jsonobjectify

A lightweight Python library for converting JSON data into Python objects, simplifying access to nested structures through dot notation. Instead of writing chained dictionary lookups, you can navigate nested JSON structures using a clean, readable, object-oriented interface.

Installation

pip install jsonobjectify

Usage

Consider the following JSON data representing an employee and their department:

response = """{
    "id": 1,
    "name": "John Doe",
    "email": "john.doe@example.com",
    "website": "www.example.dev",
    "address": {
      "city": "Austin",
      "state": "TX",
      "country": "United States",
      "geo_location": {"lat": "30.2672", "lng": "-97.7431"}
    },
    "skills": [
      {"name": "Python", "level": "Advanced"},
      {"name": "C", "level": "Advanced"},
      {"name": "C++", "level": "Intermediate"}
    ]
}"""

Create JsonPath object from JSON string.

Here, response is a string containing valid JSON. The from_string class method parses the JSON data and creates a JsonPath object that allows you to access properties using dot notation.

>>> employee = JsonPath.from_string(response)

You can now access and traverse nested JSON objects using dot notation. For JSON arrays, use the standard Python indexing syntax.

>>> employee.name
'John Doe'
>>> employee.address.city
'Austin'
>>> employee.address.geo_location.lng
'-97.7431'
>>> employee.skills[0].name
'Python'
>>> employee.skills[1].level
'Advanced'
>>>

You can also iterate over JSON arrays using a standard Python for loop and access each element's properties using dot notation.

>>> for skill in employee.skills:
...     print(f"{skill.name}, {skill.level}")
...     
Python, Advanced
C, Advanced
C++, Intermediate
>>> 

Root response is an array of JSON objects

A JSON response can contain an array of objects at the root level. You can use JsonPath.from_string to parse the response and access each object's properties using dot notation.

response = """[
  {
    "name": "Olivia Bennett",
    "email": "olivia.bennett@example.com",
    "website": "www.example.dev"
  },
  {
    "name": "Ethan Parker",
    "email": "ethan.parker@example.com",
    "website": "www.example.io"
  },
  {
    "name": "Sophia Turner",
    "email": "sophia.turner@example.com",
    "website": "www.example.edu"
  }
]"""

>>> employees = JsonPath.from_string(response)
>>> employees[0]
<jsonobjectify.jsonobject.JsonObject object at 0x101bb7d50>
>>> employees[1]
<jsonobjectify.jsonobject.JsonObject object at 0x101bb7b50>
>>> employees[2]
<jsonobjectify.jsonobject.JsonObject object at 0x101aa2120>
>>> employees[0].name
'Olivia Bennett'
>>> employees[0].email
'olivia.bennett@example.com'
>>> employees[0].website
'www.example.dev'
>>> 

You can also iterate over JSON arrays using a standard Python for loop and access each element's properties using dot notation.

>>> for employee in employees:
...     print(f"{employee.name}, {employee.email}, {employee.website}")
...     
Olivia Bennett, olivia.bennett@example.com, www.example.dev
Ethan Parker, ethan.parker@example.com, www.example.io
Sophia Turner, sophia.turner@example.com, www.example.edu
>>> 

Create a JsonPath object from a JSON file

You can also create a JsonPath object directly from a JSON file using the from_file class method. This allows you to work with JSON data stored in a file without having to read and parse its contents manually.

For example, consider an employee.json file containing the employee data shown in the previous example.

>>> employee = JsonPath.from_file("employee.json")

Once the object is created, you can access nested properties and iterate over JSON arrays in the same way

>>> employee.name
'Michael Anderson'
>>> employee.address.city
'Austin'
>>> for skill in employee.skills:
...     print(f"{skill.name}, {skill.level}")
...
Python, Advanced
C, Advanced
C++, Intermediate

Working with Scalar Values

If the root JSON value is a scalar, such as a string, number, boolean or null, you can access the underlying value using the value property.

>>> data = JsonPath.from_string("26")
>>> data.value
26
>>> data = JsonPath.from_string("true")
>>> data.value
True
>>> data = JsonPath.from_string("null")
>>> data.value
>>>
>>> json = JsonPath.from_string('"hello world"')
>>> json.value
'hello world'

Accessing JSON Properties with Normalized Keys

JSON property names may contain hyphens, spaces, or periods, which cannot be used directly in Python attribute names. jsonobjectify normalizes these characters to underscores, allowing you to access such properties using dot notation.

response = """{
  "first-name": "Olivia",
  "job title": "Software Engineer",
  "contact.email": "olivia@example.com"
}"""

>>> employee = JsonPath.from_string(response)

You can access these properties using normalized attribute names,

>>> employee.first_name
'Olivia'
>>> employee.job_title
'Software Engineer'
>>> employee.contact_email
'olivia@example.com'

The original JSON property names are preserved when converting the object back to a dictionary or JSON string.

Converting Objects Back to JSON

jsonobjectify is intended to support conversion back to standard Python dictionaries and JSON strings, making it convenient to work with transformed data.

# Convert the object to a Python dictionary
data = employee.to_dict()

# Serialize the object to a JSON string
json_data = employee.to_json()

Requirements

• Python 3.12 or later

Contributing

Contributions, bug reports, and feature suggestions are welcome. Please open an issue to discuss a proposed change before submitting a pull request.

License

This package is distributed under the terms of MIT license