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In daily programming work, sometimes we need to process JSON data and extract information, and the powerful functions of regular expressions can help us complete this work quickly and efficiently. In this article, we will introduce how to use Python regular expressions for JSON processing.
JSON is a lightweight data exchange format commonly used for network transmission and data storage. In Python, we can use the json library to parse JSON data, but in some cases, we need to perform certain processing and extraction of JSON data. At this time, regular expressions will play its role.
First, let’s take a look at the basic structure of JSON data. JSON data usually consists of key-value pairs. Keys and values are separated by colons ":", each key-value pair is separated by commas ",", and the outermost layer is usually wrapped by curly brackets "{}". For example:
{ "name": "John", "age": 30, "city": "New York" }
Now let's take a look at how to use Python regular expressions to extract this JSON data. Suppose we need to extract the "name" and "age" fields, we can use the following regular expressions :
"name":s*"([^"]+)",s*"age":s*(d+)
Analyze this regular expression:
Through the above regular expression, we can extract the value corresponding to the "name" field and the value corresponding to the "age" field. Implemented using Python code:
import re s = '{"name": "John", "age": 30, "city": "New York"}' pattern = re.compile(r'"name":s*"([^"]+)",s*"age":s*(d+)') match = pattern.search(s) if match: name = match.group(1) age = match.group(2) print(name, age)
Output:
John 30
Next, let’s take a look at more application scenarios of how to use Python regular expressions to extract JSON data.
Sometimes we only need to extract the value of a certain field, and we can use the following regular expression:
"field_name":s*"([^"]+)"
For example, if we need to extract the value corresponding to the "city" field in the JSON data above, we can use the following regular expression: :
"city":s*"([^"]+)"
Python code implementation:
import re s = '{"name": "John", "age": 30, "city": "New York"}' pattern = re.compile(r'"city":s*"([^"]+)",') match = pattern.search(s) if match: city = match.group(1) print(city)
Output:
New York
In JSON data, there are When we need to extract the value of an array type element, we can use the following regular expression:
"array_field":s*[s*([sS]*?)s*]
For example, we need to extract all elements in the value corresponding to the "pets" field in the following JSON data:
{ "name": "John", "age": 30, "pets": [ { "name": "dog", "age": 3 }, { "name": "cat", "age": 2 } ] }
You can use regular expressions as follows:
"pets":s*[s*([sS]*?)s*]
Python code implementation:
import re s = '{"name": "John", "age": 30, "pets": [{"name": "dog", "age": 3},{"name": "cat", "age": 2}]}' pattern = re.compile(r'"pets":s*[s*([sS]*?)s*]') match = pattern.search(s) if match: pets = match.group(1) print(pets)
Output:
{"name": "dog", "age": 3},{"name": "cat", "age": 2}
Sometimes we need to extract a certain value in a multi-layer nested element, you can use the following regular expression:
"object1":s*{s*[sS]*?"object2":s*{s*[sS]*?"field_name":s*"([^"]+)"
For example, we need to extract the "pets" field corresponding to the following JSON data The value corresponding to the "age" field of the second element in the value:
{ "name": "John", "age": 30, "pets": [ { "name": "dog", "age": 3 }, { "name": "cat", "age": 2 } ] }
You can use the regular expression as follows:
"pets":s*[s*[sS]*?"age":s*(d+)[sS]*?}
Python code implementation:
import re s = '{"name": "John", "age": 30, "pets": [{"name": "dog", "age": 3},{"name": "cat", "age": 2}]}' pattern = re.compile(r'"pets":s*[s*[sS]*?"age":s*(d+)[sS]*?}') match = pattern.search(s) if match: age = match.group(1) print(age)
Output :
2
Summary:
Using regular expressions for JSON processing allows us to extract and process JSON data more flexibly, which is useful for certain situations where JSON data needs to be filtered, filtered, converted, etc. It is of great significance in the application scenarios of the operation. However, it should be noted that when processing JSON data, regular expressions may not be suitable for more complex situations, and need to be selected flexibly according to the actual situation.
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