⚡️ Speed up method ImageURL.serialize_model by 20%

[codeflash-ai]

📄 20% (0.20x) speedup for ImageURL.serialize_model in src/mistralai/models/imageurl.py

⏱️ Runtime : 3.65 milliseconds → 3.03 milliseconds (best of 73 runs)

📝 Explanation and details

The optimized code achieves a 20% speedup through several key data structure and algorithmic improvements:

Primary optimizations:

1. Sets instead of lists for lookups: Changed optional_fields, nullable_fields, and null_default_fields from lists to sets, converting O(n) membership checks (k in optional_fields) to O(1) operations.

2. Cached field set access: Extracted self.__pydantic_fields_set__ to a local variable fields_set and replaced the expensive intersection({n}) operation with direct membership checking (n in fields_set). This eliminates set intersection overhead on every field.

3. Removed unnecessary serialized.pop(): The original code called serialized.pop(k, None) for every field, but since serialized is never used again, this adds unnecessary dictionary manipulation overhead with no benefit.

4. Minor syntax improvement: Changed not k in optional_fields to the more idiomatic k not in optional_fields.

Why these optimizations work:

• Set lookups are fundamentally faster than list scans for membership testing
• Avoiding repeated method calls and set operations reduces Python interpreter overhead
• Eliminating unused dictionary mutations saves CPU cycles

Test case performance patterns:
The optimizations show consistent 15-30% improvements across all test scenarios, with particularly strong gains (30%+) in cases with custom handlers or complex field combinations, indicating the optimizations scale well with serialization complexity.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 8035 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from typing import Any

# imports
import pytest
from mistralai.models.imageurl import ImageURL


# Minimal stubs to allow the function to run in isolation
class UNSET_SENTINEL_TYPE:
    pass

UNSET_SENTINEL = UNSET = UNSET_SENTINEL_TYPE()

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

# Minimal BaseModel stub with pydantic-like behavior
class BaseModel:
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)
        self.__pydantic_fields_set__ = set(kwargs.keys())

    @classmethod
    def model_fields(cls):
        # Not used in this stub, but present for compatibility
        return {}


def serialize_model(self, handler):
    optional_fields = ["detail"]
    nullable_fields = ["detail"]
    null_default_fields = []

    serialized = handler(self)

    m = {}

    # Simulate Pydantic's model_fields
    # For our stub, assume fields are just those in self.__dict__
    model_fields = {}
    for k in self.__dict__:
        model_fields[k] = type('Field', (), {'alias': None})()
    for n, f in model_fields.items():
        k = f.alias or n
        val = serialized.get(k)
        serialized.pop(k, None)

        optional_nullable = k in optional_fields and k in nullable_fields
        is_set = (
            getattr(self, '__pydantic_fields_set__', set()).intersection({n})
            or k in null_default_fields
        )

        if val is not None and val != UNSET_SENTINEL:
            m[k] = val
        elif val != UNSET_SENTINEL and (
            not k in optional_fields or (optional_nullable and is_set)
        ):
            m[k] = val

    return m
from mistralai.models.imageurl import ImageURL


# Handler function for serialization
def default_handler(obj):
    # Simulate Pydantic's dict() output
    d = {}
    for k, v in obj.__dict__.items():
        if isinstance(v, OptionalNullable):
            d[k] = v.value
        else:
            d[k] = v
    return d.copy()

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

# 1. Basic Test Cases

def test_basic_required_field_only():
    # Only required field set
    model = ImageURL(url="http://example.com")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 6.87μs -> 5.70μs (20.4% faster)

def test_basic_optional_field_set():
    # Both required and optional field set
    model = ImageURL(url="http://example.com", detail="high")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.50μs -> 3.67μs (22.7% faster)

def test_basic_optional_field_none():
    # Optional field set to None
    model = ImageURL(url="http://example.com", detail=None)
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.58μs -> 3.55μs (29.1% faster)

def test_basic_optional_field_unset():
    # Optional field not set (should be omitted)
    model = ImageURL(url="http://example.com")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 5.37μs -> 4.77μs (12.6% faster)

# 2. Edge Test Cases



def test_edge_required_field_empty_string():
    # Required field set to empty string
    model = ImageURL(url="")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 6.60μs -> 5.55μs (19.0% faster)

def test_edge_optional_field_empty_string():
    # Optional field set to empty string
    model = ImageURL(url="http://example.com", detail="")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.40μs -> 3.59μs (22.5% faster)





def test_edge_optional_field_dict():
    # Optional field set to a dict (should be included)
    model = ImageURL(url="http://example.com", detail={"foo": "bar"})
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 7.04μs -> 5.92μs (19.1% faster)




def test_edge_handler_removes_fields():
    # Handler that omits 'detail'
    def handler(obj):
        return {"url": obj.url}
    model = ImageURL(url="http://example.com", detail="high")
    codeflash_output = model.serialize_model(handler); result = codeflash_output # 4.93μs -> 3.77μs (30.8% faster)

def test_edge_handler_returns_extra_fields():
    # Handler that adds extra fields
    def handler(obj):
        return {"url": obj.url, "detail": "high", "extra": 123}
    model = ImageURL(url="http://example.com")
    codeflash_output = model.serialize_model(handler); result = codeflash_output # 3.79μs -> 3.05μs (24.3% faster)


def test_large_scale_many_instances():
    # Create 500 models with alternating detail values
    models = [ImageURL(url=f"http://example.com/{i}", detail="high" if i % 2 == 0 else None) for i in range(500)]
    for i, model in enumerate(models):
        codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 673μs -> 550μs (22.4% faster)
        if i % 2 == 0:
            pass
        else:
            pass

def test_large_scale_long_string():
    # Very long string in url and detail
    long_url = "http://" + "a" * 900 + ".com"
    long_detail = "x" * 900
    model = ImageURL(url=long_url, detail=long_detail)
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.25μs -> 3.67μs (15.8% faster)

def test_large_scale_bulk_serialization():
    # Serialize 999 models and check all outputs
    models = [ImageURL(url=f"http://example.com/{i}") for i in range(999)]
    results = [model.serialize_model(default_handler) for model in models]
    for i, result in enumerate(results):
        pass

def test_large_scale_optional_field_unset():
    # 1000 models with unset optional field
    models = [ImageURL(url=f"http://example.com/{i}") for i in range(1000)]
    for model in models:
        codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 1.54ms -> 1.30ms (18.3% faster)

def test_large_scale_optional_field_set_to_none():
    # 1000 models with detail set to None
    models = [ImageURL(url=f"http://example.com/{i}", detail=None) for i in range(1000)]
    for model in models:
        codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 1.34ms -> 1.10ms (21.4% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Dict

# imports
import pytest
from mistralai.models.imageurl import ImageURL


# Simulate UNSET and UNSET_SENTINEL
class _UnsetType:
    pass

UNSET = _UnsetType()
UNSET_SENTINEL = _UnsetType()

# Simulate OptionalNullable
def OptionalNullable(type_):
    return type_

# Simulate BaseModel
class BaseModel:
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)
        # Track which fields were set
        self.__pydantic_fields_set__ = set(kwargs.keys())

    # Simulate pydantic model_fields
    @classmethod
    def model_fields(cls):
        return {
            k: type("Field", (), {"alias": None})()
            for k in cls.__annotations__
        }

# Simulate model_serializer decorator
def model_serializer(mode=None):
    def decorator(f):
        return f
    return decorator
from mistralai.models.imageurl import ImageURL


# Helper handler for serialization
def default_handler(obj):
    # Simulate a generic dict conversion
    d = {}
    for k in obj.__annotations__:
        v = getattr(obj, k, UNSET)
        if v is UNSET:
            continue
        d[k] = v
    return d

# ----------------------
# Unit tests start here
# ----------------------

# 1. Basic Test Cases

def test_basic_url_only():
    # Test with only required field set
    img = ImageURL(url="http://example.com/image.png")
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 6.20μs -> 5.41μs (14.7% faster)

def test_basic_url_and_detail():
    # Test with both fields set
    img = ImageURL(url="http://example.com/image.png", detail="high")
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 4.13μs -> 3.38μs (22.2% faster)

def test_basic_url_and_detail_none():
    # Test with detail explicitly set to None
    img = ImageURL(url="http://example.com/image.png", detail=None)
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 4.31μs -> 3.52μs (22.5% faster)

# 2. Edge Test Cases

def test_detail_unset():
    # Test with detail unset (should not appear in output)
    img = ImageURL(url="http://example.com/image.png")
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 5.15μs -> 4.22μs (22.0% faster)


def test_url_empty_string():
    # Test with empty string for url
    img = ImageURL(url="")
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 6.76μs -> 5.44μs (24.3% faster)

def test_detail_empty_string():
    # Test with detail as empty string
    img = ImageURL(url="http://example.com/image.png", detail="")
    codeflash_output = img.serialize_model(default_handler); result = codeflash_output # 4.50μs -> 3.57μs (25.9% faster)




def test_handler_removes_fields():
    # Handler removes fields (simulate custom handler)
    def custom_handler(obj):
        return {"url": obj.url}
    img = ImageURL(url="http://example.com/image.png", detail="hi")
    codeflash_output = img.serialize_model(custom_handler); result = codeflash_output # 5.00μs -> 3.75μs (33.3% faster)

def test_handler_returns_extra_fields():
    # Handler returns extra fields (should be ignored)
    def custom_handler(obj):
        return {"url": obj.url, "detail": "hi", "extra": 123}
    img = ImageURL(url="http://example.com/image.png", detail="hi")
    codeflash_output = img.serialize_model(custom_handler); result = codeflash_output # 4.00μs -> 3.08μs (29.7% faster)

# 3. Large Scale Test Cases

def test_large_number_of_instances():
    # Test serializing a large number of instances
    N = 500  # under 1000 as per instructions
    imgs = [ImageURL(url=f"http://example.com/img{i}.png", detail=str(i)) for i in range(N)]
    results = [img.serialize_model(default_handler) for img in imgs]
    for i, result in enumerate(results):
        pass

def test_large_number_of_instances_with_none_detail():
    # Test serializing many instances with detail=None
    N = 500
    imgs = [ImageURL(url=f"http://example.com/img{i}.png", detail=None) for i in range(N)]
    results = [img.serialize_model(default_handler) for img in imgs]
    for i, result in enumerate(results):
        pass

def test_large_number_of_instances_with_unset_detail():
    # Test serializing many instances with detail=UNSET
    N = 500
    imgs = [ImageURL(url=f"http://example.com/img{i}.png") for i in range(N)]
    results = [img.serialize_model(default_handler) for img in imgs]
    for i, result in enumerate(results):
        pass

def test_large_scale_handler_performance():
    # Test with a handler that does extra work
    def heavy_handler(obj):
        # Simulate extra computation
        d = {}
        for k in obj.__annotations__:
            v = getattr(obj, k, UNSET)
            if v is UNSET:
                continue
            # Simulate transformation
            if isinstance(v, str):
                d[k] = v.upper()
            else:
                d[k] = v
        return d
    N = 500
    imgs = [ImageURL(url=f"http://example.com/img{i}.png", detail="hi") for i in range(N)]
    results = [img.serialize_model(heavy_handler) for img in imgs]
    for i, result in enumerate(results):
        pass
# 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-ImageURL.serialize_model-mh4fg93o and push.