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Datagrok Documentation

website·Indexed 33 days ago

https://datagrok.ai/help

Developer resources and user guides for the Datagrok platform, featuring comprehensive JavaScript and Python API references, low-code workflow capabilities, and scripting guides. Includes technical documentation on package structure conventions, plugin deployment, and release history for versions such as 1.27.7.

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What's inside Datagrok

  1. Overview of the DbInfo class

    The DbInfo class represents metadata for a database or catalog in Datagrok. It provides access to high-level metadata such as schemas, relations, comments, and LLM-generated annotations. It is important to note that mutation methods in this class only create metadata within Datagrok and do not modify the underlying physical database schema.

  2. Overview of DataGrok JS API Namespaces

    The DataGrok JS API organizes its functionality into namespaces. Key namespaces include dapi2 (a generated REST client, currently primarily for types) and decorators.

  3. Overview of Datagrok scripting capabilities

    Datagrok scripting allows users to extend data analysis by combining Datagrok's platform capabilities with external statistical packages and visualizations. Scripts can be written in Python, R, Octave, Julia, JavaScript, and SQL (specifically for data queries). Integration with the Datagrok environment is achieved using functional annotations, meaning developers do not need to learn the internal Datagrok JavaScript API to create custom analysis scripts and display results in viewers.

  4. Overview of the Script class

    The Script class is a specialized subclass of Func in the Datagrok platform. It encapsulates executable code written in a supported scripting language and can be executed in various environments (server-side or client-side) based on the language and platform configuration.

  5. Overview of JsInputBase class

    The JsInputBase<T> class serves as the base class for creating JS value editors. It extends InputBase<T> and is used by specific input implementations such as MarkdownInput. It is generic, where T represents the type of value the editor handles (defaulting to any).

  6. Overview of Datagrok Exploratory Data Analysis (EDA) capabilities

    Datagrok is designed for high-performance exploration of large, complex datasets (supporting millions of columns and billions of rows). It provides a visual-first approach to data analysis, allowing users to test hypotheses and validate assumptions through interactivity and speed. Key capabilities include:

    • Data Ingestion: Automatic parsing and rendering of data into a high-performance spreadsheet with built-in statistics, custom cell renderers (e.g., for molecules or sequences), and summary columns.
    • Data Wrangling: Tools for clustering data, imputing missing values, and treating duplicates or outliers directly within the visualization workspace.
    • Visualization: Over 50 interactive viewers, including scatterplots with regression lines and box-plots with statistical tests. Viewers are synchronized and support domain-specific renderers.
    • Analysis: Use of statistical functions for calculations and the ability to filter, zoom, aggregate, pivot, and cross-link data on the fly.
    • Extensibility: Support for adding custom viewers and developing new functions using R, Python, or Julia.

  7. Overview of the DataQuery class

    The DataQuery class is a specialized Func within the Datagrok platform used to represent a data query function. It encapsulates the logic for querying a data source (such as an external SQL database) using a specific DataConnection. It combines general platform function capabilities with query-specific execution details.

  8. Overview of the U2.Component base class

    The Component class serves as the foundation for every u2 component, whether visual or non-visual. It provides essential infrastructure including a unique name for selection and automation, an effect/cleanup scope for resource management, and a widget introspection surface (DD7) generated from componentMeta.

    Key architectural notes:

    • Lifecycle: A component constructed inside another component's scope is automatically disposed of when that parent scope is disposed.
    • Inheritance: In Datagrok, DG.Widget extends Control, which in turn extends Component. Standalone hosts (such as tests or galleries) must call the dispose method directly.

  9. Overview of Polytool for sequence notation

    Polytool is a suite of tools within Datagrok (provided via the Sequence Translator plugin) used for working with custom rules-based sequence notations and sequence enumeration. It allows for a simplified, human-readable dash-separated notation that supports complex structural features like branches and connections, offering a more concise alternative to BILN and HELM formats.

  10. Overview of the GroupRelation class

    The GroupRelation class represents a relationship between two groups. It defines a parent-child connection and indicates whether the child group possesses admin privileges within the parent group.

  11. Overview of FormulaLinesHelper

    FormulaLinesHelper is a utility class used to manage Formula Lines, specifically designed for use in Viewer and DataFrame metadata. It is extended by DataFrameFormulaLinesHelper and ViewerFormulaLinesHelper.

  12. Overview of the Position Statistics viewer

    The Position Statistics viewer displays statistical distributions of numeric values at specific sequence positions using violin and box plots. It is used to analyze how values vary across different monomers at a selected position, with the ability to include neighboring positions as motif context.