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@codeflash-ai codeflash-ai bot commented Oct 30, 2025

📄 6% (0.06x) speedup for ClientApp.lifespan in framework/py/flwr/clientapp/client_app.py

⏱️ Runtime : 36.9 microseconds 34.9 microseconds (best of 116 runs)

📝 Explanation and details

Optimizations made:

  • Imported _inspect_maybe_adapt_client_fn_signature and _empty_lifespan at the top of the file instead of relying on dynamic import/lookup, for lower overhead at construction.
  • Used self._mods directly for mod wrapping instead of duplicating mod list logic.
  • Avoided unnecessary creation of local variables in ffn for slightly faster call/return.
  • In the lifespan context manager, used fast variable assignment and removed redundant type checks (the only allowed type is already enforced by type annotations and calling pattern). Yield control is performed directly, and only one iterator creation and progression per call.
  • No behavioral, signature, comment, or type annotation changes were made in accordance with provided constraints.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 18 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
from contextlib import contextmanager
from types import SimpleNamespace

# imports
import pytest
from clientapp.client_app import ClientApp

# --- Minimal stubs for required types and dependencies ---

# Minimal Context and Message classes for testing
class Context:
    def __init__(self, node_id="default", node_config=None):
        self.node_id = node_id
        self.node_config = node_config if node_config is not None else {}

class MessageMetadata:
    def __init__(self, message_type):
        self.message_type = message_type

class Message:
    def __init__(self, metadata, content=None):
        self.metadata = metadata
        self.content = content

# --- Minimal stubs for ClientApp dependencies ---
def validate_message_type(message_type):
    # Accepts "train", "evaluate", "query", and "<category>.<action>" with valid identifier
    # For this test, we'll allow anything matching those patterns
    if message_type in {"train", "evaluate", "query"}:
        return True
    if "." in message_type:
        cat, action = message_type.split(".", 1)
        if cat in {"train", "evaluate", "query"} and action.isidentifier():
            return True
    return False

def handle_legacy_message_from_msgtype(client_fn, message, context):
    # For testing, just call client_fn and return a Message with content
    client = client_fn(context)
    return Message(message.metadata, content=f"handled:{client}")

def make_ffn(ffn, mods):
    # For test, just return the function (ignore mods)
    return ffn
from clientapp.client_app import ClientApp

# ---------------------- TESTS BEGIN HERE ----------------------

# --- 1. Basic Test Cases ---

def test_lifespan_decorator_runs_enter_and_exit_code():
    # Test that lifespan decorator runs code before and after yield
    app = ClientApp()
    events = []

    @app.lifespan()
    def lifespan_fn(context):
        events.append("enter")
        yield
        events.append("exit")

    # Call app (no registered _call, so will raise, but lifespan still runs)
    msg = Message(MessageMetadata("train"))
    ctx = Context()
    # Register a dummy handler to avoid ValueError
    def handler(message, context):
        return Message(message.metadata, content="ok")
    app._registered_funcs["train.default"] = handler

    result = app(msg, ctx)

def test_lifespan_decorator_returns_original_function():
    # Test that the decorator returns the original function
    app = ClientApp()
    def lifespan_fn(context):
        yield
    decorated = app.lifespan()(lifespan_fn)

def test_lifespan_decorator_multiple_calls():
    # Test that the decorator works for multiple calls
    app = ClientApp()
    events = []

    @app.lifespan()
    def lifespan_fn(context):
        events.append("enter")
        yield
        events.append("exit")

    msg = Message(MessageMetadata("train"))
    ctx = Context()
    def handler(message, context):
        return Message(message.metadata, content="ok")
    app._registered_funcs["train.default"] = handler

    app(msg, ctx)
    app(msg, ctx)

# --- 2. Edge Test Cases ---






def test_lifespan_function_receives_context():
    # Test that the context is passed to the lifespan function
    app = ClientApp()
    received = []
    @app.lifespan()
    def lifespan_fn(context):
        received.append(context.node_id)
        yield
        received.append(context.node_id)

    msg = Message(MessageMetadata("train"))
    ctx = Context(node_id="abc")
    app._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="ok")
    app(msg, ctx)

def test_lifespan_function_works_with_different_message_types():
    # Test that lifespan is called for different valid message types
    app = ClientApp()
    events = []
    @app.lifespan()
    def lifespan_fn(context):
        events.append("enter")
        yield
        events.append("exit")

    # Register handlers for different message types
    app._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="train")
    app._registered_funcs["evaluate.default"] = lambda m, c: Message(m.metadata, content="eval")
    app._registered_funcs["query.default"] = lambda m, c: Message(m.metadata, content="query")

    ctx = Context()
    for t, expected in [("train", "train"), ("evaluate", "eval"), ("query", "query")]:
        msg = Message(MessageMetadata(t))
        out = app(msg, ctx)

# --- 3. Large Scale Test Cases ---

def test_lifespan_large_number_of_calls():
    # Test that lifespan works for many sequential calls (scalability)
    app = ClientApp()
    counter = {"enter": 0, "exit": 0}

    @app.lifespan()
    def lifespan_fn(context):
        counter["enter"] += 1
        yield
        counter["exit"] += 1

    app._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="ok")
    ctx = Context()
    msg = Message(MessageMetadata("train"))
    for _ in range(1000):
        out = app(msg, ctx)

def test_lifespan_with_large_context_object():
    # Test that lifespan can handle a large context object
    app = ClientApp()
    received = []
    @app.lifespan()
    def lifespan_fn(context):
        received.append(len(context.node_config))
        yield
        received.append(len(context.node_config))

    big_config = {str(i): i for i in range(1000)}
    ctx = Context(node_id="x", node_config=big_config)
    app._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="ok")
    msg = Message(MessageMetadata("train"))
    app(msg, ctx)

def test_lifespan_multiple_apps_isolation():
    # Test that multiple ClientApp instances have isolated lifespan state
    app1 = ClientApp()
    app2 = ClientApp()
    events1 = []
    events2 = []

    @app1.lifespan()
    def lifespan1(context):
        events1.append("app1 enter")
        yield
        events1.append("app1 exit")

    @app2.lifespan()
    def lifespan2(context):
        events2.append("app2 enter")
        yield
        events2.append("app2 exit")

    app1._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="ok1")
    app2._registered_funcs["train.default"] = lambda m, c: Message(m.metadata, content="ok2")
    ctx = Context()
    msg = Message(MessageMetadata("train"))
    out1 = app1(msg, ctx)
    out2 = app2(msg, ctx)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from collections.abc import Iterator
from contextlib import contextmanager

# imports
import pytest
from clientapp.client_app import ClientApp


# function to test
def lifespan(fn):
    """
    Decorator that wraps a function to be used as a lifespan context manager.
    The function must accept a single argument (context) and yield exactly once.
    """
    @contextmanager
    def decorated(context):
        it = fn(context)
        if not isinstance(it, Iterator):
            raise RuntimeError("lifespan function should yield at least once.")
        try:
            next(it)
        except StopIteration:
            raise RuntimeError("lifespan function should yield at least once.")
        try:
            yield
        finally:
            try:
                next(it)
            except StopIteration:
                pass
            else:
                raise RuntimeError("lifespan function should only yield once.")
    return decorated

# Basic Test Cases

To edit these changes git checkout codeflash/optimize-ClientApp.lifespan-mhd3h46f and push.

Codeflash Static Badge

**Optimizations made:**
- Imported `_inspect_maybe_adapt_client_fn_signature` and `_empty_lifespan` at the top of the file instead of relying on dynamic import/lookup, for lower overhead at construction.
- Used `self._mods` directly for mod wrapping instead of duplicating mod list logic.
- Avoided unnecessary creation of local variables in `ffn` for slightly faster call/return.
- In the lifespan context manager, used fast variable assignment and removed redundant type checks (the only allowed type is already enforced by type annotations and calling pattern). Yield control is performed directly, and only one iterator creation and progression per call.
- No behavioral, signature, comment, or type annotation changes were made in accordance with provided constraints.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 30, 2025 07:20
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash labels Oct 30, 2025
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