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JSON All-in-One: json, jsonc, ndjson - view, edit, formatter, beautifier, compare, export, charts, search, JSONPath, JQ 🧭 JSON All-in-One opens JSON, JSONC, NDJSON, and NDJSONC from remote sources, local files, the clipboard (after an optional permission grant), or a manual draft. Developers, QA engineers, and analysts can inspect, edit, query, validate, compare, chart, and export data in a single browser workflow. Use the JSON viewer to view data as formatted text or as a tree, then search source text, keys, values, or paths. 🎯 Solves common problems: ✔️ No more out-of-memory "Aw, Snap!" errors ✔️ Preserves large numbers without losing precision ✔️ Opens JSON and NDJSON with line or block comments ✔️ View, compare, transform, export, and visualize data; detect images in JSON values and download them in bulk ✔️ Customize JQ aliases and save time on repetitive daily tasks ✔️ Create your own theme with an unprecedented level of detail 🛠 Formatting and inspection: Run the JSON formatter to turn dense payloads into readable structured text. Use the JSON beautifier for inspection or the JSON minifier for compact output. Open the viewer to explore nested objects and arrays. Preserve exact large numbers and surface suspicious-character markers during review. The formatter helps move from an incoming response to a structure you can inspect before editing or querying. 🔎 Query data in two complementary ways: Use standards-based RFC 9535 JSONPath for path-oriented selection. Run local JQ filters through the bundled runtime for transformations and extraction. Apply a JQ query to select fields before another workflow, such as charting. These are core browser-based operations, so you can narrow a response to relevant records and continue working with the result. ✅ Validation and schema work: ➤ Use the JSON validator while editing and inspecting documents. ➤ Infer a schema and export the resulting JSON Schema. ➤ Use the derived workflow as a json schema generator for a starting schema. ➤ Generate data models for different programming languages. A second pass with the validator can review the document after edits before code generation or export. 🧩 Editing supports several source shapes: Start with a manual draft when file creation is the task. Open JSONC when comments are part of the source you need to edit and validate. Inspect NDJSON or NDJSONC for newline-delimited records. Use JSON editor and json sorting when ordering data helps inspection. Streaming and OPFS-backed workflows are available where documented, with bounded previews; behavior depends on source shape, browser limits, and operation. 🔄 Use JSON compare to review a derived diff between two documents. Check an API fixture against a newer response, review configuration changes, or see how output differs after an edit. For QA, this makes a before-and-after review easier to follow alongside validation and search. 📤 Export for common handoffs: Export tabular data as CSV or TSV, create Markdown or HTML tables, or use XML and other supported formats. Choose the destination according to the source shape and the receiving workflow. 📊 Build charts from JQ-selected fields: ▸ Select the relevant records or values. ▸ Build cartesian charts for suitable series and axes. ▸ Build circular charts when that view fits the selected fields. ▸ Revise the filter if the result includes unwanted data. Optional AI assistance can help with JQ or charts, but it is not required for core work and uses only a provider you configure. ❓ Can I do core work without sending data to an AI provider? Answer: yes. Core editing, querying, schema, code generation, diff, chart, and export workflows run in the browser. Optional AI assistance for JQ or charts is separate and uses only a provider you configure. Optional image detection is off by default and may contact image URLs only when enabled or invoked. This boundary lets you choose optional features for each document you open. 🧪 A QA workflow: Open a browser response, local file, clipboard payload after granting access, or manual draft. Format and inspect it; search keys, values, paths, or source text. Run JSONPath or JQ to isolate the area under test. Validate edits, infer a schema when useful, and generate a model if needed. Compare revisions or export the result for the next step. The same browser-based core toolset supports each stage, while source shape and browser limits can affect behavior. ⚙️ Infer and export JSON Schema, then generate models for the programming language of your choice (TypeScript, Python 3, Go, Rust, Java, and more). Return to the source to search a field, adjust an edit, rerun a query, and regenerate output. This keeps code-generation work grounded in the data you opened. 📚 For analysis and handoff: ➤ Inspect the source before transforming it. ➤ Query only the fields needed for the task. ➤ Choose a cartesian or circular chart only when it suits the selected data. ➤ Export results in a format suited to the next workflow. JSON All-in-One connects these workflows while keeping optional network-dependent features separate from core browser processing.