A collection of benchmarking tools.

Last update: Jan 28, 2022

Related tags

Testing bench-utils

Overview

Benchmark Utilities

About

A collection of benchmarking tools. PYPI Package

Using the library
- Installing and using the library
Manually install the library
- Prerequisites
- Install the requirements
License

Using the library

Installing and using the library

First, you need to install the library either using pip:

$ pip install bench_utils

Then, import it and use it like so:

from bench_utils import timeit, profileit

# --- Timeit --- #
# Context Manager
with timeit():
    # A code block
    pass


@timeit()
def my_func():
    # Function code
    pass


# --- Profileit --- #
# Context Manager
with profileit():
    # A code block
    pass


@profileit()
def my_func():
    # Function code
    pass

For more advanced examples check example_timeit.py and example_profileit.py .

Manually install the library

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

You need to have a machine with anaconda installed and any Bash based shell (e.g. zsh) installed.

$ conda -V
conda 4.10.1

$ echo $SHELL
/usr/bin/zsh

Install the requirements

All the installation steps are being handled by the Makefile. First, create a file called ~/.pypirc with your pypi login details, as follows:

[pypi]
username = your_pypi_username
password = your_pypi_password

Then, modify the python version and everything else you need in the settings.ini.

Finally, execute the following commands:

$ make create_env
$ conda activate bench_utils
$ make release

License

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

Python tools for penetration testing

pyTools_PT python tools for penetration testing Please don't use these tool for illegal purposes. These tools is meant for penetration testing for leg

1 Dec 1, 2021

ToqueIO Nuke tools - A collection of tools designed to assist in enhancing your workflows within nuke

4 Feb 19, 2022

x-tools is a collection of tools developed in Python

x-tools X-tools is a collection of tools developed in Python Commands\

5 Jan 24, 2022

py.test fixture for benchmarking code

Overview docs tests package A pytest fixture for benchmarking code. It will group the tests into rounds that are calibrated to the chosen timer. See c

1k Jan 3, 2023

Airspeed Velocity: A simple Python benchmarking tool with web-based reporting

airspeed velocity airspeed velocity (asv) is a tool for benchmarking Python packages over their lifetime. It is primarily designed to benchmark a sing

745 Dec 28, 2022

FedNLP: A Benchmarking Framework for Federated Learning in Natural Language Processing

FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP only focuses on adavanced models and dataset, while FedML supports various federated optimizers (e.g., FedAvg) and platforms (Distributed Computing, IoT/Mobile, Standalone).

216 Nov 27, 2022

whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.

128 Dec 16, 2022

Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on

176 Dec 17, 2022

FedScale: Benchmarking Model and System Performance of Federated Learning

FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca

268 Jan 1, 2023

Pip-package for trajectory benchmarking from "Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds", ECMR'21

Map Metrics for Trajectory Quality Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consiste

31 Oct 28, 2022

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im

25 Sep 6, 2022

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.

132 Dec 23, 2022

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

12 Sep 26, 2021

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm

188 Dec 17, 2022

Molecular Sets (MOSES): A benchmarking platform for molecular generation models

Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery

3 Oct 14, 2022

Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env

48 Dec 20, 2022

Releases(1.0.3)

1.0.3(Jan 28, 2022)

Full Changelog: https://github.com/drkostas/bench-utils/compare/0.0.2...1.0.3
Source code(tar.gz)
Source code(zip)
0.0.2(Jan 26, 2022)

Full Changelog: https://github.com/drkostas/bench-utils/compare/0.0.1...0.0.2
Source code(tar.gz)
Source code(zip)
0.0.1(Dec 21, 2021)

Full Changelog: https://github.com/drkostas/bench-utils/commits/0.0.1
Source code(tar.gz)
Source code(zip)

A collection of benchmarking tools.

Related tags

Overview

Benchmark Utilities

About

Table of Contents

Using the library

Installing and using the library

Manually install the library

Prerequisites

Install the requirements

License

You might also like...

Python tools for penetration testing

ToqueIO Nuke tools - A collection of tools designed to assist in enhancing your workflows within nuke

x-tools is a collection of tools developed in Python

py.test fixture for benchmarking code

Airspeed Velocity: A simple Python benchmarking tool with web-based reporting

FedNLP: A Benchmarking Framework for Federated Learning in Natural Language Processing

whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.

Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

FedScale: Benchmarking Model and System Performance of Federated Learning

Pip-package for trajectory benchmarking from "Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds", ECMR'21

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Molecular Sets (MOSES): A benchmarking platform for molecular generation models

Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

WIP SAT benchmarking tooling, written with only my personal use in mind.

ColossalAI-Benchmark - Performance benchmarking with ColossalAI

Releases(1.0.3)

1.0.3(Jan 28, 2022)

0.0.2(Jan 26, 2022)

0.0.1(Dec 21, 2021)

Owner

Kostas Georgiou

Python Rest Testing

A pytest plugin to skip `@pytest.mark.slow` tests by default.

ApiPy was created for api testing with Python pytest framework which has also requests, assertpy and pytest-html-reporter libraries.

Using openpyxl in Python, performed following task

Declarative HTTP Testing for Python and anything else

Testing - Instrumenting Sanic framework with Opentelemetry

Make Selenium work on Github Actions

A tool to auto generate the basic mocks and asserts for faster unit testing

Photostudio是一款能进行自动化检测网页存活并实时给网页拍照的工具，通过调用Fofa/Zoomeye/360qua/shodan等 Api快速准确查询资产并进行网页截图，从而实施进一步的信息筛查。

Simple assertion library for unit testing in python with a fluent API

输入Google Hacking语句，自动调用Chrome浏览器爬取结果

An AWS Pentesting tool that lets you use one-liner commands to backdoor an AWS account's resources with a rogue AWS account - or share the resources with the entire internet 😈

AutoExploitSwagger is an automated API security testing exploit tool that can be combined with xray, BurpSuite and other scanners.

Whatsapp messages bulk sender using Python Selenium.

The Good Old Days. | Testing Out A New Module-

This is a web test framework based on python+selenium

A pytest plugin that enables you to test your code that relies on a running Elasticsearch search engine

a plugin for py.test that changes the default look and feel of py.test (e.g. progressbar, show tests that fail instantly)

An Instagram bot that can mass text users, receive and read a text, and store it somewhere with user details.

Automated mouse clicker script using PyAutoGUI and Typer.