How It Works

The tool reads your input as JSON and decodes it into a PHP array/object structure. It then walks through every node recursively, building a “path” for each leaf value. A leaf value is any scalar (string, number, boolean) or null; if the leaf is still a list/object, it can be preserved as a compact JSON string so you don’t lose information during flattening.

Each output row contains a full path and a value. Paths can be created with a delimiter (for example . or /) and you can choose how numeric indexes appear (segment-based or bracket-style). When you enable pretty output, the final JSON is formatted with indentation for easier reading and diffing.

Processing steps

• 1) Validate: checks that your input is non-empty and within your plan limits.
• 2) Decode: parses JSON into an internal structure and reports any parsing error clearly.
• 3) Traverse: recursively visits objects and arrays, tracking depth and building paths.
• 4) Emit: outputs either a JSON map (path → value) or line-based path=value format.
• 5) Export: copy to clipboard or download as a file for spreadsheets, scripts, or tickets.

Key Features

Delimiter and notation control

Pick a delimiter that matches your ecosystem. Dot notation is friendly for configuration paths and many logging tools, while slash notation is handy for URL-like structures. Numeric array indexes can be represented as normal segments (for example items.0.name) or in bracket form (items[0].name).

Two output modes

Choose JSON Map when you want a structured export you can process in code, or use Key=Value Lines for quick copy/paste into spreadsheets, notes, or comparison tools. Both modes are designed to stay stable across runs so your diffs stay clean.

Pretty formatting

Enable pretty formatting to create human-friendly output. It’s especially useful when sharing results with teammates, adding artifacts to bug reports, or reviewing changes across versions of an API response.

Depth and count insights

The result panel includes quick stats such as total extracted paths and maximum depth encountered. Those numbers help you understand how complex the payload is and whether it’s worth normalizing upstream.

Safe, in-browser convenience

The UI includes instant copy and download actions. You can keep your workflow lightweight: paste input, flatten, copy output, and continue. The tool focuses on predictable transformations rather than opinionated restructuring.

Use Cases

• API debugging: Flatten a response to quickly locate missing keys or unexpected null values.
• Data migration planning: Discover all fields present in a document-style record before mapping it into relational tables.
• Analytics event audits: Convert nested event payloads into a flat list you can compare between app versions.
• Configuration inspection: Flatten configuration JSON to find overrides, defaults, and environment-specific differences.
• Content model review: Turn CMS exports into a path list to spot inconsistent schema usage across entries.
• Spreadsheet export: Use line output to paste into a sheet and split on = for quick column creation.
• Security and privacy review: Scan flattened paths for sensitive fields like tokens, emails, or identifiers.

In practice, flattening is often the fastest way to move from “this JSON is huge” to “here are the exact fields that matter.” You can use the same output to write selectors, build allow-lists, or create test fixtures.

Optimization Tips

Use bracket indexes for readability

If your data contains lots of lists (for example items, rows, or edges), bracket indexes typically make the output easier to scan. It also reduces ambiguity when a key name is numeric.

Prefer JSON output for automation

When the next step is scripting, choose JSON output. A JSON map is easy to load in almost any language, and it keeps values typed (booleans stay booleans, numbers stay numbers) where possible.

Trim large inputs before flattening

For extremely large payloads, consider removing unrelated sections first (such as binary blobs, base64 images, or long logs). Smaller inputs flatten faster and produce more focused results for analysis.

FAQ