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
AI Virtual Calculator: This is a simple virtual calculator based on Artificial intelligence.

AI Virtual Calculator: This is a simple virtual calculator that works with gestures using OpenCV. We will use our hand in the air to click on the calc

Md. Rakibul Islam 1 Jan 13, 2022
Codebase for "Revisiting spatio-temporal layouts for compositional action recognition" (Oral at BMVC 2021).

Revisiting spatio-temporal layouts for compositional action recognition Codebase for "Revisiting spatio-temporal layouts for compositional action reco

Gorjan 20 Dec 15, 2022
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control

Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie

Boyuan Chen 34 Jul 22, 2022
An implementation of "Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport"

Optex An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240. You c

Hans Brouwer 33 Jan 05, 2023
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection

Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection Introduction This repository includes codes and models of "Effect of De

Amir Abbasi 5 Sep 05, 2022
Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

184 Dec 11, 2022
Residual Pathway Priors for Soft Equivariance Constraints

Residual Pathway Priors for Soft Equivariance Constraints This repo contains the implementation and the experiments for the paper Residual Pathway Pri

Marc Finzi 13 Oct 12, 2022
CAST: Character labeling in Animation using Self-supervision by Tracking

CAST: Character labeling in Animation using Self-supervision by Tracking (Published as a conference paper at EuroGraphics 2022) Note: The CAST paper c

15 Nov 18, 2022
Official implementation of "Generating 3D Molecules for Target Protein Binding"

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

DIVE Lab, Texas A&M University 74 Dec 07, 2022
Toontown House CT Edition

Toontown House: Classic Toontown House Classic source that should just work. ❓ W

Open Source Toontown Servers 5 Jan 09, 2022
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

Microsoft 244 Jan 06, 2023
Unofficial PyTorch Implementation for HifiFace (https://arxiv.org/abs/2106.09965)

HifiFace — Unofficial Pytorch Implementation Image source: HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping (figure 1, pg. 1)

MINDs Lab 218 Jan 04, 2023
https://arxiv.org/abs/2102.11005

LogME LogME: Practical Assessment of Pre-trained Models for Transfer Learning How to use Just feed the features f and labels y to the function, and yo

THUML: Machine Learning Group @ THSS 149 Dec 19, 2022
CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching(CVPR2021)

CFNet(CVPR 2021) This is the implementation of the paper CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching, CVPR 2021, Zhelun Shen, Yuch

106 Dec 28, 2022
Implement slightly different caffe-segnet in tensorflow

Tensorflow-SegNet Implement slightly different (see below for detail) SegNet in tensorflow, successfully trained segnet-basic in CamVid dataset. Due t

Tseng Kuan Lun 364 Oct 27, 2022
This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting

1 MAGNN This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting. 1.1 The frame

SZJ 12 Nov 08, 2022
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

Sungyong Baik 44 Dec 29, 2022
Forecasting directional movements of stock prices for intraday trading using LSTM and random forest

Forecasting directional movements of stock-prices for intraday trading using LSTM and random-forest https://arxiv.org/abs/2004.10178 Pushpendu Ghosh,

Pushpendu Ghosh 270 Dec 24, 2022
Pytorch implementation of CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation"

MUST-GAN Code | paper The Pytorch implementation of our CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generat

TianxiangMa 46 Dec 26, 2022
Official implementation of "Learning Not to Reconstruct" (BMVC 2021)

Official PyTorch implementation of "Learning Not to Reconstruct Anomalies" This is the implementation of the paper "Learning Not to Reconstruct Anomal

Marcella Astrid 13 Dec 04, 2022