How To Convert JSON to Markdown in Python

In this tutorial, we explore different methods to convert JSON to Markdown using Python.

We will cover manual conversion using string manipulation, Pandas for handling tabular data, and specialized libraries like tabulate for more conversions.

 

 

Manual Conversion (String Replacement)

First, let’s start by importing the json library and defining a sample JSON data structure.

import json
json_data = '''
{
    "user_id": 101,
    "name": "Jordan",
    "email": "jordan@example.com",
    "purchases": [
        {"item": "Laptop", "price": 1200},
        {"item": "Headphones", "price": 150}
    ]
}
'''
data = json.loads(json_data)

Output:

{
    'user_id': 101,
    'name': 'Jordan',
    'email': 'jordan@example.com',
    'purchases': [{'item': 'Laptop', 'price': 1200}, {'item': 'Headphones', 'price': 150}]
}

This output shows the JSON data successfully converted into a Python dictionary, making it easier to manipulate.

Next, let’s format this data into Markdown. We’ll create a Markdown string that represents the same data in a human-readable format.

markdown_output = f"""
## User Information

- **ID**: {data['user_id']}
- **Name**: {data['name']}
- **Email**: {data['email']}

## Purchases

"""
for purchase in data['purchases']:
    markdown_output += f"- **Item**: {purchase['item']}, **Price**: ${purchase['price']}\n"
print(markdown_output)

Output:

## User Information

- **ID**: 101
- **Name**: Jordan
- **Email**: jordan@example.com

## Purchases

- **Item**: Laptop, **Price**: $1200
- **Item**: Headphones, **Price**: $150

 

Using Pandas

First, let’s import Pandas and convert our JSON data into a Pandas DataFrame.

import pandas as pd
import json
json_data = '''
{
    "users": [
        {"id": 101, "name": "Jordan", "email": "jordan@example.com"},
        {"id": 102, "name": "Alex", "email": "alex@example.com"}
    ]
}
'''
data = json.loads(json_data)
df = pd.DataFrame(data['users'])

Output:

    id    name              email
0  101  Jordan  jordan@example.com
1  102    Alex    alex@example.com

Here, the JSON data is converted into a Pandas DataFrame, showing user details in a structured table format.

Now, let’s convert this DataFrame into Markdown format using the to_markdown() method:

markdown_table = df.to_markdown()
print(markdown_table)

Output:

|    |   id | name   | email             |
|---:|-----:|:-------|:------------------|
|  0 |  101 | Jordan | jordan@example.com|
|  1 |  102 | Alex   | alex@example.com  |

 

Using tabulate

To use the tabulate library for converting JSON to Markdown in Python, follow these steps:

Install the tabulate library using pip:

pip install tabulate

Import the necessary functions from the tabulate module:

from tabulate import tabulate

Prepare your JSON data. Here’s an example JSON:

json_data = [
{"Name": "John Doe", "Age": 30, "City": "New York"},
{"Name": "Jane Smith", "Age": 25, "City": "London"},
{"Name": "Bob Johnson", "Age": 35, "City": "Paris"}
]

Convert the JSON data to a list of lists:

table = [list(item.values()) for item in json_data]

Use the tabulate function to generate the Markdown table:

markdown = tabulate(table, headers="keys", tablefmt="pipe")

In the tabulate function, we pass the table variable as the data to be converted.

The headers="keys" parameter indicates that the keys of the JSON objects should be used as table headers.

The tablefmt="pipe" parameter specifies that the output format should be Markdown with pipe-style table borders.

Print or use the markdown variable as needed:

print(markdown)

The output will be a Markdown table:

| Name        |   Age | City      |
|:------------|------:|:----------|
| John Doe    |    30 | New York  |
| Jane Smith  |    25 | London    |
| Bob Johnson |    35 | Paris     |

You can customize the tabulate function further by specifying different table formats (plain, simple, grid, fancy_grid, etc.) and various other options.