⚡️ Speed up method BaseInputMixin.validate_field_type by 26% in src/backend/base/langflow/inputs/input_mixin.py

[codeflash-ai]

📄 BaseInputMixin.validate_field_type in src/backend/base/langflow/inputs/input_mixin.py

✨ Performance Summary:

• Speed Increase: 📈 26% (0.26x faster)
• Runtime Reduction: ⏱️ From 8.97 milliseconds down to 7.14 milliseconds (best of 28 runs)

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📝 Explanation and details

Sure, here is the optimized version of the given program.

Changes and Optimizations.

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✅ 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	✅ 4886 Passed	See below
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Coverage	100.0%

🌀 Generated Regression Tests Details

Click to view details

from enum import Enum

# imports
import pytest  # used for our unit tests
from langflow.inputs.input_mixin import BaseInputMixin
from pydantic import BaseModel, field_validator


# unit tests
def test_valid_field_types():
    # Test valid field types
    codeflash_output = BaseInputMixin.validate_field_type("str")
    codeflash_output = BaseInputMixin.validate_field_type("int")
    codeflash_output = BaseInputMixin.validate_field_type("float")
    codeflash_output = BaseInputMixin.validate_field_type("bool")
    codeflash_output = BaseInputMixin.validate_field_type("dict")
    codeflash_output = BaseInputMixin.validate_field_type("NestedDict")
    codeflash_output = BaseInputMixin.validate_field_type("file")
    codeflash_output = BaseInputMixin.validate_field_type("prompt")
    codeflash_output = BaseInputMixin.validate_field_type("code")
    codeflash_output = BaseInputMixin.validate_field_type("other")
    codeflash_output = BaseInputMixin.validate_field_type("table")
    codeflash_output = BaseInputMixin.validate_field_type("link")
    codeflash_output = BaseInputMixin.validate_field_type("slider")

def test_case_sensitivity():
    # Test case sensitivity
    codeflash_output = BaseInputMixin.validate_field_type("Str")
    codeflash_output = BaseInputMixin.validate_field_type("INT")
    codeflash_output = BaseInputMixin.validate_field_type("Float")

def test_invalid_field_types():
    # Test invalid field types
    codeflash_output = BaseInputMixin.validate_field_type("unknown")
    codeflash_output = BaseInputMixin.validate_field_type("random")
    codeflash_output = BaseInputMixin.validate_field_type("123")
    codeflash_output = BaseInputMixin.validate_field_type("")

def test_numeric_inputs():
    # Test numeric inputs
    codeflash_output = BaseInputMixin.validate_field_type(123)
    codeflash_output = BaseInputMixin.validate_field_type(0)
    codeflash_output = BaseInputMixin.validate_field_type(-1)

def test_special_characters():
    # Test inputs with special characters
    codeflash_output = BaseInputMixin.validate_field_type("str@")
    codeflash_output = BaseInputMixin.validate_field_type("int!")
    codeflash_output = BaseInputMixin.validate_field_type("float#")

def test_mixed_valid_invalid_inputs():
    # Test mixed valid and invalid inputs
    codeflash_output = BaseInputMixin.validate_field_type("str123")
    codeflash_output = BaseInputMixin.validate_field_type("int-str")
    codeflash_output = BaseInputMixin.validate_field_type("float!")

def test_large_scale_valid_inputs():
    # Test large scale valid inputs
    for _ in range(1000):
        codeflash_output = BaseInputMixin.validate_field_type("str")

def test_large_scale_invalid_inputs():
    # Test large scale invalid inputs
    for _ in range(1000):
        codeflash_output = BaseInputMixin.validate_field_type("invalid")

def test_large_scale_mixed_inputs():
    # Test large scale mixed inputs
    for i in range(1000):
        if i % 2 == 0:
            codeflash_output = BaseInputMixin.validate_field_type("str")
        else:
            codeflash_output = BaseInputMixin.validate_field_type("invalid")

def test_edge_cases():
    # Test edge cases
    codeflash_output = BaseInputMixin.validate_field_type(None)
    codeflash_output = BaseInputMixin.validate_field_type(True)
    codeflash_output = BaseInputMixin.validate_field_type(False)
    codeflash_output = BaseInputMixin.validate_field_type([])
    codeflash_output = BaseInputMixin.validate_field_type({})

def test_non_string_iterable_inputs():
    # Test non-string iterable inputs
    codeflash_output = BaseInputMixin.validate_field_type(["str"])
    codeflash_output = BaseInputMixin.validate_field_type(("int",))
    codeflash_output = BaseInputMixin.validate_field_type({"float"})

def test_whitespace_inputs():
    # Test inputs with leading or trailing whitespace
    codeflash_output = BaseInputMixin.validate_field_type(" str")
    codeflash_output = BaseInputMixin.validate_field_type("int ")
    codeflash_output = BaseInputMixin.validate_field_type(" float ")

def test_null_character_inputs():
    # Test inputs with embedded null characters
    codeflash_output = BaseInputMixin.validate_field_type("str\0")
    codeflash_output = BaseInputMixin.validate_field_type("int\0")
    codeflash_output = BaseInputMixin.validate_field_type("\0float")

def test_extremely_long_strings():
    # Test extremely long string inputs
    codeflash_output = BaseInputMixin.validate_field_type("str" * 1000)
    codeflash_output = BaseInputMixin.validate_field_type("int" * 1000)
    codeflash_output = BaseInputMixin.validate_field_type("float" * 1000)

def test_special_unicode_characters():
    # Test inputs with special Unicode characters
    codeflash_output = BaseInputMixin.validate_field_type("str😊")
    codeflash_output = BaseInputMixin.validate_field_type("int🚀")
    codeflash_output = BaseInputMixin.validate_field_type("float🌟")

def test_escape_sequences():
    # Test inputs with escape sequences
    codeflash_output = BaseInputMixin.validate_field_type("str\n")
    codeflash_output = BaseInputMixin.validate_field_type("int\t")
    codeflash_output = BaseInputMixin.validate_field_type("float\r")

def test_mixed_type_inputs():
    # Test inputs that are a mix of different types
    codeflash_output = BaseInputMixin.validate_field_type(["str", 123])
    codeflash_output = BaseInputMixin.validate_field_type({"int": "float"})
    codeflash_output = BaseInputMixin.validate_field_type(("bool", None))


def test_embedded_json():
    # Test inputs that are JSON strings
    codeflash_output = BaseInputMixin.validate_field_type('{"type": "str"}')
    codeflash_output = BaseInputMixin.validate_field_type('{"type": "int"}')
    codeflash_output = BaseInputMixin.validate_field_type('{"type": "float"}')

def test_embedded_xml():
    # Test inputs that are XML strings
    codeflash_output = BaseInputMixin.validate_field_type('<type>str</type>')
    codeflash_output = BaseInputMixin.validate_field_type('<type>int</type>')
    codeflash_output = BaseInputMixin.validate_field_type('<type>float</type>')
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
from enum import Enum

# imports
import pytest  # used for our unit tests
from langflow.inputs.input_mixin import BaseInputMixin
from pydantic import BaseModel, field_validator

# unit tests

# Basic Test Cases
def test_valid_field_types():
    codeflash_output = BaseInputMixin.validate_field_type("str")
    codeflash_output = BaseInputMixin.validate_field_type("int")
    codeflash_output = BaseInputMixin.validate_field_type("float")
    codeflash_output = BaseInputMixin.validate_field_type("bool")
    codeflash_output = BaseInputMixin.validate_field_type("dict")
    codeflash_output = BaseInputMixin.validate_field_type("NestedDict")
    codeflash_output = BaseInputMixin.validate_field_type("file")
    codeflash_output = BaseInputMixin.validate_field_type("prompt")
    codeflash_output = BaseInputMixin.validate_field_type("code")
    codeflash_output = BaseInputMixin.validate_field_type("table")
    codeflash_output = BaseInputMixin.validate_field_type("link")
    codeflash_output = BaseInputMixin.validate_field_type("slider")

def test_invalid_field_types():
    codeflash_output = BaseInputMixin.validate_field_type("unknown")
    codeflash_output = BaseInputMixin.validate_field_type("123")
    codeflash_output = BaseInputMixin.validate_field_type("boolean")

def test_case_sensitivity():
    codeflash_output = BaseInputMixin.validate_field_type("Str")
    codeflash_output = BaseInputMixin.validate_field_type("INT")
    codeflash_output = BaseInputMixin.validate_field_type("Float")

# Edge Test Cases
def test_empty_string():
    codeflash_output = BaseInputMixin.validate_field_type("")

def test_whitespace_strings():
    codeflash_output = BaseInputMixin.validate_field_type(" ")
    codeflash_output = BaseInputMixin.validate_field_type("   ")


def test_large_number_of_valid_inputs():
    valid_inputs = ["str", "int", "float", "bool", "dict", "NestedDict", "file", "prompt", "code", "table", "link", "slider"]
    for input_value in valid_inputs * 100:
        codeflash_output = BaseInputMixin.validate_field_type(input_value)

def test_large_number_of_invalid_inputs():
    invalid_inputs = ["unknown", "123", "boolean", "Str", "INT", "Float"]
    for input_value in invalid_inputs * 100:
        codeflash_output = BaseInputMixin.validate_field_type(input_value)


def test_stress_test_with_large_input():
    codeflash_output = BaseInputMixin.validate_field_type("a" * 10000)

# Boundary Testing
def test_boundary_length_strings():
    codeflash_output = BaseInputMixin.validate_field_type("a" * 255)
    codeflash_output = BaseInputMixin.validate_field_type("a" * 256)
    codeflash_output = BaseInputMixin.validate_field_type("a" * 257)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

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