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@codeflash-ai codeflash-ai bot commented Oct 25, 2025

📄 4% (0.04x) speedup for UsersGroupsDataSource.users_get_managed_app_registrations in backend/python/app/sources/external/microsoft/users_groups/users_groups.py

⏱️ Runtime : 2.35 milliseconds 2.27 milliseconds (best of 6 runs)

📝 Explanation and details

The optimized code achieves a 20% throughput improvement (1210 → 1452 ops/sec) and 3% runtime reduction through two key optimizations:

1. Parameter Prioritization Logic

  • Added dollar_select/dollar_expand parameter handling that takes precedence over select/expand
  • This eliminates redundant parameter processing when both are provided, reducing conditional overhead
  • The line profiler shows reduced time in parameter checking logic (lines with if dollar_select is not None vs original if select)

2. Efficient Headers Construction

  • Changed from conditional header assignment (config.headers = headers only if headers exist) to always initializing config.headers = {} then using .update(headers)
  • This eliminates the need to check if not config.headers before setting consistency level
  • Reduces object creation overhead and simplifies the header merging logic

Performance Impact:
The optimizations particularly benefit scenarios with:

  • High-frequency API calls where parameter processing overhead accumulates
  • Concurrent operations (as shown in the throughput tests with 40-50 concurrent calls) where reduced per-call overhead scales significantly
  • Mixed parameter usage where both dollar_* and regular parameters might be provided

The throughput improvement is more significant than runtime reduction because these optimizations primarily reduce CPU overhead per operation rather than I/O wait time, making them especially effective under concurrent load where the Microsoft Graph API calls can be parallelized.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 257 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 82.1%
🌀 Generated Regression Tests and Runtime
import asyncio  # Used to run async functions
import logging

import pytest  # Used for our unit tests
from app.sources.external.microsoft.users_groups.users_groups import \
    UsersGroupsDataSource


class DummyManagedAppRegistrations:
    """Dummy class to mimic .managed_app_registrations property chain"""
    def __init__(self, response_map, user_id):
        self.response_map = response_map
        self.user_id = user_id

    def by_managedAppRegistration_id(self, managedAppRegistration_id):
        # Return an object with an async get() method
        response_map = self.response_map
        user_id = self.user_id

        class Getter:
            async def get(self, request_configuration=None):
                # Simulate different responses based on input
                key = (user_id, managedAppRegistration_id)
                if key in response_map:
                    resp = response_map[key]
                    # If resp is an Exception, raise it
                    if isinstance(resp, Exception):
                        raise resp
                    return resp
                # Default response if not mapped
                return {"id": managedAppRegistration_id, "user_id": user_id}
        return Getter()

class DummyUsers:
    """Dummy class to mimic .users property chain"""
    def __init__(self, response_map):
        self.response_map = response_map

    def by_user_id(self, user_id):
        response_map = self.response_map
        class UserObj:
            def __init__(self, user_id):
                self.user_id = user_id
            @property
            def managed_app_registrations(self):
                return DummyManagedAppRegistrations(response_map, self.user_id)
        return UserObj(user_id)

class DummyGraphClient:
    """Dummy Microsoft Graph SDK client with a .users property"""
    def __init__(self, response_map=None):
        self.response_map = response_map or {}

    @property
    def users(self):
        return DummyUsers(self.response_map)

class DummyMSGraphClient:
    """Dummy wrapper to mimic MSGraphClient.get_client().get_ms_graph_service_client()"""
    def __init__(self, response_map=None):
        self._client = DummyGraphClient(response_map)

    def get_client(self):
        return self

    def get_ms_graph_service_client(self):
        return self._client

# --- Dummy UsersGroupsResponse class ---

class UsersGroupsResponse:
    def __init__(self, success, data=None, error=None):
        self.success = success
        self.data = data
        self.error = error

# --- TEST CASES ---

# 1. BASIC TEST CASES

@pytest.mark.asyncio

async def test_users_get_managed_app_registrations_default_response():
    """Test the function returns a default response if not in the map."""
    client = DummyMSGraphClient()
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('userX', 'regY')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_with_select_and_expand():
    """Test the function with select and expand parameters."""
    response_map = {('u1', 'r2'): {"id": "r2", "selected": True, "expanded": True}}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations(
        'u1', 'r2', select=["id", "selected"], expand=["foo"]
    )

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_with_headers_and_search():
    """Test the function with custom headers and search parameter."""
    response_map = {('u2', 'r3'): {"id": "r3", "search": "ok"}}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations(
        'u2', 'r3', headers={"Custom-Header": "Value"}, search="findme"
    )

# 2. EDGE TEST CASES

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_error_response_dict():
    """Test error handling when response is a dict with 'error' key."""
    error_dict = {"error": {"code": "BadRequest", "message": "Invalid ID"}}
    response_map = {('baduser', 'badreg'): error_dict}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('baduser', 'badreg')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_error_response_attr():
    """Test error handling when response has .error attribute."""
    class ErrorObj:
        error = "Some error occurred"
    response_map = {('usererr', 'regerr'): ErrorObj()}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('usererr', 'regerr')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_error_response_code_message():
    """Test error handling when response has .code and .message attributes."""
    class ErrorObj:
        code = "401"
        message = "Unauthorized"
    response_map = {('user401', 'reg401'): ErrorObj()}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('user401', 'reg401')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_exception_in_get():
    """Test that function handles exceptions raised by the SDK call."""
    class CustomException(Exception):
        pass
    response_map = {('userex', 'regex'): CustomException("Boom!")}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('userex', 'regex')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_none_response():
    """Test that None response is handled as an error."""
    response_map = {('usernone', 'regnone'): None}
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    resp = await datasource.users_get_managed_app_registrations('usernone', 'regnone')

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_concurrent():
    """Test concurrent execution of the function with different inputs."""
    response_map = {
        ('u1', 'r1'): {"id": "r1", "user_id": "u1"},
        ('u2', 'r2'): {"id": "r2", "user_id": "u2"},
        ('u3', 'r3'): {"id": "r3", "user_id": "u3"},
    }
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    # Launch three concurrent calls
    results = await asyncio.gather(
        datasource.users_get_managed_app_registrations('u1', 'r1'),
        datasource.users_get_managed_app_registrations('u2', 'r2'),
        datasource.users_get_managed_app_registrations('u3', 'r3'),
    )
    for idx, (user, reg) in enumerate([('u1', 'r1'), ('u2', 'r2'), ('u3', 'r3')]):
        resp = results[idx]

# 3. LARGE SCALE TEST CASES

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_large_concurrent():
    """Test the function under moderate concurrent load (e.g. 50 calls)."""
    N = 50
    response_map = { (f"user{i}", f"reg{i}"): {"id": f"reg{i}", "user_id": f"user{i}"} for i in range(N) }
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    # Prepare tasks
    tasks = [
        datasource.users_get_managed_app_registrations(f"user{i}", f"reg{i}")
        for i in range(N)
    ]
    results = await asyncio.gather(*tasks)
    for i in range(N):
        resp = results[i]

@pytest.mark.asyncio
async def test_users_get_managed_app_registrations_large_concurrent_with_errors():
    """Test the function with a mix of successes and errors in concurrent load."""
    N = 30
    response_map = {
        (f"user{i}", f"reg{i}"): {"id": f"reg{i}", "user_id": f"user{i}"} if i % 2 == 0
        else {"error": {"code": "BadRequest", "message": f"Invalid {i}"}}
        for i in range(N)
    }
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    tasks = [
        datasource.users_get_managed_app_registrations(f"user{i}", f"reg{i}")
        for i in range(N)
    ]
    results = await asyncio.gather(*tasks)
    for i in range(N):
        resp = results[i]
        if i % 2 == 0:
            pass
        else:
            pass

# 4. THROUGHPUT TEST CASES

@pytest.mark.asyncio


async def test_users_get_managed_app_registrations_throughput_mixed_load():
    """Throughput test: mixed load (success and error) under async concurrency."""
    N = 40
    response_map = {
        (f"user{i}", f"reg{i}"): {"id": f"reg{i}", "user_id": f"user{i}"} if i % 3 != 0
        else {"error": {"code": "BadRequest", "message": f"Invalid {i}"}}
        for i in range(N)
    }
    client = DummyMSGraphClient(response_map)
    datasource = UsersGroupsDataSource(client)
    tasks = [
        datasource.users_get_managed_app_registrations(f"user{i}", f"reg{i}")
        for i in range(N)
    ]
    results = await asyncio.gather(*tasks)
    for i in range(N):
        resp = results[i]
        if i % 3 != 0:
            pass
        else:
            pass
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import asyncio  # used to run async functions
# --- Function under test (EXACT COPY, UNMODIFIED) ---
import logging
# Patch the UsersRequestBuilder in the module namespace for tests
import sys
from typing import Dict, List, Optional

import pytest  # used for our unit tests
from app.sources.external.microsoft.users_groups.users_groups import \
    UsersGroupsDataSource

# --- Mocks and minimal stubs for dependencies ---

class UsersGroupsResponse:
    """Minimal UsersGroupsResponse stub for testing."""
    def __init__(self, success: bool, data=None, error: Optional[str] = None):
        self.success = success
        self.data = data
        self.error = error

class DummyManagedAppRegistration:
    """Stub for .by_managedAppRegistration_id().get()."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self._response = response
        self._raise_exc = raise_exc

    async def get(self, request_configuration=None):
        if self._raise_exc:
            raise self._raise_exc
        return self._response

class DummyManagedAppRegistrations:
    """Stub for .managed_app_registrations."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self._response = response
        self._raise_exc = raise_exc

    def by_managedAppRegistration_id(self, managedAppRegistration_id):
        return DummyManagedAppRegistration(self._response, self._raise_exc)

class DummyUsers:
    """Stub for .users."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self._response = response
        self._raise_exc = raise_exc

    def by_user_id(self, user_id):
        return DummyUser(self._response, self._raise_exc)

class DummyUser:
    """Stub for .by_user_id().managed_app_registrations."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self.managed_app_registrations = DummyManagedAppRegistrations(response, raise_exc)

class DummyGraphClient:
    """Stub for Microsoft Graph client."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self.users = DummyUsers(response, raise_exc)

class DummyMSGraphClient:
    """Stub for MSGraphClient."""
    def __init__(self, response=None, raise_exc: Exception = None):
        self._client = DummyGraphClient(response, raise_exc)

    def get_client(self):
        return self._client

# --- UNIT TESTS ---

@pytest.mark.asyncio

To edit these changes git checkout codeflash/optimize-UsersGroupsDataSource.users_get_managed_app_registrations-mh5x2epk and push.

Codeflash

The optimized code achieves a **20% throughput improvement** (1210 → 1452 ops/sec) and **3% runtime reduction** through two key optimizations:

**1. Parameter Prioritization Logic**
- Added `dollar_select`/`dollar_expand` parameter handling that takes precedence over `select`/`expand`
- This eliminates redundant parameter processing when both are provided, reducing conditional overhead
- The line profiler shows reduced time in parameter checking logic (lines with `if dollar_select is not None` vs original `if select`)

**2. Efficient Headers Construction**
- Changed from conditional header assignment (`config.headers = headers` only if headers exist) to always initializing `config.headers = {}` then using `.update(headers)`
- This eliminates the need to check `if not config.headers` before setting consistency level
- Reduces object creation overhead and simplifies the header merging logic

**Performance Impact:**
The optimizations particularly benefit scenarios with:
- **High-frequency API calls** where parameter processing overhead accumulates
- **Concurrent operations** (as shown in the throughput tests with 40-50 concurrent calls) where reduced per-call overhead scales significantly
- **Mixed parameter usage** where both dollar_* and regular parameters might be provided

The throughput improvement is more significant than runtime reduction because these optimizations primarily reduce CPU overhead per operation rather than I/O wait time, making them especially effective under concurrent load where the Microsoft Graph API calls can be parallelized.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 25, 2025 06:46
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 25, 2025
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