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      "body": "[Google Colaboratory](https://colab.research.google.com/) is a Jupyter Notebook enviornment that doesn't require any setup and completely runs in the cloud.\nThe notebooks are stored on Google Drive, so it can be easily shared. Over all of this, one of the major selling points is that they are giving \nfree computation on GPUs for upto 12 hours in a single session. And because of all these reason, I have been writing all my python code on Google Colab for \nthe last couple of weeks. But one of the major issues I faced was importing data to the notebook. Since the intances are created on the fly, the data \ngets deleted once the notebook is closed, so we need to keep on transferring it again and again and there isn't a simple way to transfer data unless you \nhave your data hosted somewhere where you can use something like `wget`.\n\nSo, I compiled a list of ways to import data to Google Colab:\n\nUsing wget\n----------\nThe Google Colab machines are built on Debian based linux, therefore the simplest way for downloading data is `wget` or your faviorite tool for \ndownloading data.\n\n```\nwget url_to_data\n```\n\nUsing google.colab python module\n--------------------------------\nGoogle Colaboratory provided a python module `google.colab` with some utility tools, one of which is transfering files from/to your local system.\n```\nfrom google.colab import files\nfiles.upload()\n```\nThis creates a button using which you can select the files you want to upload. But in my experience till now, this is the worst way since the \nupload was super slow (Took me more than 2 minutes to upload 30 MBs) and no it wasn't my internet. And I couldn't exactly figure out any \npossible reasons for the upload to be so slow.\n\nMount google drive using google-drive-ocamlfuse\n-----------------------------------------------\nAnother possible option is to use google drive to store your data and mount your google drive on the machine using `google-drive-ocamlfuse`.\n\nInstalling `google-drive-ocamlfuse`:\n```\n!apt-get install -y -qq software-properties-common python-software-properties module-init-tools\n!add-apt-repository -y ppa:alessandro-strada/ppa 2>&1 > /dev/null\n!apt-get update -qq 2>&1 > /dev/null\n!apt-get -y install -qq google-drive-ocamlfuse fuse\n```\nAuthenticate and get credentials:\n```\nfrom google.colab import auth\nauth.authenticate_user()\nfrom oauth2client.client import GoogleCredentials\ncreds = GoogleCredentials.get_application_default()\n```\nSetting up `google-drive-ocamlfuse`:\n```\nimport getpass\n!google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret} < /dev/null 2>&1 | grep URL\nvcode = getpass.getpass()\n!echo {vcode} | google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret}\n```\nAnd then you can finally mount your google drive:\n```\n!mkdir gdrive\n!google-drive-ocamlfuse gdrive\n!ls gdrive\n```\n\nGetting data from google cloud storage using gsutil\n---------------------------------------------------\nAlternatively you can download data from google cloud storage. \nStart by authenticating the user:\n```\nfrom google.colab import auth\nauth.authenticate_user()\n```\nAnd set the project and download data:\n```\nproject_id = 'Your_project_ID_here'\n\n# Download the file.\n!gsutil cp gs://{bucket_name}/{filename} {download_dir}\n```\n\nAnother possible option is to mount the bucket using [Cloud Storage Fuse](https://cloud.google.com/storage/docs/gcs-fuse) but good luck setting the right permissions to access data :P.",
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