flatson 0.1.0

Tool to flatten stream of JSON-like objects, configured via schema

A tool to flatten JSON-like objects, allowing to configure via an annotated JSON schema

• Free software: BSD license

• Documentation: https://flatson.readthedocs.org.

Features

• Flattens Python dictionaries using a JSON schema

• Supports per-field configuration via the schema

Usage:

>>> from flatson import Flatson
>>> schema = {
        "$schema": "http://json-schema.org/draft-04/schema",
        "type": "object",
        "properties": {
            "name": {"type": "string"},
            "age": {"type": "number"},
            "address": {
                "type": "object",
                "properties": {"city": {"type": "string"}, "street": {"type": "string"}}
            },
            "skills": {"type": "array", "items": {"type": "string"}}
        }
    }
>>> sample = {
            "name": "Claudio", "age": 42,
            "address": {"city": "Paris", "street": "Rue de Sevres"},
            "skills": ["hacking", "soccer"]}
>>> f = Flatson(schema)
>>> f.fieldnames
['address.city', 'address.street', 'age', 'name', 'skills']
>>> f.flatten(sample)
['Paris', 'Rue de Sevres', 42, 'Claudio', '["hacking","soccer"]']

You can get a dict with the field names order preserved:

>>> f.flatten_dict(sample)
OrderedDict([('address.city', 'Paris'), ('address.street', 'Rue de Sevres'), ('age', 42), ('name', 'Claudio'), ('skills', '["hacking","soccer"]')])

You can also configure array serialization behavior through the schema (default JSON):

>>> schema = {
        "$schema": "http://json-schema.org/draft-04/schema",
        "type": "object",
        "properties": {
            "name": {"type": "string"},
            "skills": {
                "type": "array",
                "items": {"type": "string"},
                "flatson_serialize": {"method": "join_values"},
            }
        }
    }
>>> f = Flatson(schema)
>>> f.flatten({"name": "Salazar", "skills": ["hacking", "socker", "partying"]})
['Salazar', 'hacking,socker,partying']

History

0.1.0 (2015-06-02)

• First release on PyPI.