pytimers 2.3.1

Timing of functions, methods or blocks of code made easy.

PyTimers

Python micro library for easy to use code timing with the elapsed times logged using the standard logging library.

Requires Python 3.6 and higher.

How to Install

# pip install pytimers

Usage Example

The library allows you to measure the run time of your code in two ways. Using decorators and using context manager to measure run time of any code block.

Timer Decorator

The timer decorator can be applied to both synchronous and asynchronous functions and methods. Decorating classes is not supported and will raise TypeError. PyTimers leverage python library decorator to make sure decorating will preserve the function/method signature, name and docstring.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

@timer
def func(*args: int):
    print("Hello from func.")
    sleep(1)
    return sum(args)


if __name__ == "__main__":
    func(1, 2, 3)

Hello from func.
INFO:pytimers.timer:Finished func in 1.0018878109985963s.

Class Methods and Static methods

To combine timer decorator with decorators @staticmethoid and @classmethod you have to first apply timer decorator. Applying the decorators the other way around will result in TypeError exception.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

class Foo:
    @staticmethod
    @timer
    def method(*args: int):
        print("Hello from static method.")
        sleep(1)
        return sum(args)


if __name__ == "__main__":
    foo = Foo()    
    foo.method(1, 2, 3)

Hello from static method.
INFO:pytimers.timer:Finished Foo.method in 1.0001546249259263s.

Block Timer

To measure time of any code not enclosed in a callable object you can use timer context manager.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

if __name__ == "__main__":
    with timer:
        print("Hello from code block.")
        sleep(1)

Hello from code block.
INFO:pytimers.timer:Finished code block in 1.0027356049977243s.

You can use the latest time measurement from the timer in your own code by accessing the time field.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

if __name__ == "__main__":
    with timer:
        print("We want to run this under 5s.")
        sleep(1)
    print(f"We still had {5 - timer.time}s remaining.")

We want to run this under 5s.
INFO:pytimers.timer:Finished code block in 1.003774584038183s.
We still had 3.996225415961817s remaining.

Block of code can also be named to increase log readability.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

if __name__ == "__main__":
    with timer.named("data processing pipeline"):
        print("Hello from code block.")
        sleep(1)

Hello from code block.
INFO:pytimers.timer:Finished data processing pipeline in 1.0051407059945632s.

Timer context manager also allows you to stack context managers freely without a worry of interference.

import logging
from time import sleep

from pytimers import timer


logging.basicConfig(level=logging.INFO)

if __name__ == "__main__":
    with timer.named("data collecting pipeline"):
        print("Hello from code block n.1.")
        sleep(1)
        with timer:
            print("Hello from code block n.2.")
            sleep(1)
            with timer.named("data processing pipeline"):
                print("Hello from code block n.3.")
                sleep(1)

Hello from code block n.1.
Hello from code block n.2.
Hello from code block n.3.
INFO:pytimers.timer:Finished data processing pipeline in 1.0008160540019162s.
INFO:pytimers.timer:Finished code block in 2.005773539072834s.
INFO:pytimers.timer:Finished data collecting pipeline in 3.007467524963431s.

Timer Custom Configuration

If you need to customize the timer you can create your own timer using provided Timer class. Customization consists of disabling logging, setting the log level, setting the log message template as string.Template compatible stings and adding custom triggers.

import logging
from time import sleep

from pytimers import Timer


logging.basicConfig(level=logging.INFO)

custom_timer = Timer(
    log_template="Processing ${name} took ${duration}s.",
    log_level=logging.WARNING,
)

@custom_timer
def func(*args: int):
    print("Hello from func.")
    sleep(1)
    return sum(args)


if __name__ == "__main__":
    func(1, 2, 3)

Hello from func.
WARNING:pytimers.timer:Processing func took 1.0028993980085943s.

Triggers should be functions with the following signature.

def trigger(duration: float, name: str, code_block: bool) -> None:
    pass

Build Status

PyPi