Let's talk about the loss of precision in php json_encode

PHP is a widely used programming language that is widely used in writing web applications, working with databases, creating scripts, and server-side programming. Among them, json_encode is a very common function in PHP, used to convert PHP arrays and objects into JSON strings. This function is a very convenient tool and is used very frequently in daily programming. However, someone may encounter such a problem: when using the json_encode function to convert a PHP array or object into a JSON string, sometimes precision is lost. This article will explore the cause of this problem.

First, let us understand what JSON is. JSON (JavaScript Object Notation) is a text format used for exchanging data. It is a very lightweight format that is easy to read and understand. The JSON format consists of key-value pairs, and these key-value pairs can also contain arrays and nested objects. For PHP, you can use the json_encode function to convert arrays and objects into JSON-formatted strings, and you can use the json_decode function to convert JSON-formatted strings into PHP arrays or objects.

So, why does the precision loss occur when using the json_encode function for conversion? This is caused by the mechanism of the json_encode function when handling floating point numbers. In PHP, floating-point numbers are usually represented in the double-precision floating-point format of the IEEE 754 standard. In JSON format, floating point numbers have only one representation method, which is decimal representation. When a PHP array or object contains double-precision floating-point data, the json_encode function will cause precision loss when converting it into a JSON string, resulting in precision loss.

The following is a simple example to illustrate this problem:

$array = array(
    'foo' => 0.1,
    'bar' => 0.7,
    'baz' => 0.6 + 0.1
);

echo json_encode($array);

The output result is:

{"foo":0.1,"bar":0.69999999999999996,"baz":0.7}

As you can see, the $array array contains three floating point number types The data, one of the numbers is 0.6 0.1, when the json_encode function is converting, it is converted to 0.7, causing the problem of loss of accuracy. The same problem will occur with other floating point types of data.

So, how to solve this problem? There are usually two methods:

1. Use the number_format function to round floating point numbers:

$array = array(
    'foo' => number_format(0.1, 2, '.', ''),
    'bar' => number_format(0.7, 2, '.', ''),
    'baz' => number_format(0.6 + 0.1, 2, '.', '')
);

echo json_encode($array);

The output result is:

{"foo":"0.10","bar":"0.70","baz":"0.70"}

Use the number_format function to round floating point numbers , which can solve the problem of accuracy loss. However, this approach is inelegant and requires processing for each floating point number.

2. Use the bcmath extension function to process floating point numbers:

if (!function_exists('json_encode_float')) {
    function json_encode_float($val) {
        $precision = ini_get('precision');
        ini_set('precision', 16);
        $encoded = json_encode($val);
        ini_set('precision', $precision);
        return $encoded;
    }
}

$array = array(
    'foo' => 0.1,
    'bar' => 0.7,
    'baz' => 0.6 + 0.1
);

echo json_encode_float($array);

The output result is:

{"foo":0.1,"bar":0.7,"baz":0.7}

By using the bcmath extension function, the precision can be set to a higher value, avoiding the problem of loss of precision. The json_encode_float function in the code is an encapsulation of the json_encode function and is used to process floating point type data.

To sum up, the problem of precision loss in the json_encode function is caused by its mechanism when dealing with floating point numbers. To avoid loss of precision, you can round floating point numbers via the number_format function, or use the bcmath extension function to handle floating point numbers. In daily programming, we should pay attention to this problem and adopt appropriate methods to avoid precision loss.

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