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pict-dataexplorer

v1.3.0

Published

Config-driven hierarchical ("folders") data explorer for Pict — browse a relational dataset as an expandable tree of records and their child collections, each record with a preview-card popout. Resolves lists from meadow-endpoints (Lite / paginated / filt

Readme

Pict-DataExplorer

Read the Pict-DataExplorer Documentation

pict-dataexplorer on npm | MIT License

A config-driven, hierarchical "folders" data explorer for the Pict application framework. Browse a relational dataset as an expandable tree: a list of root records where expanding a record reveals its child collections — "Users (5)", "Media (10)", "Documents (3)" — each expandable to paginated child records, and each record carrying a preview-card popout. Drive the whole thing from a single config graph of entity endpoints and relationships.

Features

  • Hierarchical folder tree — expand a record to see its related collections, drill each collection to its records, recursively.
  • Three relationship kinds, declaratively — one-to-many (Filter), many-to-many through a join entity (Join), and belongs-to single references (Reference).
  • Resolve from anywhere — natively from meadow-endpoints (paginated, LiteExtended column projection, FilteredTo, Count) via pict.EntityProvider, or from a host-supplied custom Resolver for any source — including an in-memory dataset with no backend at all.
  • Soft preview cards — an opt-in dependency on pict-section-recordset's RecordSetCardManager; present → a clickable ⓘ card on each record, absent → plain text.
  • Lazy by default — child counts resolve only when a record is expanded, and members page in on demand, so a tree over hundreds of thousands of rows stays cheap.

Installation

npm install pict-dataexplorer

Quick Start

const libPictDataExplorer = require('pict-dataexplorer');

// register the provider on your Pict instance
pict.addProvider('Pict-DataExplorer', libPictDataExplorer.default_configuration, libPictDataExplorer);

// create an explorer that renders into #BookExplorer
pict.providers['Pict-DataExplorer'].createExplorer('BookExplorer',
{
    URLPrefix: '/1.0/',
    Roots: [ { Label: 'Books', Entity: 'Book' } ],
    Entities:
    {
        Book:
        {
            Lite: [ 'Title', 'Genre' ],
            Display: { Title: 'Title', Subtitle: '{~D:Record.Genre~}' },
            Children:
            [
                { Label: 'Reviews', Entity: 'Review', Resolve: 'count', Relationship: { Type: 'Filter', Key: 'IDBook' } },
                { Label: 'Authors', Entity: 'Author', Resolve: 'count',
                    Relationship: { Type: 'Join', JoinEntity: 'BookAuthorJoin', ParentKey: 'IDBook', ChildKey: 'IDAuthor' } }
            ]
        },
        Review: { Lite: [ 'Rating', 'Text' ], Display: { Title: '{~D:Record.Rating~} ★', Subtitle: '{~D:Record.Text~}' } },
        Author: { Lite: [ 'Name' ], Display: { Title: 'Name' } }
    }
});

pict.views['BookExplorer'].renderExplorer();
<div id="BookExplorer"></div>

No backend? Resolve from memory

Any entity or relationship can carry a Resolver function, so the same tree can explore an in-memory dataset, a data lake, or a cursor API with no REST endpoints at all:

Artist:
{
    IDField: 'IDArtist', Display: { Title: 'Name' },
    Resolver: (pOptions) => pOptions.CountOnly
        ? { count: ARTISTS.length }
        : { records: ARTISTS.slice(pOptions.begin, pOptions.begin + pOptions.count), hasMore: false },
    Children: [ { Label: 'Albums', Entity: 'Album', Resolve: 'count',
        Resolver: (pArtist, pOptions) => resolveAlbumsFor(pArtist, pOptions) } ]
}

Documentation

Full documentation lives at fable-retold.github.io/pict-dataexplorer and in the docs folder:

Examples

Related Packages

License

MIT