⚡️ Speed up method Representation.__repr__ by 25%

[codeflash-ai]

📄 25% (0.25x) speedup for Representation.__repr__ in pydantic/_internal/_repr.py

⏱️ Runtime : 1.67 microseconds → 1.33 microsecond (best of 414 runs)

📝 Explanation and details

To optimize the provided Representation class for faster execution, we'll streamline some of the generator expressions and function calls that could be causing unnecessary overhead. One major change is to cache the result of self.__repr_args__() since it's called multiple times. We'll store it in a variable to avoid recomputing it, which will save time. We'll also simplify string join operations to make them more efficient.

Here is the optimized version.

Key optimizations.

1. Cache the result of self.__repr_args__() in __repr_str__ to avoid multiple calls.
2. Simplify the string join process within __repr_str__ by using a list and join method.
3. Remove unnecessary generator expressions to reduce overhead.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 29 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	✅ 1 Passed
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

import typing
from typing import Any

# imports
import pytest  # used for our unit tests
from pydantic._internal._repr import Representation

# unit tests

# Basic Functionality
def test_single_attribute():
    class SingleAttr(Representation):
        __slots__ = ['attr1']
        def __init__(self, attr1):
            self.attr1 = attr1

    instance = SingleAttr(attr1='value')

def test_multiple_attributes():
    class MultiAttr(Representation):
        __slots__ = ['attr1', 'attr2']
        def __init__(self, attr1, attr2):
            self.attr1 = attr1
            self.attr2 = attr2

    instance = MultiAttr(attr1='value1', attr2='value2')

# Edge Cases
def test_no_attributes():
    class NoAttr(Representation):
        pass

    instance = NoAttr()

def test_dynamic_attributes():
    class DynamicAttr(Representation):
        pass

    instance = DynamicAttr()
    instance.attr1 = 'value1'
    instance.attr2 = 'value2'

def test_special_characters_in_attributes():
    class SpecialCharAttr(Representation):
        __slots__ = ['attr1']
        def __init__(self, attr1):
            self.attr1 = attr1

    instance = SpecialCharAttr(attr1='value\nwith\nnewlines')

# Integration with Libraries
def test_pretty_print():
    class DevToolsAttr(Representation):
        __slots__ = ['attr1', 'attr2']
        def __init__(self, attr1, attr2):
            self.attr1 = attr1
            self.attr2 = attr2

    instance = DevToolsAttr(attr1='value1', attr2='value2')

def test_rich_repr():
    class RichAttr(Representation):
        __slots__ = ['attr1', 'attr2']
        def __init__(self, attr1, attr2):
            self.attr1 = attr1
            self.attr2 = attr2

    instance = RichAttr(attr1='value1', attr2='value2')

# Performance and Scalability
def test_large_number_of_attributes():
    class LargeAttr(Representation):
        __slots__ = [f'attr{i}' for i in range(1000)]
        def __init__(self, **kwargs):
            for key, value in kwargs.items():
                setattr(self, key, value)

    instance = LargeAttr(**{f'attr{i}': i for i in range(1000)})

def test_large_data_in_attributes():
    class LargeDataAttr(Representation):
        __slots__ = ['attr1']
        def __init__(self, attr1):
            self.attr1 = attr1

    large_data = 'a' * 10000
    instance = LargeDataAttr(attr1=large_data)

# Error Handling
def test_invalid_attribute_names():
    class InvalidAttr(Representation):
        __slots__ = ['attr_with_spaces']
        def __init__(self, attr_with_spaces):
            self.attr_with_spaces = attr_with_spaces

    instance = InvalidAttr(attr_with_spaces='value')


def test_nested_instances():
    class NestedAttr(Representation):
        __slots__ = ['attr1', 'attr2']
        def __init__(self, attr1, attr2):
            self.attr1 = attr1
            self.attr2 = attr2

    class SingleAttr(Representation):
        __slots__ = ['attr1']
        def __init__(self, attr1):
            self.attr1 = attr1

    nested_instance = SingleAttr(attr1='nested')
    instance = NestedAttr(attr1=nested_instance, attr2='value2')

def test_collections_as_attributes():
    class CollectionAttr(Representation):
        __slots__ = ['attr1', 'attr2']
        def __init__(self, attr1, attr2):
            self.attr1 = attr1
            self.attr2 = attr2

    instance_list = CollectionAttr(attr1=[1, 2, 3], attr2='value2')

    instance_dict = CollectionAttr(attr1={'key': 'value'}, attr2='value2')

# Mocks for Side Effects
def test_mock_side_effects(mocker):
    class IOAttr(Representation):
        __slots__ = ['attr1']
        def __init__(self, attr1):
            self.attr1 = attr1

    instance = IOAttr(attr1='value')
    mocker.patch('builtins.print')
    print(instance)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import typing
from typing import Any

# imports
import pytest  # used for our unit tests
from pydantic._internal._repr import Representation

# unit tests

class TestRepresentation:
    def test_default_behavior(self):
        # Test a class with no attributes
        class EmptyClass(Representation):
            pass
        
        instance = EmptyClass()
    
    def test_simple_attributes(self):
        # Test a class with simple attributes
        class SimpleClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = SimpleClass(1, "test")
    
    def test_slots_attributes(self):
        # Test a class with __slots__
        class SlotsClass(Representation):
            __slots__ = ['a', 'b']
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = SlotsClass(1, "test")
    
    def test_none_values(self):
        # Test attributes with None values
        class NoneValuesClass(Representation):
            def __init__(self, a, b=None):
                self.a = a
                self.b = b
        
        instance = NoneValuesClass(1)
    
    def test_complex_values(self):
        # Test attributes with complex data types
        class ComplexClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = ComplexClass([1, 2, 3], {"key": "value"})
    
    def test_empty_class(self):
        # Test an empty class inheriting from Representation
        class EmptyClass(Representation):
            pass
        
        instance = EmptyClass()
    
    def test_special_characters(self):
        # Test attributes with special characters
        class SpecialCharClass(Representation):
            def __init__(self, a):
                self.a = a
        
        instance = SpecialCharClass("new\nline")
    
    def test_large_number_of_attributes(self):
        # Test a class with a large number of attributes
        class LargeAttrClass(Representation):
            def __init__(self):
                for i in range(100):
                    setattr(self, f'attr{i}', i)
        
        instance = LargeAttrClass()
        expected_repr = "LargeAttrClass(" + ", ".join(f"attr{i}={i}" for i in range(100)) + ")"
    
    def test_large_data_structures(self):
        # Test attributes with large data structures
        class LargeDataClass(Representation):
            def __init__(self, data):
                self.data = data
        
        instance = LargeDataClass(list(range(1000)))
    
    def test_overridden_repr_args(self):
        # Test a class that overrides __repr_args__
        class CustomReprArgsClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
            
            def __repr_args__(self):
                return [("custom_a", self.a), ("custom_b", self.b)]
        
        instance = CustomReprArgsClass(1, "test")
    
    def test_multiple_inheritance(self):
        # Test a class with multiple inheritance
        class BaseClass:
            def base_method(self):
                return "base"
        
        class MultipleInheritanceClass(Representation, BaseClass):
            def __init__(self, a):
                self.a = a
        
        instance = MultipleInheritanceClass(1)
    
    def test_consistent_output(self):
        # Ensure consistent output across multiple calls
        class ConsistentClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = ConsistentClass(1, "test")
    
    def test_custom_str_repr_methods(self):
        # Test a class that defines custom __str__ and __repr__ methods
        class CustomStrReprClass(Representation):
            def __init__(self, a):
                self.a = a
            
            def __str__(self):
                return f"CustomStrReprClass with a={self.a}"
            
            def __repr__(self):
                return f"CustomStrReprClass(a={self.a})"
        
        instance = CustomStrReprClass(1)
    
    def test_invalid_attributes(self):
        # Test a class with invalid attribute names
        class InvalidAttrClass(Representation):
            def __init__(self):
                setattr(self, "invalid-attr", 1)
        
        instance = InvalidAttrClass()
    
    def test_pretty_print(self):
        # Test the __pretty__ method
        class PrettyPrintClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = PrettyPrintClass(1, "test")
        pretty_output = list(instance.__pretty__(lambda x: repr(x)))
    
    def test_rich_repr(self):
        # Test the __rich_repr__ method
        class RichReprClass(Representation):
            def __init__(self, a, b):
                self.a = a
                self.b = b
        
        instance = RichReprClass(1, "test")
        rich_output = list(instance.__rich_repr__())
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from pydantic._internal._repr import Representation

def test_Representation___repr__():
    assert Representation.__repr__(Representation()) == 'Representation()'

📢 Feedback on this optimization?