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@codeflash-ai codeflash-ai bot commented Dec 22, 2025

📄 8% (0.08x) speedup for OneNoteDataSource.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section in backend/python/app/sources/external/microsoft/one_note/one_note.py

⏱️ Runtime : 345 microseconds 319 microseconds (best of 5 runs)

📝 Explanation and details

The optimization eliminates unnecessary object creation by consolidating two RequestConfiguration instances into one, achieving an 8% runtime improvement from 345µs to 319µs.

Key optimization: Instead of creating separate query_params and config objects, the optimized version directly sets query parameters on a single RequestConfiguration instance. This removes:

  • One object allocation (query_params = RequestConfiguration())
  • One attribute assignment (config.query_parameters = query_params)

Performance impact: The line profiler shows the original code spent 12.4% of total time (244,010ns) creating the first RequestConfiguration and 9.6% (188,364ns) creating the second one, plus 3% (59,731ns) for the assignment. The optimized version consolidates this into a single 14.9% allocation, saving approximately 26µs per call.

Why this matters: Object instantiation in Python involves memory allocation, attribute initialization, and method binding. By reducing from two objects to one, the optimization decreases memory pressure and eliminates redundant initialization overhead.

Test case performance: The optimization benefits all test scenarios equally since every call path creates these configuration objects. The 8% improvement applies consistently across basic operations, edge cases with error handling, and large-scale concurrent operations (20 simultaneous calls), making it particularly valuable for high-throughput OneNote API integrations.

The throughput remains unchanged at 1,530 operations/second because the optimization reduces per-operation latency rather than affecting the async concurrency model, but the lower latency translates to better resource utilization in production workloads.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 140 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
import logging
from typing import Any, Dict, List, Mapping, Optional

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


class DummyCopyToSection:
    """Dummy async endpoint for copy_to_section."""
    def __init__(self, should_fail=False, return_error=False, return_none=False, return_dict_error=False):
        self.should_fail = should_fail
        self.return_error = return_error
        self.return_none = return_none
        self.return_dict_error = return_dict_error

    async def post(self, body=None, request_configuration=None):
        # Simulate different behaviors for edge case testing
        if self.should_fail:
            raise Exception("Simulated API failure")
        if self.return_error:
            class ErrorObj:
                error = "Simulated error"
            return ErrorObj()
        if self.return_none:
            return None
        if self.return_dict_error:
            return {"error": {"code": "BadRequest", "message": "Invalid request"}}
        # Simulate a successful copy
        return {"id": "new-page-id", "status": "copied"}

class DummyPages:
    def __init__(self, copy_to_section):
        self.by_onenote_page_id = lambda onenotePage_id: self
        self.copy_to_section = copy_to_section

class DummySections:
    def __init__(self, copy_to_section):
        self.by_onenote_section_id = lambda onenoteSection_id: DummyPages(copy_to_section)

class DummySectionGroups:
    def __init__(self, copy_to_section):
        self.by_section_group_id = lambda sectionGroup_id: DummySections(copy_to_section)

class DummyOnenote:
    def __init__(self, copy_to_section):
        self.section_groups = DummySectionGroups(copy_to_section)

class DummyUsers:
    def __init__(self, copy_to_section):
        self.by_user_id = lambda user_id: self
        self.onenote = DummyOnenote(copy_to_section)

class DummyClient:
    def __init__(self, copy_to_section):
        self.users = DummyUsers(copy_to_section)
        self.me = True  # For __init__ check

    def get_ms_graph_service_client(self):
        return self

class DummyMSGraphClient:
    def __init__(self, copy_to_section):
        self._client = DummyClient(copy_to_section)

    def get_client(self):
        return self._client

# --- Unit tests ---

@pytest.mark.asyncio

async def test_copy_to_section_with_select_and_expand():
    """Basic: Test select and expand parameters are handled."""
    copy_to_section = DummyCopyToSection()
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user2",
        sectionGroup_id="sg2",
        onenoteSection_id="sec2",
        onenotePage_id="page2",
        select=["id", "title"],
        expand=["parentNotebook"]
    )

@pytest.mark.asyncio
async def test_copy_to_section_with_search_and_headers():
    """Basic: Test search parameter sets ConsistencyLevel header."""
    copy_to_section = DummyCopyToSection()
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user3",
        sectionGroup_id="sg3",
        onenoteSection_id="sec3",
        onenotePage_id="page3",
        search="notebook",
        headers={"Custom-Header": "value"}
    )

@pytest.mark.asyncio
async def test_copy_to_section_with_request_body():
    """Basic: Test passing a request_body."""
    copy_to_section = DummyCopyToSection()
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    body = {"destinationId": "section42"}
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user4",
        sectionGroup_id="sg4",
        onenoteSection_id="sec4",
        onenotePage_id="page4",
        request_body=body
    )

# --- Edge case tests ---

@pytest.mark.asyncio
async def test_copy_to_section_api_failure_handling():
    """Edge: Simulate API raising an exception."""
    copy_to_section = DummyCopyToSection(should_fail=True)
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user5",
        sectionGroup_id="sg5",
        onenoteSection_id="sec5",
        onenotePage_id="page5"
    )

@pytest.mark.asyncio
async def test_copy_to_section_error_object_handling():
    """Edge: Simulate API returning an object with 'error' attribute."""
    copy_to_section = DummyCopyToSection(return_error=True)
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user6",
        sectionGroup_id="sg6",
        onenoteSection_id="sec6",
        onenotePage_id="page6"
    )

@pytest.mark.asyncio
async def test_copy_to_section_none_response_handling():
    """Edge: Simulate API returning None."""
    copy_to_section = DummyCopyToSection(return_none=True)
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user7",
        sectionGroup_id="sg7",
        onenoteSection_id="sec7",
        onenotePage_id="page7"
    )

@pytest.mark.asyncio
async def test_copy_to_section_dict_error_handling():
    """Edge: Simulate API returning a dict with 'error' key."""
    copy_to_section = DummyCopyToSection(return_dict_error=True)
    client = DummyMSGraphClient(copy_to_section)
    ds = OneNoteDataSource(client)
    resp = await ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
        user_id="user8",
        sectionGroup_id="sg8",
        onenoteSection_id="sec8",
        onenotePage_id="page8"
    )

@pytest.mark.asyncio


async def test_copy_to_section_large_scale_mixed_concurrent():
    """Large Scale: Test 20 concurrent operations with mixed success/failure."""
    # 10 success, 5 error, 5 fail
    ds_list = []
    for i in range(10):
        ds_list.append(OneNoteDataSource(DummyMSGraphClient(DummyCopyToSection())))
    for i in range(5):
        ds_list.append(OneNoteDataSource(DummyMSGraphClient(DummyCopyToSection(return_error=True))))
    for i in range(5):
        ds_list.append(OneNoteDataSource(DummyMSGraphClient(DummyCopyToSection(should_fail=True))))

    tasks = [
        ds.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section(
            user_id=f"user{i}",
            sectionGroup_id=f"sg{i}",
            onenoteSection_id=f"sec{i}",
            onenotePage_id=f"page{i}"
        )
        for i, ds in enumerate(ds_list)
    ]
    results = await asyncio.gather(*tasks)

# --- Throughput tests ---

@pytest.mark.asyncio

To edit these changes git checkout codeflash/optimize-OneNoteDataSource.users_user_onenote_section_groups_section_group_sections_onenote_section_pages_onenote_page_copy_to_section-mjgsfdhk and push.

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…group_sections_onenote_section_pages_onenote_page_copy_to_section

The optimization eliminates unnecessary object creation by consolidating two `RequestConfiguration` instances into one, achieving an 8% runtime improvement from 345µs to 319µs.

**Key optimization:** Instead of creating separate `query_params` and `config` objects, the optimized version directly sets query parameters on a single `RequestConfiguration` instance. This removes:
- One object allocation (`query_params = RequestConfiguration()`)
- One attribute assignment (`config.query_parameters = query_params`)

**Performance impact:** The line profiler shows the original code spent 12.4% of total time (244,010ns) creating the first `RequestConfiguration` and 9.6% (188,364ns) creating the second one, plus 3% (59,731ns) for the assignment. The optimized version consolidates this into a single 14.9% allocation, saving approximately 26µs per call.

**Why this matters:** Object instantiation in Python involves memory allocation, attribute initialization, and method binding. By reducing from two objects to one, the optimization decreases memory pressure and eliminates redundant initialization overhead.

**Test case performance:** The optimization benefits all test scenarios equally since every call path creates these configuration objects. The 8% improvement applies consistently across basic operations, edge cases with error handling, and large-scale concurrent operations (20 simultaneous calls), making it particularly valuable for high-throughput OneNote API integrations.

The throughput remains unchanged at 1,530 operations/second because the optimization reduces per-operation latency rather than affecting the async concurrency model, but the lower latency translates to better resource utilization in production workloads.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 December 22, 2025 06:41
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: High Optimization Quality according to Codeflash labels Dec 22, 2025
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