A powerful, user-friendly JSON Schema generator.
Project description
GenSON
GenSON (rhymes with Gen Con) is a powerful, user-friendly JSON Schema generator built in Python.
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:
Every object it is given must validate under the generated schema.
Any object that is valid under any schema it is given must also validate under the generated schema.
The generated schema should be as strict as possible given the first 2 rules.
JSON Schema Implementation
GenSON is a Draft 4 generator. Draft 3 support may come in the future.
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.
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 mutliple 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 items in an array share the same schema. The alternate behavior is to create a different schema for each item in an array, only consolidating identical ones.
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"]}}}
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 run any test file directly:
$ python test/test_gen_single.py
TODO
Validation for add_schema
Headers
Support for JSON Schema Draft 3
History
0.1.0 (2014-11-29)
Initial release.
Credits
GenSON is written and maintained by Jon Wolverton.
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