add Dockerfile

.dockerignore

@@ -0,0 +1,2 @@
+__pycache__
+.venv

.gitignore

@@ -1 +1,2 @@
 __pycache__
+.venv

.vscode/settings.json

@@ -0,0 +1,9 @@
+{
+    "[python]": {
+        "editor.formatOnSave": true,
+        "editor.defaultFormatter": "charliermarsh.ruff",
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+    },
+}

Dockerfile

@@ -0,0 +1,9 @@
+FROM python:3.12-slim
+COPY --from=ghcr.io/astral-sh/uv:0.4.10 /uv /bin/uv
+
+COPY uv.lock pyproject.toml ./
+RUN uv sync --frozen 
+
+COPY ./simulation simulation
+
+ENTRYPOINT [ "uv", "run", "python", "-m", "simulation.app" ]

Makefile

@@ -0,0 +1,19 @@
+GIT_COMMIT_HASH := $(shell git rev-parse --short HEAD)
+DOCKER_REGISTRY = registry.crapts.org
+
+all: run
+
+run:
+	uv run python -m simulation.app
+
+docker/build:
+	docker build -t simulation:latest .
+	
+docker/run: docker/build
+	docker run -it --rm simulation
+
+docker/push: docker/build
+	docker buildx rm builder
+	docker buildx create --name builder --driver docker-container --use
+	docker buildx build --platform linux/amd64,linux/arm64 --push -t $(DOCKER_REGISTRY)/simulation:latest .
+	docker buildx build --platform linux/amd64,linux/arm64 --push -t $(DOCKER_REGISTRY)/simulation:$(GIT_COMMIT_HASH) .

README.md

@@ -0,0 +1,3 @@
+Run the simulation using:
+
+    uv run python -m simulation.app

poetry.lock

@@ -1,101 +0,0 @@
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-
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-]
-
-[[package]]
-name = "polars"
-version = "1.4.1"
-description = "Blazingly fast DataFrame library"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.extras]
-adbc = ["adbc-driver-manager[dbapi]", "adbc-driver-sqlite[dbapi]"]
-all = ["polars[async,cloudpickle,database,deltalake,excel,fsspec,graph,iceberg,numpy,pandas,plot,pyarrow,pydantic,style,timezone]"]
-async = ["gevent"]
-calamine = ["fastexcel (>=0.9)"]
-cloudpickle = ["cloudpickle"]
-connectorx = ["connectorx (>=0.3.2)"]
-database = ["nest-asyncio", "polars[adbc,connectorx,sqlalchemy]"]
-deltalake = ["deltalake (>=0.15.0)"]
-excel = ["polars[calamine,openpyxl,xlsx2csv,xlsxwriter]"]
-fsspec = ["fsspec"]
-gpu = ["cudf-polars-cu12"]
-graph = ["matplotlib"]
-iceberg = ["pyiceberg (>=0.5.0)"]
-numpy = ["numpy (>=1.16.0)"]
-openpyxl = ["openpyxl (>=3.0.0)"]
-pandas = ["pandas", "polars[pyarrow]"]
-plot = ["hvplot (>=0.9.1)", "polars[pandas]"]
-pyarrow = ["pyarrow (>=7.0.0)"]
-pydantic = ["pydantic"]
-sqlalchemy = ["polars[pandas]", "sqlalchemy"]
-style = ["great-tables (>=0.8.0)"]
-timezone = ["backports-zoneinfo", "tzdata"]
-xlsx2csv = ["xlsx2csv (>=0.8.0)"]
-xlsxwriter = ["xlsxwriter"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.10"
-content-hash = "3b5f1c763a56f03ec547b2513ce2ef1a9935ac6df8a8caca8288795aee44cbbf"

pyproject.toml

@@ -1,16 +1,12 @@
-[tool.poetry]
+[project]
 name = "simulation"
 version = "0.1.0"
-description = ""
+description = "Add your description here"
-authors = ["Marco Crapts <mcrapts@gmail.com>"]
 readme = "README.md"
-
+requires-python = ">=3.12"
-[tool.poetry.dependencies]
+dependencies = [
-python = "^3.10"
+    "numpy>=2.1.1",
-numpy = "^2.0.1"
+    "polars>=1.7.1",
-polars = "^1.4.1"
+    "pydantic-settings>=2.5.2",
-
+    "tqdm>=4.66.5",
-
+]
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

simulation/app.py

@@ -1,61 +1,149 @@
-from dataclasses import asdict, dataclass
+import os
+import random
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from dataclasses import dataclass
 
 import numpy as np
 import polars as pl
+from pydantic import Field, field_validator
+from pydantic_settings import BaseSettings, SettingsConfigDict
+from tqdm import tqdm
 
 from simulation.lib import Process, Simulation
 
 
-@dataclass
+class Settings(BaseSettings):
-class Customer:
+    model_config = SettingsConfigDict(cli_parse_args=True)
-    arrived_at: float
+
-    started_at: float | None = None
+    workers: int = Field(default="auto")
-    handling_time: float | None = None
+
-    finished_at: float | None = None
+    @field_validator("workers", mode="before")
+    def check_workers(cls, value):
+        if value == "auto":
+            return max((os.cpu_count() or 0) - 1, 1)
+        return value
 
 
-customers_unhandled: list[Customer] = []
+print("Settings: ", Settings().model_dump())
-customers_in_progress: list[Customer] = []
-customers_handled: list[Customer] = []
 
 
-class Server(Process):
+def run_simulation(n_servers=2, lam=40):
-    def run(self):
+    @dataclass
-        while True:
+    class Customer:
-            if len(customers_unhandled) > 0:
+        arrived_at: float
-                customer = customers_unhandled[0]
+        started_at: float | None = None
-                customers_unhandled.remove(customer)
+        handling_time: float | None = None
-                customers_in_progress.append(customer)
+        finished_at: float | None = None
-                customer.started_at = self.simulation.clock
+
-                handling_time = float(max(0, np.random.normal(5, 2.5, size=1)[0]))
+    customers_unhandled: list[Customer] = []
-                yield from self.hold(handling_time)
+    customers_in_progress: list[Customer] = []
-                customer.handling_time = handling_time
+    customers_handled: list[Customer] = []
-                customer.finished_at = self.simulation.clock
+
-                customers_in_progress.remove(customer)
+    class Server(Process):
-                customers_handled.append(customer)
+        def run(self):
-                self.simulation.log(f"unhandled customers: {len(customers_unhandled)}")
+            while True:
-            else:
+                if len(customers_unhandled) > 0:
-                yield from self.suspend()
+                    customer = customers_unhandled[0]
+                    customers_unhandled.remove(customer)
+                    customers_in_progress.append(customer)
+                    customer.started_at = self.simulation.clock
+                    handling_time = float(max(0, np.random.normal(5, 2.5, size=1)[0]))
+                    yield from self.hold(handling_time)
+                    customer.handling_time = handling_time
+                    customer.finished_at = self.simulation.clock
+                    customers_in_progress.remove(customer)
+                    customers_handled.append(customer)
+                    self.simulation.log(
+                        f"unhandled customers: {len(customers_unhandled)}"
+                    )
+                else:
+                    yield from self.suspend()
+
+    class CustomerGenerator(Process):
+        def __init__(self, lam=40, servers=[]):
+            self.lam = lam
+            self.servers = servers
+            super().__init__()
+
+        def run(self):
+            while True:
+                wait_for = float(
+                    max(0, (np.random.poisson(lam=self.lam, size=1) / 10)[0])
+                )
+                customer = Customer(arrived_at=self.simulation.clock)
+                customers_unhandled.append(customer)
+                for server in self.servers:
+                    server.resume()
+                yield from self.hold(wait_for)
+
+    servers = [Server() for _ in range(n_servers)]
+    simulation = Simulation(
+        processes=[CustomerGenerator(servers=servers, lam=lam), *servers],
+        enable_logging=False,
+    )
+    simulation.start()
+
+    df_customers = pl.DataFrame(
+        [customer.__dict__ for customer in customers_handled]
+    ).with_columns(queue_time=pl.col("started_at") - pl.col("arrived_at"))
+
+    df_servers = pl.DataFrame([server.__dict__ for server in servers])
+
+    utilization = {
+        f"utilization_server_{key}": value
+        for key, value in dict(
+            zip(df_servers["id"].to_list(), df_servers["utilization"].to_list())
+        ).items()
+    }
+    return {
+        "n_servers": n_servers,
+        "lam": lam,
+        "queue_time": df_customers["queue_time"].mean(),
+        "handling_time": df_customers["handling_time"].mean(),
+        **utilization,
+    }
 
 
-class CustomerGenerator(Process):
+if __name__ == "__main__":
-    def run(self):
+    with ProcessPoolExecutor(max_workers=Settings().workers) as executor:
-        while True:
+        n_servers = [n + 1 for n in range(10)]
-            wait_for = float(max(0, (np.random.poisson(lam=40, size=1) / 10)[0]))
+        lam = [(n + 1) * 4 for n in range(10)]
-            customer = Customer(arrived_at=self.simulation.clock)
+        parameter_values = [
-            customers_unhandled.append(customer)
+            {"lam": m, "n_servers": n}
-            for server in servers:
+            for m in lam
-                server.resume()
+            for n in n_servers
-            yield from self.hold(wait_for)
+            for _ in range(100)
+        ]
+        futures = [
+            executor.submit(run_simulation, **parameters)
+            for parameters in random.sample(parameter_values, len(parameter_values))
+        ]
 
+        results = []
+        for future in tqdm(as_completed(futures), total=len(parameter_values)):
+            result = future.result()
+            results.append(result)
 
-servers = [Server() for _ in range(2)]
+        df = (
-simulation = Simulation(processes=[CustomerGenerator(), *servers])
+            pl.DataFrame(results)
-simulation.start()
+            .fill_null(0)
+            .group_by(["n_servers", "lam"])
+            .agg(pl.all().mean())
+            .sort(["n_servers", "lam"])
+        )
 
-df = pl.DataFrame([asdict(customer) for customer in customers_handled]).with_columns(
+        df_queue_time = df.pivot("lam", index="n_servers", values="queue_time").sort(
-    queue_time=pl.col('started_at') - pl.col('arrived_at')
+            "n_servers"
-)
+        )
 
-print(f"\nservers: {len(servers)}")
+        def stats(column):
-print(df[["queue_time", "handling_time"]].mean())
+            return (
+                df.pivot("lam", index="n_servers", values=column)
+                .sort("n_servers")
+                .with_columns(pl.all().round(2))
+            )
+
+        pl.Config.set_tbl_cols(20)
+        print(df)
+        print(stats("queue_time"))
+        print(stats("utilization_server_1"))

simulation/lib.py

@@ -3,10 +3,11 @@ from typing import Any, Generator, Protocol
 
 class BaseSimulation:
     clock: float
+    enable_logging: bool
 
     def log(self, msg):
-        print(f"{'{:.2f}'.format(self.clock)}: {msg}")
+        if self.enable_logging:
-        pass
+            print(f"{'{:.2f}'.format(self.clock)}: {msg}")
 
 
 class BaseProcess(Protocol):
@@ -17,19 +18,33 @@ class Process(BaseProcess):
     def __init__(self):
         self.id: int = 1
         self.simulation = BaseSimulation()
+        self.started_at: float = 0
         self.resume_at: float = 0
+        self.time_active: float = 0
+        self.utilization: float = 0
         self.suspended = False
         self._gen = self.run()
 
-    @property
+    def start(self, simulation, id):
-    def name(self):
+        self.id = id
-        return f"{self.__class__.__name__} {self.id}"
+        self.started_at = simulation.clock
+        self.simulation = simulation
 
     def hold(self, hold_for: float):
         hold_for_formatted = "{:.2f}".format(hold_for)
         self.simulation.log(f"holding {self.name} for {hold_for_formatted} seconds")
         self.resume_at = self.simulation.clock + hold_for
+        t_start = self.simulation.clock
         yield
+        t_end = self.simulation.clock
+        self.time_active += t_end - t_start
+        try:
+            self.utilization = self.time_active / (
+                self.simulation.clock - self.started_at
+            )
+        except Exception as e:
+            if self.simulation.enable_logging:
+                print(e)
 
     def suspend(self):
         self.suspended = True
@@ -42,11 +57,16 @@ class Process(BaseProcess):
             self.suspended = False
             next(self._gen)
 
+    @property
+    def name(self):
+        return f"{self.__class__.__name__} {self.id}"
+
 
 class Simulation(BaseSimulation):
-    def __init__(self, processes: list[Process]):
+    def __init__(self, processes: list[Process], enable_logging=True):
         self.clock = 0
         self.processes = []
+        self.enable_logging = enable_logging
         for process in processes:
             self.register_process(process)
 
@@ -56,8 +76,7 @@ class Simulation(BaseSimulation):
             for p in self.processes
             if p.__class__.__name__ == process.__class__.__name__
         ]
-        process.id = 1 + len(processes_with_same_class)
+        process.start(simulation=self, id=1 + len(processes_with_same_class))
-        process.simulation = self
         self.processes.append(process)
 
     @property

uv.lock

@@ -0,0 +1,184 @@
+version = 1
+requires-python = ">=3.12"
+resolution-markers = [
+    "python_full_version < '3.13'",
+    "python_full_version >= '3.13'",
+]
+
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+version = "0.7.0"
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