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⚡️ Speed up function custom_job_console_uri by 16%#50

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⚡️ Speed up function custom_job_console_uri by 16%#50
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📄 16% (0.16x) speedup for custom_job_console_uri in google/cloud/aiplatform/utils/console_utils.py

⏱️ Runtime : 3.18 milliseconds → 2.73 milliseconds (best of 60 runs)

📝 Explanation and details

The optimized code achieves a 16% speedup through two targeted micro-optimizations that reduce expensive attribute lookups and dictionary access overhead:

Key Optimization 1: Method Caching in _parse_resource_name

  • What: Added class-level caching of the expensive getattr(cls.client_class.get_gapic_client_class(), cls._parse_resource_name_method) call using a cached attribute _cached__parse_resource_name_callable
  • Why faster: The original code performed this complex attribute chain lookup on every call (2038 times in profiling), taking 3726.9ns per hit. The optimized version does this lookup only once per class and reuses the cached callable, reducing per-call overhead to just 242.7ns for the cache check
  • Impact: Line profiler shows the expensive lookup line went from 100% of method time to only 0.1% after caching

Key Optimization 2: Local Variable Binding in custom_job_console_uri

  • What: Extracted fields['location'], fields['custom_job'], and fields['project'] into local variables before the f-string construction
  • Why faster: Eliminates repeated dictionary key lookups during f-string formatting. Each dictionary access has overhead, and the original code performed these lookups inline within the f-string
  • Impact: F-string construction time reduced from 378.9ns to 287.5ns per hit

Performance Characteristics:

  • Most effective for workloads with repeated calls to the same class (caching benefit grows over time)
  • High-frequency scenarios see the best gains, as shown in large-scale tests (15-27% speedup)
  • Edge cases with long strings show smaller but still meaningful improvements (9-13% speedup)
  • All functional behavior preserved - no changes to return values, error handling, or external interfaces

✅ Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests ✅ 2018 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime 
import pytest  # used for our unit tests
from aiplatform.utils.console_utils import custom_job_console_uri


# --- stub for jobs.CustomJob._parse_resource_name for testing purposes ---
class jobs:
    class CustomJob:
        @staticmethod
        def _parse_resource_name(resource_name: str):
            # Expected format: projects/{project}/locations/{location}/customJobs/{custom_job}
            # Parse and return dict with keys: project, location, custom_job
            parts = resource_name.split('/')
            if len(parts) != 6:
                raise ValueError("Invalid resource name format")
            if parts[0] != "projects" or parts[2] != "locations" or parts[4] != "customJobs":
                raise ValueError("Invalid resource name format")
            return {
                "project": parts[1],
                "location": parts[3],
                "custom_job": parts[5]
            }

# ---------------------- UNIT TESTS ----------------------

# 1. Basic Test Cases
def test_basic_valid_resource_name():
    # Test with a typical valid resource name
    resource_name = "projects/my-project/locations/us-central1/customJobs/1234567890"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/us-central1/training/1234567890?project=my-project"
    codeflash_output = custom_job_console_uri(resource_name) # 4.95μs -> 4.27μs (16.0% faster)

def test_basic_valid_resource_name_with_different_project_and_location():
    # Test with different project and location
    resource_name = "projects/proj-abc/locations/europe-west4/customJobs/job-42"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/europe-west4/training/job-42?project=proj-abc"
    codeflash_output = custom_job_console_uri(resource_name) # 4.91μs -> 4.08μs (20.1% faster)

def test_basic_valid_resource_name_with_alphanumeric_job_id():
    # Test with alphanumeric job id
    resource_name = "projects/proj123/locations/asia-east1/customJobs/jobABC123"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/asia-east1/training/jobABC123?project=proj123"
    codeflash_output = custom_job_console_uri(resource_name) # 5.00μs -> 3.95μs (26.7% faster)

# 2. Edge Test Cases







def test_edge_job_id_with_special_characters():
    # Job id contains special characters
    resource_name = "projects/p1/locations/l1/customJobs/job!@#$%^&*()"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/l1/training/job!@#$%^&*()?project=p1"
    codeflash_output = custom_job_console_uri(resource_name) # 7.74μs -> 6.61μs (17.0% faster)

def test_edge_project_and_location_with_hyphens_and_underscores():
    # Project and location contain hyphens and underscores
    resource_name = "projects/my_project-1/locations/us_central-1/customJobs/123"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/us_central-1/training/123?project=my_project-1"
    codeflash_output = custom_job_console_uri(resource_name) # 5.79μs -> 4.62μs (25.3% faster)

def test_edge_job_id_is_numeric():
    # Job id is just numbers
    resource_name = "projects/proj/locations/loc/customJobs/999999"
    expected_url = "https://console.cloud.google.com/ai/platform/locations/loc/training/999999?project=proj"
    codeflash_output = custom_job_console_uri(resource_name) # 5.31μs -> 4.18μs (27.0% faster)







def test_large_scale_many_different_resource_names():
    # Generate 1000 resource names and test each one
    for i in range(1000):
        project = f"project{i}"
        location = f"location{i%10}"
        jobid = f"job{i*12345}"
        resource_name = f"projects/{project}/locations/{location}/customJobs/{jobid}"
        expected_url = f"https://console.cloud.google.com/ai/platform/locations/{location}/training/{jobid}?project={project}"
        codeflash_output = custom_job_console_uri(resource_name) # 1.57ms -> 1.35ms (15.7% faster)

def test_large_scale_long_project_and_job_id():
    # Test with very long project and job id strings (max 1000 chars)
    long_project = "p" * 1000
    long_location = "loc" * 333 + "l"
    long_jobid = "j" * 1000
    resource_name = f"projects/{long_project}/locations/{long_location}/customJobs/{long_jobid}"
    expected_url = f"https://console.cloud.google.com/ai/platform/locations/{long_location}/training/{long_jobid}?project={long_project}"
    codeflash_output = custom_job_console_uri(resource_name) # 31.9μs -> 31.2μs (2.37% faster)

def test_large_scale_project_jobid_with_unicode():
    # Test with unicode characters in project and job id
    project = "项目"
    location = "位置"
    jobid = "作业123"
    resource_name = f"projects/{project}/locations/{location}/customJobs/{jobid}"
    expected_url = f"https://console.cloud.google.com/ai/platform/locations/{location}/training/{jobid}?project={project}"
    codeflash_output = custom_job_console_uri(resource_name) # 5.77μs -> 4.87μs (18.5% faster)

def test_large_scale_all_segments_max_length():
    # All segments at max reasonable length (250 chars each)
    max_len = 250
    project = "p" * max_len
    location = "l" * max_len
    jobid = "j" * max_len
    resource_name = f"projects/{project}/locations/{location}/customJobs/{jobid}"
    expected_url = f"https://console.cloud.google.com/ai/platform/locations/{location}/training/{jobid}?project={project}"
    codeflash_output = custom_job_console_uri(resource_name) # 11.4μs -> 10.4μs (9.32% faster)

def test_large_scale_job_id_with_mixed_types():
    # Job id with mix of numbers, letters, symbols, and unicode
    project = "proj"
    location = "loc"
    jobid = "job-123_测试!@#"
    resource_name = f"projects/{project}/locations/{location}/customJobs/{jobid}"
    expected_url = f"https://console.cloud.google.com/ai/platform/locations/{location}/training/{jobid}?project={project}"
    codeflash_output = custom_job_console_uri(resource_name) # 5.67μs -> 4.67μs (21.4% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import pytest  # used for our unit tests
from aiplatform.utils.console_utils import custom_job_console_uri

# --------------------- Unit Tests ---------------------

# Basic Test Cases

def test_basic_valid_resource_name():
    # Basic valid resource name
    resource_name = "projects/my-project/locations/us-central1/customJobs/123456789"
    expected_uri = "https://console.cloud.google.com/ai/platform/locations/us-central1/training/123456789?project=my-project"
    codeflash_output = custom_job_console_uri(resource_name) # 6.54μs -> 5.46μs (19.8% faster)

def test_basic_valid_resource_name_with_different_project_and_location():
    # Valid resource name with different project and location
    resource_name = "projects/proj-abc/locations/europe-west4/customJobs/job-0001"
    expected_uri = "https://console.cloud.google.com/ai/platform/locations/europe-west4/training/job-0001?project=proj-abc"
    codeflash_output = custom_job_console_uri(resource_name) # 5.40μs -> 4.32μs (25.0% faster)

def test_basic_valid_resource_name_with_alphanumeric_job():
    # Valid resource name with alphanumeric custom job id
    resource_name = "projects/proj123/locations/asia-east1/customJobs/jobXYZ987"
    expected_uri = "https://console.cloud.google.com/ai/platform/locations/asia-east1/training/jobXYZ987?project=proj123"
    codeflash_output = custom_job_console_uri(resource_name) # 5.12μs -> 4.21μs (21.6% faster)

# Edge Test Cases






def test_edge_resource_name_with_numeric_project_and_location():
    # Numeric project and location names should work
    resource_name = "projects/12345/locations/67890/customJobs/98765"
    expected_uri = "https://console.cloud.google.com/ai/platform/locations/67890/training/98765?project=12345"
    codeflash_output = custom_job_console_uri(resource_name) # 8.01μs -> 6.78μs (18.1% faster)

def test_edge_resource_name_with_special_characters():
    # Special characters in project, location, and job id
    resource_name = "projects/proj-!@#/locations/loc-$$/customJobs/job-*&^%"
    expected_uri = "https://console.cloud.google.com/ai/platform/locations/loc-$$/training/job-*&^%?project=proj-!@#"
    codeflash_output = custom_job_console_uri(resource_name) # 5.55μs -> 4.38μs (26.6% faster)




def test_large_scale_many_unique_resource_names():
    # Generate and test 1000 unique resource names
    for i in range(1, 1001):
        resource_name = f"projects/proj{i}/locations/loc{i}/customJobs/job{i}"
        expected_uri = f"https://console.cloud.google.com/ai/platform/locations/loc{i}/training/job{i}?project=proj{i}"
        codeflash_output = custom_job_console_uri(resource_name) # 1.46ms -> 1.25ms (17.1% faster)

def test_large_scale_long_project_location_job_ids():
    # Test with very long project, location, and job ids (max 255 chars each)
    long_project = "p" * 255
    long_location = "l" * 255
    long_job = "j" * 255
    resource_name = f"projects/{long_project}/locations/{long_location}/customJobs/{long_job}"
    expected_uri = f"https://console.cloud.google.com/ai/platform/locations/{long_location}/training/{long_job}?project={long_project}"
    codeflash_output = custom_job_console_uri(resource_name) # 13.4μs -> 11.7μs (13.8% faster)

def test_large_scale_job_id_with_maximum_allowed_characters():
    # Job id with maximum allowed characters (assuming 255 is max for this test)
    max_job_id = "job" + "X" * 252
    resource_name = f"projects/proj/locations/loc/customJobs/{max_job_id}"
    expected_uri = f"https://console.cloud.google.com/ai/platform/locations/loc/training/{max_job_id}?project=proj"
    codeflash_output = custom_job_console_uri(resource_name) # 7.22μs -> 6.40μs (12.9% faster)

def test_large_scale_all_numeric_fields():
    # All fields are numeric and large
    resource_name = "projects/" + "1"*100 + "/locations/" + "2"*100 + "/customJobs/" + "3"*100
    expected_uri = f"https://console.cloud.google.com/ai/platform/locations/{'2'*100}/training/{'3'*100}?project={'1'*100}"
    codeflash_output = custom_job_console_uri(resource_name) # 7.48μs -> 6.46μs (15.8% faster)
# 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-custom_job_console_uri-mglof1zt and push.

Codeflash

@codeflash-ai
Optimize custom_job_console_uri
c780a68 
The optimized code achieves a **16% speedup** through two targeted micro-optimizations that reduce expensive attribute lookups and dictionary access overhead:

**Key Optimization 1: Method Caching in `_parse_resource_name`**
- **What**: Added class-level caching of the expensive `getattr(cls.client_class.get_gapic_client_class(), cls._parse_resource_name_method)` call using a cached attribute `_cached__parse_resource_name_callable`
- **Why faster**: The original code performed this complex attribute chain lookup on every call (2038 times in profiling), taking 3726.9ns per hit. The optimized version does this lookup only once per class and reuses the cached callable, reducing per-call overhead to just 242.7ns for the cache check
- **Impact**: Line profiler shows the expensive lookup line went from 100% of method time to only 0.1% after caching

**Key Optimization 2: Local Variable Binding in `custom_job_console_uri`**
- **What**: Extracted `fields['location']`, `fields['custom_job']`, and `fields['project']` into local variables before the f-string construction
- **Why faster**: Eliminates repeated dictionary key lookups during f-string formatting. Each dictionary access has overhead, and the original code performed these lookups inline within the f-string
- **Impact**: F-string construction time reduced from 378.9ns to 287.5ns per hit

**Performance Characteristics:**
- Most effective for workloads with **repeated calls to the same class** (caching benefit grows over time)
- **High-frequency scenarios** see the best gains, as shown in large-scale tests (15-27% speedup)
- **Edge cases with long strings** show smaller but still meaningful improvements (9-13% speedup)
- All **functional behavior preserved** - no changes to return values, error handling, or external interfaces
@codeflash-ai codeflash-ai Bot requested a review from mashraf-222 October 11, 2025 02:48
@codeflash-ai codeflash-ai Bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 11, 2025
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