278 Repositories
Python performance-bottleneck Libraries
Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"
High-Performance Brain-to-Text Communication via Handwriting Overview This repo is associated with this manuscript, preprint and dataset. The code can
Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"
Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"
Cinder is Instagram's internal performance-oriented production version of CPython
Cinder is Instagram's internal performance-oriented production version of CPython 3.8. It contains a number of performance optimizations, including bytecode inline caching, eager evaluation of coroutines, a method-at-a-time JIT, and an experimental bytecode compiler that uses type annotations to emit type-specialized bytecode that performs better in the JIT.
A modular, high performance, headless e-commerce platform built with Python, GraphQL, Django, and React.
Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL-first e-commerce platform delivering ultra-fast, dynamic, personaliz
No effort, no worry, maximum performance.
Django Cachalot Caches your Django ORM queries and automatically invalidates them. Documentation: http://django-cachalot.readthedocs.io Table of Conte
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation
LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transformer, etc. It is therefore best useful for Machine Translation, Text Generation, Dialog, Language Modelling, and other related tasks using these models.
codes for Image Inpainting with External-internal Learning and Monochromic Bottleneck
Image Inpainting with External-internal Learning and Monochromic Bottleneck This repository is for the CVPR 2021 paper: 'Image Inpainting with Externa
An easy-to-use high-performance asynchronous web framework.
An easy-to-use high-performance asynchronous web framework.
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance
Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification》(AAAI 2021) GitHub:
LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea
The most widely used Python to C compiler
Welcome to Cython! Cython is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports mo
ArrayFire: a general purpose GPU library.
ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures i
A high performance and generic framework for distributed DNN training
BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith
PyTorch extensions for high performance and large scale training.
Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext
High-performance TensorFlow library for quantitative finance.
TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples
Performance analysis of predictive (alpha) stock factors
Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour
Common financial risk and performance metrics. Used by zipline and pyfolio.
empyrical Common financial risk metrics. Table of Contents Installation Usage Support Contributing Testing Installation pip install empyrical Usage S
The next generation relational database.
What is EdgeDB? EdgeDB is an open-source object-relational database built on top of PostgreSQL. The goal of EdgeDB is to empower its users to build sa
Performance analysis of predictive (alpha) stock factors
Alphalens Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open sour
A Python package for manipulating 2-dimensional tabular data structures
datatable This is a Python package for manipulating 2-dimensional tabular data structures (aka data frames). It is close in spirit to pandas or SFrame
High performance datastore for time series and tick data
Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
High performance implementation of Extreme Learning Machines (fast randomized neural networks).
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
A modular, high performance, headless e-commerce platform built with Python, GraphQL, Django, and ReactJS.
Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL-first e-commerce platform delivering ultra-fast, dynamic, personaliz
High-performance Async REST API, in Python. FastAPI + GINO + Arq + Uvicorn (w/ Redis and PostgreSQL).
fastapi-gino-arq-uvicorn High-performance Async REST API, in Python. FastAPI + GINO + Arq + Uvicorn (powered by Redis & PostgreSQL). Contents Get Star
Docker image with Uvicorn managed by Gunicorn for high-performance FastAPI web applications in Python 3.6 and above with performance auto-tuning. Optionally with Alpine Linux.
Supported tags and respective Dockerfile links python3.8, latest (Dockerfile) python3.7, (Dockerfile) python3.6 (Dockerfile) python3.8-slim (Dockerfil
A FastAPI Middleware of joerick/pyinstrument to check your service performance.
fastapi_profiler A FastAPI Middleware of joerick/pyinstrument to check your service performance. 📣 Info A FastAPI Middleware of pyinstrument to check
CPU inference engine that delivers unprecedented performance for sparse models
The DeepSparse Engine is a CPU runtime that delivers unprecedented performance by taking advantage of natural sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.
Intel® Nervana™ reference deep learning framework committed to best performance on all hardware
DISCONTINUATION OF PROJECT. This project will no longer be maintained by Intel. Intel will not provide or guarantee development of or support for this
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Scalene: a high-performance, high-precision CPU and memory profiler for Python
scalene: a high-performance CPU and memory profiler for Python by Emery Berger 中文版本 (Chinese version) About Scalene % pip install -U scalene Scalen
🚴 Call stack profiler for Python. Shows you why your code is slow!
pyinstrument Pyinstrument is a Python profiler. A profiler is a tool to help you 'optimize' your code - make it faster. It sounds obvious, but to get
Yet Another Python Profiler, but this time thread&coroutine&greenlet aware.
Yappi Yet Another Python Profiler, but this time thread&coroutine&greenlet aware. Highlights Fast: Yappi is fast. It is completely written in C and lo
Sampling profiler for Python programs
py-spy: Sampling profiler for Python programs py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spe
Create standalone executables from Python scripts, with the same performance and is cross-platform.
About cx_Freeze cx_Freeze creates standalone executables from Python scripts, with the same performance, is cross-platform and should work on any plat
Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, and 3.9. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
Nuitka User Manual Contents Overview Usage Requirements Command Line Installation License Tutorial Setup and build on Windows Setup Install Python Ins
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
Python ASN.1 library with a focus on performance and a pythonic API
asn1crypto A fast, pure Python library for parsing and serializing ASN.1 structures. Features Why Another Python ASN.1 Library? Related Crypto Librari
Better directory iterator and faster os.walk(), now in the Python 3.5 stdlib
scandir, a better directory iterator and faster os.walk() scandir() is a directory iteration function like os.listdir(), except that instead of return
🦉 Modern high-performance serialization utilities for Python (JSON, MessagePack, Pickle)
srsly: Modern high-performance serialization utilities for Python This package bundles some of the best Python serialization libraries into one standa
Full-text multi-table search application for Django. Easy to install and use, with good performance.
django-watson django-watson is a fast multi-model full-text search plugin for Django. It is easy to install and use, and provides high quality search
No effort, no worry, maximum performance.
Django Cachalot Caches your Django ORM queries and automatically invalidates them. Documentation: http://django-cachalot.readthedocs.io Table of Conte
Automatically monitor the evolving performance of Flask/Python web services.
Flask Monitoring Dashboard A dashboard for automatic monitoring of Flask web-services. Key Features • How to use • Live Demo • Feedback • Documentatio
Load and performance benchmark tool
Yandex Tank Yandextank has been moved to Python 3. Latest stable release for Python 2 here. Yandex.Tank is an extensible open source load testing tool
Scalable user load testing tool written in Python
Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
Meinheld is a high performance asynchronous WSGI Web Server (based on picoev)
What's this This is a high performance python wsgi web server. And Meinheld is a WSGI compliant web server. (PEP333 and PEP3333 supported) You can als
The no-nonsense, minimalist REST and app backend framework for Python developers, with a focus on reliability, correctness, and performance at scale.
The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition Experiments Model Params (M) Acc (%) ResNet50 baseline (ref) 23.5M 93.62 BoTNet-50 18.8M 95.11% BoTNet-
A fast PostgreSQL Database Client Library for Python/asyncio.
asyncpg -- A fast PostgreSQL Database Client Library for Python/asyncio asyncpg is a database interface library designed specifically for PostgreSQL a
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. 150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
Stock Analysis Engine Build and tune investment algorithms for use with artificial intelligence (deep neural networks) with a distributed stack for ru
High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features :fire:
Releases | Gears | Documentation | Installation | License VidGear is a High-Performance Video Processing Python Library that provides an easy-to-use,
Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.
Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes
Scalable user load testing tool written in Python
Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst
Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.
Mimesis - Fake Data Generator Description Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes
Scalable user load testing tool written in Python
Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst
FastAPI framework, high performance, easy to learn, fast to code, ready for production
FastAPI framework, high performance, easy to learn, fast to code, ready for production Documentation: https://fastapi.tiangolo.com Source Code: https:
The no-nonsense, minimalist REST and app backend framework for Python developers, with a focus on reliability, correctness, and performance at scale.
The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou
A high performance implementation of HDBSCAN clustering. http://hdbscan.readthedocs.io/en/latest/
HDBSCAN Now a part of scikit-learn-contrib HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over va
Simple, realtime visualization of neural network training performance.
pastalog Simple, realtime visualization server for training neural networks. Use with Lasagne, Keras, Tensorflow, Torch, Theano, and basically everyth
ML-Ensemble – high performance ensemble learning
A Python library for high performance ensemble learning ML-Ensemble combines a Scikit-learn high-level API with a low-level computational graph framew
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Intel® Nervana™ reference deep learning framework committed to best performance on all hardware
DISCONTINUATION OF PROJECT. This project will no longer be maintained by Intel. Intel will not provide or guarantee development of or support for this
Cython implementation of Toolz: High performance functional utilities
CyToolz Cython implementation of the toolz package, which provides high performance utility functions for iterables, functions, and dictionaries. tool
pyinfra automates infrastructure super fast at massive scale. It can be used for ad-hoc command execution, service deployment, configuration management and more.
pyinfra automates/provisions/manages/deploys infrastructure super fast at massive scale. It can be used for ad-hoc command execution, service deployme
Sampling profiler for Python programs
py-spy: Sampling profiler for Python programs py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spe
FastAPI framework, high performance, easy to learn, fast to code, ready for production
FastAPI framework, high performance, easy to learn, fast to code, ready for production Documentation: https://fastapi.tiangolo.com Source Code: https:
Fast, asynchronous and elegant Python web framework.
Warning: This project is being completely re-written. If you're curious about the progress, reach me on Slack. Vibora is a fast, asynchronous and eleg
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