RapidCanvas Docs
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  • BASIC
    • Projects
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        • Creating a project
        • Reviewing the Projects listing page
        • Duplicating a Project
        • Modifying the project settings
        • Deleting Project(s)
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        • Generating AI snippets for each node on the Canvas
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      • Importing dataset(s) from the local system
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        • Importing data from Google Cloud Storage (GCS)
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      • Adding Artifacts at the Project Level
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  • ADVANCED
    • Starter Guide
      • Quick Start
    • Setup and Installation
      • Installing and setting up the SDK
    • Helper Functions
    • Notebook Guide
      • Introduction
      • Create a template
      • Code Snippets
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      • How to
        • How to Authenticate
        • Create a new project
        • Create a Custom Environment
        • Add a dataset
        • Add a recipe to the dataset
        • Manage cloud connection
        • Code recipes
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        • Create Template
        • Use a template in a flow notebook
      • Reference Implementations
        • DataApps
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        • Multiple Files
      • Sample Projects
        • Model build and predict
  • Additional Reading
    • Release Notes
      • April 21, 2025
      • April 01, 2025
      • Mar 18, 2025
      • Feb 27, 2025
      • Jan 27, 2025
      • Dec 26, 2024
      • Nov 26, 2024
      • Oct 24, 2024
      • Sep 11, 2024
        • Aug 08, 2024
      • Aug 29, 2024
      • July 18, 2024
      • July 03, 2024
      • June 19, 2024
      • May 30, 2024
      • May 15, 2024
      • April 17, 2024
      • Mar 28, 2024
      • Mar 20, 2024
      • Feb 28, 2024
      • Feb 19, 2024
      • Jan 30, 2024
      • Jan 16, 2024
      • Dec 12, 2023
      • Nov 07, 2023
      • Oct 25, 2023
      • Oct 01, 2024
    • Glossary
Powered by GitBook
On this page
  • Get access key
  • List and upload
  • Upload from local
  • To download file from GCP to local folder
  • Use files
  1. ADVANCED
  2. Notebook Guide
  3. How to

Manage cloud connection

from utils.rc.client.requests import Requests
from utils.rc.client.auth import AuthClient

from utils.rc.dtos.project import Project
from utils.rc.dtos.dataset import Dataset

from utils.rc.dtos.dataSource import DataSource
from utils.rc.dtos.dataSource import DataSourceType
from utils.rc.dtos.dataSource import GcpConfig

from utils.notebookhelpers.gcs import GCSHelper

import logging
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)
Requests.setRootHost("http://staging.dev.rapidcanvas.net/api/")
AuthClient.setToken()

Get access key

Get your GCP Access key json from Rapidcanvas and save it locally

### Get your GCP Access key json and the cloud bucket name from Rapidcanvas and save it locally
gcp_key_path = "/yourlocalpath/gcloud_bucket_cred.json"
gcp_bucket_name = "your_bucket_root"

List and upload

List and upload files to GCP bucket

gcs_helper = GCSHelper.init(gcp_key_path, gcp_bucket_name)
gcs_helper.list_files('')

Upload from local

Upload File from your local folders to GCP Cloud storage bucket You may need to upload just once

gcs_helper.upload_file('./data/transactions.csv', 'transactions_dataset')
gcs_helper.list_files('/transactions_dataset')

To download file from GCP to local folder

gcs_helper.download_file('transactions_dataset/transactions.csv', './data' )

#optionally to delete it
#gcs_helper.delete_file('transactions_dataset/transactions.csv')

Use files

Use the uploaded files on GCP in your RC Projects

your_datasource_name = "my_cloud_ds"

dataSource = DataSource.createDataSource(
    your_datasource_name,
    DataSourceType.GCP_STORAGE,
    {
        GcpConfig.BUCKET: gcp_bucket_name, 
        GcpConfig.ACCESS_KEY: gcp_key_path
    })
# Create project on RC
project = Project.create(
    name='SampleProject',
    description='Sample Project',
    createEmpty=True
)
project.id
gcp_remote_filepath_trx = "transactions_dataset/transactions.csv"

# Create dataset in RC using the remote cloud bucket csv file
raw_data = project.addDataset(
    dataset_name="transactions",
     dataset_description="transactions",
     data_source_id=dataSource.id,
     data_source_options={GcpConfig.FILE_PATH: gcp_remote_filepath_trx} #saving output with csv input in recipe not working properly
)

#project.deleteDataset(raw_data.id)
raw_data.getData()
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