How to Detect Duplicate Attributes in JSON Strings Using Golang?

Detecting Duplicate Attributes in JSON Strings Using Golang

In JSON strings, it's essential to maintain data integrity by preventing duplicate attributes. Golang provides a convenient way to detect and handle such duplicates.

Solution:

To detect duplicate attributes in a JSON string, we can utilize the json.Decoder to traverse the JSON structure. While decoding, we inspect objects and their keys, checking for duplicates.

The provided Golang code demonstrates this process:

func check(d *json.Decoder, path []string, dup func(path []string) error) error {
    // Handle token and delimeters
    t, err := d.Token()
    if err != nil {
        return err
    }

    delim, ok := t.(json.Delim)

    // Skip scaler types
    if !ok {
        return nil
    }

    switch delim {
    case '{':
        // Initialize map for keys and avoid duplicates
        keys := make(map[string]bool)

        for d.More() {
            key := t.(string)

            if keys[key] {
                return dup(append(path, key))
            }

            keys[key] = true

            if err := check(d, append(path, key), dup); err != nil {
                return err
            }
        }
    case '[':
        i := 0
        for d.More() {
            if err := check(d, append(path, strconv.Itoa(i)), dup); err != nil {
                return err
            }
            i++
        }
    }
    return nil
}

Example Usage:

data := `{"a": "b", "a":true,"c":["field_3 string 1","field3 string2"], "d": {"e": 1, "e": 2}}`

if err := check(json.NewDecoder(strings.NewReader(data)), nil, printDup); err != nil {
    log.Fatal(err)
}

This example will report the following duplicates:

Duplicate a
Duplicate d/e

Custom Error Handling:

To throw an error upon encountering the first duplicate key, modify the dupErr() function as follows:

func dupErr(path []string) error {
    return ErrDuplicate
}

This approach allows for the detection of duplicate attributes, enabling you to take appropriate actions such as logging the issue or filtering out the duplicate data.

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