All clouds

Use data stored on the cloud without needing to download it all to your computer, saving time and space.

Imagine you're working on a project with a huge amount of data stored online. Instead of waiting hours to download it all, you can start working with the data almost immediately by streaming it.

Once you've optimized the dataset with LitData, stream it as follows:

from litdata import StreamingDataset, StreamingDataLoader

dataset = StreamingDataset('s3://my-bucket/my-data', shuffle=True)
dataloader = StreamingDataLoader(dataset, batch_size=64)

for batch in dataloader:
    process(batch)  # Replace with your data processing logic

Read data from AWS S3

import os
import litdata as ld

aws_storage_options={
    "AWS_ACCESS_KEY_ID": os.environ['AWS_ACCESS_KEY_ID'],
    "AWS_SECRET_ACCESS_KEY": os.environ['AWS_SECRET_ACCESS_KEY'],
}
dataset = ld.StreamingDataset("s3://my-bucket/my-data", storage_options=aws_storage_options)

Read data from GCS

import os
import litdata as ld

gcp_storage_options={
    "project": os.environ['PROJECT_ID'],
}
dataset = ld.StreamingDataset("gs://my-bucket/my-data", storage_options=gcp_storage_options)

Read data from Azure

import os
import litdata as ld

azure_storage_options={
    "account_url": f"https://{os.environ['AZURE_ACCOUNT_NAME']}.blob.core.windows.net",
    "credential": os.environ['AZURE_ACCOUNT_ACCESS_KEY']
}
dataset = ld.StreamingDataset("azure://my-bucket/my-data", storage_options=azure_storage_options)

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