Prototype implementation of lazy loading for check/detection_kit.py

MANIFEST.in

@@ -0,0 +1,2 @@
+recursive-include perun *.pyi
+include perun/py.typed

meson.build

@@ -18,6 +18,7 @@ perun_files = files(
     'LICENSE',
     'pyproject.toml',
     'tox.ini',
+    'MANIFEST.in',
 )
 
 perun_dir = 'perun'

perun/check/__init__.py

@@ -2,3 +2,7 @@
 
 Contains the actual methods in isolate modules, and then a factory module,
 containing helper and generic stuff."""
+
+import lazy_loader as lazy
+
+__getattr__, __dir__, __all__ = lazy.attach_stub(__name__, __file__)

perun/check/__init__.pyi

@@ -0,0 +1 @@
+from .detection_kit import get_filtered_best_models_of as get_filtered_best_models_of, general_detection as general_detection, create_model_record as create_model_record, get_function_values as get_function_values, create_filter_by_model as create_filter_by_model

perun/check/meson.build

@@ -2,6 +2,7 @@ perun_check_dir = perun_dir / 'check'
 
 perun_check_files = files(
     '__init__.py',
+    '__init__.pyi',
     'factory.py',
     'detection_kit.py',
     'nonparam_kit.py',

perun/check/methods/best_model_order_equality.py

@@ -50,7 +50,7 @@
 # Perun Imports
 from perun.check.methods.abstract_base_checker import AbstractBaseChecker
 from perun.utils.structs.common_structs import DegradationInfo, PerformanceChange
-import perun.check.detection_kit as detection
+import perun.check as check
 
 if TYPE_CHECKING:
     from perun.profile.factory import Profile
@@ -81,10 +81,8 @@ def check(
         :param _: unification with other detection methods (unused in this method)
         :returns: tuple (degradation result, degradation location, degradation rate)
         """
-        best_baseline_models = detection.get_filtered_best_models_of(
-            baseline_profile, group="param"
-        )
-        best_target_models = detection.get_filtered_best_models_of(target_profile, group="param")
+        best_baseline_models = check.get_filtered_best_models_of(baseline_profile, group="param")
+        best_target_models = check.get_filtered_best_models_of(target_profile, group="param")
 
         for uid, best_model in best_target_models.items():
             best_baseline_model = best_baseline_models.get(uid)

perun/check/methods/fast_check.py

@@ -17,7 +17,7 @@
 from perun.check.methods.abstract_base_checker import AbstractBaseChecker
 from perun.logic import runner
 from perun.utils.structs.common_structs import DegradationInfo, ClassificationMethod
-import perun.check.detection_kit as detect
+import perun.check as check
 
 if TYPE_CHECKING:
     from perun.profile.factory import Profile
@@ -35,7 +35,7 @@ def check(
         :param _: unification with other detection methods (unused in this method)
         :returns: tuple (degradation result, degradation location, degradation rate, confidence)
         """
-        return detect.general_detection(
+        return check.general_detection(
             baseline_profile, target_profile, ClassificationMethod.FastCheck
         )
 

perun/check/methods/linear_regression.py

@@ -14,7 +14,7 @@
 from scipy import stats
 
 # Perun Imports
-from perun.check import detection_kit as detect
+import perun.check as check
 from perun.check.methods import fast_check
 from perun.check.methods.abstract_base_checker import AbstractBaseChecker
 from perun.utils.common import common_kit
@@ -40,7 +40,7 @@ def check(
         :returns: tuple (degradation result, degradation location, degradation rate, confidence)
         """
 
-        return detect.general_detection(
+        return check.general_detection(
             baseline_profile, target_profile, ClassificationMethod.LinearRegression
         )
 
@@ -107,15 +107,15 @@ def exec_linear_regression(
         uid, baseline_profile, baseline_x_pts, lin_abs_error
     )
     # obtaining the models (linear and quadratic) from the new regressed profile
-    quad_err_model = detect.get_filtered_best_models_of(
+    quad_err_model = check.get_filtered_best_models_of(
         std_err_profile,
         group="param",
-        model_filter=detect.create_filter_by_model("quadratic"),
+        model_filter=check.create_filter_by_model("quadratic"),
     )
-    linear_err_model = detect.get_filtered_best_models_of(
+    linear_err_model = check.get_filtered_best_models_of(
         std_err_profile,
         group="param",
-        model_filter=detect.create_filter_by_model("linear"),
+        model_filter=check.create_filter_by_model("linear"),
     )
 
     # check the last quadratic type of change
@@ -127,7 +127,7 @@ def exec_linear_regression(
 
     # We did not classify the change
     if not change_type:
-        std_err_model = detect.get_filtered_best_models_of(std_err_profile, group="param")
+        std_err_model = check.get_filtered_best_models_of(std_err_profile, group="param")
         change_type = std_err_model[uid].type
 
     return change_type

perun/check/methods/polynomial_regression.py

@@ -15,7 +15,7 @@
 # Perun Imports
 from perun.check.methods.abstract_base_checker import AbstractBaseChecker
 from perun.utils.structs.common_structs import DegradationInfo, ClassificationMethod
-import perun.check.detection_kit as detect
+import perun.check as check
 
 if TYPE_CHECKING:
     import numpy.typing as npt
@@ -37,7 +37,7 @@ def check(
         :param _: unification with other detection methods (unused in this method)
         :returns: tuple (degradation result, degradation location, degradation rate, confidence)
         """
-        return detect.general_detection(
+        return check.general_detection(
             baseline_profile,
             target_profile,
             ClassificationMethod.PolynomialRegression,

perun/check/nonparam_kit.py

@@ -11,7 +11,7 @@
 from perun.postprocess.regression_analysis import data_provider
 from perun.utils import log
 from perun.utils.structs.common_structs import PerformanceChange, ModelRecord
-import perun.check.detection_kit as methods
+import perun.check as check
 import perun.postprocess.regressogram.methods as rg_methods
 
 if TYPE_CHECKING:
@@ -107,7 +107,7 @@ def unify_buckets_in_regressogram(
 
     # match the regressogram model with the right 'uid'
     model = [model for model in new_regressogram_models if model["uid"] == uid][0]
-    return methods.create_model_record(model)
+    return check.create_model_record(model)
 
 
 def preprocess_nonparam_models(
@@ -146,7 +146,7 @@ def get_model_coordinates(model: ModelRecord) -> tuple[list[float], list[float]]
         :return: obtained x and y coordinates - x-points, y-points
         """
         if model.b1 is not None:
-            x_pts, y_pts = methods.get_function_values(model)
+            x_pts, y_pts = check.get_function_values(model)
         else:
             x_pts = np.linspace(model.x_start, model.x_end, num=len(model.b0))
             y_pts = model.b0

perun/cli.py

@@ -41,28 +41,8 @@
 
 from __future__ import annotations
 
-import cProfile, pstats, io
-import atexit
-
-pr = cProfile.Profile()
-pr.enable()
-
-
-def terminate_profiling():
-    pr.disable()
-    s = io.StringIO()
-    sortby = pstats.SortKey.CUMULATIVE
-    ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
-    ps.print_stats("perun/collect")
-    # ps.print_stats(100)
-    print(s.getvalue())
-
-
-atexit.register(terminate_profiling)
-
-
 # Standard Imports
-from typing import Optional, Any
+from typing import Optional, Any, TYPE_CHECKING
 import os
 import sys
 
@@ -76,7 +56,6 @@ def terminate_profiling():
 from perun.utils import exceptions, log as perun_log
 from perun.utils.common import cli_kit, common_kit
 from perun.utils.external import commands as external_commands
-from perun.profile.factory import Profile
 from perun.utils.exceptions import (
     UnsupportedModuleException,
     NotPerunRepositoryException,
@@ -93,6 +72,10 @@ def terminate_profiling():
 import perun.deltadebugging.factory as delta
 
 
+if TYPE_CHECKING:
+    from perun.profile.factory import Profile
+
+
 DEV_MODE = False
 
 

perun/meson.build

@@ -1,6 +1,7 @@
 perun_files = files(
     'cli.py',
     '__init__.py',
+    'py.typed',
 )
 
 py3.install_sources(

perun/profile/factory.py

@@ -24,7 +24,7 @@
 from perun.profile import convert, query, stats, helpers
 from perun.utils import log
 from perun.utils.common import common_kit
-import perun.check.detection_kit as detection
+import perun.check as check
 import perun.postprocess.regressogram.methods as nparam_methods
 
 if TYPE_CHECKING:
@@ -374,9 +374,9 @@ def all_filtered_models(self, models_strategy: str) -> dict[str, ModelRecord]:
         """
         group = models_strategy.rsplit("-")[1]
         if models_strategy in ("all-param", "all-nonparam"):
-            return detection.get_filtered_best_models_of(self, group=group, model_filter=None)
+            return check.get_filtered_best_models_of(self, group=group, model_filter=None)
         elif models_strategy in ("best-nonparam", "best-model", "best-param"):
-            return detection.get_filtered_best_models_of(self, group=group)
+            return check.get_filtered_best_models_of(self, group=group)
         else:
             return {}
 

pyproject.toml

@@ -32,6 +32,9 @@ dependencies = [
     "ninja>=1.11",
     "wheel>=0.43.0",
 
+    # Lazy loading
+    "lazy-loader>=0.4",
+
     # Other
     "psutil>=6.0.0",
 
@@ -140,6 +143,7 @@ module = [
     "statsmodels.*",
     "holoviews.*",
     "bcc.*",
+    "lazy_loader.*",
 ]
 ignore_missing_imports = true