JSONPath Tester

JSONPath is a query language for extracting data from JSON documents, analogous to XPath for XML. Writing a JSONPath expression against a JSON document returns every matching node along with its location in the document tree; a built-in sample store document, containing books and a bicycle, is available for quick experimentation without supplying data of one's own.

Every expression starts with $, which represents the root of the document. The match count updates as an expression is refined, and every matching node appears in the results alongside the value it holds.

$ is the root node of the document. .key or ['key'] accesses a child property by name; bracket notation is required when a key contains spaces or special characters. .. is recursive descent, searching all descendants for a matching key regardless of depth. [*] is a wildcard, matching every element in an array or every value in an object. [0], [2], and [-1] access array elements by index, with negative indices counting from the end of the array. [0:3] and [1:5:2] slice an array with start, end, and an optional step parameter, following Python slice semantics. [?(@.price < 10)] is a filter expression, selecting elements where a condition on a child property holds true; the six comparison operators are ==, !=, <, <=, >, and >=, and a string value inside a filter must be enclosed in single quotes.

Pretty-printing displays matched nodes with indentation for readability. Showing matched node paths displays the full JSONPath location of each matched node alongside its value. Auto-evaluation can be turned off when working with a very large document, so evaluation only runs on demand rather than after every keystroke.

Against the default sample data, $.store.book[*].author returns every author name, $..price returns every price value via recursive descent, $.store.book[?(@.price < 10)] returns books priced under 10, and $.store.book[0:2] returns the first two books using array slicing.

JSONPath expressions provide a concise way to locate and extract specific values from complex JSON structures. The following scenarios illustrate practical applications across multiple domains.

• API Development: Validate API response payloads by writing JSONPath expressions that target expected fields, confirming that $.data.users[*].email returns the correct number of email addresses before writing integration tests.
• Data Extraction: Pull specific values from deeply nested configuration files or database exports. Target nested arrays with expressions like $.config.servers[*].endpoints[?(@.protocol == 'https')] to extract only HTTPS endpoints from a multi-server configuration document.
• Debugging: Inspect webhook payloads or event streams by querying for the fields that matter. Recursive descent with $..error surfaces every error object regardless of nesting depth, making it faster to locate failure points in complex response trees.
• Documentation: Verify that JSON schema examples contain the fields described in technical documentation. Evaluate expressions against sample payloads to confirm that every documented path resolves to a value, catching mismatches between docs and actual data structures.
• ETL Pipelines: Prototype extraction queries before embedding them in data pipeline code. Test expressions like $.records[*].metrics.revenue against sample data exports to confirm the correct values are selected, then copy the validated expression directly into pipeline configuration files.
• Log Analysis: Parse structured JSON log entries by querying for specific severity levels or service names. Filtering with $.logs[?(@.level == 'error')] isolates error entries from a batch of log records, reducing manual scanning through large log files.
• Front-End Development: Map API response fields to UI components by testing JSONPath expressions against mock data. Confirm that $.products[*].images[0] returns the primary image URL for each product before binding the data to a template.