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https://github.com/morpheus65535/bazarr.git
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eb296e13c1
* Use Hamming textdistance library Used Hamming textdistance to sort by closest match. * Global search UI improvements Increased dropdown height to show more results initially (and which can also be scrolled into view). Scrollbars will appear automatically as needed. Remove dropdown when Search box is cleared. * Added textdistance 4.6.2 library
139 lines
3.7 KiB
Python
139 lines
3.7 KiB
Python
from __future__ import annotations
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# built-in
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import json
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import math
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from collections import defaultdict
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from timeit import timeit
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from typing import Iterable, Iterator, NamedTuple
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# external
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from tabulate import tabulate
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# app
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from .libraries import LIBRARIES_PATH, prototype
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# python3 -m textdistance.benchmark
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libraries = prototype.clone()
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class Lib(NamedTuple):
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algorithm: str
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library: str
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function: str
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time: float
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setup: str
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@property
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def row(self) -> tuple[str, ...]:
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time = '' if math.isinf(self.time) else f'{self.time:0.05f}'
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return (self.algorithm, self.library.split('.')[0], time)
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INTERNAL_SETUP = """
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from textdistance import {} as cls
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func = cls(external=False)
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"""
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STMT = """
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func('text', 'test')
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func('qwer', 'asdf')
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func('a' * 15, 'b' * 15)
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"""
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RUNS = 4000
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class Benchmark:
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@staticmethod
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def get_installed() -> Iterator[Lib]:
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for alg in libraries.get_algorithms():
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for lib in libraries.get_libs(alg):
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# try load function
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if not lib.get_function():
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print(f'WARNING: cannot get func for {lib}')
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continue
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# return library info
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yield Lib(
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algorithm=alg,
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library=lib.module_name,
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function=lib.func_name,
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time=float('Inf'),
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setup=lib.setup,
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)
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@staticmethod
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def get_external_benchmark(installed: Iterable[Lib]) -> Iterator[Lib]:
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for lib in installed:
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time = timeit(
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stmt=STMT,
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setup=lib.setup,
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number=RUNS,
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)
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yield lib._replace(time=time)
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@staticmethod
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def get_internal_benchmark() -> Iterator[Lib]:
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for alg in libraries.get_algorithms():
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setup = f'func = __import__("textdistance").{alg}(external=False)'
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yield Lib(
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algorithm=alg,
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library='**textdistance**',
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function=alg,
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time=timeit(
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stmt=STMT,
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setup=setup,
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number=RUNS,
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),
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setup=setup,
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)
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@staticmethod
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def filter_benchmark(
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external: Iterable[Lib],
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internal: Iterable[Lib],
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) -> Iterator[Lib]:
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limits = {i.algorithm: i.time for i in internal}
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return filter(lambda x: x.time < limits[x.algorithm], external)
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@staticmethod
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def get_table(libs: list[Lib]) -> str:
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table = tabulate(
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[lib.row for lib in libs],
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headers=['algorithm', 'library', 'time'],
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tablefmt='github',
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)
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table += f'\nTotal: {len(libs)} libs.\n\n'
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return table
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@staticmethod
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def save(libs: Iterable[Lib]) -> None:
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data = defaultdict(list)
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for lib in libs:
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data[lib.algorithm].append([lib.library, lib.function])
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with LIBRARIES_PATH.open('w', encoding='utf8') as f:
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json.dump(obj=data, fp=f, indent=2, sort_keys=True)
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@classmethod
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def run(cls) -> None:
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print('# Installed libraries:\n')
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installed = list(cls.get_installed())
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installed.sort()
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print(cls.get_table(installed))
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print('# Benchmarks (with textdistance):\n')
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benchmark = list(cls.get_external_benchmark(installed))
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benchmark_internal = list(cls.get_internal_benchmark())
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benchmark += benchmark_internal
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benchmark.sort(key=lambda x: (x.algorithm, x.time))
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print(cls.get_table(benchmark))
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benchmark = list(cls.filter_benchmark(benchmark, benchmark_internal))
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cls.save(benchmark)
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if __name__ == '__main__':
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Benchmark.run()
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