run multiple simulations for different sets of parameters

poetry.lock

@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "colorama"
+version = "0.4.6"
+description = "Cross-platform colored terminal text."
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+files = [
+    {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
+    {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
+]
+
 [[package]]
 name = "numpy"
 version = "2.0.1"
@@ -95,7 +106,27 @@ timezone = ["backports-zoneinfo", "tzdata"]
 xlsx2csv = ["xlsx2csv (>=0.8.0)"]
 xlsxwriter = ["xlsxwriter"]
 
+[[package]]
+name = "tqdm"
+version = "4.66.5"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
+    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "3b5f1c763a56f03ec547b2513ce2ef1a9935ac6df8a8caca8288795aee44cbbf"
+content-hash = "e518e9e57f22023c75b734bc9fdfb85e25b6b937f87bbf5a26c1b31ff370b15f"

pyproject.toml

@@ -9,6 +9,7 @@ readme = "README.md"
 python = "^3.10"
 numpy = "^2.0.1"
 polars = "^1.4.1"
+tqdm = "^4.66.5"
 
 
 [build-system]

simulation/app.py

@@ -1,25 +1,27 @@
+from concurrent.futures import ProcessPoolExecutor, as_completed
 from dataclasses import dataclass
 
 import numpy as np
 import polars as pl
+from tqdm import tqdm
 
 from simulation.lib import Process, Simulation
 
 
-@dataclass
+def run_simulation(n_servers=2, lam=40):
-class Customer:
+
+    @dataclass
+    class Customer:
         arrived_at: float
         started_at: float | None = None
         handling_time: float | None = None
         finished_at: float | None = None
 
+    customers_unhandled: list[Customer] = []
+    customers_in_progress: list[Customer] = []
+    customers_handled: list[Customer] = []
 
-customers_unhandled: list[Customer] = []
+    class Server(Process):
-customers_in_progress: list[Customer] = []
-customers_handled: list[Customer] = []
-
-
-class Server(Process):
         def run(self):
             while True:
                 if len(customers_unhandled) > 0:
@@ -33,12 +35,13 @@ class Server(Process):
                     customer.finished_at = self.simulation.clock
                     customers_in_progress.remove(customer)
                     customers_handled.append(customer)
-                self.simulation.log(f"unhandled customers: {len(customers_unhandled)}")
+                    self.simulation.log(
+                        f"unhandled customers: {len(customers_unhandled)}"
+                    )
                 else:
                     yield from self.suspend()
 
-
+    class CustomerGenerator(Process):
-class CustomerGenerator(Process):
         def __init__(self, lam=40, servers=[]):
             self.lam = lam
             self.servers = servers
@@ -46,18 +49,19 @@ class CustomerGenerator(Process):
 
         def run(self):
             while True:
-            wait_for = float(max(0, (np.random.poisson(lam=self.lam, size=1) / 10)[0]))
+                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)
 
-
-def run_simulation(n_servers=2, lam=40):
     servers = [Server() for _ in range(n_servers)]
     simulation = Simulation(
-        processes=[CustomerGenerator(servers=servers, lam=lam), *servers]
+        processes=[CustomerGenerator(servers=servers, lam=lam), *servers],
+        enable_logging=False,
     )
     simulation.start()
 
@@ -67,9 +71,56 @@ def run_simulation(n_servers=2, lam=40):
 
     df_servers = pl.DataFrame([server.__dict__ for server in servers])
 
-    # print(f"\nservers: {len(servers)}")
+    utilization = {
-    print("\ncustomers", df_customers[["queue_time", "handling_time"]].mean())
+        f"utilization_server_{key}": value
-    print("\nservers", df_servers[["id", "utilization"]])
+        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,
+    }
 
 
-run_simulation(n_servers=3)
+with ProcessPoolExecutor(max_workers=4) as executor:
+    n_servers = [n + 1 for n in range(10)]
+    lam = [(n + 1) * 4 for n in range(10)]
+    parameter_values = [
+        {"n_servers": n, "lam": m} for n in n_servers for m in lam for _ in range(10)
+    ]
+    futures = [
+        executor.submit(run_simulation, **parameters) for parameters in parameter_values
+    ]
+
+    results = []
+    for future in tqdm(as_completed(futures), total=len(parameter_values)):
+        result = future.result()
+        results.append(result)
+
+    df = (
+        pl.DataFrame(results)
+        .fill_null(0)
+        .group_by(["n_servers", "lam"])
+        .agg(pl.all().mean())
+        .sort(["n_servers", "lam"])
+    )
+
+    df_queue_time = df.pivot("lam", index="n_servers", values="queue_time").sort(
+        "n_servers"
+    )
+
+    def stats(column):
+        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):
+        if self.enable_logging:
             print(f"{'{:.2f}'.format(self.clock)}: {msg}")
-        pass
 
 
 class BaseProcess(Protocol):
@@ -42,6 +43,7 @@ class Process(BaseProcess):
                 self.simulation.clock - self.started_at
             )
         except Exception as e:
+            if self.simulation.enable_logging:
                 print(e)
 
     def suspend(self):
@@ -61,9 +63,10 @@ class Process(BaseProcess):
 
 
 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)