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⚡️ Speed up method StringParser._next_state by 15% in src/black/trans.py #61

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@codeflash-ai codeflash-ai bot commented Dec 16, 2024

📄 StringParser._next_state in src/black/trans.py

✨ Performance Summary:

  • Speed Increase: 📈 15% (0.15x faster)
  • Runtime Reduction: ⏱️ From 98.7 microseconds down to 86.1 microseconds (best of 26 runs)

📝 Explanation and details

To optimize the given Python code, we can follow a few key strategies.

  1. Efficient Data Structures: Use appropriate data structures.

Here’s the optimized version of the code.

Key Improvements.


Correctness verification

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

Test Status Details
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 25 Passed See below
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Coverage 100.0%

🌀 Generated Regression Tests Details

Click to view details
from collections.abc import Iterator
from typing import Any, Final, Optional
from unittest.mock import MagicMock, patch

# imports
import pytest  # used for our unit tests
# function to test
from black.nodes import is_empty_lpar, is_empty_rpar
from black.trans import StringParser
from blib2to3.pgen2 import token
from blib2to3.pytree import Leaf

LPAR: Final = 7
RPAR: Final = 8
from black.trans import StringParser

# unit tests

@pytest.fixture
def parser():
    return StringParser()

# Basic Functionality


def test_non_parenthesis_tokens(parser):
    leaf_name = Leaf(token.NAME, 'name')
    codeflash_output = parser._next_state(leaf_name)

# Empty Parentheses Handling
def test_empty_lpar(parser):
    leaf_empty_lpar = Leaf(token.LPAR, '')
    codeflash_output = parser._next_state(leaf_empty_lpar)

def test_empty_rpar(parser):
    leaf_empty_rpar = Leaf(token.RPAR, '')
    codeflash_output = parser._next_state(leaf_empty_rpar)

# Unmatched Parentheses
def test_single_unmatched_lpar(parser):
    leaf_lpar = Leaf(token.LPAR, '(')
    codeflash_output = parser._next_state(leaf_lpar)


def test_state_transition_using_lookup_table(parser):
    leaf_lpar = Leaf(token.LPAR, '(')
    leaf_rpar = Leaf(token.RPAR, ')')
    parser._goto = {(parser.START, token.LPAR): parser.LPAR, (parser.LPAR, token.RPAR): parser.RPAR}
    codeflash_output = parser._next_state(leaf_lpar)
    codeflash_output = parser._next_state(leaf_rpar)

def test_state_transition_with_default_token(parser):
    leaf_name = Leaf(token.NAME, 'name')
    parser._goto = {(parser.START, parser.DEFAULT_TOKEN): parser.DONE}
    codeflash_output = parser._next_state(leaf_name)

# Error Handling

def test_non_leaf_object(parser):
    non_leaf = "not a leaf"
    with pytest.raises(AttributeError):
        parser._next_state(non_leaf)

# Large Scale Test Cases


def test_maximum_token_type(parser):
    leaf_max = Leaf(255, 'max')
    codeflash_output = parser._next_state(leaf_max)

def test_minimum_token_type(parser):
    leaf_min = Leaf(0, 'min')
    codeflash_output = parser._next_state(leaf_min)

# State Persistence

def test_integration_with_leaf_class_methods(parser):
    leaf = Leaf(token.NAME, 'name')
    codeflash_output = parser._next_state(leaf)

# Rare or Unexpected Edge Cases
def test_leaf_with_missing_attributes(parser):
    class IncompleteLeaf:
        def __init__(self, value):
            self.value = value
    leaf_missing_type = IncompleteLeaf('(')
    with pytest.raises(AttributeError):
        parser._next_state(leaf_missing_type)




def test_state_reset_during_parsing(parser):
    leaf_lpar = Leaf(token.LPAR, '(')
    leaf_rpar = Leaf(token.RPAR, ')')
    codeflash_output = parser._next_state(leaf_lpar)
    parser._state = parser.START
    codeflash_output = parser._next_state(leaf_rpar)


def test_special_characters_in_leaf_values(parser):
    leaf_newline = Leaf(token.STRING, '\n')
    codeflash_output = parser._next_state(leaf_newline)

def test_leaf_with_complex_context(parser):
    complex_context = ("prefix", ((1, 2), (3, 4)))
    leaf_complex = Leaf(token.NAME, 'name', context=complex_context)
    codeflash_output = parser._next_state(leaf_complex)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
from typing import Any, Final, Iterator, Optional

# imports
import pytest  # used for our unit tests
from black.trans import StringParser
from blib2to3.pgen2 import token
from blib2to3.pytree import Leaf

# function to test
LPAR: Final = 7
RPAR: Final = 8
from black.trans import StringParser

# unit tests

# Helper function to create a Leaf node
def create_leaf(type: int, value: str) -> Leaf:
    return Leaf(type, value)

# Basic Functionality Tests

def test_simple_invalid_transitions():
    parser = StringParser()
    codeflash_output = parser._next_state(create_leaf(token.STRING, "string"))
    with pytest.raises(RuntimeError):
        parser._next_state(create_leaf(token.COLON, ":"))

# Parentheses Handling Tests


def test_empty_parentheses():
    parser = StringParser()
    codeflash_output = parser._next_state(create_leaf(token.LPAR, ""))
    codeflash_output = parser._next_state(create_leaf(token.RPAR, ""))

# Edge Case Tests

def test_single_token():
    parser = StringParser()
    codeflash_output = parser._next_state(create_leaf(token.STRING, "string"))

📣 **Feedback**

If you have any feedback or need assistance, feel free to join our Discord community:

Discord

To optimize the given Python code, we can follow a few key strategies.

2. **Efficient Data Structures:** Use appropriate data structures.

Here’s the optimized version of the code.

Key Improvements.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Dec 16, 2024
@codeflash-ai codeflash-ai bot requested a review from misrasaurabh1 December 16, 2024 05:35
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