DOCSEARCHbyAlgolia
Submit Docs

Keboola User Documentation

website·Indexed 36 days ago

https://help.keboola.com/

Technical guidance for the Keboola data platform, covering data loading, storage, transformations, and flows. Includes documentation for AI features like Kai, building Data Apps, CLI usage, external integrations, and platform extensions.

Tokens
1.7K
Snippets
1
Records
30
Agent score
67%

What's inside Keboola

  1. Define a Semantic Layer for AI assistants

    The Keboola Semantic Layer allows users to describe their data using business terms, including datasets, metrics, relationships, glossary terms, and business rules. This ensures that AI assistants can accurately understand the meaning and context of the data.

  2. Extract data using the Generic Extractor

    The Generic Extractor is a versatile tool for pulling data from APIs. It supports complex configurations including:

    • Authentication: API Key, Basic, Bearer Token, Login, OAuth 1.0, OAuth 2.0 (including Client Credentials), and Query authentication.
    • Pagination: Various scroller types including Cursor, Offset, Page Number, Response Parameter, and Response URL.
    • Advanced Features: SSH Proxy configuration, incremental loading, child jobs, and custom mapping.

  3. Manage Keboola projects using the kbagent CLI

    The kbagent CLI is the primary command-line interface for managing Keboola projects, configurations, jobs, storage, flows, and development branches. It is designed to be AI-friendly and can be used by developers or coding agents to automate platform management across an organization.

  4. Parametrize component configurations using Variables

    Keboola allows you to parametrize component configurations using placeholders. You can define these variables within a flow or drive them from external sources to make configurations dynamic.

  8. Extend Keboola with custom components

    Developers can extend the Keboola platform by building custom components. This involves implementing a Common Interface that handles configuration files, environment specifications, and logging. Components can be developed in Python, PHP, or R. The process includes defining UI options via a configuration schema, managing input/output mapping, and utilizing the Queue API to run and poll component jobs.

  9. Access Keboola documentation as plain markdown

    Every page in the Keboola documentation can be accessed as a plain markdown file by appending index.md to the end of the page URL. For example, the storage documentation at https://help.keboola.com/storage/ can be accessed as https://help.keboola.com/storage/index.md.

  12. Build and deploy Keboola Data Apps

    Keboola allows developers to build and run Python and JavaScript applications that operate on governed data within a project. Apps can be created using Kai (an AI assistant) for rapid prototyping and publishing, or developed locally using a scaffolded environment with server-side data access and repository syncing. Deployment options include Streamlit for Python-only quick tools, with a migration path available to move Streamlit apps to a full Python/JS stack (React UI) via Kai.