⚡️ Speed up method `AstraDBVectorStoreComponent.get_database_object` by 1,269% in PR #6236 (`LFOSS-492`) by codeflash-ai[bot] · Pull Request #6640 · langflow-ai/langflow

codeflash-ai · 2025-02-14T21:45:37Z

⚡️ This pull request contains optimizations for PR #6236

If you approve this dependent PR, these changes will be merged into the original PR branch LFOSS-492.

This PR will be automatically closed if the original PR is merged.

📄 1,269% (12.69x) speedup for `AstraDBVectorStoreComponent.get_database_object` in `src/backend/base/langflow/components/vectorstores/astradb.py`

⏱️ Runtime : 9.04 milliseconds → 660 microseconds (best of 19 runs)

📝 Explanation and details

To optimize the provided code for better performance, we can implement a few strategies.

Below is the refactored code with these performance optimizations.

Key Changes.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1012 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	undefined

🌀 Generated Regression Tests Details

from unittest import mock

# imports
import pytest  # used for our unit tests
# function to test
from astrapy import DataAPIClient
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent


# unit tests
def test_valid_api_endpoint_provided():
    # Test with a valid API endpoint provided
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_no_api_endpoint_provided():
    # Test with no API endpoint provided, should call get_api_endpoint
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        with mock.patch.object(component, 'get_api_endpoint', return_value="https://mocked.endpoint"):
            codeflash_output = component.get_database_object()

def test_empty_keyspace():
    # Test with an empty keyspace
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_whitespace_keyspace():
    # Test with a keyspace containing only whitespace
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="   ")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_none_keyspace():
    # Test with a None keyspace
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace=None)
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_invalid_token():
    # Test with an invalid token
    component = AstraDBVectorStoreComponent(token="invalid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', side_effect=Exception("Invalid token")):
        with pytest.raises(ValueError, match="Error fetching database object: Invalid token"):
            component.get_database_object(api_endpoint="https://valid.endpoint")


def test_invalid_api_endpoint():
    # Test with an invalid API endpoint
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', side_effect=Exception("Invalid API endpoint")):
        with pytest.raises(ValueError, match="Error fetching database object: Invalid API endpoint"):
            component.get_database_object(api_endpoint="invalid_endpoint")


def test_extremely_long_api_endpoint():
    # Test with an extremely long API endpoint
    long_api_endpoint = "https://" + "a" * 1000 + ".endpoint"
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint=long_api_endpoint)

def test_extremely_long_keyspace():
    # Test with an extremely long keyspace
    long_keyspace = "a" * 1000
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace=long_keyspace)
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_large_scale():
    # Large scale test with multiple requests
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
        for _ in range(1000):
            codeflash_output = component.get_database_object(api_endpoint="https://valid.endpoint")

def test_exception_propagation():
    # Test exception propagation
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(DataAPIClient, 'get_database', side_effect=Exception("Some error")):
        with pytest.raises(ValueError, match="Error fetching database object: Some error"):
            component.get_database_object(api_endpoint="https://valid.endpoint")

def test_correct_method_calls():
    # Test that correct methods are called
    component = AstraDBVectorStoreComponent(token="valid_token", environment="prod", keyspace="valid_keyspace")
    with mock.patch.object(component, 'get_api_endpoint', return_value="https://mocked.endpoint") as mock_get_api_endpoint:
        with mock.patch.object(component, 'get_keyspace', return_value="mocked_keyspace") as mock_get_keyspace:
            with mock.patch.object(DataAPIClient, 'get_database', return_value="mock_database"):
                codeflash_output = component.get_database_object()
                mock_get_api_endpoint.assert_called_once()
                mock_get_keyspace.assert_called_once()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from unittest.mock import MagicMock, patch

# imports
import pytest  # used for our unit tests
# function to test
from astrapy import DataAPIClient
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent

# unit tests

# Helper function to create a mock AstraDBVectorStoreComponent instance
def create_mock_component(token, environment, api_endpoint, keyspace):
    component = AstraDBVectorStoreComponent()
    component.token = token
    component.environment = environment
    component.api_endpoint = api_endpoint
    component.keyspace = keyspace
    return component

# Basic Test Cases




def test_get_database_object_invalid_api_endpoint():
    component = create_mock_component("valid_token", "valid_environment", "invalid_url", "my_keyspace")
    with pytest.raises(ValueError, match="Error fetching database object:"):
        component.get_database_object()

# Error Handling Test Cases

…by 1,269% in PR #6236 (`LFOSS-492`) To optimize the provided code for better performance, we can implement a few strategies. Below is the refactored code with these performance optimizations. ### Key Changes.

codeflash-ai · 2025-02-14T21:59:15Z

src/backend/base/langflow/components/vectorstores/astradb.py

+        if not self.api_endpoint_cache:
+            self.api_endpoint_cache = self.get_api_endpoint_static_cached(
+                token=self.token,
+                environment=self.environment,
+                api_endpoint=self.api_endpoint,


Suggested change

if not self.api_endpoint_cache:

self.api_endpoint_cache = self.get_api_endpoint_static_cached(

token=self.token,

environment=self.environment,

api_endpoint=self.api_endpoint,

if self.api_endpoint_cache is None:

self.token, self.environment, self.api_endpoint, self.database_name

codeflash-ai · 2025-02-14T21:59:15Z

src/backend/base/langflow/components/vectorstores/astradb.py

+        return self.get_api_endpoint_static(
+            token=token,
+            environment=environment,
+            api_endpoint=api_endpoint,
+            database_name=database_name,
+        )


Suggested change

return self.get_api_endpoint_static(

token=token,

environment=environment,

api_endpoint=api_endpoint,

database_name=database_name,

)

return self.get_api_endpoint_static(token, environment, api_endpoint, database_name)

codeflash-ai · 2025-02-14T21:59:18Z

⚡️ Codeflash found optimizations for this PR

📄 21% (0.21x) speedup for `AstraDBVectorStoreComponent.get_api_endpoint` in `src/backend/base/langflow/components/vectorstores/astradb.py`

⏱️ Runtime : 70.3 microseconds → 58.1 microseconds (best of 38 runs)

📝 Explanation and details

Here's the rewritten Python program for optimized runtime using caching more effectively.

Explanation.

Removed Redundant Re-checks:
- Setting api_endpoint_cache to None directly in the constructor simplifies the logic of get_api_endpoint.
Efficient Cache Handling.
- The functools.lru_cache is used to cache results of get_api_endpoint_static_cached, making repetitive calls with the same parameters more efficient.
- By initializing the cache as None in the __init__ method, we ensure it's only set once and reused.
Extract and Initialize Constructor Arguments.
- Storing token, environment, api_endpoint, and database_name as instance variables within the constructor directly avoids multiple lookups and facilitates faster access.

This optimizes the code by reducing overhead through caching and ensuring that the initialization sets up the required parameters in a better organized manner.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 7 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	undefined

🌀 Generated Regression Tests Details

import functools
from unittest.mock import patch

# imports
import pytest  # used for our unit tests
# function to test
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent


# unit tests
@pytest.fixture
def setup_component():
    # Fixture to set up the component with default attributes
    component = AstraDBVectorStoreComponent(
        token="default_token",
        environment="default_environment",
        api_endpoint="default_endpoint",
        database_name="default_db"
    )
    return component


def test_different_input_combinations(setup_component):
    # Test different valid inputs
    component = setup_component
    with patch.object(component, 'get_api_endpoint_static', return_value="endpoint_value"):
        component.token = "tokenA"
        component.environment = "envA"
        component.api_endpoint = "endpointA"
        component.database_name = "dbA"
        codeflash_output = component.get_api_endpoint()


def test_edge_cases(setup_component):
    # Test edge cases with special characters and long strings
    component = setup_component
    with patch.object(component, 'get_api_endpoint_static', return_value="endpoint_value"):
        component.token = "!@#$"
        component.environment = "%^&*"
        component.api_endpoint = "()_+"
        component.database_name = "{}|:"
        codeflash_output = component.get_api_endpoint()
        
        component.token = "a" * 1000
        component.environment = "b" * 1000
        component.api_endpoint = "c" * 1000
        component.database_name = "d" * 1000
        codeflash_output = component.get_api_endpoint()






import functools
import threading

# imports
import pytest  # used for our unit tests
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent


# Mocking the LCVectorStoreComponent and get_api_endpoint_static for testing
class MockLCVectorStoreComponent:
    def __init__(self, **kwargs):
        pass

    def get_api_endpoint_static(self, token, environment, api_endpoint, database_name):
        return f"{token}-{environment}-{api_endpoint}-{database_name}"

AstraDBVectorStoreComponent.__bases__ = (MockLCVectorStoreComponent,)


# unit tests

# Basic Functionality






def test_missing_attributes():
    component = AstraDBVectorStoreComponent()
    with pytest.raises(AttributeError):
        component.get_api_endpoint()

# Concurrency



def test_integration_with_parent_class():
    component = AstraDBVectorStoreComponent(
        token="valid_token",
        environment="production",
        api_endpoint="https://api.example.com",
        database_name="main_db"
    )

# State Verification

codeflash-ai · 2025-02-14T22:03:42Z

src/backend/base/langflow/components/vectorstores/astradb.py

+        if self.keyspace:
+            return self.strip_keyspace(self.keyspace)
        return None


Suggested change

if self.keyspace:

return self.strip_keyspace(self.keyspace)

return None

return self.strip_keyspace(self.keyspace) if self.keyspace else None

codeflash-ai · 2025-02-14T22:03:42Z

src/backend/base/langflow/components/vectorstores/astradb.py

+        )
+
+    @staticmethod
+    @functools.lru_cache(maxsize=128)


Suggested change

@functools.lru_cache(maxsize=128)

@functools.cache

codeflash-ai · 2025-02-14T22:03:45Z

⚡️ Codeflash found optimizations for this PR

📄 18% (0.18x) speedup for `AstraDBVectorStoreComponent.get_keyspace` in `src/backend/base/langflow/components/vectorstores/astradb.py`

⏱️ Runtime : 3.41 milliseconds → 2.90 milliseconds (best of 6 runs)

📝 Explanation and details

Explanation of Changes.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1379 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	undefined

🌀 Generated Regression Tests Details

import functools

# imports
import pytest  # used for our unit tests
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent


# unit tests
def test_basic_functionality():
    # Non-empty keyspace with no whitespace
    component = AstraDBVectorStoreComponent(keyspace="test_keyspace")
    codeflash_output = component.get_keyspace()
    
    # Non-empty keyspace with leading and trailing whitespace
    component = AstraDBVectorStoreComponent(keyspace="  test_keyspace  ")
    codeflash_output = component.get_keyspace()
    
    # Non-empty keyspace with only leading whitespace
    component = AstraDBVectorStoreComponent(keyspace="  test_keyspace")
    codeflash_output = component.get_keyspace()
    
    # Non-empty keyspace with only trailing whitespace
    component = AstraDBVectorStoreComponent(keyspace="test_keyspace  ")
    codeflash_output = component.get_keyspace()

def test_edge_cases():
    # Empty string as keyspace
    component = AstraDBVectorStoreComponent(keyspace="")
    codeflash_output = component.get_keyspace()
    
    # None as keyspace
    component = AstraDBVectorStoreComponent(keyspace=None)
    codeflash_output = component.get_keyspace()
    
    # String with only whitespace
    component = AstraDBVectorStoreComponent(keyspace="   ")
    codeflash_output = component.get_keyspace()
    
    # String with special characters
    component = AstraDBVectorStoreComponent(keyspace="  @#$%^&*()_+  ")
    codeflash_output = component.get_keyspace()

def test_type_handling():
    # Integer as keyspace (should raise an error)
    with pytest.raises(AttributeError):
        component = AstraDBVectorStoreComponent(keyspace=12345)
        component.get_keyspace()
    
    # List as keyspace (should raise an error)
    with pytest.raises(AttributeError):
        component = AstraDBVectorStoreComponent(keyspace=["test_keyspace"])
        component.get_keyspace()
    
    # Dictionary as keyspace (should raise an error)
    with pytest.raises(AttributeError):
        component = AstraDBVectorStoreComponent(keyspace={"key": "value"})
        component.get_keyspace()

def test_caching_behavior():
    # Repeated calls with the same keyspace
    component = AstraDBVectorStoreComponent(keyspace="  test_keyspace  ")
    codeflash_output = component.get_keyspace()
    codeflash_output = component.get_keyspace()
    
    # Different keyspaces to test cache eviction
    for i in range(129):
        component = AstraDBVectorStoreComponent(keyspace=f"keyspace{i}")
        codeflash_output = component.get_keyspace()

def test_performance_and_scalability():
    # Large keyspace string
    large_keyspace = "a" * 10000
    component = AstraDBVectorStoreComponent(keyspace=large_keyspace)
    codeflash_output = component.get_keyspace()
    
    # Very large number of different keyspaces
    for i in range(1000):
        component = AstraDBVectorStoreComponent(keyspace=f"keyspace{i}")
        codeflash_output = component.get_keyspace()


def test_boundary_conditions():
    # Minimum length keyspace
    component = AstraDBVectorStoreComponent(keyspace="a")
    codeflash_output = component.get_keyspace()
    
    # Maximum length keyspace (feasible within reasonable limits)
    max_length_keyspace = "a" * 1000
    component = AstraDBVectorStoreComponent(keyspace=max_length_keyspace)
    codeflash_output = component.get_keyspace()

def test_special_characters_and_unicode():
    # Unicode characters in keyspace
    component = AstraDBVectorStoreComponent(keyspace="  测试键空间  ")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with newline characters
    component = AstraDBVectorStoreComponent(keyspace="  test\nkeyspace  ")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with tab characters
    component = AstraDBVectorStoreComponent(keyspace="  test\tkeyspace  ")
    codeflash_output = component.get_keyspace()

def test_rare_edge_cases():
    # Keyspace with embedded null characters
    component = AstraDBVectorStoreComponent(keyspace="test\0keyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with mixed whitespace characters
    component = AstraDBVectorStoreComponent(keyspace=" \t\n test_keyspace \n\t ")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with escape sequences
    component = AstraDBVectorStoreComponent(keyspace="test\\nkeyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with control characters
    component = AstraDBVectorStoreComponent(keyspace="test\x1b[31mkeyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with extremely large whitespace padding
    component = AstraDBVectorStoreComponent(keyspace=" " * 1000 + "test_keyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with non-printable characters
    component = AstraDBVectorStoreComponent(keyspace="test\x07keyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with high Unicode characters
    component = AstraDBVectorStoreComponent(keyspace="test\u200bkeyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with SQL injection-like patterns
    component = AstraDBVectorStoreComponent(keyspace="test_keyspace; DROP TABLE users;")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with JSON-like strings
    component = AstraDBVectorStoreComponent(keyspace='{"key": "value"}')
    codeflash_output = component.get_keyspace()
    
    # Keyspace with HTML/XML-like content
    component = AstraDBVectorStoreComponent(keyspace="<div>test_keyspace</div>")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with path-like strings
    component = AstraDBVectorStoreComponent(keyspace="/path/to/keyspace")
    codeflash_output = component.get_keyspace()
    
    # Keyspace with special whitespace characters
    component = AstraDBVectorStoreComponent(keyspace="test\u00A0keyspace")
    codeflash_output = component.get_keyspace()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import functools

# imports
import pytest  # used for our unit tests
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent

# unit tests

# Test basic functionality
def test_basic_keyspace_no_whitespace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "keyspace1"
    codeflash_output = component.get_keyspace()

def test_basic_keyspace_leading_whitespace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  keyspace2"
    codeflash_output = component.get_keyspace()

def test_basic_keyspace_trailing_whitespace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "keyspace3  "
    codeflash_output = component.get_keyspace()

def test_basic_keyspace_both_whitespace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  keyspace4  "
    codeflash_output = component.get_keyspace()

# Test edge cases
def test_edge_empty_keyspace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = ""
    codeflash_output = component.get_keyspace()

def test_edge_none_keyspace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = None
    codeflash_output = component.get_keyspace()

def test_edge_whitespace_only_keyspace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "    "
    codeflash_output = component.get_keyspace()

def test_edge_special_characters_keyspace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  key$pace_5  "
    codeflash_output = component.get_keyspace()

def test_edge_non_ascii_keyspace():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  ключевое_пространство  "
    codeflash_output = component.get_keyspace()

# Test cache behavior
def test_cache_behavior_repeated_calls():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  keyspace6  "
    codeflash_output = component.get_keyspace()
    codeflash_output = component.get_keyspace()

def test_cache_behavior_different_keyspaces_same_stripped_value():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  keyspace7  "
    codeflash_output = component.get_keyspace()
    component.keyspace = "keyspace7  "
    codeflash_output = component.get_keyspace()

# Test performance and scalability
def test_large_keyspace_string():
    component = AstraDBVectorStoreComponent()
    large_keyspace = "  " + "a" * 10000 + "  "
    component.keyspace = large_keyspace
    codeflash_output = component.get_keyspace()

def test_cache_limit():
    component = AstraDBVectorStoreComponent()
    keyspaces = [f"  keyspace_{i}  " for i in range(200)]
    for keyspace in keyspaces:
        component.keyspace = keyspace
        codeflash_output = component.get_keyspace()

# Test invalid inputs
def test_invalid_input_integer():
    component = AstraDBVectorStoreComponent()
    component.keyspace = 12345
    with pytest.raises(AttributeError):
        component.get_keyspace()



def test_class_keyspace_set_and_retrieve():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "  keyspace10  "
    codeflash_output = component.get_keyspace()

def test_class_keyspace_not_set():
    component = AstraDBVectorStoreComponent()
    codeflash_output = component.get_keyspace()

# Test side effects and state management
def test_strip_keyspace_does_not_modify_original():
    component = AstraDBVectorStoreComponent()
    original_keyspace = "  keyspace11  "
    component.keyspace = original_keyspace
    component.get_keyspace()

# Test special cases
def test_keyspace_with_newline_characters():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "\nkeyspace11\n"
    codeflash_output = component.get_keyspace()

def test_keyspace_with_tab_characters():
    component = AstraDBVectorStoreComponent()
    component.keyspace = "\tkeyspace12\t"
    codeflash_output = component.get_keyspace()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

codeflash-ai · 2025-02-14T22:14:06Z

src/backend/base/langflow/components/vectorstores/astradb.py

+        )
+
+    @staticmethod
+    @functools.lru_cache(maxsize=128)


Suggested change

@functools.lru_cache(maxsize=128)

@functools.lru_cache(maxsize=512) # Increased cache size for better performance on frequent look-ups

codeflash-ai · 2025-02-14T22:14:09Z

⚡️ Codeflash found optimizations for this PR

📄 53% (0.53x) speedup for `AstraDBVectorStoreComponent.strip_keyspace` in `src/backend/base/langflow/components/vectorstores/astradb.py`

⏱️ Runtime : 3.51 milliseconds → 2.29 milliseconds (best of 157 runs)

📝 Explanation and details

To optimize the given Python code for improved performance, I will focus on implementing a more efficient method to handle repetitive operations and streamline the processing within the AstraDBVectorStoreComponent class. The code provided is already quite minimal, but I can optimize it further by improving the caching mechanism as applicable.

Here's the optimized code.

Changes made.

Increased the LRU Cache Size.
- Increased the maxsize of the lru_cache from 128 to 512. This change will allow caching more keyspace values, which might be beneficial if the application frequently uses various keyspace strings, ultimately reducing the number of times the function needs to recompute the stripped value.
Comment Annotations for Better Understanding.
- Added a comment to explain the reason for increasing the cache size for better performance on frequent look-ups.

This optimization ensures that the code runs faster by enhancing the memoization capability of the strip_keyspace method, accommodating more unique keys in the cache, which is crucial when there is a high variance in keyspace values.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 555 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	undefined

🌀 Generated Regression Tests Details

import functools

# imports
import pytest  # used for our unit tests
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent

# unit tests

# Basic Functionality
def test_strip_keyspace_standard_input():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(" keyspace ")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("  keyspace")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("keyspace  ")

# Edge Cases
def test_strip_keyspace_empty_string():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("")

def test_strip_keyspace_whitespace_only():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(" ")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("    ")

def test_strip_keyspace_no_whitespace():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("keyspace")

# Mixed Whitespace Characters
def test_strip_keyspace_tabs_and_newlines():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("\tkeyspace\t")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("\nkeyspace\n")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("\t\n keyspace \n\t")

# Non-String Input (should raise an error)
def test_strip_keyspace_non_string_input():
    with pytest.raises(AttributeError):
        AstraDBVectorStoreComponent.strip_keyspace(None)
    with pytest.raises(AttributeError):
        AstraDBVectorStoreComponent.strip_keyspace(123)
    with pytest.raises(AttributeError):
        AstraDBVectorStoreComponent.strip_keyspace(["keyspace"])

# Unicode and Special Characters
def test_strip_keyspace_unicode_whitespace():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("\u2003keyspace\u2003")  # Em space
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("\u3000keyspace\u3000")  # Ideographic space

def test_strip_keyspace_special_characters():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("key space")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace("key\tspace")

# Large Scale Test Cases
def test_strip_keyspace_large_input_string():
    large_input = " " * 1000000 + "keyspace" + " " * 1000000
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(large_input)

def test_strip_keyspace_large_input_with_mixed_content():
    large_input = " a " * 1000000 + "keyspace" + " b " * 1000000
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(large_input)

# Performance and Scalability
def test_strip_keyspace_repeated_calls_same_input():
    for _ in range(100):
        codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(" keyspace ")

def test_strip_keyspace_different_inputs_cache_size():
    for i in range(150):
        codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(f" keyspace{i} ")

# Deterministic Behavior
def test_strip_keyspace_consistent_results():
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(" keyspace ")
    codeflash_output = AstraDBVectorStoreComponent.strip_keyspace(" keyspace ")
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import functools

# imports
import pytest  # used for our unit tests
from langflow.base.vectorstores.model import LCVectorStoreComponent
from langflow.components.vectorstores.astradb import \
    AstraDBVectorStoreComponent

# unit tests

# Define the class to access the static method
component = AstraDBVectorStoreComponent()

def test_basic_functionality():
    # Basic functionality tests
    codeflash_output = component.strip_keyspace("keyspace")
    codeflash_output = component.strip_keyspace("  keyspace  ")
    codeflash_output = component.strip_keyspace("   keyspace")
    codeflash_output = component.strip_keyspace("keyspace   ")

def test_edge_cases():
    # Edge cases tests
    codeflash_output = component.strip_keyspace("")
    codeflash_output = component.strip_keyspace("   ")
    with pytest.raises(AttributeError):
        component.strip_keyspace(None)
    with pytest.raises(AttributeError):
        component.strip_keyspace(123)
    with pytest.raises(AttributeError):
        component.strip_keyspace(["keyspace"])

def test_special_characters():
    # Special characters tests
    codeflash_output = component.strip_keyspace("\tkeyspace\t")
    codeflash_output = component.strip_keyspace("\nkeyspace\n")
    codeflash_output = component.strip_keyspace("keyspace\n")
    codeflash_output = component.strip_keyspace("\t\nkeyspace\t\n")

def test_unicode_and_multilingual_strings():
    # Unicode and multilingual strings tests
    codeflash_output = component.strip_keyspace("  ключевое пространство  ")
    codeflash_output = component.strip_keyspace("   空間   ")
    codeflash_output = component.strip_keyspace("  keyspace空間  ")

def test_performance_and_scalability():
    # Performance and scalability tests
    codeflash_output = component.strip_keyspace(" " * 10000 + "keyspace" + " " * 10000)
    codeflash_output = component.strip_keyspace("key" + " " * 100000 + "space")

def test_cache_behavior():
    # Cache behavior tests
    # Repeated calls with the same input
    for _ in range(100):
        codeflash_output = component.strip_keyspace("  keyspace  ")
    
    # Cache size limit
    for i in range(150):
        component.strip_keyspace(f"keyspace{i}")
    # After more than 128 unique calls, the first entry should be evicted
    codeflash_output = component.strip_keyspace("  keyspace  ")

def test_whitespace_characters_other_than_space():
    # Whitespace characters other than space tests
    codeflash_output = component.strip_keyspace("\t\t\t")
    codeflash_output = component.strip_keyspace("\n\n\n")
    codeflash_output = component.strip_keyspace("\t \n \t")

def test_strings_with_embedded_whitespace():
    # Strings with embedded whitespace tests
    codeflash_output = component.strip_keyspace("   key space   ")
    codeflash_output = component.strip_keyspace("\tkey\tspace\t")
    codeflash_output = component.strip_keyspace("\nkey\nspace\n")

def test_strings_with_non_printable_characters():
    # Strings with non-printable characters tests
    codeflash_output = component.strip_keyspace("\x00keyspace\x00")
    codeflash_output = component.strip_keyspace("\x01\x02keyspace\x03\x04")
    codeflash_output = component.strip_keyspace(" \x00keyspace\x00 ")

def test_strings_with_escape_sequences():
    # Strings with escape sequences tests
    codeflash_output = component.strip_keyspace("  key\\nspace  ")
    codeflash_output = component.strip_keyspace("  key\\tspace  ")

def test_strings_with_various_encodings():
    # Strings with various encodings tests
    codeflash_output = component.strip_keyspace("  \u006B\u0065\u0079\u0073\u0070\u0061\u0063\u0065  ")
    codeflash_output = component.strip_keyspace("  \U0000006B\U00000065\U00000079\U00000073\U00000070\U00000061\U00000063\U00000065  ")

def test_strings_with_control_characters():
    # Strings with control characters tests
    codeflash_output = component.strip_keyspace("  keyspace\u0007  ")
    codeflash_output = component.strip_keyspace("\u0007keyspace\u0007")

if __name__ == "__main__":
    pytest.main()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

⚡️ Speed up method AstraDBVectorStoreComponent.get_database_object …

f55a73f

…by 1,269% in PR #6236 (`LFOSS-492`) To optimize the provided code for better performance, we can implement a few strategies. Below is the refactored code with these performance optimizations. ### Key Changes.

codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Feb 14, 2025

codeflash-ai bot mentioned this pull request Feb 14, 2025

feat: Generic Callback Dialog Input for Custom Component #6236

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dosubot bot added the size:M This PR changes 30-99 lines, ignoring generated files. label Feb 14, 2025

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⚡️ Speed up method `AstraDBVectorStoreComponent.get_database_object` by 1,269% in PR #6236 (`LFOSS-492`)#6640

⚡️ Speed up method `AstraDBVectorStoreComponent.get_database_object` by 1,269% in PR #6236 (`LFOSS-492`)#6640
codeflash-ai[bot] wants to merge 2 commits intoLFOSS-492from
codeflash/optimize-pr6236-2025-02-14T21.45.31

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	@functools.lru_cache(maxsize=128)
	@functools.lru_cache(maxsize=512) # Increased cache size for better performance on frequent look-ups

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codeflash-ai bot commented Feb 14, 2025

⚡️ This pull request contains optimizations for PR #6236

📄 1,269% (12.69x) speedup for AstraDBVectorStoreComponent.get_database_object in src/backend/base/langflow/components/vectorstores/astradb.py

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⚡️ Codeflash found optimizations for this PR

📄 21% (0.21x) speedup for AstraDBVectorStoreComponent.get_api_endpoint in src/backend/base/langflow/components/vectorstores/astradb.py

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⚡️ Codeflash found optimizations for this PR

📄 18% (0.18x) speedup for AstraDBVectorStoreComponent.get_keyspace in src/backend/base/langflow/components/vectorstores/astradb.py

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⚡️ Codeflash found optimizations for this PR

📄 53% (0.53x) speedup for AstraDBVectorStoreComponent.strip_keyspace in src/backend/base/langflow/components/vectorstores/astradb.py

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📄 1,269% (12.69x) speedup for `AstraDBVectorStoreComponent.get_database_object` in `src/backend/base/langflow/components/vectorstores/astradb.py`

📄 21% (0.21x) speedup for `AstraDBVectorStoreComponent.get_api_endpoint` in `src/backend/base/langflow/components/vectorstores/astradb.py`

📄 18% (0.18x) speedup for `AstraDBVectorStoreComponent.get_keyspace` in `src/backend/base/langflow/components/vectorstores/astradb.py`

📄 53% (0.53x) speedup for `AstraDBVectorStoreComponent.strip_keyspace` in `src/backend/base/langflow/components/vectorstores/astradb.py`