Convert Array of Dictionaries to JSON in Python

In this tutorial, you’ll learn various methods to convert an array of dictionaries to JSON.

We’ll start with basic methods using the json module and progress to more advanced techniques involving Pandas and list comprehension.

 

 

Using json.dumps

The json.dumps method serializes your Python object into a JSON formatted string.

First, you’ll need to import the json module:

import json

Now, consider the following sample data:

data = [
    {"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.50},
    {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75},
    {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.00}
]

To convert this array of dictionaries to a JSON string, you can use json.dumps:

json_data = json.dumps(data)
print(json_data)

Output:

[{"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.5}, {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75}, {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.0}]

This output shows your data array transformed into a JSON-formatted string.

Each dictionary in the array becomes a JSON object, and the entire array is enclosed in square brackets, following the JSON array format.

 

Using json.dump

While json.dumps is excellent for converting data to a JSON string, json.dump allows you to write JSON data directly to a file.

Let’s say you want to save the customer data array to a JSON file. Here’s how you do it:

Recall the sample data:

data = [
    {"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.50},
    {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75},
    {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.00}
]

To write this data to a file in JSON format, you can use json.dump:

with open('customers.json', 'w') as file:
    json.dump(data, file)

After executing this code, a file named customers.json will be created in your working directory.

The use of the with statement ensures that the file is properly closed after the write operation, which is a best practice in file handling.

 

Using Pandas

First, import the Pandas library:

import pandas as pd

We’ll use the same sample data:

data = [
    {"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.50},
    {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75},
    {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.00}
]

To convert this data into a JSON string with Pandas, start by creating a DataFrame from the array of dictionaries:

df = pd.DataFrame(data)

Then, convert the DataFrame to a JSON string:

json_data = df.to_json(orient='records')
print(json_data)

Output:

[{"customer_id":101,"name":"Jordan","plan":"Premium","balance":45.5},{"customer_id":102,"name":"Taylor","plan":"Basic","balance":15.75},{"customer_id":103,"name":"Alex","plan":"Standard","balance":30.0}]

You can filter, sort, or apply other operations before conversion.

The to_json method with the records orientation produces a list of records, which is a common format for JSON data.

 

Using List Comprehension

List comprehension in Python provides a concise way to create lists. It can also be used innovatively for converting arrays of dictionaries into JSON format.

This method is particularly useful when you need to preprocess each dictionary in the array before converting it to JSON.

Let’s continue using our example from the telecom company:

First, remember to import the json module:

import json

Here’s our sample data again:

data = [
    {"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.50},
    {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75},
    {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.00}
]

To convert this data to JSON using list comprehension, you might want to preprocess the data. For example, let’s say you want to round the balance to 2 decimal places in each dictionary:

You can use list comprehension to process the data:

processed_data = [{key: round(value, 2) if isinstance(value, float) else value for key, value in customer.items()} for customer in data]

Then you can convert the processed data to a JSON string:

json_data = json.dumps(processed_data)
print(json_data)

Output:

[{"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.5}, {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75}, {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.0}]

In this method, the list comprehension first processes each dictionary in the array (e.g., rounding off float values) and then the json.dumps method is used to convert the processed array into a JSON string.

 

Serializing Custom Objects

JSON format does not directly support Python’s custom object serialization.

However, with a bit of extra coding, you can serialize these objects into JSON.

Let’s assume you have a custom class representing customers and you want to serialize it:

First, define the custom class:

class Customer:
    def __init__(self, customer_id, name, plan, balance):
        self.customer_id = customer_id
        self.name = name
        self.plan = plan
        self.balance = balance
    def serialize(self):
        return {
            "customer_id": self.customer_id,
            "name": self.name,
            "plan": self.plan,
            "balance": self.balance
        }

Let’s create a list of customer objects:

customers = [
    Customer(101, "Jordan", "Premium", 45.50),
    Customer(102, "Taylor", "Basic", 15.75),
    Customer(103, "Alex", "Standard", 30.00)
]

To serialize these custom objects to JSON, you’ll need to convert each object to a dictionary using serialize method in the Customer class and then use json.dumps:

import json
serialized_data = [customer.serialize() for customer in customers]
json_data = json.dumps(serialized_data)
print(json_data)

Output:

[{"customer_id": 101, "name": "Jordan", "plan": "Premium", "balance": 45.5}, {"customer_id": 102, "name": "Taylor", "plan": "Basic", "balance": 15.75}, {"customer_id": 103, "name": "Alex", "plan": "Standard", "balance": 30.0}]

In this method, the serialize function of each Customer instance converts the object’s attributes to a dictionary.

This collection of dictionaries is then turned into a JSON string using json.dumps.