_inputs=1, n_outputs=3, output_values=values)
    tx = Transaction(tx_hex)
    codeflash_output = tx.output_value(); v1 = codeflash_output
    codeflash_output = tx.output_value(); v2 = codeflash_output
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from typing import List, Optional, Sequence

# imports
import pytest  # used for our unit tests
from electrum.transaction import Transaction


class BCDataStream:
    """Minimal stub for BCDataStream to allow parsing."""
    def __init__(self):
        self.input = b''
        self.read_cursor = 0

    def write(self, data):
        self.input = data
        self.read_cursor = 0

    def read_int32(self):
        # Read 4 bytes as little-endian int32
        val = int.from_bytes(self.input[self.read_cursor:self.read_cursor+4], 'little')
        self.read_cursor += 4
        return val

    def read_compact_size(self):
        # Read 1 byte as compact size (for simplicity)
        val = self.input[self.read_cursor]
        self.read_cursor += 1
        return val

    def read_bytes(self, n):
        val = self.input[self.read_cursor:self.read_cursor+n]
        self.read_cursor += n
        return val

    def read_uint32(self):
        # Read 4 bytes as little-endian uint32
        val = int.from_bytes(self.input[self.read_cursor:self.read_cursor+4], 'little')
        self.read_cursor += 4
        return val

    def can_read_more(self):
        return self.read_cursor < len(self.input)

class TxOutput:
    def __init__(self, value):
        self.value = value

# --- Unit tests ---

# Basic Test Cases

def test_output_value_single_output():
    # Test with a single output of value 1
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(1)]
    codeflash_output = tx.output_value() # 2.37μs -> 2.10μs (13.0% faster)

def test_output_value_multiple_outputs():
    # Test with multiple outputs
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(1), TxOutput(2), TxOutput(3)]
    codeflash_output = tx.output_value() # 1.93μs -> 1.76μs (9.77% faster)

def test_output_value_zero_outputs():
    # Test with no outputs (should sum to 0)
    tx = Transaction.__new__(Transaction)
    tx._outputs = []
    codeflash_output = tx.output_value() # 1.55μs -> 1.40μs (10.9% faster)

def test_output_value_mixed_values():
    # Test with mixed positive and zero values
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(0), TxOutput(5), TxOutput(10)]
    codeflash_output = tx.output_value() # 1.74μs -> 1.64μs (5.78% faster)

def test_output_value_negative_value():
    # Test with a negative output value (should sum correctly)
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(-1), TxOutput(2)]
    codeflash_output = tx.output_value() # 1.76μs -> 1.65μs (6.42% faster)

# Edge Test Cases

def test_output_value_large_integer():
    # Test with very large output values
    large_value = 2**63
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(large_value), TxOutput(1)]
    codeflash_output = tx.output_value() # 2.15μs -> 1.92μs (11.9% faster)

def test_output_value_all_zero_outputs():
    # All outputs zero
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(0), TxOutput(0), TxOutput(0)]
    codeflash_output = tx.output_value() # 1.78μs -> 1.52μs (17.0% faster)


def test_output_value_non_integer_values():
    # Output values are floats
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(1.5), TxOutput(2.5)]
    codeflash_output = tx.output_value() # 2.67μs -> 2.54μs (4.99% faster)

def test_output_value_large_number_of_outputs():
    # Edge: many outputs, each value 1
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(1) for _ in range(1000)]
    codeflash_output = tx.output_value() # 32.4μs -> 30.2μs (7.02% faster)

def test_output_value_outputs_with_max_int():
    # Edge: output value is sys.maxsize
    import sys
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(sys.maxsize)]
    codeflash_output = tx.output_value() # 1.94μs -> 1.81μs (6.89% faster)

def test_output_value_outputs_with_min_int():
    # Edge: output value is -sys.maxsize-1
    import sys
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(-sys.maxsize-1)]
    codeflash_output = tx.output_value() # 1.85μs -> 1.64μs (13.5% faster)

def test_output_value_outputs_with_non_numeric_value():
    # Edge: output value is not a number, should raise TypeError
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput("not_a_number")]
    with pytest.raises(TypeError):
        tx.output_value() # 3.46μs -> 3.20μs (7.93% faster)

def test_output_value_outputs_with_none_value():
    # Edge: output value is None, should raise TypeError
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(None)]
    with pytest.raises(TypeError):
        tx.output_value() # 3.15μs -> 2.99μs (5.32% faster)

# Large Scale Test Cases

def test_output_value_large_scale_sum():
    # Test with 1000 outputs of value 2
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(2) for _ in range(1000)]
    codeflash_output = tx.output_value() # 32.4μs -> 30.3μs (6.83% faster)

def test_output_value_large_scale_mixed_values():
    # Test with 500 outputs of 1, 500 outputs of 3
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(1) for _ in range(500)] + [TxOutput(3) for _ in range(500)]
    codeflash_output = tx.output_value() # 32.3μs -> 30.6μs (5.69% faster)

def test_output_value_large_scale_negative_values():
    # Test with 500 outputs of -1, 500 outputs of 2
    tx = Transaction.__new__(Transaction)
    tx._outputs = [TxOutput(-1) for _ in range(500)] + [TxOutput(2) for _ in range(500)]
    codeflash_output = tx.output_value() # 31.7μs -> 30.7μs (3.36% faster)


def test_output_value_performance_large_scale():
    # Large scale performance: 999 outputs of random values
    import random
    tx = Transaction.__new__(Transaction)
    values = [random.randint(0, 1000000) for _ in range(999)]
    tx._outputs = [TxOutput(v) for v in values]
    codeflash_output = tx.output_value() # 33.9μs -> 31.8μs (6.51% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from electrum.transaction import Transaction
import pytest

def test_Transaction_output_value():
    with pytest.raises(SerializationError, match="a\\ bytes\\-like\\ object\\ is\\ required,\\ not\\ 'SymbolicByteArray'"):
        Transaction.output_value(Transaction(b''))

To edit these changes git checkout codeflash/optimize-Transaction.output_value-mhooc6ci and push.