fast lambda expression serializer
Project description
lambdser
A lambda expression serializer for python. Can be used to make pickle eat lambdas with closures.
A typical use case is serializing lambdas for multiprocessing. Using lambdser in front, let multiprocessing eat the lambda expression.
Install
pip install lambdser
or install it from github
pip install git+https://github.com/cloasdata/lambdser.git
or just clone it
todo
I did not find a way to register lambdser es pickler in the pickle module. It would be really useful if somebody can help me. However, one can use the LambdserPickler class to overwrite the default behaviour of pickle.Pickler (?) or use LamdserPickler as the one pickler.
I also did not test for particular edge cases. But feel free to contribute such tests.
usage
Example 1: module namespace
using it in module namespace.
import pickle
import lambdser
two = "2"
expression = lambda x: "number" + x + two
result1 = expression("4")
ser = lambdser.dumps(expression)
# now pickle can dump!
s = pickle.dumps(ser)
ser = pickle.loads(s)
expression = lambdser.loads(ser)
result2 = expression("4")
assert result1 == result2
Example 2: Using closure
Make a proxy of what you want to spawn in a separate process.
import lambdser
import multiprocessing as mp
def make_proxy(para, *funcs):
# make proxy for the mp
ser_list = []
for f in funcs:
ser_list.append(lambdser.dumps(f))
return para, ser_list
def processor(*ser):
# unzip the proxy and to the work
para, funcs = ser
funcs = [lambdser.loads(ser) for ser in funcs]
res = None
for f in funcs:
res = f(para)
print(res)
return res
def do_stuff():
two = "2"
ser = make_proxy("4", lambda x: x + two)
mp.Process(target=processor, args=ser).start()
do_stuff()
performance
it is around 100 times faster than dill. This was one reason to develop this package.
py .\test\profiling.py
Results dumps
lambdser: 0.012459
dill: 1.485589
times: 119.236291
Copyright © 2022 Simon Bauer
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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