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Table to JSON

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CategoryDeveloper Tools
PlatformAll
Pricing Free
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About this app

WHAT IT DOES Table to JSON is a floating panel that instantly converts any HTML table on the current page into well‑structured JSON data. Select a table from a list of automatically detected tables, choose the output structure—array of objects (with column names as keys) or nested arrays (row data only)—and specify whether to use the first row as headers. The panel displays the generated JSON in a text area with syntax‑friendly formatting, ready to copy, download, or insert directly into your workflow. You can convert a single table or all tables on the page at once, with the output organized as a single JSON object keyed by table names or indices. The panel includes options to prettify the JSON for readability and to control how null and empty values are handled. You can copy the JSON to your clipboard with one click, download it as a .json file, or insert it directly into any editable field on the page (input, textarea, or contenteditable). Perfect for developers scraping web data, data analysts exporting table data for processing, API developers needing sample payloads, or anyone who needs to quickly convert web tables into machine‑readable JSON format. WHERE IT RUNS The panel overlays any website that loads the BotGentz extension—whether you're on a data dashboard, a documentation page, a CMS, a wiki, a project management tool, or any other web page. It works on all modern Chromium‑based browsers (Chrome, Edge, Brave, Arc) and Firefox. The script injects a self‑contained UI element that does not interfere with the host page's layout, styles, or JavaScript execution. It runs client‑side only, with no external API calls or cloud dependencies. HOW TO USE After installing the free BotGentz extension, visit any page and click the extension icon to activate the panel. The first time you use Table to JSON, it will appear as a draggable widget near the bottom‑right corner of your viewport. To convert a table: - Select a table from the dropdown menu. The panel automatically detects all tables on the page. - Choose the output format: "Array of objects" (column names become object keys) or "Nested arrays" (row data as arrays). - Toggle "Use first row as headers" on or off to control whether the first row provides column names. - Toggle "Prettify JSON output" for readable formatting or off for compact JSON. - Toggle "Include null/empty values" to preserve empty cells as null or omit them. - Click "Convert Table" to generate the JSON for the selected table, or "Convert All Tables" to convert every table on the page. The generated JSON appears in the output area below. To use the result: - Click "Copy to Clipboard" to copy the JSON for pasting elsewhere. - Click "Download JSON" to download the JSON as a .json file. - Click "Insert JSON into Active Field" to paste the JSON directly into the focused editable field on the page. The panel remembers your output format, header preference, prettify setting, and null handling preference across sessions. INTELLIGENT TABLE PARSER WITH TYPE INFERENCE AND FLEXIBLE OUTPUT ENGINE Unlike naive converters that simply flatten table data into strings, this panel uses an intelligent table parser that recursively traverses the DOM, distinguishing between and elements and correctly handling tables with irregular row structures. The parser automatically detects header rows by checking for elements and promotes them to JSON keys in object mode. The type inference engine attempts to parse cell values as numbers (removing commas), booleans, and nulls, preserving data types rather than treating everything as strings. The output engine supports two distinct modes: "objects" mode generates an array of key‑value objects with column names as keys (ideal for API payloads and data processing), while "arrays" mode generates a nested array structure that preserves the exact row/column layout. When converting multiple tables, the engine bundles each table's data into a single JSON object with table names or indices as keys, making it easy to export entire page data in one operation. The prettify toggle controls the spacing of the JSON output, and the null handling option allows users to decide whether empty cells should be preserved or omitted. THE PANEL - Drag: Click and hold the panel's header bar to move it anywhere on the screen. - Per‑site position: The panel stores its last position separately for each domain (e.g., different positions for GitHub vs. Confluence) using the browser's localStorage, keyed by hostname. - Snap: When dragged near any edge of the viewport, the panel snaps to that edge with a 16px margin for a clean, docked feel. - Collapse: Click the "−" button in the header to collapse the panel to a compact title bar, preserving all current values. Click "+" to expand it back. - Resize: Drag the bottom‑right corner handle to resize the panel from 280px to 600px wide and 200px to 500px tall; the layout adapts responsively. - Escape: Press the Escape key while the panel is focused to close it entirely (you can reopen it from the extension toolbar). PLEASE NOTE This script requires the free BotGentz extension to run—it is not a standalone bookmarklet or user script. Websites frequently update their DOM structures and security policies; while we strive to keep the panel functional across thousands of sites, occasional updates may be needed. The converter performs all operations entirely in your browser—no data is sent to any server, and no cookies or tracking identifiers are used. Your table data and generated JSON remain private to your local session and are persisted only via GM_setValue (the extension's local storage) for convenience, not shared across devices or sessions. The converter handles most standard HTML tables, but tables with complex structures (e.g., nested tables, rowspan, colspan) may produce unexpected results. For best results, use tables with regular row and column structures. Always verify the generated JSON for correctness before using it in production systems. The type inference is a best‑effort conversion—you may need to manually adjust data types for specialized use cases.

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