🔀⏳ Easy throttling with asyncio support

Overview

Throttler

Python PyPI License: MIT

Build Status codecov Codacy Badge

Zero-dependency Python package for easy throttling with asyncio support.

Demo

📝 Table of Contents

🎒 Install

Just

pip install throttler

🛠 Usage Examples

All run-ready examples are here.

Throttler and ThrottlerSimultaneous

Throttler:

Context manager for limiting rate of accessing to context block.

from throttler import Throttler

# Limit to three calls per second
t = Throttler(rate_limit=3, period=1.0)
async with t:
    pass

Or

import asyncio

from throttler import throttle

# Limit to three calls per second
@throttle(rate_limit=3, period=1.0)
async def task():
    return await asyncio.sleep(0.1)

ThrottlerSimultaneous:

Context manager for limiting simultaneous count of accessing to context block.

from throttler import ThrottlerSimultaneous

# Limit to five simultaneous calls
t = ThrottlerSimultaneous(count=5)
async with t:
    pass

Or

import asyncio

from throttler import throttle_simultaneous

# Limit to five simultaneous calls
@throttle_simultaneous(count=5)
async def task():
    return await asyncio.sleep(0.1)

Simple Example

import asyncio
import time

from throttler import throttle


# Limit to two calls per second
@throttle(rate_limit=2, period=1.0)
async def task():
    return await asyncio.sleep(0.1)


async def many_tasks(count: int):
    coros = [task() for _ in range(count)]
    for coro in asyncio.as_completed(coros):
        _ = await coro
        print(f'Timestamp: {time.time()}')

asyncio.run(many_tasks(10))

Result output:

Timestamp: 1585183394.8141203
Timestamp: 1585183394.8141203
Timestamp: 1585183395.830335
Timestamp: 1585183395.830335
Timestamp: 1585183396.8460555
Timestamp: 1585183396.8460555
...

API Example

import asyncio
import time

import aiohttp

from throttler import Throttler, ThrottlerSimultaneous


class SomeAPI:
    api_url = 'https://example.com'

    def __init__(self, throttler):
        self.throttler = throttler

    async def request(self, session: aiohttp.ClientSession):
        async with self.throttler:
            async with session.get(self.api_url) as resp:
                return resp

    async def many_requests(self, count: int):
        async with aiohttp.ClientSession() as session:
            coros = [self.request(session) for _ in range(count)]
            for coro in asyncio.as_completed(coros):
                response = await coro
                print(f'{int(time.time())} | Result: {response.status}')


async def run():
    # Throttler can be of any type
    t = ThrottlerSimultaneous(count=5)        # Five simultaneous requests
    t = Throttler(rate_limit=10, period=3.0)  # Ten requests in three seconds

    api = SomeAPI(t)
    await api.many_requests(100)

asyncio.run(run())

Result output:

1585182908 | Result: 200
1585182908 | Result: 200
1585182908 | Result: 200
1585182909 | Result: 200
1585182909 | Result: 200
1585182909 | Result: 200
1585182910 | Result: 200
1585182910 | Result: 200
1585182910 | Result: 200
...

ExecutionTimer

Context manager for time limiting of accessing to context block. Simply sleep period secs before next accessing, not analog of Throttler. Also it can align to start of minutes.

import time

from throttler import ExecutionTimer

et = ExecutionTimer(60, align_sleep=True)

while True:
    with et:
        print(time.asctime(), '|', time.time())

Or

import time

from throttler import execution_timer

@execution_timer(60, align_sleep=True)
def f():
    print(time.asctime(), '|', time.time())

while True:
    f()

Result output:

Thu Mar 26 00:56:17 2020 | 1585173377.1203406
Thu Mar 26 00:57:00 2020 | 1585173420.0006166
Thu Mar 26 00:58:00 2020 | 1585173480.002517
Thu Mar 26 00:59:00 2020 | 1585173540.001494

Timer

Context manager for pretty printing start, end, elapsed and average times.

import random
import time

from throttler import Timer

timer = Timer('My Timer', verbose=True)

for _ in range(3):
    with timer:
        time.sleep(random.random())

Or

import random
import time

from throttler import timer

@timer('My Timer', verbose=True)
def f():
    time.sleep(random.random())

for _ in range(3):
    f()

Result output:

#1 | My Timer | begin: 2020-03-26 01:46:07.648661
#1 | My Timer |   end: 2020-03-26 01:46:08.382135, elapsed: 0.73 sec, average: 0.73 sec
#2 | My Timer | begin: 2020-03-26 01:46:08.382135
#2 | My Timer |   end: 2020-03-26 01:46:08.599919, elapsed: 0.22 sec, average: 0.48 sec
#3 | My Timer | begin: 2020-03-26 01:46:08.599919
#3 | My Timer |   end: 2020-03-26 01:46:09.083370, elapsed: 0.48 sec, average: 0.48 sec

👨🏻‍💻 Author

Ramzan Bekbulatov:

💬 Contributing

Contributions, issues and feature requests are welcome!

📝 License

This project is MIT licensed.

You might also like...
asyncio (PEP 3156) Redis support

aioredis asyncio (PEP 3156) Redis client library. Features hiredis parser Yes Pure-python parser Yes Low-level & High-level APIs Yes Connections Pool

File support for asyncio

aiofiles: file support for asyncio aiofiles is an Apache2 licensed library, written in Python, for handling local disk files in asyncio applications.

Pytest support for asyncio.

pytest-asyncio: pytest support for asyncio pytest-asyncio is an Apache2 licensed library, written in Python, for testing asyncio code with pytest. asy

Tortoise ORM is an easy-to-use asyncio ORM  inspired by Django.
Tortoise ORM is an easy-to-use asyncio ORM inspired by Django.

Tortoise ORM was build with relations in mind and admiration for the excellent and popular Django ORM. It's engraved in it's design that you are working not with just tables, you work with relational data.

Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

Free and Open Source Group Voice chat music player for telegram ❤️ with button support youtube playback support
Free and Open Source Group Voice chat music player for telegram ❤️ with button support youtube playback support

Free and Open Source Group Voice chat music player for telegram ❤️ with button support youtube playback support

As easy as /aitch-tee-tee-pie/ 🥧 Modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more. https://twitter.com/httpie
As easy as /aitch-tee-tee-pie/ 🥧 Modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more. https://twitter.com/httpie

HTTPie: human-friendly CLI HTTP client for the API era HTTPie (pronounced aitch-tee-tee-pie) is a command-line HTTP client. Its goal is to make CLI in

Easy and comprehensive assessment of predictive power, with support for neuroimaging features
Easy and comprehensive assessment of predictive power, with support for neuroimaging features

Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t

Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.

dataset: databases for lazy people In short, dataset makes reading and writing data in databases as simple as reading and writing JSON files. Read the

As easy as /aitch-tee-tee-pie/ 🥧 Modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more. https://twitter.com/httpie
As easy as /aitch-tee-tee-pie/ 🥧 Modern, user-friendly command-line HTTP client for the API era. JSON support, colors, sessions, downloads, plugins & more. https://twitter.com/httpie

HTTPie: human-friendly CLI HTTP client for the API era HTTPie (pronounced aitch-tee-tee-pie) is a command-line HTTP client. Its goal is to make CLI in

FastAPI extension that provides JWT Auth support (secure, easy to use, and lightweight)

FastAPI JWT Auth Documentation: https://indominusbyte.github.io/fastapi-jwt-auth Source Code: https://github.com/IndominusByte/fastapi-jwt-auth Featur

Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.

dataset: databases for lazy people In short, dataset makes reading and writing data in databases as simple as reading and writing JSON files. Read the

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. An example o

一个多语言支持、易使用的 OCR 项目。An easy-to-use OCR project with multilingual support.

AgentOCR 简介 AgentOCR 是一个基于 PaddleOCR 和 ONNXRuntime 项目开发的一个使用简单、调用方便的 OCR 项目 本项目目前包含 Python Package 【AgentOCR】 和 OCR 标注软件 【AgentOCRLabeling】 使用指南 Pytho

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. An example o

Easy and secure implementation of Azure AD for your FastAPI APIs 🔒 Single- and multi-tenant support.
Easy and secure implementation of Azure AD for your FastAPI APIs 🔒 Single- and multi-tenant support.

Easy and secure implementation of Azure AD for your FastAPI APIs 🔒 Single- and multi-tenant support.

Ultra fast asyncio event loop.
Ultra fast asyncio event loop.

uvloop is a fast, drop-in replacement of the built-in asyncio event loop. uvloop is implemented in Cython and uses libuv under the hood. The project d

A curated list of awesome Python asyncio frameworks, libraries, software and resources

Awesome asyncio A carefully curated list of awesome Python asyncio frameworks, libraries, software and resources. The Python asyncio module introduced

Comments
  • from source installation fails because `readme.md` is missing

    from source installation fails because `readme.md` is missing

    I'm running into the following when using pip install using the source tarball for throttle 0.2.2 obtained from PyPI:

        Running command python setup.py egg_info
        Traceback (most recent call last):
          File "<string>", line 1, in <module>
          File "/tmp/eb-pc17jo6j/pip-req-build-o1s1r0pd/setup.py", line 43, in <module>
            long_description=read('readme.md'),
          File "/tmp/eb-pc17jo6j/pip-req-build-o1s1r0pd/setup.py", line 10, in read
            with open(filename, encoding='utf-8') as file:
        FileNotFoundError: [Errno 2] No such file or directory: 'readme.md'
    WARNING: Discarding file:///tmp/vsc40023/easybuild_build/snakemake/7.18.2/foss-2021b/throttler/throttler-1.2.1. Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
    ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
    

    The problem is that readme.md is not included in the source tarball.

    opened by boegel 5
Releases(v1.2.2)
Owner
Ramzan Bekbulatov
Software Engineer
Ramzan Bekbulatov
Opentracing support for Starlette and FastApi

Starlette-OpenTracing OpenTracing support for Starlette and FastApi. Inspired by: Flask-OpenTracing OpenTracing implementations exist for major distri

Rene Dohmen 26 Feb 11, 2021
Drop-in MessagePack support for ASGI applications and frameworks

msgpack-asgi msgpack-asgi allows you to add automatic MessagePack content negotiation to ASGI applications (Starlette, FastAPI, Quart, etc.), with a s

Florimond Manca 128 Jan 2, 2023
Pagination support for flask

flask-paginate Pagination support for flask framework (study from will_paginate). It supports several css frameworks. It requires Python2.6+ as string

Lix Xu 264 Nov 7, 2022
Adds GraphQL support to your Flask application.

Flask-GraphQL Adds GraphQL support to your Flask application. Usage Just use the GraphQLView view from flask_graphql from flask import Flask from flas

GraphQL Python 1.3k Dec 31, 2022
A FastAPI Plug-In to support authentication authorization using the Microsoft Authentication Library (MSAL)

FastAPI/MSAL - MSAL (Microsoft Authentication Library) plugin for FastAPI FastAPI - https://github.com/tiangolo/fastapi FastAPI is a modern, fast (hig

Dudi Levy 15 Jul 20, 2022
FastAPI Server Session is a dependency-based extension for FastAPI that adds support for server-sided session management

FastAPI Server-sided Session FastAPI Server Session is a dependency-based extension for FastAPI that adds support for server-sided session management.

DevGuyAhnaf 5 Dec 23, 2022
Stac-fastapi built on Tile38 and Redis to support caching

stac-fastapi-caching Stac-fastapi built on Tile38 to support caching. This code is built on top of stac-fastapi-elasticsearch 0.1.0 with pyle38, a Pyt

Jonathan Healy 4 Apr 11, 2022
:rocket: CLI tool for FastAPI. Generating new FastAPI projects & boilerplates made easy.

Project generator and manager for FastAPI. Source Code: View it on Github Features ?? Creates customizable project boilerplate. Creates customizable a

Yagiz Degirmenci 1k Jan 2, 2023
Easy and secure implementation of Azure AD for your FastAPI APIs 🔒

FastAPI-Azure-auth Azure AD Authentication for FastAPI apps made easy. ?? Description FastAPI is a modern, fast (high-performance), web framework for

Intility 216 Dec 27, 2022
FastAPI native extension, easy and simple JWT auth

fastapi-jwt FastAPI native extension, easy and simple JWT auth

Konstantin Chernyshev 19 Dec 12, 2022