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@codeflash-ai codeflash-ai bot commented Nov 13, 2025

📄 575% (5.75x) speedup for _get_store_registry in mlflow/tracking/_model_registry/utils.py

⏱️ Runtime : 93.4 microseconds 13.8 microseconds (best of 5 runs)

📝 Explanation and details

The optimized code achieves a 575% speedup through several key micro-optimizations that reduce Python interpreter overhead:

Key Optimizations:

  1. Moved expensive imports to module level - The Unity Catalog store imports (UcModelRegistryStore, UnityCatalogOssStore) are now at the top instead of being imported every time _get_store_registry() is called. This eliminates repeated import overhead.

  2. Reduced attribute lookups in loops - Created local variable reg = registry.register to avoid repeated method lookups during the scheme registration loops. Also used _register = self.register in register_entrypoints().

  3. Optimized global variable access - Used local variable registry = _model_registry_store_registry to minimize global name lookups within the function.

  4. String formatting optimization - In register_entrypoints(), replaced .format() with f-string for warning message construction, which is faster in modern Python.

  5. Changed list to tuple literals - Used tuples ("http", "https") and ("", "file") instead of lists, as tuples have slightly less overhead for small, immutable collections.

Performance Impact:
The line profiler shows the main bottleneck is still the register_entrypoints() call (~333ms), but the optimizations reduce the registry setup overhead significantly. Since _get_store_registry() is called from _get_store() which is likely in hot paths for MLflow tracking operations, this 575% speedup for registry access will have meaningful impact on model tracking workflows.

Test Results:
The annotated tests show consistent 5-7x speedups across all registry access patterns (503%-738% improvements), indicating the optimizations are effective for both singleton access patterns and fresh registry creation scenarios.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 25 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
import pytest
from mlflow.tracking._model_registry.utils import _get_store_registry


# Mocks for external dependencies and classes (minimal viable implementation)
class DummyStore:
    def __init__(self, *args, **kwargs):
        self.args = args
        self.kwargs = kwargs

class DummyRestStore(DummyStore):
    pass

class DummyFileStore(DummyStore):
    pass

class DummySqlAlchemyStore(DummyStore):
    pass

class DummyDatabricksStore(DummyStore):
    pass

class DummyUcStore(DummyStore):
    pass

class DummyOssStore(DummyStore):
    pass

class DummyModelRegistryStoreRegistry:
    def __init__(self):
        self._registry = {}
        self.registered_entrypoints = []
    def register(self, scheme, store_builder):
        self._registry[scheme] = store_builder
    def register_entrypoints(self):
        self.registered_entrypoints.append(True)
    def get_store(self, scheme, *args, **kwargs):
        if scheme not in self._registry:
            raise ValueError(f"Unknown scheme: {scheme}")
        return self._registry[scheme](*args, **kwargs)

# Constants used in the function
DATABASE_ENGINES = ["sqlite", "mysql", "postgresql"]
_DATABRICKS_UNITY_CATALOG_SCHEME = "databricks-uc"
_OSS_UNITY_CATALOG_SCHEME = "oss-uc"

# Global variable for registry
_model_registry_store_registry = None
from mlflow.tracking._model_registry.utils import _get_store_registry

# 1. Basic Test Cases

def test_registry_singleton_behavior():
    # Test that _get_store_registry returns the same instance on repeated calls
    codeflash_output = _get_store_registry(); reg1 = codeflash_output # 3.84μs -> 637ns (503% faster)
    codeflash_output = _get_store_registry(); reg2 = codeflash_output # 1.60μs -> 212ns (656% faster)

def test_registry_has_expected_schemes():
    # Test that all expected schemes are registered
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.90μs -> 552ns (606% faster)
    expected_schemes = set(
        ["databricks", _DATABRICKS_UNITY_CATALOG_SCHEME, _OSS_UNITY_CATALOG_SCHEME,
         "http", "https", "", "file"] + DATABASE_ENGINES
    )

def test_registry_file_store_builder():
    # Test that file store builder is correct and works for both "" and "file"
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.15μs -> 611ns (579% faster)
    for scheme in ["", "file"]:
        store = registry.get_store(scheme, "some_path")

def test_registry_rest_store_builder():
    # Test that rest store builder is correct for http/https
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.61μs -> 675ns (584% faster)
    for scheme in ["http", "https"]:
        store = registry.get_store(scheme, "http://host")

def test_registry_sqlalchemy_store_builder():
    # Test that sqlalchemy store builder works for all database engines
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.15μs -> 597ns (595% faster)
    for scheme in DATABASE_ENGINES:
        store = registry.get_store(scheme, "db_uri")


def test_registry_uc_and_oss_uc_store_builder():
    # Test that UC and OSS UC schemes return correct store types
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.05μs -> 580ns (599% faster)
    uc_store = registry.get_store(_DATABRICKS_UNITY_CATALOG_SCHEME, "uc_uri")
    oss_store = registry.get_store(_OSS_UNITY_CATALOG_SCHEME, "oss_uri")

def test_registry_entrypoints_called():
    # Test that register_entrypoints is called during registry creation
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.90μs -> 585ns (566% faster)

# 2. Edge Test Cases


def test_registry_empty_scheme_and_file_equivalence():
    # "" and "file" should use the same builder
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.92μs -> 692ns (466% faster)
    store_blank = registry.get_store("", "path")
    store_file = registry.get_store("file", "path")

def test_registry_sqlalchemy_store_with_empty_uri():
    # Edge case: empty URI for SQLAlchemy store
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.73μs -> 655ns (622% faster)
    store = registry.get_store("sqlite", "")






def test_registry_performance_large_scale():
    # Basic performance test: registry creation and lookup under large scale
    import time
    large_db_engines = [f"engine{i}" for i in range(500)]
    global DATABASE_ENGINES
    DATABASE_ENGINES = large_db_engines
    global _model_registry_store_registry
    _model_registry_store_registry = None
    start = time.time()
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.87μs -> 623ns (521% faster)
    elapsed = time.time() - start
    # Lookup for all schemes should be fast
    start = time.time()
    for scheme in large_db_engines:
        store = registry.get_store(scheme, f"uri_{scheme}")
    elapsed = time.time() - start
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import pytest
from mlflow.tracking._model_registry.utils import _get_store_registry

# --- Minimal stubs and constants to allow isolated testing of _get_store_registry ---

# Simulate database engines used for registration
DATABASE_ENGINES = ["sqlite", "mysql", "postgresql"]

# Simulate Unity Catalog schemes
_DATABRICKS_UNITY_CATALOG_SCHEME = "databricks-uc"
_OSS_UNITY_CATALOG_SCHEME = "oss-uc"

# Dummy implementations for store classes
class DummySqlAlchemyStore:
    def __init__(self, store_uri):
        self.store_uri = store_uri

class DummyRestStore:
    def __init__(self, creds):
        self.creds = creds

class DummyDatabricksWorkspaceModelRegistryRestStore:
    def __init__(self, store_uri, tracking_uri):
        self.store_uri = store_uri
        self.tracking_uri = tracking_uri

class DummyFileStore:
    def __init__(self, store_uri):
        self.store_uri = store_uri

class DummyUcModelRegistryStore:
    def __init__(self, store_uri):
        self.store_uri = store_uri

class DummyUnityCatalogOssStore:
    def __init__(self, store_uri):
        self.store_uri = store_uri

# Dummy entry points
class DummyEntryPoint:
    def __init__(self, name, loader):
        self.name = name
        self._loader = loader
    def load(self):
        return self._loader

def get_entry_points(group):
    # For testing, return a fixed entrypoint
    if group == "test_group":
        return [DummyEntryPoint("custom", lambda store_uri: "custom_store")]
    return []

# --- _get_store_registry function ---
_model_registry_store_registry = None
from mlflow.tracking._model_registry.utils import _get_store_registry

# 1. Basic Test Cases

def test_registry_returns_store_registry_instance():
    # Should return a StoreRegistry instance
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.93μs -> 614ns (541% faster)

def test_registry_is_singleton():
    # Should always return the same instance
    codeflash_output = _get_store_registry(); reg1 = codeflash_output # 3.82μs -> 529ns (623% faster)
    codeflash_output = _get_store_registry(); reg2 = codeflash_output # 1.41μs -> 234ns (503% faster)

def test_file_scheme_returns_file_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.77μs -> 538ns (601% faster)
    store = registry.get_store("file:/tmp/foo")

def test_empty_scheme_returns_file_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.75μs -> 559ns (570% faster)
    store = registry.get_store("/tmp/foo")

def test_http_scheme_returns_rest_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.26μs -> 508ns (738% faster)
    store = registry.get_store("http://host:5000")

def test_https_scheme_returns_rest_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.67μs -> 603ns (509% faster)
    store = registry.get_store("https://host:5000")

def test_sqlite_scheme_returns_sqlalchemy_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.83μs -> 538ns (612% faster)
    store = registry.get_store("sqlite:///foo.db")




def test_unity_catalog_scheme_returns_uc_store():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.00μs -> 661ns (506% faster)
    store = registry.get_store(f"{_DATABRICKS_UNITY_CATALOG_SCHEME}://workspace")




def test_scheme_with_no_uri_part():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 3.90μs -> 571ns (584% faster)
    # Should treat as empty scheme, so return DummyFileStore
    store = registry.get_store("")

def test_file_scheme_with_no_path():
    codeflash_output = _get_store_registry(); registry = codeflash_output # 4.97μs -> 628ns (692% faster)
    store = registry.get_store("file:")

def test_registry_entrypoint_exception_handling():
    # Patch get_entry_points to raise exception
    def bad_entry_points(group):
        raise Exception("bad entrypoints")
    global get_entry_points
    orig = get_entry_points
    get_entry_points = bad_entry_points
    try:
        codeflash_output = _get_store_registry(); registry = codeflash_output
        # Should not crash, registry still usable
        store = registry.get_store("file:/tmp")
    finally:
        get_entry_points = orig

def test_registry_reuse_after_entrypoint_error():
    # Registry should be reusable even if entrypoint registration fails
    def bad_entry_points(group):
        raise Exception("bad entrypoints")
    global get_entry_points
    orig = get_entry_points
    get_entry_points = bad_entry_points
    try:
        codeflash_output = _get_store_registry(); reg1 = codeflash_output
        codeflash_output = _get_store_registry(); reg2 = codeflash_output
    finally:
        get_entry_points = orig

# 3. Large Scale Test Cases



from mlflow.tracking._model_registry.utils import _get_store_registry
import pytest

def test__get_store_registry():
    with pytest.raises(SideEffectDetected, match='A\\ "fcntl\\.ioctl\\(0,\\ 21523,\\ b\'\\\\x00\\\\x00\\\\x00\\\\x00\\\\x00\\\\x00\\\\x00\\\\x00\'\\)"\\ operation\\ was\\ detected\\.\\ CrossHair\\ should\\ not\\ be\\ run\\ on\\ code\\ with\\ side\\ effects'):
        _get_store_registry()

To edit these changes git checkout codeflash/optimize-_get_store_registry-mhx67ghu and push.

Codeflash Static Badge

The optimized code achieves a **575% speedup** through several key micro-optimizations that reduce Python interpreter overhead:

**Key Optimizations:**

1. **Moved expensive imports to module level** - The Unity Catalog store imports (`UcModelRegistryStore`, `UnityCatalogOssStore`) are now at the top instead of being imported every time `_get_store_registry()` is called. This eliminates repeated import overhead.

2. **Reduced attribute lookups in loops** - Created local variable `reg = registry.register` to avoid repeated method lookups during the scheme registration loops. Also used `_register = self.register` in `register_entrypoints()`.

3. **Optimized global variable access** - Used local variable `registry = _model_registry_store_registry` to minimize global name lookups within the function.

4. **String formatting optimization** - In `register_entrypoints()`, replaced `.format()` with f-string for warning message construction, which is faster in modern Python.

5. **Changed list to tuple literals** - Used tuples `("http", "https")` and `("", "file")` instead of lists, as tuples have slightly less overhead for small, immutable collections.

**Performance Impact:**
The line profiler shows the main bottleneck is still the `register_entrypoints()` call (~333ms), but the optimizations reduce the registry setup overhead significantly. Since `_get_store_registry()` is called from `_get_store()` which is likely in hot paths for MLflow tracking operations, this 575% speedup for registry access will have meaningful impact on model tracking workflows.

**Test Results:**
The annotated tests show consistent 5-7x speedups across all registry access patterns (503%-738% improvements), indicating the optimizations are effective for both singleton access patterns and fresh registry creation scenarios.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 November 13, 2025 08:32
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: High Optimization Quality according to Codeflash labels Nov 13, 2025
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