Working with JSON Files in Python

JSON (JavaScript Object Notation) is a lightweight, human-readable format for storing and exchanging data. Python provides built-in support for JSON through the json module.

Why use JSON?

Widely used in web APIs and data storage.
Easily readable by humans and machines.
Language-independent and supported across programming languages.

1. Importing the JSON Module

import json

2. JSON Data Format

A JSON object is similar to a Python dictionary and consists of key-value pairs.

Example JSON Data (String Format)

{
    "name": "Alice",
    "age": 25,
    "city": "New York",
    "languages": ["English", "Spanish"]
}

3. Converting Between JSON and Python Objects

Method 1: Converting JSON String to Python Object (`json.loads`)

json.loads() parses a JSON string and converts it into a Python dictionary.

import json

json_data = '{"name": "Alice", "age": 25, "city": "New York"}'

# Convert JSON string to Python dictionary
python_dict = json.loads(json_data)

print(python_dict)        # Output: {'name': 'Alice', 'age': 25, 'city': 'New York'}
print(python_dict["name"])  # Output: Alice

Use this method when receiving JSON data as a string (e.g., from an API).

Method 2: Converting Python Dictionary to JSON String (`json.dumps`)

json.dumps() converts a Python dictionary into a JSON string.

import json

data = {"name": "Alice", "age": 25, "city": "New York"}

# Convert Python dictionary to JSON string
json_string = json.dumps(data)

print(json_string)  # Output: '{"name": "Alice", "age": 25, "city": "New York"}'

dumps() is useful when sending data to APIs or storing JSON in files.

4. Reading and Writing JSON Files

Method 1: Reading a JSON File (`json.load`)

import json

# Open and read JSON file
with open("data.json", "r") as file:
    data = json.load(file)

print(data)  # Output: Dictionary representation of JSON

Use json.load() for reading JSON files.

Method 2: Writing to a JSON File (`json.dump`)

import json

data = {"name": "Alice", "age": 25, "city": "New York"}

# Write Python dictionary to JSON file
with open("data.json", "w") as file:
    json.dump(data, file)

print("Data saved to data.json")

Use json.dump() to write Python dictionaries to a JSON file.

5. Formatting JSON Output (`indent`, `sort_keys`)

Pretty-Printing JSON

indent makes JSON easier to read, and sort_keys=True sorts keys alphabetically.

import json

data = {"name": "Alice", "age": 25, "city": "New York"}

formatted_json = json.dumps(data, indent=4, sort_keys=True)

print(formatted_json)

Output (Formatted JSON):

{
    "age": 25,
    "city": "New York",
    "name": "Alice"
}

Useful for debugging and saving structured JSON data.

6. Working with Nested JSON

Example: Parsing Nested JSON

import json

json_data = '''
{
    "name": "Alice",
    "details": {
        "age": 25,
        "city": "New York",
        "languages": ["English", "Spanish"]
    }
}
'''

data = json.loads(json_data)

# Access nested values
print(data["details"]["city"])       # Output: New York
print(data["details"]["languages"])  # Output: ['English', 'Spanish']

Use ["key"] to access values inside nested dictionaries.

7. Appending Data to a JSON File

To append new data, read the file, update the dictionary, and write back.

import json

# Read existing data
with open("data.json", "r") as file:
    data = json.load(file)

# Append new data
data["email"] = "alice@example.com"

# Write updated data back to file
with open("data.json", "w") as file:
    json.dump(data, file, indent=4)

print("Data updated successfully!")

JSON files must be read first before modifying them.

8. Handling JSON Errors with `try-except`

Avoid program crashes due to malformed JSON.

import json

try:
    with open("data.json", "r") as file:
        data = json.load(file)
except FileNotFoundError:
    print("Error: File not found!")
except json.JSONDecodeError:
    print("Error: Invalid JSON format!")

json.JSONDecodeError is raised when JSON is not formatted correctly.

9. Converting JSON to a Pandas DataFrame

For data analysis, convert JSON into a Pandas DataFrame.

import json
import pandas as pd

json_data = '''
[
    {"name": "Alice", "age": 25, "city": "New York"},
    {"name": "Bob", "age": 30, "city": "London"}
]
'''

data = json.loads(json_data)

df = pd.DataFrame(data)  # Convert JSON list to DataFrame

print(df)

Best for working with structured JSON in data science projects.

10. Checking If a JSON File Exists

Before reading a file, check if it exists.

import os

if os.path.exists("data.json"):
    print("File exists")
else:
    print("File not found")

11. Summary Table

Operation	Function	Example
Convert JSON string to dict	`json.loads()`	`data = json.loads(json_string)`
Convert dict to JSON string	`json.dumps()`	`json_string = json.dumps(data)`
Read JSON file	`json.load()`	`data = json.load(file)`
Write JSON to file	`json.dump()`	`json.dump(data, file)`
Pretty-print JSON	`json.dumps(indent=4)`	`print(json.dumps(data, indent=4))`
Handle nested JSON	`data["key"]["subkey"]`	`data["details"]["age"]`
Append to JSON file	Modify dict and use `json.dump()`	`data["new_key"] = "value"`