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@codeflash-ai codeflash-ai bot commented Apr 5, 2025

📄 132% (1.32x) speedup for InfraResource.matches_filters in libs/agno/agno/infra/resource.py

⏱️ Runtime : 2.39 milliseconds 1.03 millisecond (best of 355 runs)

📝 Explanation and details

To optimize the provided Python program for performance, we'll focus on reducing the overall computational complexity and memory access times. The main bottlenecks seem to be in the matches_filters function and the frequent calls to get_group_name, get_resource_name, and get_resource_type_list. To improve efficiency, we'll refactor the relevant portions of the code and make sure that functions and conditional checks are carried out in a more optimized manner.

Here's the refactored code.

Changes Made.

  1. Pre-calculate values: For filter checks in matches_filters, the relevant values (group_name, resource_name, resource_type_list) are calculated once and reused. This reduces repetitive method calls.
  2. Reduce Conditional Checks: Instead of nested conditional checks within each filter check, we pre-calculate values where necessary, minimizing the overhead of conditional branches.
  3. Efficient List Operations: Ensured list operations are performed in a concise manner without repetitive checks.

The optimization should improve the overall performance of the provided Python program, specifically in reducing the time complexity of repeated operations. The results after optimization should be more efficient, especially when dealing with large numbers of InfraResource objects.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 6086 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests Details
import logging
from pathlib import Path
from typing import Any, Dict, List, Optional

# imports
import pytest  # used for our unit tests
from agno.infra.base import InfraBase
from agno.infra.resource import InfraResource
from agno.utils.log import logger
# function to test
from agno.workspace.settings import WorkspaceSettings
from pydantic import BaseModel, ConfigDict

# unit tests

# Basic Functionality
def test_no_filters():
    resource = InfraResource(name="test-resource")
    codeflash_output = resource.matches_filters()

def test_group_filter():
    resource = InfraResource(name="test-resource", group="test-group")
    codeflash_output = resource.matches_filters(group_filter="test-group")

def test_name_filter():
    resource = InfraResource(name="test-resource")
    codeflash_output = resource.matches_filters(name_filter="test-resource")

def test_type_filter():
    resource = InfraResource(name="test-resource", resource_type="test-type")
    codeflash_output = resource.matches_filters(type_filter="test-type")

# Combination of Filters
def test_group_and_name_filters():
    resource = InfraResource(name="test-resource", group="test-group")
    codeflash_output = resource.matches_filters(group_filter="test-group", name_filter="test-resource")

def test_group_and_type_filters():
    resource = InfraResource(name="test-resource", group="test-group", resource_type="test-type")
    codeflash_output = resource.matches_filters(group_filter="test-group", type_filter="test-type")

def test_name_and_type_filters():
    resource = InfraResource(name="test-resource", resource_type="test-type")
    codeflash_output = resource.matches_filters(name_filter="test-resource", type_filter="test-type")

def test_all_filters():
    resource = InfraResource(name="test-resource", group="test-group", resource_type="test-type")
    codeflash_output = resource.matches_filters(group_filter="test-group", name_filter="test-resource", type_filter="test-type")

# Edge Cases
def test_empty_string_filters():
    resource = InfraResource(name="", group="", resource_type="")
    codeflash_output = resource.matches_filters(group_filter="", name_filter="", type_filter="")

def test_non_matching_filters():
    resource = InfraResource(name="test-resource", group="test-group", resource_type="test-type")
    codeflash_output = resource.matches_filters(group_filter="non-existent-group")
    codeflash_output = resource.matches_filters(name_filter="non-existent-name")
    codeflash_output = resource.matches_filters(type_filter="non-existent-type")

# Case Sensitivity
def test_case_insensitive_matching():
    resource = InfraResource(name="test-resource", group="test-group", resource_type="test-type")
    codeflash_output = resource.matches_filters(group_filter="Test-Group")
    codeflash_output = resource.matches_filters(name_filter="Test-Name")
    codeflash_output = resource.matches_filters(type_filter="Test-Type")

# Special Characters
def test_special_characters():
    resource = InfraResource(name="test-resource@", group="test-group!", resource_type="test-type#")
    codeflash_output = resource.matches_filters(group_filter="test-group!")
    codeflash_output = resource.matches_filters(name_filter="test-resource@")
    codeflash_output = resource.matches_filters(type_filter="test-type#")

# Large Scale Test Cases
def test_large_scale():
    resources = [InfraResource(name=f"resource-{i}", group="test-group", resource_type="test-type") for i in range(1000)]
    for resource in resources:
        codeflash_output = resource.matches_filters(group_filter="test-group")

# Complex Resource Types
def test_resource_type_list():
    resource = InfraResource(name="test-resource", resource_type_list=["test-type", "another-type"])
    codeflash_output = resource.matches_filters(type_filter="test-type")
    codeflash_output = resource.matches_filters(type_filter="another-type")

# Dependencies and Cached Data
def test_with_dependencies_and_cached_data():
    resource = InfraResource(name="test-resource", depends_on=["dependency"], cached_workspace_dir=Path("/tmp"))
    codeflash_output = resource.matches_filters()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import logging
from pathlib import Path
from typing import Any, Dict, List, Optional

# imports
import pytest  # used for our unit tests
from agno.infra.base import InfraBase
from agno.infra.resource import InfraResource
from agno.utils.log import logger
# function to test
from agno.workspace.settings import WorkspaceSettings
from pydantic import BaseModel, ConfigDict

# unit tests

# Basic Functionality Tests
def test_no_filters():
    # Test with no filters provided
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters()

def test_single_group_filter():
    # Test with only group filter provided
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="dev")

def test_single_name_filter():
    # Test with only name filter provided
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(name_filter="resource1")

def test_single_type_filter():
    # Test with only type filter provided
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(type_filter="type1")

# Matching Filters Tests
def test_all_filters_match():
    # Test with all filters matching
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="dev", name_filter="resource1", type_filter="type1")

def test_some_filters_match():
    # Test with some filters matching
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="dev", name_filter="resource1", type_filter="type2")

# Non-Matching Filters Tests
def test_no_filters_match():
    # Test with no filters matching
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="prod", name_filter="resource2", type_filter="type2")

def test_some_filters_do_not_match():
    # Test with some filters not matching
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="prod", name_filter="resource1", type_filter="type2")

# Case Sensitivity Tests
def test_type_filter_case_insensitivity():
    # Test with type filter case insensitivity
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(type_filter="TYPE1")
    codeflash_output = resource.matches_filters(type_filter="Type1")

# Edge Cases Tests
def test_empty_string_filters():
    # Test with empty string filters
    resource = InfraResource(name="resource1", group="dev", resource_type="type1")
    codeflash_output = resource.matches_filters(group_filter="", name_filter="", type_filter="")

def test_none_resource_attributes():
    # Test with resource attributes as None
    resource = InfraResource(name=None, group=None, resource_type=None)
    codeflash_output = resource.matches_filters(group_filter="dev", name_filter="resource1", type_filter="type1")

# Large Scale Test Cases
def test_large_number_of_resources():
    # Test with a large number of resources
    resources = [InfraResource(name=f"resource{i}", group="dev", resource_type="type1") for i in range(1000)]
    for resource in resources:
        codeflash_output = resource.matches_filters(group_filter="dev", name_filter="resource1", type_filter="type1")

def test_complex_resource_type_list():
    # Test with a complex resource type list
    resource = InfraResource(name="resource1", group="dev", resource_type_list=[f"type{i}" for i in range(100)])
    codeflash_output = resource.matches_filters(type_filter="type50")
    codeflash_output = resource.matches_filters(type_filter="type100")
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-InfraResource.matches_filters-m93k1mfn and push.

Codeflash

To optimize the provided Python program for performance, we'll focus on reducing the overall computational complexity and memory access times. The main bottlenecks seem to be in the `matches_filters` function and the frequent calls to `get_group_name`, `get_resource_name`, and `get_resource_type_list`. To improve efficiency, we'll refactor the relevant portions of the code and make sure that functions and conditional checks are carried out in a more optimized manner.

Here's the refactored code.



### Changes Made.
1. **Pre-calculate values:** For filter checks in `matches_filters`, the relevant values (`group_name`, `resource_name`, `resource_type_list`) are calculated once and reused. This reduces repetitive method calls.
2. **Reduce Conditional Checks:** Instead of nested conditional checks within each filter check, we pre-calculate values where necessary, minimizing the overhead of conditional branches.
3. **Efficient List Operations:** Ensured list operations are performed in a concise manner without repetitive checks.

The optimization should improve the overall performance of the provided Python program, specifically in reducing the time complexity of repeated operations. The results after optimization should be more efficient, especially when dealing with large numbers of InfraResource objects.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Apr 5, 2025
@codeflash-ai codeflash-ai bot requested a review from misrasaurabh1 April 5, 2025 01:48
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