⚡️ Speed up function is_successful by 13% in PR #1505 (test/verify-aws-bedrock-workflow)

[codeflash-ai]

⚡️ This pull request contains optimizations for PR #1505

If you approve this dependent PR, these changes will be merged into the original PR branch test/verify-aws-bedrock-workflow.

This PR will be automatically closed if the original PR is merged.

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📄 13% (0.13x) speedup for is_successful in codeflash/either.py

⏱️ Runtime : 12.1 microseconds → 10.7 microseconds (best of 250 runs)

📝 Explanation and details

The optimization achieves a 13% runtime improvement by replacing the dynamic isinstance(self, Success) check with static method overrides.

Key Changes:

• Result.is_successful() now returns False directly instead of checking isinstance(self, Success)
• Success.is_successful() overrides the base method to return True directly

Why This Is Faster:
The original code performed a runtime type check (isinstance(self, Success)) on every call, which requires:

1. Walking the method resolution order (MRO)
2. Comparing against the Success class
3. Returning the boolean result

The optimized version leverages Python's method dispatch mechanism, which happens once during attribute lookup. When is_successful() is called, Python's vtable-like dispatch directly invokes the appropriate override (Success.is_successful() or Result.is_successful()), eliminating the per-call isinstance overhead.

Performance Impact by Test Case:

• Failure instances: 47.8-57.5% faster - Biggest wins as these frequently checked failure paths no longer need isinstance checks
• Success instances: 4.3-21.7% faster - Still improved by avoiding isinstance overhead
• Base Result instances: 21.7-29.6% faster - Now returns False immediately instead of checking type
• Large-scale tests: Consistent 8-21% improvements across 500-1000 iterations, showing the optimization scales well

Workload Impact:
Based on function_references, is_successful() is called extensively in test detection and optimization workflows (test_unused_helper_revert.py). Since the function appears in critical path testing logic where many Result objects are checked for success/failure status, this optimization provides meaningful improvements to CI/CD and development iteration times. The method is particularly beneficial in loops and bulk operations where thousands of calls accumulate (as demonstrated by the large-scale test showing consistent speedups at 1000 instances).

The optimization maintains identical semantics - subclass polymorphism is preserved, all test cases pass with the same boolean results, and the API remains unchanged.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 32 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Click to see Generated Regression Tests

import pytest  # used for our unit tests
from codeflash.either import Failure, Result, Success, is_successful

def test_success_instance_returns_true():
    # Basic: creating a Success with a typical payload should be reported as successful.
    s = Success("payload")  # construct a real Success instance with a normal string value
    # the module-level helper should return True for Success
    codeflash_output = is_successful(s) # 481ns -> 461ns (4.34% faster)
    # and the instance method should also return True (consistency check)
    codeflash_output = s.is_successful() # 280ns -> 230ns (21.7% faster)

def test_failure_instance_returns_false():
    # Basic: creating a Failure with a typical payload should be reported as not successful.
    f = Failure("error")  # construct a real Failure instance with a normal string value
    # the module-level helper should return False for Failure
    codeflash_output = is_successful(f) # 742ns -> 471ns (57.5% faster)
    # and the instance method should also return False (consistency check)
    codeflash_output = f.is_successful() # 340ns -> 230ns (47.8% faster)

def test_base_result_instance_is_not_successful():
    # Edge: a plain Result (not a Success subclass) should not be considered successful.
    r = Result("neutral")  # create a base Result instance directly
    # The helper should return False because Result is not a Success instance.
    codeflash_output = is_successful(r) # 561ns -> 461ns (21.7% faster)
    # The instance method should mirror the behavior.
    codeflash_output = r.is_successful() # 311ns -> 240ns (29.6% faster)

def test_success_with_various_falsy_values_still_successful():
    # Edge: Success should report True even when holding values that are falsy (None, 0, '', False, [])
    falsy_values = [None, 0, "", False, []]
    for v in falsy_values:
        s = Success(v)  # construct Success with each falsy value
        # is_successful should still return True for Success wrappers of falsy payloads
        codeflash_output = is_successful(s) # 1.29μs -> 1.19μs (8.21% faster)
        codeflash_output = s.is_successful()

def test_failure_with_various_falsy_values_still_not_successful():
    # Edge: Failure should report False even when holding falsy values.
    falsy_values = [None, 0, "", False, []]
    for v in falsy_values:
        f = Failure(v)  # construct Failure with each falsy value
        codeflash_output = is_successful(f) # 1.46μs -> 1.21μs (20.6% faster)
        codeflash_output = f.is_successful()

def test_non_result_inputs_raise_attribute_error():
    # Edge: Passing an object that does not implement is_successful should raise AttributeError
    with pytest.raises(AttributeError):
        # integers do not have an is_successful method; the helper will attempt to call it.
        is_successful(42) # 2.42μs -> 2.48μs (2.42% slower)
    with pytest.raises(AttributeError):
        # None also lacks an is_successful attribute
        is_successful(None) # 1.40μs -> 1.41μs (0.778% slower)

def test_method_and_function_consistency_over_many_instances():
    # Large-scale: create many Success and Failure instances and verify the helper and method agree.
    n = 500  # moderate large-scale count (keeps test fast but exercises loops)
    instances = []
    expected = []
    for i in range(n):
        if i % 3 == 0:
            inst = Success(i)  # every third is Success
            expected.append(True)
        else:
            inst = Failure(i)  # others are Failure
            expected.append(False)
        instances.append(inst)

    # Verify element-wise that both the helper and instance method produce the same expected boolean.
    results_helper = [is_successful(x) for x in instances]
    results_method = [x.is_successful() for x in instances]

def test_large_scale_alternating_1000_instances_performance_and_correctness():
    # Large-scale: create 1000 alternating Success/Failure instances to check scalability and correctness.
    n = 1000
    instances = [Success(i) if i % 2 == 0 else Failure(i) for i in range(n)]
    # Expected booleans: True for even indices, False for odd indices
    expected = [i % 2 == 0 for i in range(n)]
    # Compute results using the helper function
    results = [is_successful(obj) for obj in instances]

def test_success_with_large_payload_still_successful():
    # Large-scale: use a very large payload to ensure value handling does not affect success detection.
    large_payload = "x" * 100_000  # 100k characters string
    s = Success(large_payload)
    codeflash_output = is_successful(s) # 571ns -> 511ns (11.7% faster)
    codeflash_output = s.is_successful() # 290ns -> 241ns (20.3% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-pr1505-2026-02-17T15.01.13 and push.