JSON Editor

A JSON file management system with a graphical interface, developed in Python with Tkinter. It allows editing, validating, and maintaining structured JSON files according to a defined schema.

Description

This system is designed to function as a visual JSON database editor, allowing you to:

• Validate JSON data against a schema defined in a model file
• View and edit data in a user-friendly way with appropriate widgets for each data type
• Add and remove records following the defined schema
• Easily search for information, navigate, and manipulate records
• Export and save the edited data

Requirements

• Python 3.6 or higher
• Tkinter (included in most standard Python installations)
• For full drag-and-drop support on Windows, the pywin32 module is recommended:

  pip install pywin32
  

Installation

1. Clone this repository or download the files
2. Ensure that Python 3.6+ is installed
3. (Optional) Install pywin32 for full drag-and-drop support on Windows

How to Use

Run the main file:

python main.py

Basic workflow:

1. Load a JSON model file (containing the __meta__ definition)
2. Load a JSON data file or create a new dataset
3. Edit, add, or remove records as needed
4. Save the changes to the original file or a new file

Model File Structure

The model file must contain a JSON object with a __meta__ property that defines the expected data structure:

{
  "__meta__": {
    "field_name": {
      "type": "data_type",
      "required": true_or_false
    },
    ...
  }
}

Supported data types:

• str - Strings
• int - Integers
• float - Floating-point numbers
• bool - Boolean values (true/false)
• list - Generic lists
• list[type] - Typed lists (e.g., list[str]). This also applies to list[dict], allowing the creation of lists of objects with a defined structure.
• dict or object - Nested dictionaries. If the model specifies the dictionary fields, the editing interface will display structured fields. Otherwise, a generic key-value pair interface will be used.

Example:

{
  "__meta__": {
    "name": { "type": "str", "required": true },
    "email": { "type": "str", "required": false },
    "age": { "type": "int", "required": false },
    "active": { "type": "bool", "required": true },
    "tags": { "type": "list[str]", "required": false },
    "address": {
      "type": "dict",
      "required": false,
      "fields": {
        "street": { "type": "str", "required": true },
        "city": { "type": "str", "required": true },
        "zipcode": { "type": "str", "required": false }
      }
    }
  }
}

Features

Main features:

• Real-time validation: Identifies missing required fields and incorrect data types
• Spreadsheet-like interface: Grid view with individual cell editing
• Type-appropriate editing: Text inputs, checkboxes, numeric fields, etc.
• Search: Searches for content in any field
• Action history: Support for undo/redo operations
• Light/dark theme: Toggles between themes for better visual comfort
• Drag and drop: Support for loading files via drag & drop
• Export: Saves data in JSON format

Keyboard Shortcuts:

• Ctrl+O - Load model file
• Ctrl+D - Load data file
• Ctrl+S - Save data
• Ctrl+N - Add new entry
• Delete - Delete selected entry
• Ctrl+Z - Undo
• Ctrl+Y - Redo
• Ctrl+F - Focus on search field
• F3 - Next search result
• Shift+F3 - Previous search result

Examples

The system comes with example files in the examples/ folder:

• example_model.json - An example model with various field types
• example_data.json - Example data compatible with the model.
• complex_model.json - A more complex model, demonstrating dictionaries and lists with nested structures.
• complex_data.json - Corresponding data for the complex model.

Current Limitations

• Limited support for deeply nested structures
• No support for schema validation via JSON Schema or similar
• No native support for cross-object references

License

This project is distributed under the MIT license.