JSON Studio — Format, Validate, Diff, Transform, and Explore JSON Documents

What does it do?

JSON Studio is an all-in-one enterprise JSON toolkit that lets you format, validate, minify, diff, infer schemas, flatten, extract with JSONPath, and convert JSON to YAML — all through a single actor. Whether you're debugging a malformed API response, comparing two config files, or generating a JSON Schema from sample data, JSON Studio handles the grunt work in one call. Eight operation modes mean you never need to install another JSON library or visit an online formatter again.

Who is it for?

Persona	What they use it for
Backend Developer	Formatting raw JSON logs, validating API payloads, and diffing config file changes across environments
Data Engineer	Flattening nested JSON for CSV export and inferring schemas from streaming data samples
QA Engineer	Minifying responses before storing in test fixtures and diffing expected versus actual outputs
API Integrator	Extracting specific values via JSONPath queries and converting JSON responses to YAML configs
DevOps Engineer	Comparing deployment configs across staging and production, and validating CloudFormation/Terraform JSON templates
Frontend Developer	Formatting API responses during development and converting mock data between JSON and YAML
Technical Writer	Generating JSON Schema documentation from sample API responses and formatting pretty-printed code samples

Why use this?

• 8 operation modes in one tool — format, validate, minify, diff, schema inference, JSON-to-YAML, flatten, and JSONPath extract. No need to install separate libraries or visit half a dozen websites for different JSON tasks.
• Batched input support — process hundreds of JSON documents in a single run. Great for pipeline integration, ETL workflows, and bulk processing jobs where you'd otherwise loop over files.
• Enterprise-grade diffing — spot exactly what changed between two JSON structures with clear, structured output that distinguishes added, removed, changed, and unchanged keys. No more squinting at raw text diffs that don't understand JSON structure.
• JSON Schema inference — automatically generate a schema from sample data so you can validate future payloads, document your API contract, or generate type definitions for TypeScript and other languages.
• Programmatic API built-in — call it from cURL, Python, or any HTTP client. Drop it into your CI/CD pipeline, ETL job, deployment script, or monitoring workflow without any local dependencies.
• Lightning fast for single documents — individual format or validate operations return in milliseconds, making JSON Studio practical for real-time tooling and editor integrations.

Input Parameters

Field	Type	Required	Default	Description
mode	string	yes	format	Operation mode. One of: format, validate, minify, diff, infer-schema, to-yaml, flatten, jsonpath
input	string or array	yes	—	The JSON document(s) to process. For diff mode, this is the first document. Accepts a single JSON string or an array of JSON strings for batch mode.
indentSize	integer	no	2	Number of spaces for indentation in format and to-yaml modes. Set to 4 for Python-style indentation or 2 for compact readability.
sortKeys	boolean	no	false	When true, sorts object keys alphabetically in format and minify modes. Useful for making consistent, diff-friendly output.
input2	string	no	—	The second JSON document for diff mode. Ignored in all other modes. Must be valid JSON.
jsonpath	string	no	—	JSONPath expression for jsonpath mode (e.g., $.store.books[*].title). Ignored in all other modes. Uses RFC 9535 standard syntax.

Example Input

{
  "mode": "format",
  "input": "{\"name\":\"JSON Studio\",\"version\":2,\"features\":[\"format\",\"validate\",\"diff\",\"schema-inference\",\"to-yaml\",\"flatten\",\"jsonpath\",\"minify\"],\"active\":true}",
  "indentSize": 2,
  "sortKeys": true
}

Diff mode example

{
  "mode": "diff",
  "input": "{\"name\":\"API v1\",\"endpoint\":\"/v1/users\",\"timeout\":30,\"retries\":0}",
  "input2": "{\"name\":\"API v2\",\"endpoint\":\"/v2/users\",\"timeout\":60,\"retries\":3,\"rateLimit\":100}"
}

Batch mode example

{
  "mode": "validate",
  "input": [
    "{\"id\":1,\"name\":\"Alice\"}",
    "{\"id\":2,\"name\":\"Bob\"}",
    "{\"id\":3,\"name\":\"invalid"
  ]
}

Output Structure

Field	Type	Description
mode	string	The operation mode that was executed
result	string or object	The output of the operation. Type varies by mode (see below).
success	boolean	Whether the operation completed without errors
error	string	Present only if success is false — contains a descriptive error message

Mode-specific result details

Mode	result type	Description
format	string	Pretty-printed JSON with specified indentation and key sorting
minify	string	Compact JSON with no whitespace, stripped to the minimum valid representation
validate	object	{ "valid": true/false, "errors": ["..."] } — lists every validation failure
diff	object	{ "added": {...}, "removed": {...}, "changed": {...}, "unchanged": {...} } — structured diff
infer-schema	object	A JSON Schema (draft-07 compatible) inferred from the input data
to-yaml	string	YAML representation of the input JSON with configurable indentation
flatten	object	Flat key-value object with dot-notation keys (e.g., "user.address.city")
jsonpath	array	Array of values matching the JSONPath expression, or empty array if no matches

Example Output

Format mode

{
  "mode": "format",
  "result": "{\n  \"active\": true,\n  \"features\": [\n    \"diff\",\n    \"flatten\",\n    \"format\",\n    \"jsonpath\",\n    \"minify\",\n    \"schema-inference\",\n    \"to-yaml\",\n    \"validate\"\n  ],\n  \"name\": \"JSON Studio\",\n  \"version\": 2\n}",
  "success": true
}

Diff mode

{
  "mode": "diff",
  "result": {
    "added": {
      "rateLimit": 100
    },
    "removed": {},
    "changed": {
      "name": { "from": "API v1", "to": "API v2" },
      "endpoint": { "from": "/v1/users", "to": "/v2/users" },
      "timeout": { "from": 30, "to": 60 },
      "retries": { "from": 0, "to": 3 }
    },
    "unchanged": {}
  },
  "success": true
}

Validate mode (with errors)

{
  "mode": "validate",
  "result": {
    "valid": false,
    "errors": [
      "Input at index 2: Invalid JSON at position 24: Unterminated string"
    ]
  },
  "success": true
}

API Usage

cURL

# Format a JSON document
curl -X POST "https://api.apify.com/v2/acts/perryay~json-studio/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "mode": "format",
    "input": "{\"name\":\"JSON Studio\",\"version\":2}",
    "indentSize": 2,
    "sortKeys": true
  }'

# Diff two JSON documents
curl -X POST "https://api.apify.com/v2/acts/perryay~json-studio/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "mode": "diff",
    "input": "{\"name\":\"old\",\"version\":1}",
    "input2": "{\"name\":\"new\",\"version\":2}"
  }'

# Infer a JSON Schema
curl -X POST "https://api.apify.com/v2/acts/perryay~json-studio/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "mode": "infer-schema",
    "input": "{\"users\":[{\"id\":1,\"name\":\"Alice\",\"email\":\"alice@example.com\"}]}"
  }'

# Extract with JSONPath
curl -X POST "https://api.apify.com/v2/acts/perryay~json-studio/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "mode": "jsonpath",
    "input": "{\"store\":{\"books\":[{\"title\":\"Book A\",\"price\":10},{\"title\":\"Book B\",\"price\":15}]}}",
    "jsonpath": "$.store.books[*].title"
  }'

Python

import requests

API_TOKEN = "YOUR_API_TOKEN"
ACTOR_URL = "https://api.apify.com/v2/acts/perryay~json-studio/runs"

# Format and sort keys
response = requests.post(
    ACTOR_URL,
    headers={"Content-Type": "application/json",
             "Authorization": f"Bearer {API_TOKEN}"},
    json={
        "mode": "format",
        "input": '{"zebra":1,"apple":2,"banana":3}',
        "indentSize": 4,
        "sortKeys": True
    }
)
result = response.json()
print(result["result"])
# Output:
# {
#     "apple": 2,
#     "banana": 3,
#     "zebra": 1
# }

# Infer a JSON Schema from sample data
response = requests.post(
    ACTOR_URL,
    headers={"Content-Type": "application/json",
             "Authorization": f"Bearer {API_TOKEN}"},
    json={
        "mode": "infer-schema",
        "input": '{"users":[{"id":1,"name":"Alice"},{"id":2,"name":"Bob"}]}'
    }
)
schema = response.json()["result"]
print(schema)
# {
#   "$schema": "http://json-schema.org/draft-07/schema#",
#   "type": "object",
#   "properties": {
#     "users": {
#       "type": "array",
#       "items": {
#         "type": "object",
#         "properties": {
#           "id": {"type": "integer"},
#           "name": {"type": "string"}
#         }
#       }
#     }
#   }
# }

# Batch validate multiple documents
response = requests.post(
    ACTOR_URL,
    headers={"Content-Type": "application/json",
             "Authorization": f"Bearer {API_TOKEN}"},
    json={
        "mode": "validate",
        "input": [
            '{"valid": true}',
            '{"valid": true}',
            '{"invalid": broken'
        ]
    }
)
results = response.json()["result"]
for idx, doc_result in enumerate(results if isinstance(results, list) else [results]):
    valid = "✅" if doc_result.get("valid") else "❌"
    print(f"Doc {idx}: {valid}")

Use Cases

1. CI/CD Config Validation — Include a JSON Studio validation step in your pipeline pipeline to catch malformed deployment configs before they reach production. Reject builds with invalid JSON automatically. TeamCity, Jenkins, GitHub Actions, and GitLab CI can all call the API as part of a quality gate.

2. API Response Debugging — When an API returns garbled or minified JSON, pipe it through JSON Studio's format mode to get a clean, human-readable view in seconds. No more pasting into online formatters or writing one-liner Python scripts in the terminal.

3. Schema Discovery from Legacy APIs — Point JSON Studio at undocumented API responses in infer-schema mode to automatically generate a JSON Schema. Use it to write type-safe SDKs, generate TypeScript interfaces, or validate future responses against the inferred contract.

4. Environment Config Comparison — Use diff mode to compare staging versus production config files before a deployment. Spot missing keys, changed values, or unexpected additions. The structured diff output makes it easy to script approval workflows.

5. JSON-to-YAML Migration — Convert your application's JSON config files to YAML with to-yaml mode. Keep the same data, switch to a more human-friendly format for your ops team. Perfect for Docker Compose, Kubernetes, and Ansible config migration.

6. Data Pipeline Flattening — Flatten deeply nested JSON from an API or event stream into a flat key-value structure suitable for CSV export, database INSERT statements, or loading into spreadsheet tools. The dot-notation keys preserve the original hierarchy information.

7. Test Fixture Minification — Minify expected API responses before storing them as test fixtures. Smaller fixture files mean faster test suites and less noise in your version control diffs when fixtures change.

8. JSONPath Data Extraction — Use jsonpath mode to extract specific values from complex JSON documents without writing recursive descent code. Extract all email addresses, all IDs, or all prices with a single expression.

FAQ

Q: Can I process more than one JSON document in a single run? A: Yes. Pass an array of JSON strings in the input field and JSON Studio will process each one independently. In batch mode, the output includes results for every input document, making it easy to validate a set of files or format multiple responses at once.

Q: What is the maximum input size? A: JSON Studio handles inputs up to several megabytes in size. For extremely large documents (100 MB+), consider splitting them into smaller batches for optimal performance and response times.

Q: Does the diff mode work on deeply nested objects? A: Yes. The diff algorithm performs a deep comparison, detecting additions, removals, and changes at any nesting level. Nested objects that haven't changed are reported under unchanged so you can focus on what actually moved between versions.

Q: What JSONPath syntax does the extract mode support? A: JSON Studio uses standard JSONPath expressions (RFC 9535 compatible). You can use bracket notation ($['books'][0]), dot notation ($.books[0]), wildcards ($.*), filters ($[?(@.price > 10)]), recursive descent ($..title), slice notation, and union selectors.

Q: Can I minify and validate at the same time? A: Validation is always performed as part of every mode — if the input is not valid JSON, JSON Studio returns an error immediately regardless of the selected mode. To get only the validation result without a formatted output, use mode: "validate".

Q: Does JSON Schema inference handle arrays of mixed types? A: When an array contains elements of different types, the inferred schema uses oneOf or anyOf to represent each variant. For arrays with a single consistent type, it emits a clean items schema with that type.

Q: How does the flatten mode handle duplicate keys from array elements? A: Array indices are used in the flattened key path (e.g., users.0.name, users.1.name), so there are no duplicate keys. Each value retains its full path from the root of the document.

Q: Is there a way to preserve the original JSON structure when converting to YAML? A: Yes. The to-yaml mode preserves the full structure including nesting, arrays, and data types. Only the formatting and serialization change — no data is lost or transformed.

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