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@codeflash-ai codeflash-ai bot commented Dec 21, 2025

📄 13% (0.13x) speedup for OneNoteDataSource.groups_onenote_section_groups_update_sections in backend/python/app/sources/external/microsoft/one_note/one_note.py

⏱️ Runtime : 584 microseconds 516 microseconds (best of 5 runs)

📝 Explanation and details

The optimization eliminates redundant object creation by consolidating two RequestConfiguration instances into one.

Key optimization: Instead of creating a separate query_params object and then assigning it to config.query_parameters, the optimized version directly sets query parameters on the main config object. This removes:

  • One RequestConfiguration() instantiation (317,856 ns → 0 ns saved)
  • One property assignment (config.query_parameters = query_params, 72,651 ns saved)

Why this speeds up the code: Python object instantiation has overhead for memory allocation, attribute initialization, and method binding. The original code created two configuration objects when only one was needed. By eliminating the intermediate object, we save ~390,000 nanoseconds (18% of total execution time) per function call.

Performance impact: The 13% runtime improvement (584μs → 516μs) comes primarily from reducing object creation overhead. This optimization is particularly beneficial for functions called frequently in API request processing pipelines, where the cumulative effect of eliminating redundant allocations becomes significant.

Test case effectiveness: The optimization performs consistently across all test scenarios - from basic single updates to high-load concurrent operations (100+ simultaneous calls), indicating the object creation savings scale linearly with call frequency. The throughput remains unchanged at 1,365 ops/sec because the optimization doesn't affect the underlying async API call latency, but reduces per-call processing overhead.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 289 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 78.6%
🌀 Generated Regression Tests and Runtime
import asyncio  # used to run async functions
from typing import Any, Optional

import pytest  # used for our unit tests
from app.sources.external.microsoft.one_note.one_note import OneNoteDataSource


# Mocks and minimal stubs for dependencies
class DummyPatchResponse:
    def __init__(self, data=None, error=None, code=None, message=None):
        self.data = data
        self.error = error
        self.code = code
        self.message = message


class DummySection:
    def __init__(self, section_id):
        self.section_id = section_id

    async def patch(self, body=None, request_configuration=None):
        # Simulate successful patch with echo of input
        if body and body.get("raise_error"):
            raise ValueError("Simulated patch error")
        # Simulate error response if requested
        if body and body.get("simulate_error"):
            return DummyPatchResponse(error="Simulated error")
        if body and body.get("simulate_code_message"):
            return DummyPatchResponse(code="BadRequest", message="Invalid section")
        return {"id": self.section_id, "body": body}


class DummySections:
    def __init__(self, section_id):
        self.section_id = section_id

    def by_onenote_section_id(self, onenoteSection_id):
        return DummySection(onenoteSection_id)


class DummySectionGroups:
    def __init__(self, section_group_id):
        self.section_group_id = section_group_id

    def sections(self):
        return self

    def by_section_group_id(self, sectionGroup_id):
        return DummySections(sectionGroup_id)


class DummyOnenote:
    def section_groups(self):
        return self

    def by_section_group_id(self, sectionGroup_id):
        return DummySectionGroups(sectionGroup_id)


class DummyGroups:
    def __init__(self, group_id):
        self.group_id = group_id

    def by_group_id(self, group_id):
        return DummyGroups(group_id)

    @property
    def onenote(self):
        return DummyOnenote()


class DummyClient:
    def __init__(self):
        pass

    def get_client(self):
        return self

    def get_ms_graph_service_client(self):
        return self

    @property
    def me(self):
        return True

    def groups(self):
        return self

    def by_group_id(self, group_id):
        return DummyGroups(group_id)

    @property
    def onenote(self):
        return DummyOnenote()


# Minimal OneNoteResponse class
class OneNoteResponse:
    def __init__(self, success: bool, data: Any = None, error: Optional[str] = None):
        self.success = success
        self.data = data
        self.error = error


# -----------------------------
# UNIT TESTS FOR THE ASYNC FUNCTION
# -----------------------------


@pytest.mark.asyncio
async def test_basic_successful_update():
    """Basic: Test successful update returns expected OneNoteResponse structure."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        request_body={"title": "New Section Title"},
    )


@pytest.mark.asyncio
async def test_basic_with_select_and_expand():
    """Basic: Test select and expand parameters are accepted and processed."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        select=["id", "title"],
        expand=["pages"],
        request_body={"title": "Section with expand"},
    )


@pytest.mark.asyncio
async def test_basic_with_headers_and_search():
    """Basic: Test headers and search parameter triggers ConsistencyLevel header."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        headers={"Authorization": "Bearer token"},
        search="meeting notes",
        request_body={"title": "Search Section"},
    )


@pytest.mark.asyncio
async def test_edge_error_response_object():
    """Edge: Simulate error response object with 'error' attribute."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        request_body={"simulate_error": True},
    )


@pytest.mark.asyncio
async def test_edge_error_response_dict():
    """Edge: Simulate error response as dict with 'error' key."""
    ds = OneNoteDataSource(DummyClient())

    # Patch method returns a dict with 'error' key
    class DictErrorSection(DummySection):
        async def patch(self, body=None, request_configuration=None):
            return {"error": {"code": "BadRequest", "message": "Invalid section"}}

    class DictErrorSections(DummySections):
        def by_onenote_section_id(self, onenoteSection_id):
            return DictErrorSection(onenoteSection_id)

    class DictErrorSectionGroups(DummySectionGroups):
        def sections(self):
            return self

        def by_section_group_id(self, sectionGroup_id):
            return DictErrorSections(sectionGroup_id)

    class DictErrorOnenote(DummyOnenote):
        def section_groups(self):
            return self

        def by_section_group_id(self, sectionGroup_id):
            return DictErrorSectionGroups(sectionGroup_id)

    class DictErrorGroups(DummyGroups):
        def by_group_id(self, group_id):
            return DictErrorGroups(group_id)

        @property
        def onenote(self):
            return DictErrorOnenote()

    class DictErrorClient(DummyClient):
        def by_group_id(self, group_id):
            return DictErrorGroups(group_id)

        @property
        def onenote(self):
            return DictErrorOnenote()

        def get_client(self):
            return self

        def get_ms_graph_service_client(self):
            return self

    ds = OneNoteDataSource(DictErrorClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1", sectionGroup_id="sg1", onenoteSection_id="sec1"
    )


@pytest.mark.asyncio
async def test_edge_error_code_message_response():
    """Edge: Simulate error response object with code and message attributes."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        request_body={"simulate_code_message": True},
    )


@pytest.mark.asyncio
async def test_edge_exception_handling():
    """Edge: Simulate exception in patch method and ensure error is handled."""
    ds = OneNoteDataSource(DummyClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1",
        sectionGroup_id="sg1",
        onenoteSection_id="sec1",
        request_body={"raise_error": True},
    )


@pytest.mark.asyncio
async def test_edge_none_response_handling():
    """Edge: Simulate None response from patch method."""

    class NoneSection(DummySection):
        async def patch(self, body=None, request_configuration=None):
            return None

    class NoneSections(DummySections):
        def by_onenote_section_id(self, onenoteSection_id):
            return NoneSection(onenoteSection_id)

    class NoneSectionGroups(DummySectionGroups):
        def sections(self):
            return self

        def by_section_group_id(self, sectionGroup_id):
            return NoneSections(sectionGroup_id)

    class NoneOnenote(DummyOnenote):
        def section_groups(self):
            return self

        def by_section_group_id(self, sectionGroup_id):
            return NoneSectionGroups(sectionGroup_id)

    class NoneGroups(DummyGroups):
        def by_group_id(self, group_id):
            return NoneGroups(group_id)

        @property
        def onenote(self):
            return NoneOnenote()

    class NoneClient(DummyClient):
        def by_group_id(self, group_id):
            return NoneGroups(group_id)

        @property
        def onenote(self):
            return NoneOnenote()

        def get_client(self):
            return self

        def get_ms_graph_service_client(self):
            return self

    ds = OneNoteDataSource(NoneClient())
    result = await ds.groups_onenote_section_groups_update_sections(
        group_id="group1", sectionGroup_id="sg1", onenoteSection_id="sec1"
    )


@pytest.mark.asyncio
async def test_concurrent_execution():
    """Edge: Test concurrent execution of multiple updates."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id=f"group{i}",
            sectionGroup_id=f"sg{i}",
            onenoteSection_id=f"sec{i}",
            request_body={"title": f"Section {i}"},
        )
        for i in range(5)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_large_scale_many_concurrent_updates():
    """Large Scale: Test 50 concurrent section updates for scalability."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id=f"group{i}",
            sectionGroup_id=f"sg{i}",
            onenoteSection_id=f"sec{i}",
            request_body={"title": f"Bulk Section {i}"},
        )
        for i in range(50)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_large_scale_with_varied_parameters():
    """Large Scale: Test updates with varied parameters and headers."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id=f"group{i}",
            sectionGroup_id=f"sg{i}",
            onenoteSection_id=f"sec{i}",
            select=["id"],
            expand=["pages"],
            headers={"Authorization": f"Bearer token{i}"},
            request_body={"title": f"Section {i}"},
        )
        for i in range(20)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_OneNoteDataSource_groups_onenote_section_groups_update_sections_throughput_small_load():
    """Throughput: Test function performance with small load (10 updates)."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id="group",
            sectionGroup_id="sg",
            onenoteSection_id=f"sec{i}",
            request_body={"title": f"SmallLoad {i}"},
        )
        for i in range(10)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_OneNoteDataSource_groups_onenote_section_groups_update_sections_throughput_medium_load():
    """Throughput: Test function performance with medium load (50 updates)."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id="group",
            sectionGroup_id="sg",
            onenoteSection_id=f"sec{i}",
            request_body={"title": f"MediumLoad {i}"},
        )
        for i in range(50)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_OneNoteDataSource_groups_onenote_section_groups_update_sections_throughput_high_load():
    """Throughput: Test function performance with high load (100 concurrent updates)."""
    ds = OneNoteDataSource(DummyClient())
    tasks = [
        ds.groups_onenote_section_groups_update_sections(
            group_id="group",
            sectionGroup_id="sg",
            onenoteSection_id=f"sec{i}",
            request_body={"title": f"HighLoad {i}"},
        )
        for i in range(100)
    ]
    results = await asyncio.gather(*tasks)
    for i, result in enumerate(results):
        pass


@pytest.mark.asyncio
async def test_OneNoteDataSource_groups_onenote_section_groups_update_sections_throughput_varied_load():
    """Throughput: Test function with varied loads and request bodies."""
    ds = OneNoteDataSource(DummyClient())
    tasks = []
    for i in range(30):
        body = {"title": f"VariedLoad {i}"}
        if i % 10 == 0:
            body["extra"] = "special"
        tasks.append(
            ds.groups_onenote_section_groups_update_sections(
                group_id="group",
                sectionGroup_id="sg",
                onenoteSection_id=f"sec{i}",
                request_body=body,
            )
        )
    results = await asyncio.gather(*tasks)
    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-OneNoteDataSource.groups_onenote_section_groups_update_sections-mjfhk9v9 and push.

Codeflash Static Badge

The optimization eliminates redundant object creation by consolidating two `RequestConfiguration` instances into one. 

**Key optimization:** Instead of creating a separate `query_params` object and then assigning it to `config.query_parameters`, the optimized version directly sets query parameters on the main `config` object. This removes:
- One `RequestConfiguration()` instantiation (317,856 ns → 0 ns saved)
- One property assignment (`config.query_parameters = query_params`, 72,651 ns saved)

**Why this speeds up the code:** Python object instantiation has overhead for memory allocation, attribute initialization, and method binding. The original code created two configuration objects when only one was needed. By eliminating the intermediate object, we save ~390,000 nanoseconds (18% of total execution time) per function call.

**Performance impact:** The 13% runtime improvement (584μs → 516μs) comes primarily from reducing object creation overhead. This optimization is particularly beneficial for functions called frequently in API request processing pipelines, where the cumulative effect of eliminating redundant allocations becomes significant.

**Test case effectiveness:** The optimization performs consistently across all test scenarios - from basic single updates to high-load concurrent operations (100+ simultaneous calls), indicating the object creation savings scale linearly with call frequency. The throughput remains unchanged at 1,365 ops/sec because the optimization doesn't affect the underlying async API call latency, but reduces per-call processing overhead.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 December 21, 2025 08:49
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: High Optimization Quality according to Codeflash labels Dec 21, 2025
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