Rate-limit-semaphore - Semaphore implementation with rate limit restriction for async-style (any core)

Overview

Rate Limit Semaphore

Rate limit semaphore for async-style (any core)

PyPI - Python Version PyPI - Implementation PyPI Coverage Status


There are two implementations of rate limit semaphore. Live demo shows how FixedNewPreviousDelaySemaphore and FixedNewFirstDelaySemaphore work


Live demo Live demo

Overview

import datetime
import ralisem

# Or another implementation
sem = ralisem.FixedNewPreviousDelaySemaphore(
    access_times=3, per=datetime.timedelta(seconds=1)
)
async with sem:
    ...

Difference:

  • FixedNewPreviousDelaySemaphore: Sures the last and a new access have a fixed required delay (per / access_times)
  • FixedNewFirstDelaySemaphore: Sures first and last in series (serias is access_times) have a fixed delay (per)

Methods

All of these implementations are inherited from one base TimeRateLimitSemaphoreBase. Check out full methods here

Installation

Via PyPI:

python -m pip install ralisem

Or via GitHub

python -m pip install https://github.com/deknowny/rate-limit-semaphore/archive/main.zip

Contributing

Check out Contributing section

You might also like...
A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.
A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

Implementation of
Implementation of "Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner"

Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner This repository is the official implementation of Meta-rPPG: Remote Heart Ra

PyTorch implementation of the paper Deep Networks from the Principle of Rate Reduction
PyTorch implementation of the paper Deep Networks from the Principle of Rate Reduction

Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl

PyTorch implementation of some learning rate schedulers for deep learning researcher.
PyTorch implementation of some learning rate schedulers for deep learning researcher.

pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu

Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

A Pytorch Implementation of a continuously rate adjustable learned image compression framework.
A Pytorch Implementation of a continuously rate adjustable learned image compression framework.

GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N

Pytorch implementation of Learning Rate Dropout.
Pytorch implementation of Learning Rate Dropout.

Learning-Rate-Dropout Pytorch implementation of Learning Rate Dropout. Paper Link: https://arxiv.org/pdf/1912.00144.pdf Train ResNet-34 for Cifar10: r

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

Releases(v0.1.0)
  • v0.1.0(Feb 15, 2022)

    A few words…

    Если вы, как и я, уже устали писать что-то под API, имеющее rate limit на запросы, и постоянно делать костыли, чтобы этот rate limit не превысить, то эта библиотека именно для вас

    ralisem предоставляет две имплементации семафора с ограничением по частоте исполнения вместо ограничения по количеству исполняемых одновременно задач, что предоставляет стандартный asyncio.Semaphore. Одна из них ожидает равное количество времени между каждыми исполняемыми задачами, другая проверяет, чтобы 1 и последняя задача в серии имели заданный промежуток ожидания (прикрепил две лайв демки). Сделано на anyio, поэтому будет работать как на asyncio, так и на trio

    Да, будет заюзано в квике для ограничения частоты обращений к API (собственно, это и послужило поводом)

    Если кто подскажет, как на такое писать юнит тесты — буду рад (думал как-то через моки текущего времени, но жутко лень). Сейчас работает на честном слове

    Доки здесь не нужно, чисто пара слов в ридми. На PyPI залита

    Source code(tar.gz)
    Source code(zip)
Owner
Yan Kurbatov
Open Source and Back-End Python developer
Yan Kurbatov
MAT: Mask-Aware Transformer for Large Hole Image Inpainting

MAT: Mask-Aware Transformer for Large Hole Image Inpainting (CVPR2022, Oral) Wenbo Li, Zhe Lin, Kun Zhou, Lu Qi, Yi Wang, Jiaya Jia [Paper] News This

254 Dec 29, 2022
TigerLily: Finding drug interactions in silico with the Graph.

Drug Interaction Prediction with Tigerlily Documentation | Example Notebook | Youtube Video | Project Report Tigerlily is a TigerGraph based system de

Benedek Rozemberczki 91 Dec 30, 2022
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train

20 May 28, 2022
Training Structured Neural Networks Through Manifold Identification and Variance Reduction

Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari

0 Dec 23, 2021
Collection of generative models in Tensorflow

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

3.8k Dec 30, 2022
This is a code repository for the paper "Graph Auto-Encoders for Financial Clustering".

Repository for the paper "Graph Auto-Encoders for Financial Clustering" Requirements Python 3.6 torch torch_geometric Instructions This is a simple c

Edward Turner 1 Dec 02, 2021
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

[ICCV2021] TransReID: Transformer-based Object Re-Identification [pdf] The official repository for TransReID: Transformer-based Object Re-Identificati

DamoCV 569 Dec 30, 2022
Saeed Lotfi 28 Dec 12, 2022
Generative Flow Networks

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Implementation for our paper, submitted to NeurIPS 2021 (also chec

Emmanuel Bengio 381 Jan 04, 2023
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.

AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the

Accenture 13 Dec 22, 2022
Customizable RecSys Simulator for OpenAI Gym

gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac

Xingdong Zuo 14 Dec 08, 2022
Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL)

LUPerson-NL Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL) The repository is for our CVPR2022 paper Large-Scale

43 Dec 26, 2022
This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.

EEND-vector clustering The EEND-vector clustering (End-to-End-Neural-Diarization-vector clustering) is a speaker diarization framework that integrates

45 Dec 26, 2022
Code for CMaskTrack R-CNN (proposed in Occluded Video Instance Segmentation)

CMaskTrack R-CNN for OVIS This repo serves as the official code release of the CMaskTrack R-CNN model on the Occluded Video Instance Segmentation data

Q . J . Y 61 Nov 25, 2022
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.

deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis

1 Jan 12, 2022
Help you understand Manual and w/ Clutch point while driving.

简体中文 forza_auto_gear forza_auto_gear is a tool for Forza Horizon 5. It will help us understand the best gear shift point using Manual or w/ Clutch in

15 Oct 08, 2022
When are Iterative GPs Numerically Accurate?

When are Iterative GPs Numerically Accurate? This is a code repository for the paper "When are Iterative GPs Numerically Accurate?" by Wesley Maddox,

Wesley Maddox 1 Jan 06, 2022
Official Repsoitory for "Activate or Not: Learning Customized Activation." [CVPR 2021]

CVPR 2021 | Activate or Not: Learning Customized Activation. This repository contains the official Pytorch implementation of the paper Activate or Not

184 Dec 27, 2022
a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version

pytorch-liteflownet This is a personal reimplementation of LiteFlowNet [1] using PyTorch. Should you be making use of this work, please cite the paper

Simon Niklaus 365 Dec 31, 2022
A Re-implementation of the paper "A Deep Learning Framework for Character Motion Synthesis and Editing"

What is This This is a simple re-implementation of the paper "A Deep Learning Framework for Character Motion Synthesis and Editing"(1). Only Sections

102 Dec 14, 2022