Clean and refactor

Author: GioeleB00

documentation/tests_documentation/unit_tests/test_sampler_helper.md

@@ -1,6 +1,6 @@
 """Application constants and configuration values."""
 
-from enum import Enum, IntEnum
+from enum import IntEnum, StrEnum
 
 
 class TimeDefaults(IntEnum):
@@ -14,10 +14,10 @@ class TimeDefaults(IntEnum):
     MAX_USER_SAMPLING_WINDOW = 120 # 2 minutes
 
 
-class Distribution(str, Enum):
+class Distribution(StrEnum):
     """Allowed probability distributions for an RVConfig."""
 
     POISSON = "poisson"
     NORMAL = "normal"
-    GAUSSIAN = "gaussian"
+
 

documentation/tests_documentation/unit_tests/test_simulation_input.md

@@ -16,7 +16,7 @@
     truncated_gaussian_generator,
     uniform_variable_generator,
 )
-from app.schemas.simulation_input import SimulationInput
+from app.schemas.requests_generator_input import SimulationInput
 
 
 def gaussian_poisson_sampling(
@@ -41,11 +41,6 @@ def gaussian_poisson_sampling(
 
     simulation_time = input_data.total_simulation_time
     user_sampling_window = input_data.user_sampling_window
-    # pydantic in the validation assign a value and mypy is not
-    # complaining because a None cannot be compared in the loop
-    # to a float
-    assert simulation_time is not None
-    assert user_sampling_window is not None
 
     # λ_u : mean concurrent users per window
     mean_concurrent_user = float(input_data.avg_active_users.mean)

src/app/config/constants.py

@@ -13,7 +13,7 @@
     poisson_variable_generator,
     uniform_variable_generator,
 )
-from app.schemas.simulation_input import SimulationInput
+from app.schemas.requests_generator_input import SimulationInput
 
 
 def poisson_poisson_sampling(
@@ -38,11 +38,6 @@ def poisson_poisson_sampling(
 
     simulation_time = input_data.total_simulation_time
     user_sampling_window = input_data.user_sampling_window
-    # pydantic in the validation assign a value and mypy is not
-    # complaining because a None cannot be compared in the loop
-    # to a float
-    assert simulation_time is not None
-    assert user_sampling_window is not None
 
     # λ_u : mean concurrent users per window
     mean_concurrent_user = float(input_data.avg_active_users.mean)

src/app/core/event_samplers/gaussian_poisson.py

@@ -16,7 +16,7 @@
 
     import numpy as np
 
-    from app.schemas.simulation_input import SimulationInput
+    from app.schemas.requests_generator_input import SimulationInput
 
 
 def requests_generator(
@@ -37,7 +37,7 @@ def requests_generator(
     """
     dist = input_data.avg_active_users.distribution.lower()
 
-    if dist in {Distribution.GAUSSIAN, Distribution.NORMAL}:
+    if dist == Distribution.NORMAL:
         #Gaussian-Poisson model
         return gaussian_poisson_sampling(
             input_data=input_data,

src/app/core/event_samplers/poisson_poisson.py

@@ -27,10 +27,7 @@ def ensure_mean_is_numeric(
     @model_validator(mode="after")  # type: ignore[arg-type]
     def default_variance(cls, model: "RVConfig") -> "RVConfig":  # noqa: N805
         """Set variance = mean when distribution == 'normal' and variance is missing."""
-        if model.variance is None and model.distribution in {
-            Distribution.NORMAL,
-            Distribution.GAUSSIAN,
-        }:
+        if model.variance is None and model.distribution == Distribution.NORMAL:
             model.variance = model.mean
         return model
 
@@ -41,7 +38,7 @@ class SimulationInput(BaseModel):
     avg_request_per_minute_per_user: RVConfig
     total_simulation_time: int = Field(
         default=TimeDefaults.SIMULATION_TIME,
-        ge=TimeDefaults.MIN_SIMULATION_TIME, # minimum simulation time in seconds
+        ge=TimeDefaults.MIN_SIMULATION_TIME,
         description=(
             f"Simulation time in seconds (>= {TimeDefaults.MIN_SIMULATION_TIME})."
         ),

src/app/core/simulation/requests_generator.py

@@ -10,7 +10,7 @@
 
 from app.config.constants import TimeDefaults
 from app.core.event_samplers.gaussian_poisson import gaussian_poisson_sampling
-from app.schemas.simulation_input import RVConfig, SimulationInput
+from app.schemas.requests_generator_input import RVConfig, SimulationInput
 
 # ---------------------------------------------------------------------------
 # Fixture
@@ -22,7 +22,7 @@ def base_input() -> SimulationInput:
     """Return a minimal, valid SimulationInput for the Gaussian-Poisson sampler."""
     return SimulationInput(
         avg_active_users=RVConfig(
-            mean=10.0, variance=4.0, distribution="gaussian",
+            mean=10.0, variance=4.0, distribution="normal",
         ),
         avg_request_per_minute_per_user=RVConfig(mean=30.0),
         total_simulation_time=TimeDefaults.MIN_SIMULATION_TIME,

src/app/schemas/simulation_input.py …/app/schemas/requests_generator_input.pysrc/app/schemas/simulation_input.py renamed to src/app/schemas/requests_generator_input.py src/app/schemas/simulation_input.py renamed to src/app/schemas/requests_generator_input.py

@@ -11,7 +11,7 @@
 
 from app.config.constants import TimeDefaults
 from app.core.event_samplers.poisson_poisson import poisson_poisson_sampling
-from app.schemas.simulation_input import RVConfig, SimulationInput
+from app.schemas.requests_generator_input import RVConfig, SimulationInput
 
 
 @pytest.fixture

tests/unit/sampler/test_gaussian_poisson.py

@@ -11,7 +11,7 @@
 from app.config.constants import TimeDefaults
 from app.core.simulation.requests_generator import requests_generator
 from app.core.simulation.simulation_run import run_simulation
-from app.schemas.simulation_input import SimulationInput
+from app.schemas.requests_generator_input import SimulationInput
 
 if TYPE_CHECKING:
 
@@ -57,7 +57,6 @@ def test_default_requests_generator_uses_poisson_poisson_sampling(
     [
         ("poisson", "poisson_poisson_sampling"),
         ("normal", "gaussian_poisson_sampling"),
-        ("gaussian", "gaussian_poisson_sampling"),
     ],
 )
 def test_requests_generator_dispatches_to_correct_sampler(
@@ -69,7 +68,6 @@ def test_requests_generator_dispatches_to_correct_sampler(
     comes from the appropriate sampler function based on distribution:
       - 'poisson' → poisson_poisson_sampling
       - 'normal'  → gaussian_poisson_sampling
-      - 'gaussian'→ gaussian_poisson_sampling
     """
     input_data = SimulationInput(
         avg_active_users={"mean": 1.0, "distribution": dist},