PapaJSON Documentation

PapaJSON is a comprehensive suite of JSON tools designed for developers and data analysts. This documentation provides detailed information about all features and functionalities available in PapaJSON.

Quick Start Guide

Get started with PapaJSON in three simple steps:

  1. Import your JSON data using any of our import methods
  2. Use the validation and formatting tools to clean your data
  3. Analyze, query, or export your data as needed

Excel Import

Convert Excel spreadsheets to JSON format with our Excel import feature.

Supported Formats

  • .xlsx (Excel 2007+)
  • .xls (Excel 97-2003)
Note: The first row of your Excel sheet will be used as the property names in the resulting JSON.

JSON Import

Import JSON data directly from files or paste it into the editor.

Features

  • Automatic validation on import
  • Large file support (up to 100MB)
  • UTF-8 encoding support

URL Import

Fetch JSON data directly from URLs.

Configuration Options

{
  "url": "https://api.example.com/data",
  "method": "GET",
  "headers": {
    "Authorization": "Bearer token"
  }
}

API Import

Connect to APIs with advanced configuration options.

Authentication Methods

Method Description
No Auth Public API endpoints
Basic Auth Username and password authentication
OAuth 2.0 Token-based authentication
API Key Custom header or parameter-based authentication

Google Sheets Import

Import data directly from Google Sheets into JSON format with our seamless integration tool.

Features

  • Direct import from public Google Sheets
  • Automatic column header detection
  • Smart data type conversion
  • Support for multiple sheets
  • Configuration saving for frequent imports

How to Use

  1. Make your Google Sheet public or share with "Anyone with the link"
  2. Copy the Google Sheet URL from your browser
  3. Paste the URL into the Google Sheets import field
  4. Click "Fetch" to import the data

URL Format

https://docs.google.com/spreadsheets/d/YOUR_SHEET_ID/edit?usp=sharing

Data Type Conversion

Sheet Data JSON Type Example
Text String "Hello"
Number Number 42
Date String (ISO format) "2024-01-01"
TRUE/FALSE Boolean true
Empty cell null null

Configuration Management

Save and manage frequently used Google Sheet configurations:

  • Save configurations with custom names
  • Quick load of saved configurations
  • Delete outdated configurations
  • Multiple configuration support
Important: Ensure your Google Sheet is properly shared before attempting to import. Private sheets cannot be accessed.
Pro Tip: For large sheets, consider splitting data into multiple sheets of less than 50,000 rows each for optimal performance.

Limitations

  • Maximum 50,000 rows per sheet recommended
  • Sheet must be publicly accessible
  • First row must contain column headers
  • Complex formatting and formulas are not imported

JSON Validation

Ensure your JSON is valid with our real-time validation tool.

Validation Checks

  • Syntax validation
  • Structure validation
  • Data type checking
  • Error location identification
Important: Invalid JSON will be highlighted with detailed error messages.

JSON Formatting

The JSON formatter provides a clean, properly indented representation of your JSON data, making it human-readable and easier to understand.

Features

  • Proper indentation with configurable spacing
  • Syntax highlighting
  • Real-time validation while formatting
  • Copy formatted JSON to clipboard

Example

Unformatted JSON:

{"name":"John","age":30,"address":{"street":"123 Main St","city":"Boston"}}

Formatted JSON:

{
  "name": "John",
  "age": 30,
  "address": {
    "street": "123 Main St",
    "city": "Boston"
  }
}
Tip: Use the "Copy" button to quickly copy the formatted JSON to your clipboard.

JSON Minification

The minification tool removes all unnecessary whitespace and formatting to create the smallest possible valid JSON string.

Benefits

  • Reduced file size for storage and transmission
  • Improved parsing performance
  • Optimal for production environments
  • Maintains data integrity while reducing size

Size Reduction Example

JSON Type Size Reduction
Small JSON (< 1KB) 20-30%
Medium JSON (1KB - 100KB) 30-40%
Large JSON (> 100KB) 40-50%
Note: Minified JSON is valid JSON but may be harder to read. Use formatting for development and debugging.

JSON Interpreter

The JSON Interpreter provides detailed analysis and insights about your JSON data structure.

Analysis Features

  • Data type detection and validation
  • Structure analysis and visualization
  • Property type mapping
  • Array content analysis

Data Type Detection

Type Description Example
String Text values "Hello World"
Number Integer or floating-point 42, 3.14
Boolean True/false values true, false
Object Nested key-value pairs {"key": "value"}
Array Ordered collections [1, 2, 3]
Null Empty/undefined values null
Pro Tip: Use the interpreter to identify potential data inconsistencies and type mismatches in your JSON structure.

JSON Tree View

The Tree View provides a hierarchical visualization of your JSON structure, making it easy to navigate and understand complex data relationships.

Key Features

  • Collapsible/expandable nodes
  • Visual hierarchy representation
  • Type indicators for each value
  • Optimized rendering for large datasets
  • Interactive navigation

Performance Optimization

For large JSON structures, the tree view implements several optimizations:

  • Lazy loading of nested structures
  • Showing only first items of large arrays
  • Collapsible sections for better navigation
  • Memory-efficient rendering

Visual Indicators

Symbol Meaning
Expandable node (click to collapse)
Collapsed node (click to expand)
... Additional items indicator
Tip: Use the tree view to quickly navigate through nested structures and identify data patterns.

JSON Differ

The JSON Differ tool allows you to compare two JSON structures and identify all differences between them, including added, removed, and modified values.

Key Features

  • Side-by-side comparison of two JSON structures
  • Color-coded differences for easy identification
  • Support for nested object comparison
  • Summary of changes with counts
  • Format both JSONs for better readability

Difference Types

Type Color Description
Added Green Properties or values present in the new JSON but not in the original
Removed Red Properties or values present in the original JSON but not in the new one
Modified Orange Properties that exist in both but have different values

How to Use

  1. Paste your original JSON in the left textarea
  2. Paste your new JSON in the right textarea
  3. Click "Compare" to see the differences
  4. Optionally use "Format Both" to improve readability

Output Format

The comparison results show:

  • A summary count of added, removed, and modified items
  • Detailed list of all differences with:
    • The exact path of each difference
    • Original and new values for modified items
    • Clear indicators for added and removed items
Pro Tip: Use the "Format Both" button before comparing to ensure both JSONs are properly formatted and easier to read.

Example Output

Removed: 1 Added: 2 Modified: 3

- user.name: "John Smith" (Modified in new JSON)
  From: "John Smith"
  To: "John Doe"

- user.age: 25 (Removed in new JSON)

- user.email: "john@example.com" (Added in new JSON)
Note: The differ performs a deep comparison of objects, so nested changes will be detected and displayed with their full path.

JSON to XML Conversion

Convert JSON data to XML format with our JSON to XML tool. This feature is useful when you need to transform JSON data into XML for compatibility with systems that require XML input.

How to Use

  1. Paste your JSON data into the JSON input area.
  2. Click the "Convert" button to transform the JSON into XML.
  3. The XML output will appear in the XML output area.
  4. You can copy the XML output or clear the input/output areas using the provided buttons.

Example

JSON Input:

{
  "name": "PapaJson",
  "version": "1.0.0",
  "features": {
    "parsing": true,
    "validation": true,
    "formatting": true
  }
}

XML Output:

<root>
  <name>PapaJson</name>
  <version>1.0.0</version>
  <features>
    <parsing>true</parsing>
    <validation>true</validation>
    <formatting>true</formatting>
  </features>
</root>

Features

  • Supports nested JSON objects and arrays.
  • Automatic conversion of JSON data types to XML elements.
  • Formatted XML output for readability.
  • Copy XML output to clipboard with a single click.
  • Clear both input and output areas with the "Clear" button.
Tip: Use the "Format JSON" button to ensure your JSON is properly formatted before conversion.

Limitations

  • Complex JSON structures with deeply nested objects may result in verbose XML output.
  • XML does not support all JSON data types natively (e.g., JSON arrays are converted to repeated XML elements).
  • Large JSON files may take longer to convert and result in large XML files.

Query Builder

Build complex queries to filter and analyze your JSON data.

Filter Components

  • Filter Groups (AND/OR logic between groups)
  • Filter Lines (AND/OR logic within group)
  • Field Selection (supports nested properties)
  • Operators (based on data type)
  • Value Input with Smart Helpers

Operator Types

Data Type Available Operators Description
String
  • equals
  • contains
  • does not contain
  • starts with
  • ends with
  • is empty
  • is not empty
Text comparison operators
Number
  • equals (=)
  • not equals (!=)
  • greater than (>)
  • less than (<)
  • greater than or equal (>=)
  • less than or equal (<=)
Numeric comparison operators
Date/DateTime
  • on (=)
  • before (<)
  • after (>)
  • at or before (<=)
  • at or after (>=)
  • is empty
  • is not empty
Date-specific comparisons
Boolean
  • is (=)
  • is not (!=)
True/false comparisons

Value Helpers

The Value Helper system provides smart assistance when entering filter values:

  • Auto-Detection: Automatically detects field type and shows relevant operators
  • Suggestions: Shows unique values from the dataset for quick selection
  • Dynamic Updates: Updates suggestions based on current dataset
  • Type Validation: Ensures entered values match the field type
Pro Tip: Use the value helper dropdown to see all possible values for a field and avoid typos in filter conditions.

Query Types

  • AND/OR conditions
  • Multiple filter groups
  • Nested property queries
  • Array filtering

Filter Groups

Create complex queries using multiple filter groups:

  • Main AND: All conditions within the group must match
  • Main OR: Any condition within the group can match
  • Nested Groups: Combine multiple groups for complex logic
  • Group Management: Add, delete, or modify groups dynamically

Example Query

{
  "group": "AND",
  "rules": [
    {
      "field": "age",
      "operator": ">",
      "value": 18
    },
    {
      "field": "status",
      "operator": "equals",
      "value": "active"
    }
  ]
}

Query Results

After executing a query, you can:

  • View filtered results in table format
  • Sort results by clicking column headers
  • Copy filtered JSON to clipboard
  • Download results as JSON or Excel
  • See the count of matching records
  • View active filters in breadcrumb format
Note: Complex queries with multiple groups may impact performance on very large datasets.

Data Export

Export your filtered or transformed JSON data in various formats.

Export Options

Format Description
JSON Formatted or minified JSON
Excel Spreadsheet format (.xlsx)
Filtered JSON Results from query builder