bbbbbbenchh

metrics/benchmarks/exceptions.py

@@ -0,0 +1,14 @@
+class BenchmarkNotFound(Exception):
+    def __init__(self, benchmark_name: str):
+        self.benchmark_name = benchmark_name
+
+    def __str__(self):
+        return f"Benchmark with name '{self.benchmark_name}' not found"
+
+
+class BenchmarksNotFound(Exception):
+    def __init__(self, type_: str):
+        self.type_ = type_
+
+    def __str__(self):
+        return f"Benchmarks with type '{self.type_}' not found"

metrics/benchmarks/models.py

@@ -1,26 +1,39 @@
 __all__ = [
     "Benchmark",
     "Benchmarks",
-    "BenchmarkResult",
+    "BenchmarkResult"
-    "benchmark"
 ]
 
 from dataclasses import dataclass
-from decimal import Decimal
+import time
-from typing import Callable, ClassVar, overload, override
+import gc
+import statistics
+from typing import Callable, override
+
+from .exceptions import BenchmarkNotFound, BenchmarksNotFound
+
 
 BenchmarkAsFunc = Callable[[], float]
 
 
-@dataclass(frozen=True)
+@dataclass(frozen=True, slots=True)
 class BenchmarkResult:
     type_: str
     name: str
     description: str
     iterations: int
-    avg_time: Decimal
+    is_gc_disabled: bool
+    avg_time: float
+    median_time: float
+    std_dev: float
+
+
+@dataclass(frozen=True, slots=True)
+class BenchmarkGroupResult:
+    type_: str
+    benchmark_results: list[BenchmarkResult]
+
 
-    
 class Benchmark:
     def __init__(
             self,
@@ -28,83 +41,109 @@ class Benchmark:
             *,
             type_: str,
             name: str,
-            description: str,
+            description: str
-            iterations: int
     ) -> None:
         self.func = func
         self.type_ = type_
         self.name = name
         self.description = description
-        self.iterations = iterations
 
-    def run(self) -> float:
+    def single_run(self, is_gc_disabled: bool = False) -> float:
-        return self.func()
+        if is_gc_disabled:
+            was_gc_enabled = gc.isenabled()
+            gc.disable()
+
+            start = time.perf_counter()
+            self.func()
+            end = time.perf_counter()
+
+            if was_gc_enabled:
+                gc.enable()
+            gc.collect()
+
+            return end - start
+        else:
+            start = time.perf_counter()
+            self.func()
+            end = time.perf_counter()
+            return end - start
+
+    def multiple_runs(self, iterations: int, is_gc_disabled: bool = False) -> tuple[float]:
+        run_attempts: list[float] = []
+        for _ in range(iterations):
+            run_attempts.append(self.single_run(is_gc_disabled))
+        return tuple(*run_attempts)
 
     @override
     def __repr__(self) -> str:
-        return f'Benchmark<{self.type_=}, {self.name=}, {self.description=}, {self.iterations=}>'
+        return f'Benchmark<{self.type_=}, {self.name=}, {self.description=}>'
 
     @override
     def __str__(self) -> str:
-        return f'Benchmark({self.type_=}, {self.name=}, {self.description=}, {self.iterations=})'
+        return f'benchmark {self.name} with type {self.type_}'
 
 
 class Benchmarks:
-    _benchmarks: ClassVar[list[Benchmark]] = []
+    def __init__(self, *benchmarks: Benchmark) -> None:
+        self._benchmarks: list[Benchmark] = list(benchmarks)
+        self._benchmarks_grouped_by_type: dict[str, list[Benchmark]] = {}
+        self._benchmarks_paired_by_name: dict[str, Benchmark] = {}
 
-    @overload
-    @classmethod
     def register(
-            cls,
+            self,
-            call: BenchmarkAsFunc,
+            type_: str,
-            *,
+            description: str = ""
-            type_: str = "",
-            description: str = "",
-            iterations: int = 100,
-    ) -> BenchmarkAsFunc:
-        ...
-
-    @overload
-    @classmethod
-    def register(
-            cls,
-            call: None = None,
-            *,
-            type_: str = "",
-            description: str = "",
-            iterations: int = 100,
     ) -> Callable[[BenchmarkAsFunc], BenchmarkAsFunc]:
-        ...
-
-    @classmethod
-    def register(
-            cls,
-            call: BenchmarkAsFunc | None = None,
-            *,
-            type_: str = "",
-            description: str = "",
-            iterations: int = 100,
-    ) -> Callable[[BenchmarkAsFunc], BenchmarkAsFunc] | BenchmarkAsFunc:
         def decorator(func: BenchmarkAsFunc) -> BenchmarkAsFunc:
-            cls._benchmarks.append(
+            benchmark = Benchmark(
-                Benchmark(
+                func,
-                    func,
+                type_=type_,
-                    type_=type_,
+                name=func.__name__,
-                    name=func.__name__,
+                description=description or f'description for {func.__name__} with type {type_}',
-                    description=description or f'description for {func.__name__} with {iterations} iterations',
-                    iterations=iterations
-                )
             )
+            self._benchmarks.append(benchmark)
+            self._benchmarks_paired_by_name[type_] = benchmark
+            self._benchmarks_grouped_by_type.setdefault(type_, []).append(benchmark)
             return func
+        return decorator
 
-        if call is None:
+    def run_benchmark_by_name(self, name: str, iterations: int = 100, is_gc_disables: bool = False) -> BenchmarkResult:
-            return decorator
+        benchmark = self.get_benchmark_by_name(name)
-        else:
+        if not benchmark:
-            return decorator(call)
+            raise BenchmarkNotFound(name)
+        run_attempts: tuple[float] = benchmark.multiple_runs(iterations, is_gc_disables)
 
-    @classmethod
+        avg = statistics.mean(run_attempts)
-    def get_benchmarks(cls) -> list[Benchmark]:
+        median = statistics.median(run_attempts)
-        return cls._benchmarks
+        std_dev = statistics.stdev(run_attempts) if len(run_attempts) > 1 else 0
 
+        return BenchmarkResult(
+            type_=benchmark.type_,
+            name=benchmark.name,
+            description=benchmark.description,
+            iterations=iterations,
+            is_gc_disabled=is_gc_disables,
+            avg_time=avg,
+            median_time=median,
+            std_dev=std_dev
+        )
 
-benchmark = Benchmarks.register
+    def run_benchmarks_by_type(self, type_: str, iterations: int = 100, is_gc_disabled: bool = False) -> BenchmarkGroupResult:
+        benchmarks = self.get_benchmarks_by_type(type_)
+        if not benchmarks:
+            raise BenchmarksNotFound(type_)
+        benchmark_results: list[BenchmarkResult] = []
+
+        for benchmark in benchmarks:
+            benchmark_results.append(self.run_benchmark_by_name(benchmark.name, iterations, is_gc_disabled))
+
+        return BenchmarkGroupResult(
+            type_=type_,
+            benchmark_results=benchmark_results
+        )
+
+    def get_benchmarks_by_type(self, type_: str) -> list[Benchmark]:
+        return self._benchmarks_grouped_by_type.get(type_, [])
+
+    def get_benchmark_by_name(self, name: str) -> Benchmark | None:
+        return self._benchmarks_paired_by_name.get(name)

metrics/benchmarks/utils.py

@@ -3,10 +3,8 @@ __all__ = [
     "get_time_of_validate_routers_for_collisions",
     "get_time_of_most_similar_command",
     "get_time_of_finds_appropriate_handler",
-    "attempts_to_average",
+    "get_kernel_version",
-    "run_benchmark",
+    "get_gpu_info"
-    "run_all_benchmarks",
-    "get_kernel_version"
 ]
 
 import io
@@ -18,6 +16,8 @@ from concurrent.futures import ProcessPoolExecutor
 from contextlib import redirect_stdout
 from decimal import ROUND_HALF_UP, Decimal
 
+import pynvml
+
 from argenta import App
 from argenta.router import Router
 from argenta.command.models import InputCommand
@@ -48,7 +48,7 @@ def get_time_of_most_similar_command(app: App, unknown_command: str) -> float:
     return (end - start) * 1000
 
 
-def get_time_of_finds_appropriate_handler(router: "Router", input_command: "InputCommand") -> float:
+def get_time_of_finds_appropriate_handler(router: Router, input_command: InputCommand) -> float:
     start = time.perf_counter()
     with redirect_stdout(io.StringIO()):
         router.finds_appropriate_handler(input_command)
@@ -90,29 +90,21 @@ def get_kernel_version() -> dict[str, str]:
             'product_name': platform.system(),
         }
 
+def get_gpu_info() -> str:
+    try:
+        pynvml.nvmlInit()
+        device_count = pynvml.nvmlDeviceGetCount()
+        if device_count == 0:
+            return "N/A"
 
-def attempts_to_average(bench_attempts: list[float], iterations: int) -> Decimal:
+        handle = pynvml.nvmlDeviceGetHandleByIndex(0)
-    return Decimal(sum(bench_attempts) / iterations).quantize(Decimal("0.0001"), rounding=ROUND_HALF_UP)
+        name = pynvml.nvmlDeviceGetName(handle)
 
+        if isinstance(name, bytes):
+            name = name.decode("utf-8")
 
-def run_all_benchmarks() -> dict[str, list[BenchmarkResult]]:
+        pynvml.nvmlShutdown()
-    all_benchmarks: list[Benchmark] = Benchmarks.get_benchmarks()
+        return name
+    except pynvml.NVMLError:
+        return "N/A"
 
-    workers = os.cpu_count() or 1
-    with ProcessPoolExecutor(max_workers=workers) as executor:
-        results = executor.map(run_benchmark, all_benchmarks)
-
-    type_paired_benchmarks: dict[str, list[BenchmarkResult]] = {}
-
-    for result in results:
-        type_paired_benchmarks.setdefault(result.type_, []).append(result)
-
-    return type_paired_benchmarks
-
-
-def run_benchmark(benchmark: Benchmark) -> BenchmarkResult:
-    bench_attempts: list[float] = []
-    for _ in range(benchmark.iterations):
-        bench_attempts.append(benchmark.run())
-    avg = attempts_to_average(bench_attempts, benchmark.iterations)
-    return BenchmarkResult(benchmark.type_, benchmark.name, benchmark.description, benchmark.iterations, avg)

metrics/handlers.py

@@ -10,7 +10,7 @@ from argenta.command.models import Command
 from argenta.response import Response
 from argenta.router import Router
 from .benchmarks.models import BenchmarkResult
-from .benchmarks.utils import run_all_benchmarks, get_kernel_version
+from .benchmarks.utils import run_all_benchmarks, get_kernel_version, get_gpu_info
 
 console = Console()
 router = Router(title="Metrics commands:")
@@ -19,6 +19,7 @@ router = Router(title="Metrics commands:")
 @router.command(Command("all-print", description="Print all benchmarks results"))
 def all_print_handler(_: Response) -> None:
     cpu_info = cpuinfo.get_cpu_info()
+    gpu_info = get_gpu_info()
     os_info = get_kernel_version()
 
     table = Table(show_header=True, header_style="bold cyan", border_style="blue", show_lines=True)
@@ -29,7 +30,8 @@ def all_print_handler(_: Response) -> None:
     table.add_row("OS Name", os_info['product_name'])
     table.add_row("OS Kernel Version", os_info['kernel_version'])
     table.add_row("Architecture", cpu_info['arch'])
-    table.add_row("Processor", cpu_info['brand_raw'])
+    table.add_row("CPU", cpu_info['brand_raw'])
+    table.add_row("GPU", gpu_info)
     table.add_row("Python Version", cpu_info['python_version'])
     table.add_row("Python Implementation", platform.python_implementation())
 

pyproject.toml

@@ -36,6 +36,7 @@ tests = [
     "pytest-mock>=3.15.1",
 ]
 metrics = [
+    "nvidia-ml-py>=13.590.44",
     "py-cpuinfo>=9.0.0",
 ]
 

uv.lock

@@ -62,6 +62,7 @@ linters = [
     { name = "wemake-python-styleguide" },
 ]
 metrics = [
+    { name = "nvidia-ml-py" },
     { name = "py-cpuinfo" },
 ]
 tests = [
@@ -95,7 +96,10 @@ linters = [
     { name = "ruff", specifier = ">=0.12.12" },
     { name = "wemake-python-styleguide", specifier = ">=0.17.0" },
 ]
-metrics = [{ name = "py-cpuinfo", specifier = ">=9.0.0" }]
+metrics = [
+    { name = "nvidia-ml-py", specifier = ">=13.590.44" },
+    { name = "py-cpuinfo", specifier = ">=9.0.0" },
+]
 tests = [
     { name = "pyfakefs", specifier = ">=5.5.0" },
     { name = "pytest", specifier = ">=8.3.2" },
@@ -557,6 +561,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" },
 ]
 
+[[package]]
+name = "nvidia-ml-py"
+version = "13.590.44"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/1b/23/3871537f204aee823c574ba25cbeb08cae779979d4d43c01adddda00bab9/nvidia_ml_py-13.590.44.tar.gz", hash = "sha256:b358c7614b0fdeea4b95f046f1c90123bfe25d148ab93bb1c00248b834703373", size = 49737, upload-time = "2025-12-08T14:41:10.872Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e4/47/4c822bd37a008e72fd5a0eae33524ae3ac97b13f7030f63bae1728b8957e/nvidia_ml_py-13.590.44-py3-none-any.whl", hash = "sha256:18feb54eca7d0e3cdc8d1a040a771eda72d9ec3148e5443087970dbfd7377ecc", size = 50683, upload-time = "2025-12-08T14:41:09.597Z" },
+]
+
 [[package]]
 name = "packaging"
 version = "25.0"