using-activeloop-storage.md

description
Storing and loading datasets from Deep Lake Storage.

Step 6: Using Activeloop Storage

How to Use Activeloop-Provided Storage

Colab Notebook

Register

You can store your Deep Lake Datasets with Activeloop by first creating an account in the Deep Lake App or in the CLI using:

activeloop register

Login

In order for the Python API to authenticate with your account, you can use API tokens (see below), or log in from the CLI using:

!activeloop login

# Alternatively, you can directly input your username and password in the same line:
# activeloop login -u <your_username> -p <your_password>

You can then access or create Deep Lake Datasets by passing the Deep Lake path to deeplake.dataset()

import deeplake

deeplake_path = 'hub://organization_name/dataset_name'
               #'hub://jane_smith/my_awesome_dataset'
               
ds = deeplake.dataset(deeplake_path)

{% hint style="info" %} When you create an account in Deep Lake, a default organization is created that has the same name as your username. You can also create other organizations that represent companies, teams, or other collections of multiple users. {% endhint %}

Public datasets such as 'hub://activeloop/mnist-train' can be accessed without logging in.

API Tokens

Once you have an Activeloop account, you can create tokens in the Deep Lake App (Organization Details -> API Tokens) and authenticate by setting the environmental variable:

os.environ['ACTIVELOOP_TOKEN'] = <your_token>

Or login in the CLI using the token:

!activeloop login --token <your_token>

If you are not logged in through the CLI, you may also pass the token to python commands that require authentication:

ds = deeplake.load(deeplake_path, token = 'xyz')