how to skip unzipping a file that already exists in google colab - google-colaboratory

I have a very large 7z file in google drive.
When I use Google Colab to unzip it, It took me too much time and sometimes runtime is out
so I can not unzip the whole file successfully.
How can I skip unzip a file that already exists in google colab?

I have used this code:
main_path = "path_to_your_dir" # Specify the path
# Check whether the specified path exists or not
if os.path.exists(main_path)== False :
!unzip your_zip_file.zip

Related

Is there a way to get the ID of a Google Drive folder from the path using Colab?

Let's say I have a folder on GDrive with the path /content/drive/MyDrive/MyFolder. I know I can access the contents of the folder from Google Colab after mounting Drive. But is it also possible to access the ID/URL of this folder using Colab, and if so, how?
You can use kora to get ID from a file path.
!pip install kora
from kora.xattr import get_id
fid = get_id('/content/drive/MyDrive/Colab Notebooks')
# 0B0l6No313QAhRGVwY0FtQ3l1ckk

Why my ipynb files are downloaded as txt file in Google Colab

This seems wierd, but my Google Colab was working fine until the last two days the Download .ipynb option is not downloading .ipynb files but rather txt files. I have to rename the file to ipynb and the notebooks are working fine. Anybody have faced such issues with Colab?
facing same problem while downloading kaggle file as .txt rather than ipynb file i just Re-named file name as ipynb then after got it.
The simple solution to this is, while saving to local system,by default colab may give as json or text file. But we can change it to All files and add .ipynb as suffix to the file name

Google Colab: mounted Drive but unable to read files

I am doing Stanford's course CS231n on deep learning and am using Google Colab.
The initialization code and all the files are given, so all i need is just to hit "run" on the given code.
I have followed step be step the official instructions and successfully mounted Google Drive, yet i get an error when trying to read the files:
"cp: cannot stat 'cs231n/assignments/assignment1/cs231n/': No such file or directory /content".
And then some more errors.
The files are located in my drive as in the path "FOLDERNAME".
The errors i get:
How it should be:
Official instructions:
https://cs231n.github.io/assignments2020/assignment1/
How can i solve it?
Thanks!
I am having the exactly same problem as you were. And here is my solution:
delete the folder named cs231n
follow the tutorial again
3. change the path %cd drive/My\ Drive into %cd drive/MyDrive
As you can see, default setting of the folder is 'MyDrive'(without space in midddle) but not 'My Drive'(My\ Drive).
Then, everything should run as your expectation.
Cheers.
Based on the course instructions, it sounds like you need to expand the course archive in your Drive.
Quoting here:
Create a folder in your personal Google Drive and upload assignment1/
folder to the Drive folder. We recommend that you call the Google
Drive folder cs231n/assignments/ so that the final uploaded folder has
the path cs231n/assignments/assignment1/.
If you already did that, I'd check the Drive web UI to make sure that the paths line up with the course instructions, and to move the files around if there's a mismatch.

How to read images from a local drive into Google Colab

I want to run deep learning models in Google Colab that has a power GPU support. I am quite new to Colab. Originally I though I could uplod the images using os.path.join and PIL.Image.open as I did in the environment of Spyder. But the Colab gives a FileNotFoundError FileNotFoundError: [Errno 2] No such file or directory (the images indeed exist in a local directory). It seems I did not do correctly for the uploading.
You can directly upload to colab or upload images to a google drive folder. Then mount that folder in google colab to use it. On the left there is an arrow that opens a sidebar which contains searchable code snippets. Here, you can search for drive to get google drive related code snippets.
This notebook contains some examples,
https://colab.research.google.com/notebooks/snippets/drive.ipynb#scrollTo=u22w3BFiOveA
The command below list contents of folder named DeepLearning,
!ls -la "/content/gdrive/My Drive/DeepLearning"
Copy contents of drive DeepLearning folder to Virtual Machine in DeepLearning folder,
!cp /content/gdrive/My\ Drive/DeepLearning ./DeepLearning
Copy contents of Virtual Machine DeepLearning folder to google drive DeepLearning folder,
!cp ./DeepLearning /content/gdrive/My\ Drive/DeepLearning
You can run %cd DeepLearning to change directory to DeepLearning folder.
GPU support can be enabled by Runtime > Change Runtime Type > Hardware Accelerator > GPU.

is there any way to load local data set folder directly from google drive to google colab?

see the image carefullyi couldn't load custom data folder from google drive to google colab.though i mounted google drive.like instead of MNIST data set i want to load my own image data set folder.i have tried pydrive wrapper.but i need simple solution.
suppose i have dataset of images inside google drive.how to load it to google colab?
from google.colab import drive
drive.mount('/content/gdrive')
then
with open('/content/gdrive/My Drive/foo.txt', 'w') as f:
f.write('Hello Google Drive!')
!cat /content/gdrive/My\ Drive/foo.txt
here insted of foo.txt i have an image folder called Dog inside ml-data folder.but i can't load it.how to load it in google colab directly from google drive as it is in my local hard drive.
To load data directly from the local machine, you need to follow these steps:
Go to files [left side menu]
Click on upload to session storage
Select file(s) from your machine to upload
It will prompt something indicating that file(s) will be available for the current session only, click ok.
The file(s) will be uploaded in the directory. Click on it (left and right-click both work the same).
And then;
Copy path & use it inside pd.read_csv() function.
Note: After the session is terminated, files will be lost from colab session. To use it again, you'll need to upload it again.
Many times, we prefer to it have all our data in a GitHub repository or in a google drive folder to fetch from there.
Reading many files from Google Drive through colab is going to be less performant and more unreliable than first copying a .zip or similar single file from Drive to the colab VM and unzipping it outside the drive mount directory, and then using that copy of the data.