Detailed explanation of JSON parsing library in Python

With the development of the Internet era, data has become the basis of every form of information we are exposed to, and among them, JSON data format is often used in network data exchange. In order to facilitate the parsing and use of this data format, the Python language provides a JSON parsing library, which will be explained in detail in this article.

1. Introduction to JSON

JSON (JavaScript Object Notation) is a lightweight data exchange format. Compared with XML, JSON is more concise, easier to read and write, and easier to parse and generate. The basic data types of JSON include strings, numbers, Boolean, null, and two composite types: arrays and objects. Various programming languages can easily generate and parse JSON data.

2. JSON module in Python

There is a JSON module built into Python, which can easily generate and parse JSON data. This module includes four functions: dumps, dump, loads and load, which are used to convert Python objects into JSON format strings, convert Python objects into JSON format and store them in a file, and convert JSON strings into Python. Objects and reads and converts JSON-formatted files into Python objects.

1. dumps and dump function

The dumps function converts Python objects into JSON format strings. The usage method is as follows:

import json data = {'name': 'Jack', 'age': 18, 'gender': 'male'} json_str = json.dumps(data) print(json_str)

The running results are as follows:

{"name": "Jack", "age": 18, "gender": "male"}

The dump function converts Python objects into JSON format and stores them in a file. The usage method is as follows:

import json data = {'name': 'Jack', 'age': 18, 'gender': 'male'} with open('data.json', 'w') as f: json.dump(data, f)

2. loads and load functions

The loads function converts a JSON string into a Python object. The usage method is as follows:

import json json_str = '{"name": "Jack", "age": 18, "gender": "male"}' data = json.loads(json_str) print(data)

The running results are as follows:

{'name': 'Jack', 'age': 18, 'gender': 'male'}

The load function reads and converts a JSON format file into a Python object. The usage method is as follows: As follows:

import json with open('data.json', 'r') as f: data = json.load(f) print(data)

Please ensure that the data.json file is in the current directory.

3. Usage Example

Now, we give an example to more intuitively explain how to use the JSON parsing library in Python.

Suppose we now need to get data in JSON format from the network, its structure is as follows:

{ "name": "Jack", "age": 18, "gender": "male", "scores": [ { "subject": "Math", "score": 90 }, { "subject": "English", "score": 85 } ] }

We first use the requests library to get the data and parse it into a Python object:

import requests import json url = 'https://example.com/data.json' response = requests.get(url) data = json.loads(response.text)

Next, we can use the following code to obtain each field:

name = data['name'] age = data['age'] gender = data['gender'] scores = data['scores'] for score in scores: subject = score['subject'] score = score['score']

Finally, we can store the obtained data in a local file:

import json with open('data.txt', 'w', encoding='utf-8') as f: f.write('name: ' + name + ' ') f.write('age: ' + str(age) + ' ') f.write('gender: ' + gender + ' ') f.write('scores: ') for score in scores: f.write(' subject: ' + score['subject'] + ' ') f.write(' score: ' + str(score['score']) + ' ')

Through this example, We can see that using the JSON parsing library in Python can easily obtain and process data in JSON format.

4. Summary

JSON is a very convenient data format and is widely used in network applications. The JSON parsing library in Python provides convenient functions for generating and parsing JSON data format, which is easy to use and easy to understand. Python's own json library can be used directly, or third-party libraries simplejson, ujson, demjson, etc. can be used. Compared with XML format, JSON is more lightweight, easier to read, easier to write, easier to parse, and can make data exchange and processing more convenient.

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