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Documentation Index

Fetch the complete documentation index at: https://docs.atomscale.ai/llms.txt

Use this file to discover all available pages before exploring further.

This quickstart walks through the essentials for calling the Atomscale API with the Python SDK.

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Prerequisites

  • Python 3.10 through 3.12
  • An active Atomscale account
  • An API key from the Atomscale Dashboard (found in User > Manage Account > Access)

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Install the client

pip install atomscale

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Create a client

The Client reads AS_API_KEY and AS_API_ENDPOINT from the environment. Export the variables or pass values explicitly. 
import os
from atomscale import Client

os.environ["AS_API_KEY"] = "YOUR_API_KEY"

client = Client()
Never commit your API key to version control. Use environment variables or a secrets manager.
Override the endpoint when pointing at staging or a private deployment: 
client = Client(
    api_key="YOUR_API_KEY",
    endpoint="https://api.atomscale.ai/",
)

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Verify the connection

Run a simple search to confirm the client is working: 
results = client.search()
print(f"Found {len(results)} items in the catalogue")

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Mute progress bars

For non-interactive environments like CI pipelines, pass mute_bars=True: 
client = Client(api_key="YOUR_API_KEY", mute_bars=True)

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Next steps

Upload Data

Send files to Atomscale for analysis.

Search Data

Find items in your data catalogue.

Inspect Results

Explore analysis outputs and plots.

Stream RHEED

Push frames from your instrument in real time.