bravado-types

Tool to generate MyPy type stubs for Bravado-generated classes to support static type checking.

Motivation

Bravado is a Python client library for interacting with APIs defined by Swagger 2.0 schemas. Bravado parses a given API schema at runtime and dynamically generates classes to represent the data types defined by the schema. This is a nice Pythonic approach, but it means that static type-checking tools like MyPy have limited ability to type-check code that uses Bravado since the attributes and method signatures of objects generated by Bravado are not known until runtime.

Bravado-types addresses this problem by pre-generating type information about the generated data for a given schema at build time. Using the generated type stubs, MyPy can statically detect errors such as calling a nonexistent operation method on a resource, failing to specify a required operation parameter, or assigning a wrongly-typed value to a model attribute. This allows for a much higher level of confidence in the correctness of code that uses Bravado clients than would otherwise be possible.

The validity of this approach relies on the assumption that the same version of the schema is used during code generation as at runtime. Without this assumption it is nearly impossible to make any useful assertions about the runtime behavior of generated clients.

Installation

pip install bravado-types

To install the latest master version directly from GitHub:

pip install -U git+https://github.com/nickgaya/bravado-types.git

Usage

Code generation

To start using bravado-types, invoke the CLI against your Swagger schema of choice:

bravado-types --url 'https://petstore.swagger.io/v2/swagger.json' \
    --name PetStore --path petstore.py

This command will download the PetStore example schema and generate a Python 3 module, petstore.py, along with a MyPy stub file petstore.pyi, for that schema. The generated module and stub file can then be used in your package. The generated code only depends on bravado, not on bravado-types, so you do not need to include the latter as a runtime package dependency.

Code generation can also be done programmatically.

from bravado import SwaggerClient
from bravado_types import Config, generate_module

client = SwaggerClient.from_url(
    "https://petstore.swagger.io/v2/swagger.json")
config = Config(name='PetStore', path='petstore.py')
generate_module(client, config)

Bravado-types supports several optional parameters to customize code generation. See the bravado_types.config.Config docstring or the CLI help output (bravado-types --help) for details.

Using the generated module

To create a type-aware client, import the relevant name from the generated module and use its from_url() or from_spec() method to create an instance.

from petstore import PetStoreSwaggerClient

client = PetStoreSwaggerClient.from_url(
    "https://petstore.swagger.io/v2/swagger.json")
reveal_type(client)  # petstore.PetStoreSwaggerClient

You can use the client like a regular Bravado client to instantiate model objects and make API calls with them.

Pet = client.get_model('Pet')
reveal_type(Pet)  # Type[petstore.PetModel]

frank = Pet(name='Frank', photoUrls=[])
reveal_type(frank)  # petstore.PetModel

pet123 = client.pet.getPetById(id=123).response().result
reveal_type(pet123)  # petstore.PetModel

The generated module also provides importable model, resource, and operation types for use in type annotations.

from petstore import PetModel

def get_name(pet: PetModel) -> str:
    reveal_type(pet)  # petstore.PetModel
    return pet.name

Generated model, resource, and operation types are only used for static type checking and must not be used for runtime interactions.

# Placeholder for static type-checking
from petstore import PetModel

# Use placeholder for type annotations and casts
pet: PetModel = ...
pet2 = typing.cast(PetModel, ...)

# Runtime model class
Pet = client.get_model('Pet')

# Use runtime class for model instantiation and runtime type checks
pet = Pet(name='Boots', photoUrls=[])
assert isinstance(pet, Pet)

Usage notes

Operation response types

Operations often have multiple different response schemas for different status codes, which presents an obstacle to static type analysis. Bravado-types offers three different options for response type annotations, specified by the response_types configuration parameter.

• 'success': The response type will be declared as the union of all response types with 2xx status. This is unsound, but may be useful if you are primarily concerned with responses when the request was successful.

• 'all': The response type will be declared as the union of all response types defined in the schema. This is probably the most correct but is cumbersome, as the developer must perform manual type checks or casts to obtain a useable type.

• 'any': The response type will be declared as Any. This gives maximum flexibility but requires the developer to manually add type hints if they want any type checking on the result of an operation.

By default, bravado-types uses the 'success' option as it is felt to be the most pragmatic option, although the least sound.

Array types

Bravado accepts either lists or tuples when marshaling values with type: array in the Swagger schema, and creates lists when unmarshaling. There are a few ways we could represent this in the type annotations:

• The most precise description would be Union[List[T], Tuple[T, ...]] but this is rather verbose and awkward.

• A less precise but more concise alternative is to use Sequence[T]. This has the downside that MyPy considers str a subtype of Sequence[str], which can lead to buggy code that passes type-checking but fails schema validation at runtime.

• A third alternative is to use only List[T] and forbid the use of tuples. This is overly restrictive, but leads to simpler annotated types.

By default, we use List[T] to represent array types, but this behavior can be overridden via the array_types configuration parameter.

User-defined formats

If using Bravado's user-defined formats feature, use the custom_formats configuration parameter to specify the python type for each user-defined format value in the schema, as well as any extra package imports required to resolve the type annotation.

For example, if you define a bravado_core.formatter.SwaggerFormat which converts values with type: string and format: ipv4 to ipaddress.IPv4Address objects, you should supply the following CLI flags to bravado-types to ensure the correct type annotations:

--custom-format string:ipv4:ipaddress.IPv4Address
--custom-format-package ipaddress

Bravado-types will emit warnings for unknown formats encountered while processing the schema.

Model inheritance

Swagger allows composing model definitions with the allOf schema property. This can be interpreted as a subclass relationship between models. Bravado implements this to some extent in its model metaclass, bravado_core.model.ModelMeta.

By default, bravado-types does not mirror this implied type hierarchy in its generated types. To enable this functionality, set the model_inheritance configuration parameter to True.

Additional model properties

Bravado-types does not currently support accessing or setting additional properties as attributes of model instances. If you need to set or access additional properties, you can use dict-like syntax instead.

For example, given this model schema...

x-model: APExample
type: object
additionalProperties:
  type: int

...you can add a property called "something" to a model instance like this:

model: APExampleModel
model['something'] = 123

MyPy will not type-check additional properties.

File parameters and responses

Bravado's handling of parameters and responses with type: file is complicated. This tool simply annotates such values with the Any type.

Development

This project uses Tox to manage virtual environments for unit tests and other self-checks. Unit tests are written with the Pytest framework.

Note: This project is not affiliated with Yelp or the Bravado project.