search
HomeBackend DevelopmentPython TutorialHow to Parse a JSON File Containing Multiple JSON Objects in Python?

How to Parse a JSON File Containing Multiple JSON Objects in Python?

Loading and Parsing a JSON File Containing Multiple JSON Objects

Unlike standard JSON files, which encapsulate all data within a single object or array, certain JSON formats store individual objects as separate lines in a text file. This can lead to challenges when attempting to parse such a file in Python.

Addressing the ValueError

When using Python's json.load() function to load a JSON file with multiple objects, you may encounter a "ValueError: Extra data" exception. This error indicates that the file contains unexpected data after the first parsed object.

Solution: Line-by-Line Parsing

To handle this issue, you need to treat each line in the file as an independent JSON object. Replace your current code with the following:

import json

data = []
with open('file') as f:
    for line in f:
        data.append(json.loads(line))

This code iterates over each line in the file, parses it as a JSON object, and appends it to a list.

Consideration for Large Files

If the JSON file is particularly large, appending all objects to a single list can consume excessive memory. To mitigate this, process each object separately before moving on to the next line. Avoid:

data = []  # List of all objects

Instead, process each object as needed:

for line in f:
    process_object(json.loads(line))

Handling Delimited JSON Objects

If your JSON file contains individual objects separated by delimiters, such as commas or newlines, you can use the following technique to parse out each object:

import json, io

# Read delimited JSON objects from a file
with open('file') as f:
    json_string = f.read()

# Create a buffered reader
json_buffer = io.StringIO(json_string)

while True:
    # Read next JSON object from the buffer
    json_object = json.load(json_buffer)
    
    # Process JSON object
    if not json_object:  # Reached the end of the file
        break

The above is the detailed content of How to Parse a JSON File Containing Multiple JSON Objects in Python?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python vs. C  : Understanding the Key DifferencesPython vs. C : Understanding the Key DifferencesApr 21, 2025 am 12:18 AM

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Python vs. C  : Which Language to Choose for Your Project?Python vs. C : Which Language to Choose for Your Project?Apr 21, 2025 am 12:17 AM

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

Reaching Your Python Goals: The Power of 2 Hours DailyReaching Your Python Goals: The Power of 2 Hours DailyApr 20, 2025 am 12:21 AM

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Maximizing 2 Hours: Effective Python Learning StrategiesMaximizing 2 Hours: Effective Python Learning StrategiesApr 20, 2025 am 12:20 AM

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Choosing Between Python and C  : The Right Language for YouChoosing Between Python and C : The Right Language for YouApr 20, 2025 am 12:20 AM

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python vs. C  : A Comparative Analysis of Programming LanguagesPython vs. C : A Comparative Analysis of Programming LanguagesApr 20, 2025 am 12:14 AM

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

2 Hours a Day: The Potential of Python Learning2 Hours a Day: The Potential of Python LearningApr 20, 2025 am 12:14 AM

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools