I have installed the jupyter lab extension to connect to google drive.
I can create and open files in the drive from the JupyterLab UI.
But I can't find a way to read files located in the drive in the notebook.
For example I would want to be able to run in my notebook the following:
df = pd.read_csv("Gdrive/MyDrive/somefileinthedrive.csv")
Any suggestions ?
You could open jupyterlab directly in the Google Drive directory like this answer: https://stackoverflow.com/a/69077943/13129641
I use to open jupyterlab from anaconda prompt with:
python -m jupyterlab --notebook-dir=G:/
Note: You can change G:/ to another directory, if you desire.
Related
In Colab, the following code snippet is used for mounting Google Drive.
from google.colab import drive
drive.mount('/test', force_remount=True)
And I'm wondering if it could work on my local machine. When implementing this locally, it says "no module named google", even after having executed pip install google.
Is there another package that should be installed, or it just cannot be achieved? I've searched for a while, but it seems that the only solution is to install Google Drive Desktop to give access to remote files.
Although google.colab python library can be found here, this library is a collection of tools meant to work in conjunction with the Google Colab product.
Indeed, Google Drive Desktop is your best option to "mount" your Google Drive to your local machine.
Alternatively, there are several 3rd party Google Drive clients available.
Use ocamlfuse.
Here are the step by step details: https://medium.com/#enthu.cutlet/how-to-mount-google-drive-on-linux-windows-systems-5ef4bff24288
Instead of mounting it to a home folder (named googledrive in tutorial), I suggest mounting it such that folder structure would be same for both colab and local machine. To do that:
create your mounting folder at root (it's not a recommended practice but there is no harm). You need to use sudo. i.e at /, use sudo mkdir test
then create MyDrive inside test.
Chnage test or MyDrive owner to yourself: sudo chown <your username> MyDrive/
Mount to MyDrive by: google-drive-ocamlfuse MyDrive/
Enjoy!
I use the 'mount drive' to use the dataset folder.
However, the google drive belongs to only me so others who want to run my code on colab have to download the dataset and upload to their google drive, then mount drive to run the code.
Is there any solution for others to run my the code without downloading the dataset?
I made a library to do just that
!pip install kora
from kora import drive
drive.download_folder(folder_id)
There seem to be lots of ways to access a file on Google Drive from Colab but no simple way to save a file from Google Colab back to Google Drive.
For example, to access a Google Drive file from Colab, you can mount the Google Drive using
from google.colab import drive
drive.mount('/content/drive')
However, to save an output file you've generated in Colab on Google Drive the methods seem very complicated as in:
Upload File From Colab to Google Drive Folder
Once Google Drive is mounted, you can even view the drive files in the Table of Contents from Colab. Is there no simple way to save or copy a file created in Colab and visible in the Colab directory back to Google Drive?
Note: I don't want to save it to a local machine using something like
from google.colab import files
files.download('example.txt')
as the file is very large
After you have mounted the drive, you can just copy it there.
# mount it
from google.colab import drive
drive.mount('/content/drive')
# copy it there
!cp example.txt /content/drive/MyDrive
Other answers suggest how to copy a specific file, I would like to mention you can also copy the entire directory, which is useful when copying logs from callbacks from Colab to Drive:
from google.colab import drive
drive.mount('/content/drive')
In my case, the folder names were:
%cp -av "/content/logs/scalars/20201228-215414" "/content/drive/MyDrive/Colab Notebooks/logs/scalars/manual_add"
You can use shutil to copy/move files between colab and google drive
import shutil
shutil.copy("/content/file.doc", "/content/gdrive/file.doc")
When you are saving files, simply specify the Google Drive path for saving the file.
When using large files, Colab sometimes syncs the VM and Drive asynchronously. To force the sync, simply run:
from google.colab import drive
drive.flush_and_unmount()
in my case I use the common approach with the !cp command.
But sometimes, it didn't work in Colab because we didn't enter the right file path.
basic code: !cp source_filepath destination_filepath
implementation code:
!cp /content/myfolder/myitem.txt /content/gdrive/MyDrive/mydrivefolder/
in addition, to correctly enter the path, you can copy the path location from the table of contents on the left side by clicking the dot menu -> copy path.
Once you see the file in the Table of Contents of Colab on the left, simply drag that file into the "/content/drive/My Drive/" directory located on the same panel. Once the file is inside your "My Drive", you will be able to see it inside your Google Drive.
After you mount your drive...
from google.colab import drive
drive.mount('/content/drive')
...just prepend the full path, including the mounted path (/content/drive) to the file you want to write.
someList = []
with open('/content/drive/My Drive/data/file.txt', 'w', encoding='utf8') as output:
for line in someList:
output.write(line + '\n')
In this case we save it in a folder called data located in the root of your Google Drive.
You may often run into quota limits using the gdown library.
Access denied with the following error:
Too many users have viewed or downloaded this file recently. Please
try accessing the file again later. If the file you are trying to
access is particularly large or is shared with many people, it may
take up to 24 hours to be able to view or download the file. If you
still can't access a file after 24 hours, contact your domain
administrator.
You may still be able to access the file from the browser:
https://drive.google.com/uc?id=FILE_ID
No doubt gdown is faster but i copy my files using the command below and avoid quota limits
!cp /content/drive/MyDrive/Dataset/test1.zip /content/dataset
I was trying to upload a big image folder into google drive and github but github not allowed and google drive taking too long. How can I upload the local folder to colab.
Sorry, I don't think there's a solution to your issue. If your fundamental problem is limited upload capacity from the machine with the images, you'll just need to wait.
A nice property to uploading to Drive is that you can use programs like Backup and Sync to retry the transfer until it's successful. And, once the images have been uploaded to Drive once, you'll be able to access them quickly in Colab thereafter without uploading again. (See this example notebook showing how to connect your Google Drive files to Colab as a filesystem.)
convert the folder to zip file and then upload it on colab.
further you can unzip your folder by following command.
! unzip "your path"
The unzip method only works for csv files.
If you use a kaggle dataset, use
os.environ['KAGGLE_USERNAME'] = 'enter_username_here' # username
os.environ['KAGGLE_KEY'] = 'enter_key_here' # key
!kaggle datasets download -d dataset_api_command_here
If you have the image in google drive, use
from google.colab import drive
drive.mount('/content/drive')
Is it possible to copy a file from Google Drive to Google Cloud Storage? I imagine it would be very fast since both are on a similar storage system.
I haven't seen any information on either ways to do this seamlessly, without having to download the file (probably to an out-of-google system) and then re-uploading it. About one year ago, a similar question was asked: Transfer files from dropbox/drive to Google cloud storage.
Is there a way to do this directly, with the file staying within-Google the entire time?
#frunkad commented a link to a nice workaround, but for completeness I will recite this here, as it is currently the top result in search.
You can open a Colab (Juypiter Notebook on Google servers), mount your gDrive and use the gCloud CLI to copy files.
open https://colab.research.google.com/ and connect to a machine
Mount your Drive by executing the code below, clicking on the link and pasting the authentification key
from google.colab import drive
drive.mount(‘/content/drive’)
Connect to your Google Cloud Storage. (Project id can be found here)
from google.colab import auth
auth.authenticate_user()
project_id = 'your-project-id'
!gcloud config set project {project_id}
!gsutil ls
Copy files using gsutil. Use -m tag for multi-threading to increase speed. (There is a Subfolder called "My Drive" that you have to address in your mounted drive)
bucket_name = 'your_bucket_name'
!gsutil -m cp -r /content/drive/My\ Drive/Your-Data/* gs://{bucket_name}/
Original Author Philip Lies
Link to his colab: https://colab.research.google.com/drive/1Xc8E8mKC4MBvQ6Sw6akd_X5Z1cmHSNca
There's no direct way to do this. You could write an App Engine or Compute Engine app that reads from Drive using its API and writes to GCS using its API.