Flatten a nested JSON hierarchy in Python

Flatten a nested JSON hierarchy in Python

Flattening a nested JSON hierarchy means converting a JSON object that may have nested structures into a simple flat structure (typically a dictionary) where all the key-value pairs are at the top level. This can be achieved using recursion to traverse through nested dictionaries and lists. Here's how you can implement it in Python:

Approach: Recursive Function to Flatten JSON

Here's a Python function that recursively flattens a nested JSON object:

def flatten_json(json_obj, prefix=''): """ Flatten a nested JSON object. Parameters: json_obj (dict): The nested JSON object to flatten. prefix (str): Optional prefix for keys in the flattened result. Returns: dict: The flattened dictionary. """ flattened = {} for key, value in json_obj.items(): new_key = f"{prefix}{key}" if isinstance(value, dict): flattened.update(flatten_json(value, new_key + '_')) elif isinstance(value, list): for i, v in enumerate(value): flattened.update(flatten_json(v, f"{new_key}_{i}_")) else: flattened[new_key] = value return flattened

Explanation:

  1. Parameters:

    • json_obj: The nested JSON object you want to flatten.
    • prefix: Optional prefix to prepend to keys in the flattened output. This helps in maintaining unique keys when there are nested structures.

  2. Function Details:

    • The function iterates through each key-value pair in the json_obj.
    • If the value associated with a key is a dictionary (dict), it recursively calls flatten_json with the value and updates the flattened dictionary.
    • If the value is a list (list), it iterates through each element (v) in the list, recursively flattening each element.
    • If the value is neither a dictionary nor a list, it adds it directly to the flattened dictionary with the new_key.

  3. Recursive Approach:

    • The function uses recursion to handle nested structures, ensuring that all levels of nesting are processed until all keys are at the top level.

Example Usage:

Consider a nested JSON object like this:

nested_json = { "name": "John", "age": 30, "address": { "city": "New York", "zipcode": "10001", "coordinates": { "latitude": 40.7128, "longitude": -74.0060 } }, "skills": ["Python", "JavaScript", "SQL"] }

Applying the flatten_json function to this object:

flattened_json = flatten_json(nested_json) print(flattened_json)

Output:

{ 'name': 'John', 'age': 30, 'address_city': 'New York', 'address_zipcode': '10001', 'address_coordinates_latitude': 40.7128, 'address_coordinates_longitude': -74.006, 'skills_0': 'Python', 'skills_1': 'JavaScript', 'skills_2': 'SQL' }

Notes:

  • Handling Lists: Lists are flattened with an index (_0, _1, etc.) appended to the key to maintain uniqueness.
  • Nested Structures: The function handles arbitrarily nested JSON structures using recursion.
  • Prefix: The optional prefix parameter allows customization of the key names in the flattened result.

This approach provides a flexible and recursive method to flatten nested JSON structures in Python, converting them into a format suitable for easy processing and analysis. Adjust the function as per your specific JSON structure and requirements.

Examples

  1. "Python flatten nested JSON with pandas"

    • Description: Use pandas to flatten a nested JSON structure into a DataFrame.
    • Code:
      import pandas as pd import json nested_json = { "name": "John", "address": { "city": "New York", "zip": "10001" }, "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] } df = pd.json_normalize(nested_json) print(df)

  2. "Flatten JSON using json_normalize"

    • Description: Utilize pandas' json_normalize function to flatten nested JSON.
    • Code:
      import pandas as pd import json nested_json = { "id": 1, "name": "Product", "details": { "manufacturer": "Company", "price": 100 }, "stock": { "warehouse": 50, "store": 20 } } df = pd.json_normalize(nested_json) print(df)

  3. "Flatten nested JSON with recursion in Python"

    • Description: Implement a recursive function to flatten nested JSON data.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if type(x) is dict: for a in x: flatten(x[a], name + a + '_') elif type(x) is list: i = 0 for a in x: flatten(a, name + str(i) + '_') i += 1 else: out[name[:-1]] = x flatten(y) return out nested_json = { "name": "John", "address": { "city": "New York", "zip": "10001" }, "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] } flat_json = flatten_json(nested_json) print(flat_json)

  4. "Flatten JSON with nested lists and dictionaries"

    • Description: Handle nested lists and dictionaries while flattening JSON.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if isinstance(x, dict): for a in x: flatten(x[a], name + a + '_') elif isinstance(x, list): for i, a in enumerate(x): flatten(a, name + str(i) + '_') else: out[name[:-1]] = x flatten(y) return out nested_json = { "employee": { "name": "John", "details": { "address": { "city": "New York", "zip": "10001" }, "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] } } } flat_json = flatten_json(nested_json) print(flat_json)

  5. "Using Python libraries to flatten JSON"

    • Description: Utilize json_flatten library to flatten a JSON structure.
    • Code:
      from flatten_json import flatten nested_json = { "user": { "name": "John", "details": { "address": { "city": "New York", "zip": "10001" }, "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] } } } flat_json = flatten(nested_json) print(flat_json)

  6. "Flatten JSON with complex nested structures"

    • Description: Flatten complex nested JSON structures with various depths.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if isinstance(x, dict): for a in x: flatten(x[a], name + a + '_') elif isinstance(x, list): for i, a in enumerate(x): flatten(a, name + str(i) + '_') else: out[name[:-1]] = x flatten(y) return out nested_json = { "user": { "id": 1, "name": "John", "details": { "contacts": { "email": "john@example.com", "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] }, "address": { "city": "New York", "zip": "10001" } } } } flat_json = flatten_json(nested_json) print(flat_json)

  7. "Flatten JSON with nested arrays in Python"

    • Description: Flatten JSON that contains nested arrays using a custom function.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if type(x) is dict: for a in x: flatten(x[a], name + a + '_') elif type(x) is list: i = 0 for a in x: flatten(a, name + str(i) + '_') i += 1 else: out[name[:-1]] = x flatten(y) return out nested_json = { "id": 1, "info": { "name": "John", "contacts": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] } } flat_json = flatten_json(nested_json) print(flat_json)

  8. "Flatten nested JSON with multiple levels"

    • Description: Flatten JSON with multiple levels of nesting using recursion.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if isinstance(x, dict): for a in x: flatten(x[a], name + a + '_') elif isinstance(x, list): for i, a in enumerate(x): flatten(a, name + str(i) + '_') else: out[name[:-1]] = x flatten(y) return out nested_json = { "person": { "name": "John", "details": { "contacts": { "email": "john@example.com", "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] }, "address": { "city": "New York", "zip": "10001" } } } } flat_json = flatten_json(nested_json) print(flat_json)

  9. "Flatten deeply nested JSON in Python"

    • Description: Handle deeply nested JSON structures with a flattening function.
    • Code:
      def flatten_json(y): out = {} def flatten(x, name=''): if isinstance(x, dict): for a in x: flatten(x[a], name + a + '_') elif isinstance(x, list): for i, a in enumerate(x): flatten(a, name + str(i) + '_') else: out[name[:-1]] = x flatten(y) return out nested_json = { "company": { "employee": { "name": "John", "details": { "contacts": { "email": "john@example.com", "phones": [ {"type": "home", "number": "212-555-1234"}, {"type": "work", "number": "646-555-4567"} ] }, "address": { "city": "New York", "zip": "10001" } } } } } flat_json = flatten_json(nested_json) print(flat_json)

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