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GenSON

GenSON is a powerful, user-friendly JSON Schema generator built in Python.

(Note: This is not to be confused with the Java Genson library. If you are coming from Java and looking for a Python equivalent, this is not it. You should instead look into Python's builtin json library.)

Its power comes from the ability to generate a single schema from multiple objects. You can also throw existing schemas into the mix. Basically, you can feed it as many schemas and objects as you want and it will spit out one, unified schema for them all.

The generator follows these three rules:

  1. Every object it is given must validate under the generated schema.
  2. Any object that is valid under any schema it is given must also validate under the generated schema.
  3. The generated schema should be as strict as possible given the first 2 rules.

JSON Schema Implementation

GenSON is a Draft 4 generator.

It is important to note that the generator uses only a small subset of JSON Schema's capabilities. This is mainly because the generator doesn't know the specifics of your data model, and it doesn't try to guess them. Its purpose is to generate the basic structure so that you can skip the boilerplate and focus on the details of the schema.

This means that headers and most keywords aren't dealt with. Specifically, the generator only deals with 4 keywords: "type", "items", "properties" and "required". You should be aware that this limited vocabulary could cause the generator to violate rules 1 and 2. If you feed it schemas with advanced keywords, it will just blindly pass them on to the final schema.

Installation

$ pip install genson

CLI Tool

The package includes a genson executable that allows you to access this functionality from the command line. For usage info, run with --help:

$ genson --help
usage: genson [-h] [-a] [-d DELIM] [-i SPACES] [-s SCHEMA] ...

Generate one, unified JSON Schema from one or more JSON objects and/or JSON
Schemas. (uses Draft 4 - http://json-schema.org/draft-04/schema)

positional arguments:
  object                files containing JSON objects (defaults to stdin if no
                        arguments are passed and the -s option is not present)

optional arguments:
  -h, --help            show this help message and exit
  -a, --no-merge-arrays
                        generate a different subschema for each element in an
                        array rather than merging them all into one
  -d DELIM, --delimiter DELIM
                        set a delimiter - Use this option if the input files
                        contain multiple JSON objects/schemas. You can pass
                        any string. A few cases ('newline', 'tab', 'space')
                        will get converted to a whitespace character, and if
                        empty string ('') is passed, the parser will try to
                        auto-detect where the boundary is.
  -i SPACES, --indent SPACES
                        pretty-print the output, indenting SPACES spaces
  -s SCHEMA, --schema SCHEMA
                        file containing a JSON Schema (can be specified
                        multiple times to merge schemas)

GenSON Python API

Schema is the basic schema generator class. Schema objects can be loaded up with existing schemas and objects before being serialized.

import genson

s = genson.Schema()
s.add_schema({"type": "object", "properties": {}})
s.add_object({"hi": "there"})
s.add_object({"hi": 5})

s.to_dict()
#=> {"type": "object", "properties": {"hi": {"type": ["integer", "string"]}}}

s.to_json()
#=> "{\"type\": \"object\", \"properties\": {\"hi\": {\"type\": [\"integer\", \"string\"]}}}"

Schema Object Methods

Schema(merge_arrays=True)

Builds a schema generator object.

arguments:

  • merge_arrays (default True): Assume all array items share the same schema (as they should). The alternate behavior is to merge schemas based on position in the array.

add_schema(schema)

Merges in an existing schema. Take care here because there is no schema validation. If you pass in a bad schema, you'll get back a bad schema.

arguments:

  • schema (required - dict or Schema): an existing JSON Schema to merge.

add_object(obj)

Modify the schema to accommodate an object.

arguments:

  • obj (required - dict): a JSON object to use in generating the schema.

to_dict()

Convert the current schema to a dict.

to_json()

Convert the current schema directly to serialized JSON.

Schema Object Interaction

Schema objects can also interact with each other:

  • You can pass one schema directly to another to merge them.
  • You can compare schema equality directly.
import genson

s1 = genson.Schema()
s1.add_schema({"type": "object", "properties": {"hi": {"type": "string"}}})

s2 = genson.Schema()
s2.add_schema({"type": "object", "properties": {"hi": {"type": "integer"}}})

s1 == s2
#=> False

s1.add_schema(s2)
s2.add_schema(s1)

s1 == s2
#=> True

s1.to_dict()
#=> {"type": "object", "properties": {"hi": {"type": ["integer", "string"]}}}

Compatibility

GenSON has been tested and verified using the following versions of Python:

  • Python 2.7.11
  • Python 3.3.5
  • Python 3.4.4
  • Python 3.5.1
  • Python 3.6.2

Contributing

When contributing, please follow these steps:

  1. Clone the repo and make your changes.
  2. Make sure your code has test cases written against it.
  3. Make sure all the tests pass.
  4. Lint your code with Flake8.
  5. Add your name to the list of contributers.
  6. Submit a Pull Request.

Tests

Tests are written in unittest. You can run them all easily with the included executable bin/test.py.

$ bin/test.py

You can also invoke individual test suites:

$ bin/test.py --test-suite test.test_gen_single