CODEWITHSUNDEEP
google-cloud-storagegoogle-colaboratory
Shubham Tiwari
Shubham Tiwari

Reputation: 402

How to import data from Google Cloud Storage to Google Colab

Currently I am working on a data set that is of 10 GB. I have uploaded it on google cloud storage but I don't know how to import it in google colab.

Upvotes: 19

Views: 17208

Answers (2)

55597
55597

Reputation: 2122

from google.colab import auth
auth.authenticate_user()

Once you run this, a link will be generated, you can click on it and get the signing in done.

!echo "deb http://packages.cloud.google.com/apt gcsfuse-bionic main" > /etc/apt/sources.list.d/gcsfuse.list
!curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
!apt -qq update
!apt -qq install gcsfuse

Use this to install gcsfuse on colab. Cloud Storage FUSE is an open source FUSE adapter that allows you to mount Cloud Storage buckets as file systems on Colab, Linux or macOS systems.

!mkdir folderOnColab
!gcsfuse folderOnBucket/content/ folderOnColab

Use this to mount the directories. (folderOnBucket is the GCS bucket URL without the gs:// part)

You can use this docs for further reading. https://cloud.google.com/storage/docs/gcs-fuse

Upvotes: 19

Kartoch
Kartoch

Reputation: 7779

Using a dedicated service account and Python:

from google.oauth2 import service_account
from google.cloud.storage import client
import io
import pandas as pd
from io import BytesIO
import json
import filecmp

Using the service account token as str:

SERVICE_ACCOUNT = json.loads(r"""{
  "type": "service_account",
  "project_id": "[REPLACE WITH YOUR FILE]",
  "privat_sae_key_id": "[REPLACE WITH YOUR FILE]",
  "private_key": "[REPLACE WITH YOUR FILE]",
  "client_email": "[REPLACE WITH YOUR FILE]",
  "client_id": "[REPLACE WITH YOUR FILE]",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "[REPLACE WITH YOUR FILE]"
}""")

BUCKET = "[NAME OF YOUR BUCKET TO READ/WITE YOUR DATA]"

Using the service token to create the client:

credentials = service_account.Credentials.from_service_account_info(
    SERVICE_ACCOUNT,
    scopes=["https://www.googleapis.com/auth/cloud-platform"],
)

client = client.Client(
    credentials=credentials,
    project=credentials.project_id,
)

Save and download functions:

def save_file(local_filename, remote_filename):
    bucket = client.get_bucket(BUCKET)
    blob = bucket.blob(remote_filename)
    blob.upload_from_filename(local_filename)

def download_file(local_filename, remote_filename):
    bucket = client.get_bucket(BUCKET)
    blob = bucket.blob(remote_filename)
    blob.download_to_filename(local_filename)

Let's check with a CSV file generated by Pandas:

df_test = pd.DataFrame(
    {"col1": [1,2,3],
     "col2": [4,5,6]}
).to_csv(path_or_buf="/tmp/test.csv")

save_file("/tmp/test.csv","test.csv")
download_file("/tmp/test2.csv","test.csv")
assert filecmp.cmp('/tmp/test.csv', '/tmp/test2.csv')

Upvotes: 3

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