⚡️ Speed up method UpdateFTModelIn.serialize_model by 23%

[codeflash-ai]

📄 23% (0.23x) speedup for UpdateFTModelIn.serialize_model in src/mistralai/models/updateftmodelin.py

⏱️ Runtime : 823 microseconds → 669 microseconds (best of 85 runs)

📝 Explanation and details

The optimization achieves a 23% speedup by converting data structure operations from O(n) to O(1) and eliminating redundant computations:

Key optimizations:

1. Set-based membership tests: Changed optional_fields and nullable_fields from lists to sets, converting k in optional_fields from O(n) to O(1) lookup time. This is especially beneficial since these checks happen in every loop iteration.

2. Eliminated redundant set operations: Replaced self.__pydantic_fields_set__.intersection({n}) with direct n in fields_set lookup, avoiding expensive set creation and intersection operations for each field.

3. Reduced dictionary operations: Combined serialized.get(k) and serialized.pop(k, None) into a single serialized.pop(k, None) call, halving dictionary lookups per iteration.

4. Cached expensive lookups: Moved type(self).model_fields.items() outside the loop to avoid repeated method calls and attribute lookups.

Performance impact by test case:

• Simple cases (few fields): 10-25% improvement due to reduced overhead
• Large batch operations (500-1000 instances): 15-24% improvement where the O(1) vs O(n) difference compounds
• Mixed field scenarios: Consistent 15-20% gains across different field combinations

The optimizations are most effective for models with multiple optional/nullable fields and high-volume serialization scenarios, as shown by the larger improvements in batch test cases.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1102 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from __future__ import annotations

from typing import Any, Dict

# imports
import pytest
from mistralai.models.updateftmodelin import UpdateFTModelIn
from pydantic import BaseModel as PydanticBaseModel
from pydantic import Field, model_serializer


# Simulate OptionalNullable, UNSET, UNSET_SENTINEL for testing
class UnsetType:
    pass

UNSET = UnsetType()
UNSET_SENTINEL = object()

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

    def __eq__(self, other):
        if isinstance(other, OptionalNullable):
            return self.value == other.value
        return self.value == other

    def __repr__(self):
        return f"OptionalNullable({self.value!r})"

# Simulate BaseModel for testing
class BaseModel(PydanticBaseModel):
    pass
from mistralai.models.updateftmodelin import UpdateFTModelIn


# Helper handler function for serialization
def default_handler(obj: UpdateFTModelIn) -> Dict[str, Any]:
    # Simulate pydantic serialization
    result = {}
    for field in obj.model_fields:
        value = getattr(obj, field)
        # Unwrap OptionalNullable if present
        if isinstance(value, OptionalNullable):
            result[field] = value.value
        elif value is UNSET:
            result[field] = UNSET_SENTINEL
        else:
            result[field] = value
    return result

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

# --- BASIC TEST CASES ---




def test_serialize_model_basic_unset_fields():
    """Test with both fields unset"""
    model = UpdateFTModelIn()
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 7.52μs -> 6.80μs (10.5% faster)

# --- EDGE TEST CASES ---















#------------------------------------------------
from __future__ import annotations

# imports
import pytest  # used for our unit tests
from mistralai.models.updateftmodelin import UpdateFTModelIn


# Minimal stubs for external dependencies to allow testing
class UNSET_SENTINEL_TYPE:
    pass
UNSET_SENTINEL = UNSET = UNSET_SENTINEL_TYPE()

# Minimal BaseModel and field simulation for testing
class Field:
    def __init__(self, alias=None):
        self.alias = alias

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

    @classmethod
    def model_fields(cls):
        # Should be overridden in subclass
        return {}

# The function/class under test
def model_serializer(mode=None):
    # Decorator stub: just returns the function unchanged
    def decorator(fn):
        return fn
    return decorator
from mistralai.models.updateftmodelin import UpdateFTModelIn


# Helper handler function for serialization
def default_handler(obj):
    # Simulates Pydantic's serialization to dict
    result = {}
    for field in obj.model_fields:
        val = getattr(obj, field, UNSET_SENTINEL)
        result[field] = val
    return result

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

# 1. BASIC TEST CASES

def test_serialize_model_with_all_fields_set():
    # Both fields set to normal strings
    model = UpdateFTModelIn(name="test_name", description="test_description")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 6.13μs -> 4.91μs (24.8% faster)

def test_serialize_model_with_one_field_set_name():
    # Only name set
    model = UpdateFTModelIn(name="only_name")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 6.24μs -> 5.12μs (21.8% faster)

def test_serialize_model_with_one_field_set_description():
    # Only description set
    model = UpdateFTModelIn(description="only_description")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 5.28μs -> 4.67μs (13.1% faster)

def test_serialize_model_with_no_fields_set():
    # Neither field set (both UNSET)
    model = UpdateFTModelIn()
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 5.30μs -> 4.75μs (11.8% faster)

def test_serialize_model_with_none_values():
    # Both fields explicitly set to None
    model = UpdateFTModelIn(name=None, description=None)
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.47μs -> 3.83μs (16.6% faster)

def test_serialize_model_with_name_none_description_set():
    # name=None, description set
    model = UpdateFTModelIn(name=None, description="desc")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.28μs -> 3.69μs (15.9% faster)

def test_serialize_model_with_name_set_description_none():
    # name set, description=None
    model = UpdateFTModelIn(name="abc", description=None)
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.37μs -> 3.75μs (16.5% faster)

# 2. EDGE TEST CASES

def test_serialize_model_with_empty_strings():
    # Both fields set to empty string
    model = UpdateFTModelIn(name="", description="")
    codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 4.23μs -> 3.48μs (21.6% faster)





def test_serialize_model_with_field_not_in_handler_output():
    # Handler omits a field
    model = UpdateFTModelIn(name="present", description="present")
    def handler(obj):
        return {"name": "present"}  # 'description' omitted
    codeflash_output = model.serialize_model(handler); result = codeflash_output # 5.09μs -> 3.97μs (28.2% faster)

def test_serialize_model_with_handler_returns_extra_field():
    # Handler returns an extra field not in model_fields
    model = UpdateFTModelIn(name="x", description="y")
    def handler(obj):
        d = default_handler(obj)
        d["extra"] = 42
        return d
    codeflash_output = model.serialize_model(handler); result = codeflash_output # 5.16μs -> 4.43μs (16.4% faster)


def test_serialize_model_large_number_of_instances():
    # Serialize 500 models with unique values
    for i in range(500):
        model = UpdateFTModelIn(name=f"name_{i}", description=f"desc_{i}")
        codeflash_output = model.serialize_model(default_handler); result = codeflash_output # 689μs -> 554μs (24.2% faster)

def test_serialize_model_large_batch_with_none_and_unset():
    # Mix of None, UNSET, and values in 1000 instances
    for i in range(0, 1000, 100):
        # name set, description unset
        model1 = UpdateFTModelIn(name=f"name_{i}")
        codeflash_output = model1.serialize_model(default_handler); res1 = codeflash_output # 21.5μs -> 18.6μs (15.8% faster)

        # name unset, description set
        model2 = UpdateFTModelIn(description=f"desc_{i}")
        codeflash_output = model2.serialize_model(default_handler); res2 = codeflash_output # 18.2μs -> 15.3μs (18.8% faster)

        # both set to None
        model3 = UpdateFTModelIn(name=None, description=None)
        codeflash_output = model3.serialize_model(default_handler); res3 = codeflash_output

        # both unset
        model4 = UpdateFTModelIn() # 16.4μs -> 13.4μs (22.1% faster)
        codeflash_output = model4.serialize_model(default_handler); res4 = codeflash_output

To edit these changes git checkout codeflash/optimize-UpdateFTModelIn.serialize_model-mh2un61a and push.