How to Split JSON File into Multiple Files: A Complete Developer’s Guide

Working with JSON files is common in web development, data processing, and software automation. But as these files grow in size, they can become difficult to manage or process efficiently. That’s where splitting a JSON file into multiple smaller files comes in handy.

In this comprehensive, step-by-step guide, you’ll learn multiple ways to split a JSON file into multiple files using Python, online tools, command-line utilities, and more. Whether you're handling a large JSON array or separating nested JSON structures, this article has got you covered.

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🚀 Why Split a JSON File?

Before diving into the how, let’s talk about the why. Here are common reasons why developers or analysts need to split JSON files:

• Improve performance: Smaller files are faster to process
• Avoid memory issues: Some systems can’t handle massive JSON files
• Facilitate uploads: APIs or software may have file size limits
• Better organization: Separate records into logical groupings
• Easier collaboration: Distribute pieces of data among teams
• Enable version control: Smaller files make it easier to track changes

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🧠 JSON File Structures: What You’re Splitting

JSON files can come in different formats:

1. An array of objects

Code Snippet
[
  { "id": 1, "name": "Alice" },
  { "id": 2, "name": "Bob" },
  { "id": 3, "name": "Charlie" }
]

2. Nested JSON

Code Snippet
{
  "users": [
    { "id": 1, "name": "Alice" },
    { "id": 2, "name": "Bob" }
  ],
  "metadata": { "count": 2 }
}

3. Line-delimited JSON (JSONL)

Code Snippet
{"id": 1, "name": "Alice"}
{"id": 2, "name": "Bob"}

Understanding the structure is key before you split it. JSON arrays are the most common target for splitting.

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🐍 Method 1: Split JSON File in Python

Python offers the most flexible and scalable method to split a JSON file.

Step 1: Read the JSON File

Code Snippet
import json

with open('large_file.json') as f:
    data = json.load(f)

Step 2: Split into Chunks

Code Snippet
chunk_size = 100  # records per file

for i in range(0, len(data), chunk_size):
    chunk = data[i:i+chunk_size]
    with open(f'chunk_{i//chunk_size + 1}.json', 'w') as f:
        json.dump(chunk, f, indent=4)

This will create files like chunk_1.json, chunk_2.json, and so on.

When to Use This:

• Large array of objects
• Complete control over output format
• Automate tasks for large data pipelines

Tip:

Use argparse to turn this into a reusable CLI script:

Code Snippet
import argparse

parser = argparse.ArgumentParser()
parser.add_argument('input_file')
parser.add_argument('--size', type=int, default=100)
args = parser.parse_args()

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🧰 Method 2: Use Online JSON Split Tools

If you're not comfortable coding, online JSON splitters are a great alternative.

Recommended Tool:

👉 merge-json-files.com/json-file-splitter

How to Use:

1. Upload your JSON file
2. Choose the number of records per file
3. Click Split
4. Download the resulting files

Benefits:

• No setup required
• Beginner-friendly
• Great for quick splits
• Mobile and browser-friendly

Use Case:

Perfect for splitting exported API data or JSON dumps without installing software.

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🖥️ Method 3: Command Line (Using jq on Linux/macOS)

For developers comfortable with the terminal, jq is a powerful command-line tool.

Install jq:

Code Snippet
sudo apt install jq   # Debian/Ubuntu
brew install jq       # macOS

Example: Split JSON Array

Code Snippet
jq -c '.[]' large_file.json | split -l 100 - chunk_

This will create files chunk_aa, chunk_ab, etc., each with 100 JSON lines.

Tip:

Convert each split back to a JSON array:

Code Snippet
for file in chunk_*; do
  jq -s '.' "$file" > "$file.json"
  rm "$file"
  mv "$file.json" "$file"
done

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📋 Bonus: Splitting Nested JSON Structures

Let’s say your file contains deeply nested objects or grouped sections like:

Code Snippet
{
  "users": [...],
  "admins": [...]
}

You can split it by key:

Code Snippet
with open('nested.json') as f:
    data = json.load(f)

with open('users.json', 'w') as f:
    json.dump(data['users'], f)

with open('admins.json', 'w') as f:
    json.dump(data['admins'], f)

This allows you to isolate and split different sections of a nested JSON structure easily.

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🧪 Real-World Use Case: JSON API Pagination

Many APIs return paginated results. Here’s a simple way to split them as you collect:

Code Snippet
import requests

all_data = []
for page in range(1, 6):
    response = requests.get(f'https://api.example.com/data?page={page}')
    all_data.extend(response.json())

with open('combined.json', 'w') as f:
    json.dump(all_data, f)

Then use the Python split technique to divide the result.

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🔧 Tools Comparison Table

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❗ Common Errors When Splitting JSON Files & Solutions

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🧠 Best Practices When Splitting JSON Files

• Always validate the JSON before and after splitting
• Keep backup copies of your original files
• Use descriptive filenames like users_part_1.json
• Add logging to Python scripts for error handling
• If splitting for upload, check the file size limit of your platform
• Consider compressing large sets using .zip or .tar.gz

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🔁 Recap: Ways to Split JSON Files

• 🐍 Python: Best for automation, flexible
• 🌐 Online Tools: Great for non-coders
• 💻 jq CLI: Efficient for large file processing

Choose the method that fits your project and technical comfort level.

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🏁 Final Thoughts

Whether you're a developer, data engineer, or analyst, learning how to split a JSON file into multiple files can save time and prevent headaches. From automation scripts in Python to fast online tools and robust CLI utilities, you now have the knowledge and tools to handle even the largest JSON datasets with ease.

👉 Try our free tool: merge-json-files.com/json-file-splitter for fast, no-code splitting.

If you're working on batch processing, API integrations, or database imports, mastering JSON file splitting is a vital skill. Use this guide as a reference whenever you need to streamline your JSON workflows.

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Happy JSON splitting! 🔥📂