Extract Google Drive zip from Google colab notebook

Question

I already have a zip of (2K images) dataset on a google drive. I have to use it in a ML training algorithm. Below Code extracts the content in a string format:

Answer 1

First create a new directory:

!mkdir file_destination

Now, it's the time to inflate the directory with the unzipped files with this:

!unzip file_location -d file_destination

Answer 2

After mounting on drive, use shutil.unpack_archive. It works with almost all archive formats (e.g., “zip”, “tar”, “gztar”, “bztar”, “xztar”) and it's simple:

import shutil
shutil.unpack_archive("filename", "path_to_extract")

Answer 3

For Python

Connect to drive,

from google.colab import drive
drive.mount('/content/drive')

Check for directory

!ls and !pwd

For unzip

!unzip drive/"My Drive"/images.zip

Answer 4

First, install unzip on colab:

!apt install unzip

then use unzip to extract your files:

!unzip  source.zip -d destination.zip

Answer 5

TO unzip a file to a directory:

!unzip path_to_file.zip -d path_to_directory

Answer 6

Colab research team has a notebook for helping you out.

Still, in short, if you are dealing with a zip file, like for me it is mostly thousands of images and I want to store them in a folder within drive then do this --

!unzip -u "/content/drive/My Drive/folder/example.zip" -d "/content/drive/My Drive/folder/NewFolder"

-u part controls extraction only if new/necessary. It is important if suddenly you lose connection or hardware switches off.

-d creates the directory and extracted files are stored there.

Of course before doing this you need to mount your drive

from google.colab import drive 
drive.mount('/content/drive')

I hope this helps! Cheers!!