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https://github.com/d3rty/json

Flexible JSON decoding for Go — gracefully handling schema variations and forgiving mistakes.
https://github.com/d3rty/json

dirty-data json-parser json-schema sanitizer validator

Last synced: 7 months ago
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Flexible JSON decoding for Go — gracefully handling schema variations and forgiving mistakes.

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# d3rty/json 🧼

Flexible JSON unmarshalling for Go: gracefully handling schema variations and forgiving mistakes.

> 🚧 Project is a `Work In Progress` thing.

## Overview

**d3rty/json** is a robust Go library for parsing JSON data from third-party sources you can’t fully control or trust.
It’s built to handle real-world, unpredictable JSON — whether you're dealing with schema flakiness like stringified integers,
inconsistent key naming (camelCase vs. snake_keys), or even quirks introduced by AI-generated data.
With a forgiving approach to unmarshalling, d3rty/json ensures your application continues to work reliably while still capturing
as much meaningful data as possible.

## Key Features

- **Flexible Unmarshalling:**
Attempts standard decoding first and then gracefully falls back to a more flexible decoding when encountering schema variations.

- **Custom Data Types:**
Provides custom types (such as `Number`, `String`, `Bool`, `Array`, and `Object`) that are designed to interpret JSON values even when they deviate from the standard.

- **Seamless Integration:**
Designed to work as a drop-in replacement for the standard library’s `json.Unmarshal`, `json.NewDecoder` allowing you to easily switch without rewriting your models.

- **Error & Warning Reporting:**
Incorporates a system of result colors (🟢 Green, 🟡 Yellow, 🔴 Red) to signal the quality of the unmarshalling process—whether it was clean, achieved through forgiving conversions, or partially lossy.

## Installation

After `go get github.com/d3rty/json` you can simply import the package into your code:

```go
import "github.com/d3rty/json"
```

## Usage

```go
package main

import (
"fmt"
"log"

dirty "github.com/d3rty/json"
)

// Event is a classical "clean" model.
// Types are strict.
type Event struct {
dirty.Enabled // Enables dirty unmarshalling.

Name string `json:"name"`

// These fields will be rewritten in dirty schema.
// In case if they were dirty-read (stringified integers, etc) - they are still valid. (Yellow Mode)
ID int `json:"id"`
IsActive bool `json:"is_active"` // this will be read as is_active/IsActive/is-active, etc

// MustBool won't be rewritten in dirty schema. So this field MUST be bool or ignored (Red Mode).
MustBool bool `json:"must_bool"`
}

// Dirty method links the clean model to its dirty variant.
func (e *Event) Dirty() any {
// Both inline or defined type work here.
return &struct {
ID dirty.Number `json:"id"`
IsActive dirty.Bool `json:"is_active"`
}{}
}

func main() {
// No data loss, we forgave all the mistakes:
data := []byte(`{"id": "123", "name": "Sample Event", "IsActive": "on", "must_bool": true}`)
var event Event

if err := dirty.Unmarshal(data, &event); err != nil {
log.Fatalf("error unmarshalling: %v", err)
}

// We successfully marshalled, fixing all the mistakes that we forgave (Yellow mode):
fmt.Println(event.ID) // 123
fmt.Println(event.IsActive) // true
fmt.Println(event.MustBool) // true

// Unparsable value on strict (clean) field:
// We couldn't fix all the mistakes, so we lost the data (Red mode):
data = []byte(`{"id": "123", "name": "Sample Event", "IsActive": "on", "must_bool": "true"}`)

event = Event{}
if err := dirty.Unmarshal(data, &event); err != nil {
log.Fatalf("error unmarshalling: %v", err)
}

fmt.Println(event.ID) // 123
fmt.Println(event.IsActive) // true
fmt.Println(event.MustBool) // false (Because it's not declared in dirty scheme)
}
````