Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

timy

Package Overview
Dependencies
Maintainers
1
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

timy

Minimalist measurement of python code time

  • 0.4.2
  • PyPI
  • Socket score

Maintainers
1

timy

Python 3.3 Python 3.4 Python 3.5 Python 3.6

CircleCI Codecov

Minimalist measurement of python code time

timy comes with a different idea of the built-in module timeit. It adds flexibility and different ways of measuring code time, using simple context managers and function decorators.

Installing

pip install timy

Usage

Decorating a function

Let's say you have a calculate function and you want to keep track of its execution time

import timy

@timy.timer()
def calculate(n, r):
    """
    Divide, multiply and sum 'n' to every number in range 'r'
    returning the result list
    """
    return [i / n * n + n for i in range(r)]

Whenever you call that function, the execution time will be tracked

calculate(5, 10000000)
>> Timy executed (calculate) for 1 time(s) in 1.529540 seconds
>> Timy best time was 1.529540 seconds

Changing the ident and adding loops to the execution

import timy

@timy.timer(ident='My calculation', loops=10)
def calculate(n, r):
    return [i / n * n + n for i in range(r)]

calculate(5, 10000000)
>> My calculation executed (calculate) for 10 time(s) in 15.165313 seconds
>> My calculation best time was 1.414186 seconds

Tracking specific points along your code

The with statement can also be used to measure code time

Named tracking points can be added with the track function

import timy

with timy.Timer() as timer:
    N = 10000000
    for i in range(N):
        if i == N/2:
            timer.track('Half way')

>> Timy (Half way) 0.557577 seconds
>> Timy 0.988087 seconds            

Another usage of tracking in a prime factors function

def prime_factors(n):
    with timy.Timer('Factors') as timer:
        i = 2
        factors = []
        def add_factor(n):
            factors.append(n)
            timer.track('Found a factor')

        while i * i <= n:
            if n % i == 0:
                add_factor(i)
                n //= i
            else:
                i += 1
        return factors + [n]

factors = prime_factors(600851475143)
print(factors)

>> Factors (Found a factor) 0.000017 seconds
>> Factors (Found a factor) 0.000376 seconds
>> Factors (Found a factor) 0.001547 seconds
>> Factors 0.001754 seconds
>> [71, 839, 1471, 6857]

Configuring

Importing timy config
from timy.settings import timy_config
Enable or disable timy trackings

You can enable or disable timy trackings with the tracking value.

The default value of tracking is True

timy_config.tracking = False
Changing the way timy outputs information

You can choose between print or logging for all timy outputs by setting the value of tracking_mode.

The default value of tracking_mode is TrackingMode.PRINTING.

from timy.settings import (
    timy_config,
    TrackingMode
)

timy_config.tracking_mode = TrackingMode.LOGGING

timy logs at the INFO level, which is not printed or stored by default. To configure the logging system to print all INFO messages do

import logging
logging.basicConfig(level=logging.INFO)

or to configure the logging system to print only timy's INFO messages do

import logging
logging.basicConfig()
logging.getLogger('timy').level=logging.INFO

Contribute

Contributions are always welcome, but keep it simple and small.

License

This project is licensed under the MIT License - see the LICENSE file for details

Changelog

v 0.4.0 (September 23, 2017)

  • Drops py2 support and adds 100% coverage with CI integration

v 0.3.3 (April 19, 2017)

  • Adds an optional argument include_sleeptime to count time elapsed including sleep time (include_sleeptime=True) and excluding sleep time (include_sleeptime=False)

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc