json-key-parser

You know the pattern. You get a response back from an API and you need three fields buried inside it. So you write response['data'][0]['user']['address']['city'], wrap it in a try/except because some records have the key and some don't, repeat for the next field, and suddenly you have twenty lines of boilerplate for what should be a one-liner. json-key-parser lets you declare the keys you want and hands them back — no traversal code, no try/excepts, no nested loops.

Quick Start

from json_parser import JsonParser

data = [{"first_name": "Alice", "last_name": "Smith", "birthday": "1990-04-15",
         "address": {"street": "12 Oak Ave", "city": "Portland", "zip": "97201"}},
        {"first_name": "Bob", "last_name": "Jones", "birthday": "1985-09-30",
         "address": {"street": "88 Pine St", "city": "Seattle", "zip": "98101"}}]

result = JsonParser(data, ["first_name", "last_name", "birthday"]).get_data()

Output:

[
    {
        "first_name": "Alice",
        "last_name": "Smith",
        "birthday": "1990-04-15"
    },
    {
        "first_name": "Bob",
        "last_name": "Jones",
        "birthday": "1985-09-30"
    }
]

Why json-key-parser?

• Declare keys, skip the traversal — one call replaces nested loops across every record
• Wildcard patterns — address* matches address, address1, address2, and any other variation
• Duplicate values merged automatically — no deduplication code needed when a key appears at multiple levels
• Works at any nesting depth — one level or ten, it finds the keys you asked for
• Zero dependencies — pure Python stdlib, nothing to pin or audit

Wildcard Matching

Using the same data from above, address* matches any key that starts with address:

result = JsonParser(data, ["address*"]).get_data()

Output:

[
    {
        "address": {
            "street": "12 Oak Ave",
            "city": "Portland",
            "zip": "97201"
        }
    },
    {
        "address": {
            "street": "88 Pine St",
            "city": "Seattle",
            "zip": "98101"
        }
    }
]

This is especially useful when records are inconsistently structured — one record might have address, another address1 and address2. The pattern catches all of them without needing to know which variant each record uses.

Duplicate Key Merging

When the same key appears at more than one nesting level inside a single record, the values are automatically combined into a list. No deduplication code required.

contacts = [
    {
        "first_name": "Alice",
        "address1": {"street": "12 Oak Ave", "city": "Portland"},
        "address2": {"street": "99 River Rd", "city": "Portland"}
    },
    {
        "first_name": "Bob",
        "address": {"street": "88 Pine St", "city": "Seattle"}
    }
]

result = JsonParser(contacts, ["first_name", "street"]).get_data()

Output:

[
    {
        "first_name": "Alice",
        "street": [
            "12 Oak Ave",
            "99 River Rd"
        ]
    },
    {
        "first_name": "Bob",
        "street": "88 Pine St"
    }
]

Alice has two addresses, so street becomes a list of both values. Bob has one address, so street stays a plain string. The shape matches the data — you don't have to handle it yourself.

Installation

pip install json-key-parser

License

MIT. See the LICENSE file for details.