Optimize memoryview comparison: a memoryview is equal to itself, there is no
need to compare values, except if it uses float format.
Benchmark comparing 1 MiB:
from timeit import timeit
with open("/dev/random", 'br') as fp:
data = fp.read(2**20)
view = memoryview(data)
LOOPS = 1_000
b = timeit('x == x', number=LOOPS, globals={'x': data})
m = timeit('x == x', number=LOOPS, globals={'x': view})
print("bytes %f seconds" % b)
print("mview %f seconds" % m)
print("=> %f time slower" % (m / b))
Result before the change:
bytes 0.000026 seconds
mview 1.445791 seconds
=> 55660.873940 time slower
Result after the change:
bytes 0.000026 seconds
mview 0.000028 seconds
=> 1.104382 time slower
This missed optimization was discovered by Pierre-Yves David
while working on Mercurial.
Co-authored-by: Pieter Eendebak <pieter.eendebak@gmail.com>
In gh-145455, an outdated dependency caused an import error that was not
printed out (`2>&1`); the message instead said that the tools are missing.
Don't redirect stderr, to show warnings and failures.
Also, switch `blurb` to output a version on a single line (`--version` rather
than `help`), and, and don't redirect stdout either.
This results in two version info lines being printed out. These get drowned
in typical Sphinx output, and can be helpful when debugging.
* Added missing explanations for some parameters in glob and iglob.
* News entry.
* Added proper 'func' indication in News file.
* Consistent use of backticks.
* Improved wording.
* consistent wording between the two docstrings
---------
Co-authored-by: Gregory P. Smith <68491+gpshead@users.noreply.github.com>
Co-authored-by: Erlend E. Aasland <erlend@python.org>
Co-authored-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com>
Co-authored-by: Stan Ulbrych <89152624+StanFromIreland@users.noreply.github.com>
Remove PyThread_type_lock (now uses PyMutex internally).
Add new benchmark options:
- work_inside/work_outside: control work inside and outside the critical section to vary contention levels
- num_locks: use multiple independent locks with threads assigned round-robin
- total_iters: fixed iteration count per thread instead of time-based, useful for measuring fairness
- num_acquisitions: lock acquisitions per loop iteration
- random_locks: acquire random lock each iteration
Also return elapsed time from benchmark_locks() and switch lockbench.py to use argparse.
