def save_load_benchmark():
from relstorage.cache import LocalClientBucket
from io import BytesIO
bucket = LocalClientBucket(10*1024*1024)
i = 1
j = 0
while bucket.size < bucket.limit - i:
val = (str(j) * i).encode('ascii')
if len(val) > bucket.limit or bucket.size + len(val) > bucket.limit:
break
bucket[str(i)] = val
if i < 1096:
i += 50
j += 1
else:
j += 1
i += 1
print("Len", len(bucket), "size",bucket.size, "i", i)
print("Len", len(bucket), "size", bucket.size)
number = 50
import timeit
import statistics
import cProfile
import pstats
def write():
io = BytesIO()
bucket.write_to_file(io)
bio = BytesIO()
bucket.write_to_file(bio)
def load():
bio.seek(0)
b2 = LocalClientBucket(bucket.limit)
b2.load_from_file(bio)
write_timer = timeit.Timer(write)
write_times = write_timer.repeat(number=number)
print("write average", statistics.mean(write_times), "stddev", statistics.stdev(write_times))
#pr = cProfile.Profile()
#pr.enable()
read_timer = timeit.Timer(load)
read_times = read_timer.repeat(number=number)
#pr.disable()
#ps = pstats.Stats(pr).sort_stats('cumulative')
#ps.print_stats()
print("read average", statistics.mean(read_times), "stddev", statistics.stdev(read_times))
def load():
bio.seek(0)
b2 = LocalClientBucket(bucket.limit)
b2.load_from_file(bio)
def load():
b2 = LocalClientBucket(bucket.limit)
_Loader.load_local_cache(cache_options, cache_pfx, b2)
def save_load_benchmark():
from relstorage.cache import LocalClientBucket, _Loader
from io import BytesIO
import os
import itertools
import sys
sys.setrecursionlimit(500000)
bucket = LocalClientBucket(500 * 1024 * 1024)
print("Testing", type(bucket._dict))
size_dists = [100] * 800 + [300] * 500 + [1024] * 300 + [2048] * 200 + [
4096
] * 150
with open('/dev/urandom', 'rb') as rnd:
data = [rnd.read(x) for x in size_dists]
data_iter = itertools.cycle(data)
for j, datum in enumerate(data_iter):
if len(datum
) > bucket.limit or bucket.size + len(datum) > bucket.limit:
break
# To ensure the pickle memo cache doesn't just write out "use object X",
# but distinct copies of the strings, we need to copy them
bucket[str(j)] = datum[:-1] + b'x'
assert bucket[str(j)] is not datum
#print("Len", len(bucket), "size", bucket.size, "dlen", len(datum))
print("Len", len(bucket), "size", bucket.size)
number = 1
import timeit
import statistics
import cProfile
import pstats
cache_pfx = "pfx"
cache_options = MockOptions()
cache_options.cache_local_dir = '/tmp'
cache_options.cache_local_dir_compress = False
def write():
fname = _Loader.save_local_cache(cache_options, cache_pfx, bucket)
os.remove(fname)
def load():
b2 = LocalClientBucket(bucket.limit)
_Loader.load_local_cache(cache_options, cache_pfx, b2)
#write_timer = timeit.Timer(write)
#write_times = write_timer.repeat(number=number)
#print("write average", statistics.mean(write_times), "stddev", statistics.stdev(write_times))
#read_timer = timeit.Timer(load)
#read_times = read_timer.repeat(number=number)
#print("read average", statistics.mean(read_times), "stddev", statistics.stdev(read_times))
#pr = cProfile.Profile()
#pr.enable()
fname = _Loader.save_local_cache(cache_options, cache_pfx, bucket)
print("Saved to", fname)
#pr.disable()
#ps = pstats.Stats(pr).sort_stats('cumulative')
#ps.print_stats()
#return
pr = cProfile.Profile()
pr.enable()
_Loader.load_local_cache(cache_options, cache_pfx,
LocalClientBucket(bucket.limit))
pr.disable()
ps = pstats.Stats(pr).sort_stats('cumulative')
ps.print_stats(.4)
