⚡️ Speed up method PositionalArg.__hash__ by 9%

[codeflash-ai]

📄 9% (0.09x) speedup for PositionalArg.__hash__ in src/uberjob/graph.py

⏱️ Runtime : 117 microseconds → 107 microseconds (best of 206 runs)

📝 Explanation and details

The optimization applies two key improvements to the PositionalArg class:

1. Added __slots__ = ("index",) declaration:
This restricts the class to only store the index attribute, eliminating the default __dict__ that Python creates for each instance. This reduces memory overhead per object and slightly improves attribute access speed.

2. Simplified __hash__ method:
Changed from return hash(self.index) to return self.index. Since integers are already their own hash values in Python (hash(42) == 42), calling the hash() function is redundant overhead. The optimized version directly returns the integer, eliminating the function call.

Performance Impact:
The line profiler shows the __hash__ method improvement clearly - execution time per call dropped from 222ns to 180.4ns (about 19% faster per hash operation). With 10,117 hash calls in the profile, this micro-optimization compounds to measurable savings. The overall 9% speedup demonstrates that even small optimizations matter when methods are called frequently.

Why This Matters:
Hash operations are critical for dictionary lookups and set membership tests. Since PositionalArg objects are likely used as keys or stored in sets within the uberjob graph processing system, any hash performance improvement directly benefits graph operations. The __slots__ optimization provides additional memory efficiency that scales with the number of PositionalArg instances created.

These optimizations are most effective for workloads that create many PositionalArg instances or perform frequent hash-based operations on them, which appears to be the case based on the high hit count in the profiler results.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 3 Passed
⏪ Replay Tests	✅ 510 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest  # used for our unit tests
from uberjob.graph import PositionalArg


# function to test
class Dependency:
    pass


def repr_helper(obj, *args):
    return f"{obj.__class__.__name__}({', '.join(repr(arg) for arg in args)})"


from uberjob.graph import PositionalArg

# unit tests

# 1. Basic Test Cases


def test_hash_edge_min_max_int():
    # Test with Python's min and max int (Python ints are arbitrary precision)
    min_index = -(2**100)
    max_index = 2**100


def test_hash_edge_hash_collision():
    # Test with two indices that have the same hash (rare, but possible)
    # For 32-bit hash, hash(1) == hash(1+2**32) on some platforms
    # We'll check for a collision by searching a small range
    found_collision = False
    base = 123456
    for offset in range(1, 1000):
        if hash(base) == hash(base + offset):
            arg1 = PositionalArg(base)
            arg2 = PositionalArg(base + offset)
            found_collision = True
            break
    # It's possible to not find a collision, so we don't fail if none found

from uberjob.graph import PositionalArg


def test_PositionalArg___hash__():
    PositionalArg.__hash__(PositionalArg(0))

⏪ Replay Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_pytest_teststest_plan_py_teststest_render_py_teststest_scheduler_py_teststest_unpack_py__replay_test_0.py::test_uberjob_graph_PositionalArg___hash__	57.3μs	53.4μs	7.28%✅
test_pytest_teststest_registry_py_teststest_version_py_teststest_progress_py_teststest_atoms_py__replay_test_0.py::test_uberjob_graph_PositionalArg___hash__	59.1μs	53.0μs	11.4%✅

To edit these changes git checkout codeflash/optimize-PositionalArg.__hash__-mi5vheb4 and push.