toolbox.watcher

module, watcher is created to trace and record program performance and keep the history.

toolbox.watcher.timeit

class, put the decorator timeit on class method you want to check the run time and then check the property watcher

import toolbox.watcher.timeit as timeit

class test1:
    def __init__(self):
        pass
    @timeit
    def test_run(self):
        fake_data_gen = (x for x in range(100000))
        j=0
        for i in fake_data_gen:
            j+=i    
        return j

t1 = test1()
print(f'run time in sec: {t1.test_run()}')
print(t1.watcher)

    run time in sec: 4999950000
    {'run_time': {'code': 'test_run', 'start_time': datetime.datetime(2022, 8, 2, 0, 58, 36, 688376), 'end_time': datetime.datetime(2022, 8, 2, 0, 58, 36, 698302), 'run time(sec)': 0.009926}}

toolbox.watcher.get_obj_size

function, return the size of given object

Args:
    obj (object): any Python object

Returns:
    str: size of the object
    

from toolbox.watcher import get_obj_size
foo = lambda x:(x+1)^200000
a = foo(100)
get_obj_size(a)

'32.000 bytes'