About The Project

AppCorp design is a storybook app that houses all design philosophies that we had used previously for our clients.

Installing

install from npm

yarn add @appcorp/design

Usage

usage: fast-copy.py [-h HELP] source destination [-d DELETE] [-s SYNC] [-r REPLACE]

optional arguments:
  -h --help            show this help message and exit
  source                the drive you are copying from
  destination           the drive you are copying to
  -d --delete           delete the source files after copy
  -s --sync             delete files in destination if not found in source (do not use, if using with rsync)
  -r --replace          replace files if they exist
  -t --thread           set the amount of parallel threads used
  -l --size-limit       set max size of files copied (supports gb, mb, kb) eg 1.5gb

The source and destination fields are required. Everything else is optional.

Examples

from google.colab import drive
drive.mount('/gdrive', force_remount=False)
import os
!wget -q https://raw.githubusercontent.com/L0garithmic/fastcolabcopy/main/fastcopy.py
import fastcopy
!python fastcopy.py /gdrive/Shareddrives/Source/. /gdrive/Shareddrives/Destination --thread 20 --size-limit 400mb

If you want to see copy execution time:

!pip install -q ipython-autotime
%load_ext autotime

Check out examples.md for some more examples.

Best Practice

Colab has wildly varying transfer speeds, because of this, the best we can offer are suggestions:

• For large groups of medium/small files, 15-40 threads seems to work best.
• For 50+ files with significantly varying sizes, try 2 sequentially copies. -t 15 -l 400 then -t 2
• For files that are 100MB+, it is best to use 2 threads. It is still faster then rsync.
• Currently --sync breaks if rsync is ran after. If you are mirroring drives. Disable --sync and use the rsync's --delete function.

Credits

• Credit to ikonikon for the base multi-threading code.
• Thanks to @Ostokhoon for ALL argument and folder hierarchy functionality.