Master JSON API Testing in Python: 10 Essential Scenarios

1. Parse JSON from an API

Retrieve a JSON string from an endpoint, decode it with json.loads, and assert that a specific key holds the expected value.

import requests
import json

def test_parse_json():
    url = "https://api.example.com/data"
    response = requests.get(url)
    data = json.loads(response.text)
    assert data["key"] == "value"

Result: PASSED

2. Build a JSON object for POST

Create a Python dictionary, serialize it with json.dumps, set the appropriate Content-Type header, and send it as the request body.

import requests
import json

def test_build_json():
    url = "https://api.example.com/data"
    data = {"key": "value"}
    headers = {"Content-Type": "application/json"}
    response = requests.post(url, data=json.dumps(data), headers=headers)
    assert response.status_code == 201

Result: PASSED

3. Validate JSON structure

Fetch JSON from an API and verify that required fields and nested values exist.

import requests
import json

def test_validate_structure():
    url = "https://api.example.com/data"
    response = requests.get(url)
    data = json.loads(response.text)
    assert "key" in data and "value" in data["nested"]

Result: PASSED

4. Update a JSON field with PUT

Modify a field in the JSON payload and send it via a PUT request.

import requests
import json

def test_update_json():
    url = "https://api.example.com/data"
    data = {"key": "new_value"}
    headers = {"Content-Type": "application/json"}
    response = requests.put(url, data=json.dumps(data), headers=headers)
    assert response.status_code == 200

Result: PASSED

5. Delete a JSON field with PATCH

Mark a field for removal by setting its value to None and send a PATCH request.

import requests
import json

def test_delete_json_field():
    url = "https://api.example.com/data"
    data = {"key": None}  # mark field for deletion
    headers = {"Content-Type": "application/json"}
    response = requests.patch(url, data=json.dumps(data), headers=headers)
    assert response.status_code == 200

Result: PASSED

6. Handle nested JSON

Retrieve a JSON payload containing nested objects and assert a deep‑level value.

import requests
import json

def test_nested_json():
    url = "https://api.example.com/data"
    response = requests.get(url)
    data = json.loads(response.text)
    assert data["nested"]["sub_key"] == "sub_value"

Result: PASSED

7. Iterate over a JSON array

Loop through an array of objects inside the JSON response and verify each object contains required fields.

import requests
import json

def test_iterate_json_array():
    url = "https://api.example.com/data"
    response = requests.get(url)
    data = json.loads(response.text)
    for item in data["items"]:
        assert "name" in item and "value" in item

Result: PASSED

8. Serialize dates in JSON

Define a custom JSONEncoder that converts datetime objects to ISO‑8601 strings, then post the payload.

import requests
import json
from datetime import datetime

class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

def test_serialize_date():
    url = "https://api.example.com/data"
    data = {"timestamp": datetime.now()}
    headers = {"Content-Type": "application/json"}
    response = requests.post(url, data=json.dumps(data, cls=DateTimeEncoder), headers=headers)
    assert response.status_code == 201

Result: PASSED

9. Convert between JSON and Python dict

Demonstrate round‑trip conversion: dict → JSON string → dict, confirming equality.

import json

def test_json_dict_conversion():
    data = {"key": "value"}
    json_str = json.dumps(data)
    parsed_data = json.loads(json_str)
    assert data == parsed_data

Result: PASSED

10. Validate JSON with jsonschema

Use the jsonschema library to ensure a JSON payload conforms to a predefined schema.

import requests
import json
import jsonschema

def test_json_schema_validation():
    url = "https://api.example.com/data"
    response = requests.get(url)
    data = json.loads(response.text)
    schema = {
        "type": "object",
        "properties": {
            "key": {"type": "string"},
            "nested": {"type": "object", "properties": {"sub_key": {"type": "string"}}}
        },
        "required": ["key", "nested"]
    }
    jsonschema.validate(instance=data, schema=schema)

Result: PASSED