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PHP regular expression in action: matching JSON format

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2023-06-22 19:50:572295browse

With the increasing development of Internet technology and data interaction, JSON (JavaScript Object Notation), as a lightweight data exchange format, has been widely used in front-end and back-end development. In PHP development, we often need to use regular expressions to match and process data in JSON format. In this article, we will discuss how to match JSON format in actual PHP regular expressions.

1. Introduction to JSON format

The JSON format mainly consists of braces, square brackets, commas, colons and double quotes. Braces are used to represent objects, and square brackets are used to represent arrays. Commas are used to separate different elements in arrays and objects, colons are used to separate key-value pairs in objects, and double quotes are used to represent strings.

A typical JSON format is as follows:

{
    "name": "Tom",
    "age": 20,
    "hobbies": ["reading", "music"],
    "address": {
        "province": "Guangdong",
        "city": "Shenzhen"
    }
}

2. Basic syntax of PHP regular expressions

Before learning how to match the JSON format, let’s first briefly understand PHP regular expressions Basic syntax for expressions.

  1. Match characters

In regular expressions, "." is usually used to match any character except line breaks, "d" is used to match numbers, and "w" to match letters, numbers, and underscores, and "s" to match whitespace characters.

  1. Match special characters

If we want to match some special characters, such as period ".", backslash "", vertical bar "|", etc., we need to use Backslash escape, i.e. ".", "\", "|".

  1. Number of matches

"*" represents any number, "" represents at least one, "?" represents zero or one, "{n}" represents exactly n, "{n,}" represents at least n, "{n,m}" represents n to m.

  1. Matching position

"^" represents the beginning of the line, "$" represents the end of the line, and "" represents the word boundary.

3. Example of matching JSON format

In actual development, we often need to process and analyze strings in JSON format, such as verifying whether the JSON format is correct and extracting data in JSON format wait. The following are some common requirements and regular expression examples for matching JSON format:

  1. Match strings containing JSON format
    If we want to match whether a string contains JSON format, we can use The following regular expression:
preg_match('/{.*}/', $str, $match)

Among them, "{" and "}" match braces respectively, and ".*" matches any character within the braces.

  1. Verify whether the JSON format is correct
    If we want to determine whether a JSON string conforms to the JSON format specification, we can use the json_decode() function to parse it. If the parsing is successful, it means that the JSON format is correct, otherwise The description is formatted incorrectly. The sample code is as follows:
function is_json($str) {
    $json = json_decode($str);
    return $json && $str != $json;
}
  1. Extract data in JSON format
    If we want to extract a certain field value in JSON format, we can use the following regular expression:
preg_match('/"field_name":s*"([^"]+)"/', $str, $match)

Among them, "(?<=")field_name(?=")" matches the key name, and "(1)" matches the key value.

  1. Match JSON array
    If we want to match an array in JSON format, we can use the following regular expression:
preg_match('/[[^]]*]/', $str, $match)

Where, "[" and "] "matches square brackets respectively, and "[^]]" matches any character except "]".

  1. Match JSON objects
    If we want to match objects in JSON format, we can use the following regular expression:
preg_match('/{.*}/', $str, $match)

Where, "{" and "} "matches braces respectively,".*"matches any characters within braces.

4. Summary

This article mainly introduces some common techniques and methods for matching JSON format in PHP regular expression practice. Different scenarios and needs require the use of different regular expressions. Match and process JSON formatted data. In actual development, we can choose appropriate regular expressions for matching and processing according to specific business needs, making our code more robust and readable.


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