Merge pull request #128 from nschloe/perf-counter

use perf_counter everywhere

.github/workflows/ci.yml

@@ -23,7 +23,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ["3.7", "3.8", "3.9", "3.10-dev"]
     steps:
       - uses: actions/setup-python@v2
         with:

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = perfplot
-version = 0.9.10
+version = 0.9.11
 author = Nico Schlömer
 author_email = nico.schloemer@gmail.com
 description = Performance plots for Python code snippets
@@ -22,6 +22,7 @@ classifiers =
     Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
     Topic :: Software Development
     Topic :: Utilities
 keywords =
@@ -34,7 +35,6 @@ package_dir =
 packages = find:
 install_requires =
     dufte >= 0.2.20
-    importlib_metadata;python_version<"3.8"
     matplotlib
     numpy
     rich

src/perfplot/__init__.py

@@ -1,11 +1,3 @@
-from .__about__ import __version__
 from ._main import bench, live, plot, save, show
 
-__all__ = [
-    "__version__",
-    "bench",
-    "plot",
-    "show",
-    "save",
-    "live",
-]
+__all__ = ["bench", "plot", "show", "save", "live"]

src/perfplot/_main.py

@@ -1,7 +1,9 @@
+from __future__ import annotations
+
 import io
 import time
 import timeit
-from typing import Callable, List, Optional, Union
+from typing import Callable
 
 try:
     # Python 3.8+
@@ -55,11 +57,11 @@ def _auto_time_unit(time_s: float) -> str:
 class PerfplotData:
     def __init__(
         self,
-        n_range: List[int],
+        n_range: list[int],
         timings_s,
         flop,
-        labels: List[str],
-        xlabel: Optional[str],
+        labels: list[str],
+        xlabel: str | None,
     ):
         self.n_range = np.asarray(n_range)
         self.timings_s = timings_s
@@ -70,9 +72,9 @@ def __init__(
     def plot(  # noqa: C901
         self,
         time_unit: str = "s",
-        relative_to: Optional[int] = None,
-        logx: Union[str, bool] = "auto",
-        logy: Union[str, bool] = "auto",
+        relative_to: int | None = None,
+        logx: str | bool = "auto",
+        logy: str | bool = "auto",
     ):
         if logx == "auto":
             # Check if the x values are approximately equally spaced in log
@@ -232,9 +234,9 @@ def __next__(self):
             # with one repetition only can be somewhat off because the CPU needs to spin
             # up first. The actual times are only reached after a few hundred
             # nanoseconds of computation. Most of the time it's okay though.
-            t0_ns = time.time_ns()
+            t0_ns = time.perf_counter_ns()
             val = kernel(data)
-            t1_ns = time.time_ns()
+            t1_ns = time.perf_counter_ns()
             t_ns = t1_ns - t0_ns
 
             if t_ns == 0:
@@ -323,16 +325,16 @@ def _b(data, kernel: Callable, repeat: int):
 
 def live(
     setup: Callable,
-    kernels: List[Callable],
+    kernels: list[Callable],
     n_range: npt.ArrayLike,
-    labels: Optional[List[str]] = None,
-    xlabel: Optional[str] = None,
+    labels: list[str] | None = None,
+    xlabel: str | None = None,
     target_time_per_measurement: float = 1.0,
-    max_time: Optional[float] = None,
-    equality_check: Optional[Callable] = np.allclose,
+    max_time: float | None = None,
+    equality_check: Callable | None = np.allclose,
     show_progress: bool = True,
-    logx: Union[str, bool] = "auto",
-    logy: Union[str, bool] = "auto",
+    logx: Literal["auto"] | bool = "auto",
+    logy: Literal["auto"] | bool = "auto",
 ):
     if labels is None:
         labels = [k.__name__ for k in kernels]
@@ -441,15 +443,15 @@ def callback():
 
 
 def bench(
-    kernels: List[Callable],
-    n_range: List[int],
-    setup: Optional[Union[Callable, List[Callable]]] = None,
-    flops: Optional[Callable] = None,
-    labels: Optional[List[str]] = None,
-    xlabel: Optional[str] = None,
+    kernels: list[Callable],
+    n_range: list[int],
+    setup: Callable | list[Callable] | None = None,
+    flops: Callable | None = None,
+    labels: list[str] | None = None,
+    xlabel: str | None = None,
     target_time_per_measurement: float = 1.0,
-    max_time: Optional[float] = None,
-    equality_check: Optional[Callable] = np.allclose,
+    max_time: float | None = None,
+    equality_check: Callable | None = np.allclose,
     show_progress: bool = True,
 ):
     if labels is None:
@@ -509,9 +511,9 @@ def callback():
 def plot(
     *args,
     time_unit: str = "s",
-    logx: Union[str, bool] = "auto",
-    logy: Union[str, bool] = "auto",
-    relative_to: Optional[int] = None,
+    logx: Literal["auto"] | bool = "auto",
+    logy: Literal["auto"] | bool = "auto",
+    relative_to: int | None = None,
     **kwargs,
 ):
     out = bench(*args, **kwargs)
@@ -526,9 +528,9 @@ def plot(
 def show(
     *args,
     time_unit: str = "s",
-    relative_to: Optional[int] = None,
-    logx: Union[bool, Literal["auto"]] = "auto",
-    logy: Union[bool, Literal["auto"]] = "auto",
+    relative_to: int | None = None,
+    logx: bool | Literal["auto"] = "auto",
+    logy: bool | Literal["auto"] = "auto",
     **kwargs,
 ):
     out = bench(*args, **kwargs)
@@ -545,9 +547,9 @@ def save(
     transparent=True,
     *args,
     time_unit: str = "s",
-    logx: Union[bool, Literal["auto"]] = "auto",
-    logy: Union[bool, Literal["auto"]] = "auto",
-    relative_to: Optional[int] = None,
+    logx: bool | Literal["auto"] = "auto",
+    logy: bool | Literal["auto"] = "auto",
+    relative_to: int | None = None,
     **kwargs,
 ):
     out = bench(*args, **kwargs)