reorg test, metadata

Author: flexatone

.github/FUNDING.yml

@@ -1,14 +1,8 @@
 import functools
-import itertools
-import multiprocessing
-import operator
-import random
 import sys
-import timeit
 
 import invoke
 
-
 run = functools.partial(invoke.Context.run, echo=True, pty=True)
 
 
@@ -23,7 +17,7 @@ def install(context):
 def clean(context):
     # type: (invoke.Context) -> None
     # run(context, f"{sys.executable} setup.py develop --uninstall")
-    run(context, f"{sys.executable} -m pip uninstall --yes automap")
+    run(context, f"{sys.executable} -m pip uninstall --yes arraymap")
 
     for artifact in ("*.egg-info", "*.so", "build", "dist"):
         run(context, f"rm -rf {artifact}")
@@ -41,61 +35,3 @@ def build(context):
 def test(context):
     # type: (invoke.Context) -> None
     run(context, f"{sys.executable} -m pytest -v")
-
-
-def do_work(info):
-    import automap
-
-    namespace = {"FrozenAutoMap": automap.FrozenAutoMap}
-    create_a = timeit.Timer("a = FrozenAutoMap(keys)", globals=namespace)
-    create_d = timeit.Timer("d = {k: i for i, k in enumerate(keys)}", globals=namespace)
-    access_a = timeit.Timer(
-        "for key in a: a[key]", "a = FrozenAutoMap(keys)", globals=namespace
-    )
-    access_d = timeit.Timer(
-        "for key in d: d[key]",
-        "d = {k: i for i, k in enumerate(keys)}",
-        globals=namespace,
-    )
-    kind, power, factor = info
-    items = factor * 10**power
-    namespace["keys"] = [kind(_) for _ in range(items)]
-    random.shuffle(namespace["keys"])
-    iterations = max(create_a.autorange()[0], create_d.autorange()[0])
-    create = create_a.timeit(iterations) / create_d.timeit(iterations)
-    size = sys.getsizeof(automap.FrozenAutoMap(namespace["keys"])) / sys.getsizeof(
-        {k: i for i, k in enumerate(namespace["keys"])}
-    )
-    iterations = max(access_a.autorange()[0], access_d.autorange()[0])
-    access = access_a.timeit(iterations) / access_d.timeit(iterations)
-    return items, create, access, size
-
-
-@invoke.task(build)
-def performance(context):
-    # type: (invoke.Context) -> None
-    print("TYPE\tITEMS\tCREATE\tACCESS\tSIZE")
-
-    def geometric_mean(xs):
-        return functools.reduce(operator.mul, xs) ** (1 / len(xs))
-
-    with multiprocessing.get_context("spawn").Pool() as pool:
-        for kind in (str, int):
-            total_create = []
-            total_access = []
-            total_size = []
-
-            for items, create, access, size in pool.imap(
-                do_work, itertools.product((kind,), range(6), range(1, 10))
-            ):
-                print(
-                    f"{kind.__name__}\t{items:,}\t{create-1:+.0%}\t{access-1:+.0%}\t{size-1:+.0%}",
-                    flush=True,
-                )
-                total_create.append(create)
-                total_access.append(access)
-                total_size.append(size)
-            print(
-                f"{kind.__name__}\tMEAN\t{geometric_mean(total_create)-1:+.0%}\t{geometric_mean(total_access)-1:+.0%}\t{geometric_mean(total_size)-1:+.0%}",
-                flush=True,
-            )