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⚡️ Speed up _FunctionTransport.capture_event() by 5% in sentry_sdk/transport.py#10

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⚡️ Speed up _FunctionTransport.capture_event() by 5% in sentry_sdk/transport.py#10
codeflash-ai[bot] wants to merge 1 commit intomasterfrom
codeflash/optimize-_FunctionTransport.capture_event-2024-06-15T02.04.21

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@codeflash-ai codeflash-ai bot commented Jun 15, 2024

📄 _FunctionTransport.capture_event() in sentry_sdk/transport.py

📈 Performance improved by 5% (0.05x faster)

⏱️ Runtime went down from 310 microseconds to 294 microseconds

Explanation and details

To optimize the provided Python program for better performance, we focus on areas where we might reduce overhead while making sure the logic remains unchanged. Here, the program already seems to follow good practices, but there's a bit of room for optimization.

One possible optimization is to avoid repeated attribute lookups by storing them as local variables, which is slightly faster and can therefore make the program more efficient. Another small tweak could be improving the superclass initialization.

Here’s the optimized version of your code.

  1. Using super().__init__(): It's a more modern and efficient way to initialize the superclass.
  2. Local Variable for self._func: Storing self._func in a local variable func reduces attribute lookups when calling it. This has a slight performance gain, particularly useful if capture_event is called frequently.

These refined changes make the code more efficient while preserving existing functionality and return types.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

🔘 (none found) − ⚙️ Existing Unit Tests

✅ 14 Passed − 🌀 Generated Regression Tests

(click to show generated tests)
# imports
from unittest.mock import Mock

import pytest  # used for our unit tests


# function to test
class Transport:
    def __init__(self):
        pass
from sentry_sdk.transport import _FunctionTransport

# unit tests

# Basic Functionality
def test_basic_functionality():
    def mock_func(event):
        assert event == {"type": "test_event"}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event"})

# Handling Different Event Types
def test_minimal_event():
    def mock_func(event):
        assert event == {}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({})

def test_nested_event():
    def mock_func(event):
        assert event == {"type": "test_event", "details": {"id": 1}}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event", "details": {"id": 1}})

def test_special_characters_event():
    def mock_func(event):
        assert event == {"type": "test_event", "details": "äöüß"}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event", "details": "äöüß"})

# Edge Cases
def test_none_event():
    def mock_func(event):
        assert event is None
    transport = _FunctionTransport(mock_func)
    transport.capture_event(None)

def test_empty_event():
    def mock_func(event):
        assert event == {}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({})

def test_unexpected_attributes_event():
    def mock_func(event):
        assert event == {"unexpected": "attribute"}
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"unexpected": "attribute"})

# Invalid Function
def test_non_callable_function():
    with pytest.raises(TypeError):
        transport = _FunctionTransport("not_a_function")
        transport.capture_event({"type": "test_event"})

def test_function_raises_exception():
    def mock_func(event):
        raise ValueError("Test Exception")
    transport = _FunctionTransport(mock_func)
    with pytest.raises(ValueError):
        transport.capture_event({"type": "test_event"})

# Performance and Scalability
def test_large_number_of_events():
    def mock_func(event):
        pass
    transport = _FunctionTransport(mock_func)
    for i in range(1000000):
        transport.capture_event({"type": "test_event", "id": i})

# Side Effects
def test_modify_global_variable():
    global_var = {"count": 0}
    def mock_func(event):
        global_var["count"] += 1
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event"})
    assert global_var["count"] == 1

def test_write_to_file(tmp_path):
    def mock_func(event):
        with open(tmp_path / "test_file.txt", "w") as f:
            f.write("test")
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event"})
    with open(tmp_path / "test_file.txt", "r") as f:
        assert f.read() == "test"

def test_network_call(monkeypatch):
    mock_get = Mock()
    monkeypatch.setattr("requests.get", mock_get)
    def mock_func(event):
        import requests
        requests.get("https://httpbin.org/get")
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event"})
    mock_get.assert_called_once_with("https://httpbin.org/get")

# Return Value
def test_return_value():
    def mock_func(event):
        pass
    transport = _FunctionTransport(mock_func)
    result = transport.capture_event({"type": "test_event"})
    assert result is None

# State Preservation
def test_state_preservation():
    def mock_func(event):
        pass
    transport = _FunctionTransport(mock_func)
    transport.capture_event({"type": "test_event"})
    assert transport._func == mock_func

🔘 (none found) − ⏪ Replay Tests

To optimize the provided Python program for better performance, we focus on areas where we might reduce overhead while making sure the logic remains unchanged. Here, the program already seems to follow good practices, but there's a bit of room for optimization.

One possible optimization is to avoid repeated attribute lookups by storing them as local variables, which is slightly faster and can therefore make the program more efficient. Another small tweak could be improving the superclass initialization.

Here’s the optimized version of your code.



1. **Using `super().__init__()`**: It's a more modern and efficient way to initialize the superclass.
2. **Local Variable for `self._func`**: Storing `self._func` in a local variable `func` reduces attribute lookups when calling it. This has a slight performance gain, particularly useful if `capture_event` is called frequently.

These refined changes make the code more efficient while preserving existing functionality and return types.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Jun 15, 2024
@codeflash-ai codeflash-ai bot requested a review from misrasaurabh1 June 15, 2024 02:04
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