Batch JSON Validator

About This Tool

Validate multiple JSON files at once and get a summary report. This tool runs entirely in your browser — no data is ever sent to a server. Free to use, no account required.

How Batch Validation Works

Batch validation processes multiple JSON documents in one operation, reporting results for each one individually.

Validating Multiple JSON Strings

Paste a list of JSON strings — one per line in NDJSON format, or as a JSON array — and each entry is validated independently. The tool reports valid or invalid for each, with error details for invalid ones.

Validation Results

Results are shown per entry: a green checkmark for valid JSON and a red indicator with the error message and character position for invalid JSON. This makes it easy to find which entries need fixing in a large batch.

Use Cases for Batch JSON Validation

Batch validation is particularly valuable when you have many JSON strings to check and cannot afford to validate them one at a time.

Validating Log Files

Log files in NDJSON format contain one JSON object per line. Validate all lines at once to find which log entries are malformed — common when dealing with application crashes or partial writes.

QA Testing API Responses

Save multiple API responses from a test run and validate them all at once to ensure none contain syntax errors before they are consumed by your application code.

Batch JSON Validation Use Cases

Batch validation checks multiple JSON files simultaneously — essential for data pipelines, import workflows, configuration audits, and CI/CD checks.

Batch Validation Scenarios

CLI Batch Validation with ajv

# Install ajv CLI
npm install -g ajv-cli

# Validate all JSON files against schema
ajv validate -s schema.json -d "*.json"

# Validate specific files
ajv validate -s user-schema.json -d users/*.json

# In CI/CD (GitHub Actions example)
- name: Validate JSON fixtures
  run: ajv validate -s schema.json -d "tests/fixtures/*.json"

Python Batch Validation

import json, jsonschema, glob

with open("schema.json") as f:
    schema = json.load(f)

errors = []
for path in glob.glob("data/*.json"):
    with open(path) as f:
        data = json.load(f)
    try:
        jsonschema.validate(data, schema)
        print(f"OK: {path}")
    except jsonschema.ValidationError as e:
        print(f"FAIL: {path} — {e.message}")
        errors.append(path)

print(f"\n{len(errors)} files failed validation")

Batch JSON Validation Use Cases

Batch validation is useful whenever you need to process many JSON objects at once rather than checking them one at a time. The three scenarios below cover the most common real-world applications.

1. Validate NDJSON Log Files

Each line in an NDJSON (Newline-Delimited JSON) file is a separate JSON event. Validate all lines before importing into a log aggregator to avoid partial ingestion failures.

2. Validate API Test Fixtures

Ensure all JSON fixture files in your test suite are syntactically valid before running CI. A malformed fixture can produce confusing test failures that look like code bugs.

3. Validate Database Exports

Verify each exported record is valid JSON before reimporting into another system to prevent partial imports and data integrity issues.

// Input NDJSON (3 lines, one record per line)
{"event":"click","userId":1,"ts":1700000000}
{"event":"view","userId":2,"ts":1700000001}
{"event":"purchase","userId":1,"ts":1700000002,"amount":29.99}

// Batch validation result:
Line 1: ✓ Valid
Line 2: ✓ Valid
Line 3: ✓ Valid
3/3 records valid

Batch Validation vs Single Validation

Single validation is optimised for interactive editing with immediate feedback. Batch validation is optimised for processing pipelines where you need per-item error reporting and a total pass/fail count.