Installation
Download and install the Python SDK wheel file:Request Access
Contact us to get the SDK wheel file
Supported Filetypes
Deasy Labs can process a wide variety of document formats:Documents
.pdf, .docx, .rtf
Spreadsheets
.xls, .xlsx, .xlsm, .xlsb, .odf, .ods, .odt
Presentations
.ppt, .pptx
.msg
Web
.html, .htm, .aspx, .xml
Data Formats
.json, .csv
Plain Text
.txt, .log
Language Support
Complete Example
Copy and run this script to extract metadata from your documents:About client configuration
base_urlis required and points to your Deasy deployment (e.g.https://unstructured.your-company.com/rest/unstructured). There is no default.- Any constructor argument can be set via an environment variable instead:
UNSTRUCTURED_CLIENT_BASE_URL,UNSTRUCTURED_USERNAME,UNSTRUCTURED_PASSWORD,UNSTRUCTURED_API_TOKEN,UNSTRUCTURED_USER_ID. - API tokens are long-lived and issued from your Deasy deployment’s web UI. The SDK does not create, refresh, or revoke them.
What Just Happened?
1
Connected to Your Data
The Data Connector established a secure connection to your S3 bucket, allowing the platform to read your documents.
2
Defined What to Extract
The Tags told the platform what information to look for: document type, summary, and key date. Tags can be grouped into hierarchical Taxonomies for conditional extraction.
3
Extracted Metadata
The platform’s AI analyzed each document in a background job (tracked via
task_status) and extracted the structured metadata you defined.Next Steps
Explore Concepts
Learn how Data Connectors, Taxonomies, and Metadata work together.
Organize a SharePoint Library
Export enriched metadata to SharePoint.
API Reference
Explore all available endpoints and SDK methods.
Protect Sensitive Data
Set up sensitive data detection for compliance.
