Unified file system operation experience for different backend

Overview

megfile - Megvii FILE library

build docs Latest version Support python versions License

megfile provides a silky operation experience with different backends (currently including local file system and OSS), which enable you to focus more on the logic of your own project instead of the question of "Which backend is used for this file?"

megfile provides:

  • Almost unified file system operation experience. Target path can be easily moved from local file system to OSS.
  • Complete boundary case handling. Even the most difficult (or even you can't even think of) boundary conditions, megfile can help you easily handle it.
  • Perfect type hints and built-in documentation. You can enjoy the IDE's auto-completion and static checking.
  • Semantic version and upgrade guide, which allows you enjoy the latest features easily.

megfile's advantages are:

  • smart_open can open resources that use various protocols, including fs, s3, http(s) and stdio. Especially, reader / writer of s3 in megfile is implemented with multi-thread, which is faster than known competitors.
  • smart_glob is available on s3. And it supports zsh extended pattern syntax of [], e.g. s3://bucket/video.{mp4,avi}.
  • All-inclusive functions like smart_exists / smart_stat / smart_sync. If you don't find the functions you want, submit an issue.
  • Compatible with pathlib.Path interface, referring to S3Path and SmartPath.

Quick Start

Here's an example of writing a file to OSS, syncing to local, reading and finally deleting it.

from megfile import smart_open, smart_exists, smart_sync, smart_remove, smart_glob
from megfile.smart_path import SmartPath

# open a file in s3 bucket
with smart_open('s3://playground/refile-test', 'w') as fp:
    fp.write('refile is not silver bullet')

# test if file in s3 bucket exist
smart_exists('s3://playground/refile-test')

# copy files or directories
smart_sync('s3://playground/refile-test', '/tmp/playground')

# remove files or directories
smart_remove('s3://playground/refile-test')

# glob files or directories in s3 bucket
smart_glob('s3://playground/video-?.{mp4,avi}')

# or in local file system
smart_exists('/tmp/playground/refile-test')

# smart_open also support protocols like http / https
smart_open('https://www.google.com')

# SmartPath interface
path = SmartPath('s3://playground/megfile-test')
if path.exists():
    with path.open() as f:
        result = f.read(7)
        assert result == b'megfile'

Installation

PyPI

pip3 install megfile

You can specify megfile version as well

pip3 install "megfile~=0.0"

Build from Source

megfile can be installed from source

git clone [email protected]:megvii-research/megfile.git
cd megfile
pip3 install -U .

Development Environment

git clone [email protected]:megvii-research/megfile.git
cd megfile
sudo apt install libgl1-mesa-glx libfuse-dev fuse
pip3 install -r requirements.txt -r requirements-dev.txt

How to Contribute

  • We welcome everyone to contribute code to the megfile project, but the contributed code needs to meet the following conditions as much as possible:

    You can submit code even if the code doesn't meet conditions. The project members will evaluate and assist you in making code changes

    • Code format: Your code needs to pass code format check. megfile uses yapf as lint tool and the version is locked at 0.27.0. The version lock may be removed in the future

    • Static check: Your code needs complete type hint. megfile uses pytype as static check tool. If pytype failed in static check, use # pytype: disable=XXX to disable the error and please tell us why you disable it.

      Note : Because pytype doesn't support variable type annation, the variable type hint format introduced by py36 cannot be used.

      i.e. variable: int is invalid, replace it with variable # type: int

    • Test: Your code needs complete unit test coverage. megfile uses pyfakefs and moto as local file system and OSS virtual environment in unit tests. The newly added code should have a complete unit test to ensure the correctness

  • You can help to improve megfile in many ways:

    • Write code.
    • Improve documentation.
    • Report or investigate bugs and issues.
    • If you find any problem or have any improving suggestion, submit a new issuse as well. We will reply as soon as possible and evaluate whether to adopt.
    • Review pull requests.
    • Star megfile repo.
    • Recommend megfile to your friends.
    • Any other form of contribution is welcomed.
Owner
MEGVII Research
Power Human with AI. 持续创新拓展认知边界 非凡科技成就产品价值
MEGVII Research
Exploring Simple Siamese Representation Learning

G-SimSiam A PyTorch implementation which refers to repo for the paper Exploring Simple Siamese Representation Learning by Xinlei Chen & Kaiming He Add

zhuyun 1 Dec 19, 2021
Feup-csr - Repository holding my group's submission to the CSR project competition

CSR Competições de Swarm Robotics Swarm Robotics Competitions This repository holds the files submitted for the CSR project competition. Project group

Nuno Pereira 1 Jan 04, 2022
Riemannian Geometry for Molecular Surface Approximation (RGMolSA)

Riemannian Geometry for Molecular Surface Approximation (RGMolSA) Introduction Ligand-based virtual screening aims to reduce the cost and duration of

11 Nov 15, 2022
A tiny, friendly, strong baseline code for Person-reID (based on pytorch).

Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new

Zhedong Zheng 3.5k Jan 08, 2023
A fast python implementation of Ray Tracing in One Weekend using python and Taichi

ray-tracing-one-weekend-taichi A fast python implementation of Ray Tracing in One Weekend using python and Taichi. Taichi is a simple "Domain specific

157 Dec 26, 2022
Hippocampal segmentation using the UNet network for each axis

Hipposeg Hippocampal segmentation using the UNet network for each axis, inspired by https://github.com/MICLab-Unicamp/e2dhipseg Red: False Positive Gr

Juan Carlos Aguirre Arango 0 Sep 02, 2021
YoHa - A practical hand tracking engine.

YoHa - A practical hand tracking engine.

2k Jan 06, 2023
Deep Learning Slide Captcha

滑动验证码深度学习识别 本项目使用深度学习 YOLOV3 模型来识别滑动验证码缺口,基于 https://github.com/eriklindernoren/PyTorch-YOLOv3 修改。 只需要几百张缺口标注图片即可训练出精度高的识别模型,识别效果样例: 克隆项目 运行命令: git cl

Python3WebSpider 55 Jan 02, 2023
Official implementation of Pixel-Level Bijective Matching for Video Object Segmentation

BMVOS This is the official implementation of Pixel-Level Bijective Matching for Video Object Segmentation, to appear in WACV 2022. @article{cho2021pix

Suhwan Cho 13 Dec 14, 2022
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone In our recent paper we propose the YourTTS model. YourTTS bri

Edresson Casanova 390 Dec 29, 2022
You Only Look One-level Feature (YOLOF), CVPR2021, Detectron2

You Only Look One-level Feature (YOLOF), CVPR2021 A simple, fast, and efficient object detector without FPN. This repo provides a neat implementation

qiang chen 273 Jan 03, 2023
A simple editor for captions in .SRT file extension

WaySRT A simple editor for captions in .SRT file extension The program doesn't use any external dependecies, just run: python way_srt.py {file_name.sr

Gustavo Lopes 3 Nov 16, 2022
Empower Sequence Labeling with Task-Aware Language Model

LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra

Liyuan Liu 838 Jan 05, 2023
How to Leverage Multimodal EHR Data for Better Medical Predictions?

How to Leverage Multimodal EHR Data for Better Medical Predictions? This repository contains the code of the paper: How to Leverage Multimodal EHR Dat

13 Dec 13, 2022
Rust bindings for the C++ api of PyTorch.

tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc

Laurent Mazare 2.3k Dec 30, 2022
Trainable PyTorch reproduction of AlphaFold 2

OpenFold A faithful PyTorch reproduction of DeepMind's AlphaFold 2. Features OpenFold carefully reproduces (almost) all of the features of the origina

AQ Laboratory 1.7k Dec 29, 2022
Submanifold sparse convolutional networks

Submanifold Sparse Convolutional Networks This is the PyTorch library for training Submanifold Sparse Convolutional Networks. Spatial sparsity This li

Facebook Research 1.8k Jan 06, 2023
Prometheus exporter for Cisco Unified Computing System (UCS) Manager

prometheus-ucs-exporter Overview Use metrics from the UCS API to export relevant metrics to Prometheus This repository is a fork of Drew Stinnett's or

Marshall Wace 6 Nov 07, 2022
OpenFace – a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.

OpenFace 2.2.0: a facial behavior analysis toolkit Over the past few years, there has been an increased interest in automatic facial behavior analysis

Tadas Baltrusaitis 5.8k Dec 31, 2022
HW3 ― GAN, ACGAN and UDA

HW3 ― GAN, ACGAN and UDA In this assignment, you are given datasets of human face and digit images. You will need to implement the models of both GAN

grassking100 1 Dec 13, 2021