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import re
from collections import OrderedDict
from copy import deepcopy
from dataclasses import dataclass, field
from http import HTTPStatus
from typing import Any, Dict, Iterator, List, Optional, Set, Tuple, Union
import attr
from pydantic import ValidationError
from .. import schema as oai
from .. import utils
from ..config import Config
from ..utils import PythonIdentifier, get_content_type
from .errors import GeneratorError, ParseError, PropertyError
from .properties import (
Class,
EnumProperty,
ModelProperty,
Parameters,
Property,
Schemas,
build_parameters,
build_schemas,
property_from_data,
)
from .properties.schemas import parameter_from_reference
from .responses import Response, response_from_data
_PATH_PARAM_REGEX = re.compile("{([a-zA-Z_][a-zA-Z0-9_]*)}")
def import_string_from_class(class_: Class, prefix: str = "") -> str:
"""Create a string which is used to import a reference"""
return f"from {prefix}.{class_.module_name} import {class_.name}"
@dataclass
class EndpointCollection:
"""A bunch of endpoints grouped under a tag that will become a module"""
tag: str
endpoints: List["Endpoint"] = field(default_factory=list)
parse_errors: List[ParseError] = field(default_factory=list)
@staticmethod
def from_data(
*, data: Dict[str, oai.PathItem], schemas: Schemas, parameters: Parameters, config: Config
) -> Tuple[Dict[utils.PythonIdentifier, "EndpointCollection"], Schemas, Parameters]:
"""Parse the openapi paths data to get EndpointCollections by tag"""
endpoints_by_tag: Dict[utils.PythonIdentifier, EndpointCollection] = {}
methods = ["get", "put", "post", "delete", "options", "head", "patch", "trace"]
for path, path_data in data.items():
for method in methods:
operation: Optional[oai.Operation] = getattr(path_data, method)
if operation is None:
continue
tag = utils.PythonIdentifier(value=(operation.tags or ["default"])[0], prefix="tag")
collection = endpoints_by_tag.setdefault(tag, EndpointCollection(tag=tag))
endpoint, schemas, parameters = Endpoint.from_data(
data=operation,
path=path,
method=method,
tag=tag,
schemas=schemas,
parameters=parameters,
config=config,
)
# Add `PathItem` parameters
if not isinstance(endpoint, ParseError):
endpoint, schemas, parameters = Endpoint.add_parameters(
endpoint=endpoint, data=path_data, schemas=schemas, parameters=parameters, config=config
)
if not isinstance(endpoint, ParseError):
endpoint = Endpoint.sort_parameters(endpoint=endpoint)
if isinstance(endpoint, ParseError):
endpoint.header = (
f"WARNING parsing {method.upper()} {path} within {tag}. Endpoint will not be generated."
)
collection.parse_errors.append(endpoint)
continue
for error in endpoint.errors:
error.header = f"WARNING parsing {method.upper()} {path} within {tag}."
collection.parse_errors.append(error)
collection.endpoints.append(endpoint)
return endpoints_by_tag, schemas, parameters
def generate_operation_id(*, path: str, method: str) -> str:
"""Generate an operationId from a path"""
clean_path = path.replace("{", "").replace("}", "").replace("/", "_")
if clean_path.startswith("_"):
clean_path = clean_path[1:]
if clean_path.endswith("_"):
clean_path = clean_path[:-1]
return f"{method}_{clean_path}"
models_relative_prefix: str = "..."
# pylint: disable=too-many-instance-attributes
@dataclass
class Endpoint:
"""
Describes a single endpoint on the server
"""
data: oai.Operation
path: str
method: str
description: Optional[str]
name: str
requires_security: bool
tag: str
summary: Optional[str] = ""
relative_imports: Set[str] = field(default_factory=set)
query_parameters: Dict[str, Property] = field(default_factory=dict)
path_parameters: "OrderedDict[str, Property]" = field(default_factory=OrderedDict)
header_parameters: Dict[str, Property] = field(default_factory=dict)
cookie_parameters: Dict[str, Property] = field(default_factory=dict)
responses: List[Response] = field(default_factory=list)
form_body: Optional[Property] = None
json_body: Optional[Property] = None
multipart_body: Optional[Property] = None
errors: List[ParseError] = field(default_factory=list)
used_python_identifiers: Set[PythonIdentifier] = field(default_factory=set)
@staticmethod
def parse_request_form_body(
*, body: oai.RequestBody, schemas: Schemas, parent_name: str, config: Config
) -> Tuple[Union[Property, PropertyError, None], Schemas]:
"""Return form_body and updated schemas"""
body_content = body.content
form_body = body_content.get("application/x-www-form-urlencoded")
if form_body is not None and form_body.media_type_schema is not None:
prop, schemas = property_from_data(
name="data",
required=True,
data=form_body.media_type_schema,
schemas=schemas,
parent_name=parent_name,
config=config,
)
if isinstance(prop, ModelProperty):
schemas = attr.evolve(schemas, classes_by_name={**schemas.classes_by_name, prop.class_info.name: prop})
return prop, schemas
return None, schemas
@staticmethod
def parse_multipart_body(
*, body: oai.RequestBody, schemas: Schemas, parent_name: str, config: Config
) -> Tuple[Union[Property, PropertyError, None], Schemas]:
"""Return multipart_body"""
body_content = body.content
multipart_body = body_content.get("multipart/form-data")
if multipart_body is not None and multipart_body.media_type_schema is not None:
prop, schemas = property_from_data(
name="multipart_data",
required=True,
data=multipart_body.media_type_schema,
schemas=schemas,
parent_name=parent_name,
config=config,
)
if isinstance(prop, ModelProperty):
prop = attr.evolve(prop, is_multipart_body=True)
schemas = attr.evolve(schemas, classes_by_name={**schemas.classes_by_name, prop.class_info.name: prop})
return prop, schemas
return None, schemas
@staticmethod
def parse_request_json_body(
*, body: oai.RequestBody, schemas: Schemas, parent_name: str, config: Config
) -> Tuple[Union[Property, PropertyError, None], Schemas]:
"""Return json_body"""
json_body = None
for content_type, schema in body.content.items():
content_type = get_content_type(content_type)
if content_type == "application/json" or content_type.endswith("+json"):
json_body = schema
break
if json_body is not None and json_body.media_type_schema is not None:
return property_from_data(
name="json_body",
required=True,
data=json_body.media_type_schema,
schemas=schemas,
parent_name=parent_name,
config=config,
)
return None, schemas
@staticmethod
def _add_body(
*,
endpoint: "Endpoint",
data: oai.Operation,
schemas: Schemas,
config: Config,
) -> Tuple[Union[ParseError, "Endpoint"], Schemas]:
"""Adds form or JSON body to Endpoint if included in data"""
endpoint = deepcopy(endpoint)
if data.requestBody is None or isinstance(data.requestBody, oai.Reference):
return endpoint, schemas
form_body, schemas = Endpoint.parse_request_form_body(
body=data.requestBody, schemas=schemas, parent_name=endpoint.name, config=config
)
if isinstance(form_body, ParseError):
return (
ParseError(
header=f"Cannot parse form body of endpoint {endpoint.name}",
detail=form_body.detail,
data=form_body.data,
),
schemas,
)
json_body, schemas = Endpoint.parse_request_json_body(
body=data.requestBody, schemas=schemas, parent_name=endpoint.name, config=config
)
if isinstance(json_body, ParseError):
return (
ParseError(
header=f"Cannot parse JSON body of endpoint {endpoint.name}",
detail=json_body.detail,
data=json_body.data,
),
schemas,
)
multipart_body, schemas = Endpoint.parse_multipart_body(
body=data.requestBody, schemas=schemas, parent_name=endpoint.name, config=config
)
if isinstance(multipart_body, ParseError):
return (
ParseError(
header=f"Cannot parse multipart body of endpoint {endpoint.name}",
detail=multipart_body.detail,
data=multipart_body.data,
),
schemas,
)
# No reasons to use lazy imports in endpoints, so add lazy imports to relative here.
if form_body is not None:
endpoint.form_body = form_body
endpoint.relative_imports.update(endpoint.form_body.get_imports(prefix=models_relative_prefix))
endpoint.relative_imports.update(endpoint.form_body.get_lazy_imports(prefix=models_relative_prefix))
if multipart_body is not None:
endpoint.multipart_body = multipart_body
endpoint.relative_imports.update(endpoint.multipart_body.get_imports(prefix=models_relative_prefix))
endpoint.relative_imports.update(endpoint.multipart_body.get_lazy_imports(prefix=models_relative_prefix))
if json_body is not None:
endpoint.json_body = json_body
endpoint.relative_imports.update(endpoint.json_body.get_imports(prefix=models_relative_prefix))
endpoint.relative_imports.update(endpoint.json_body.get_lazy_imports(prefix=models_relative_prefix))
return endpoint, schemas
@staticmethod
def _add_responses(
*, endpoint: "Endpoint", data: oai.Responses, schemas: Schemas, config: Config
) -> Tuple["Endpoint", Schemas]:
endpoint = deepcopy(endpoint)
for code, response_data in data.items():
status_code: HTTPStatus
try:
status_code = HTTPStatus(int(code))
except ValueError:
endpoint.errors.append(
ParseError(
detail=(
f"Invalid response status code {code} (not a valid HTTP "
f"status code), response will be ommitted from generated "
f"client"
)
)
)
continue
response, schemas = response_from_data(
status_code=status_code, data=response_data, schemas=schemas, parent_name=endpoint.name, config=config
)
if isinstance(response, ParseError):
detail_suffix = "" if response.detail is None else f" ({response.detail})"
endpoint.errors.append(
ParseError(
detail=(
f"Cannot parse response for status code {status_code}{detail_suffix}, "
f"response will be ommitted from generated client"
),
data=response.data,
)
)
continue
# No reasons to use lazy imports in endpoints, so add lazy imports to relative here.
endpoint.relative_imports |= response.prop.get_lazy_imports(prefix=models_relative_prefix)
endpoint.relative_imports |= response.prop.get_imports(prefix=models_relative_prefix)
endpoint.responses.append(response)
return endpoint, schemas
# pylint: disable=too-many-return-statements
@staticmethod
def add_parameters(
*,
endpoint: "Endpoint",
data: Union[oai.Operation, oai.PathItem],
schemas: Schemas,
parameters: Parameters,
config: Config,
) -> Tuple[Union["Endpoint", ParseError], Schemas, Parameters]:
"""Process the defined `parameters` for an Endpoint.
Any existing parameters will be ignored, so earlier instances of a parameter take precedence. PathItem
parameters should therefore be added __after__ operation parameters.
Args:
endpoint: The endpoint to add parameters to.
data: The Operation or PathItem to add parameters from.
schemas: The cumulative Schemas of processing so far which should contain details for any references.
parameters: The cumulative Parameters of processing so far which should contain details for any references.
config: User-provided config for overrides within parameters.
Returns:
`(result, schemas, parameters)` where `result` is either an updated Endpoint containing the parameters or a
ParseError describing what went wrong. `schemas` is an updated version of the `schemas` input, adding any
new enums or classes. `parameters` is an updated version of the `parameters` input, adding new parameters.
See Also:
- https://swagger.io/docs/specification/describing-parameters/
- https://swagger.io/docs/specification/paths-and-operations/
"""
# pylint: disable=too-many-branches, too-many-locals
# There isn't much value in breaking down this function further other than to satisfy the linter.
if data.parameters is None:
return endpoint, schemas, parameters
endpoint = deepcopy(endpoint)
unique_parameters: Set[Tuple[str, oai.ParameterLocation]] = set()
parameters_by_location = {
oai.ParameterLocation.QUERY: endpoint.query_parameters,
oai.ParameterLocation.PATH: endpoint.path_parameters,
oai.ParameterLocation.HEADER: endpoint.header_parameters,
oai.ParameterLocation.COOKIE: endpoint.cookie_parameters,
}
for param in data.parameters:
# Obtain the parameter from the reference or just the parameter itself
param_or_error = parameter_from_reference(param=param, parameters=parameters)
if isinstance(param_or_error, ParseError):
return param_or_error, schemas, parameters
param = param_or_error
if param.param_schema is None:
continue
unique_param = (param.name, param.param_in)
if unique_param in unique_parameters:
return (
ParseError(
data=data,
detail=(
"Parameters MUST NOT contain duplicates. "
"A unique parameter is defined by a combination of a name and location. "
f"Duplicated parameters named `{param.name}` detected in `{param.param_in}`."
),
),
schemas,
parameters,
)
unique_parameters.add(unique_param)
# In OpenAPI specification both of a parameter, and its schema, may optionally have a description.
# openapi-python-client only uses the schema description for the parameter, so if
# the schema does not have a description we will supply the parameter's description instead.
if isinstance(param.param_schema, oai.Schema) and param.param_schema.description is None:
param.param_schema.description = param.description
prop, new_schemas = property_from_data(
name=param.name,
required=param.required,
data=param.param_schema,
schemas=schemas,
parent_name=endpoint.name,
config=config,
)
if isinstance(prop, ParseError):
return (
ParseError(detail=f"cannot parse parameter of endpoint {endpoint.name}", data=prop.data),
schemas,
parameters,
)
schemas = new_schemas
location_error = prop.validate_location(param.param_in)
if location_error is not None:
location_error.data = param
return location_error, schemas, parameters
if prop.name in parameters_by_location[param.param_in]:
# This parameter was defined in the Operation, so ignore the PathItem definition
continue
for location, parameters_dict in parameters_by_location.items():
if location == param.param_in or prop.name not in parameters_dict:
continue
existing_prop: Property = parameters_dict[prop.name]
# Existing should be converted too for consistency
endpoint.used_python_identifiers.remove(existing_prop.python_name)
existing_prop.set_python_name(new_name=f"{existing_prop.name}_{location}", config=config)
if existing_prop.python_name in endpoint.used_python_identifiers:
return (
ParseError(
detail=f"Parameters with same Python identifier `{existing_prop.python_name}` detected",
data=data,
),
schemas,
parameters,
)
endpoint.used_python_identifiers.add(existing_prop.python_name)
prop.set_python_name(new_name=f"{param.name}_{param.param_in}", config=config)
if prop.python_name in endpoint.used_python_identifiers:
return (
ParseError(
detail=f"Parameters with same Python identifier `{prop.python_name}` detected", data=data
),
schemas,
parameters,
)
if param.param_in == oai.ParameterLocation.QUERY and (prop.nullable or not prop.required):
# There is no NULL for query params, so nullable and not required are the same.
prop = attr.evolve(prop, required=False, nullable=True)
# No reasons to use lazy imports in endpoints, so add lazy imports to relative here.
endpoint.relative_imports.update(prop.get_lazy_imports(prefix=models_relative_prefix))
endpoint.relative_imports.update(prop.get_imports(prefix=models_relative_prefix))
endpoint.used_python_identifiers.add(prop.python_name)
parameters_by_location[param.param_in][prop.name] = prop
return endpoint, schemas, parameters
@staticmethod
def sort_parameters(*, endpoint: "Endpoint") -> Union["Endpoint", ParseError]:
"""
Sorts the path parameters of an `endpoint` so that they match the order declared in `endpoint.path`.
Args:
endpoint: The endpoint to sort the parameters of.
Returns:
Either an updated `endpoint` with sorted path parameters or a `ParseError` if something was wrong with
the path parameters and they could not be sorted.
"""
endpoint = deepcopy(endpoint)
parameters_from_path = re.findall(_PATH_PARAM_REGEX, endpoint.path)
try:
sorted_params = sorted(
endpoint.path_parameters.values(), key=lambda param: parameters_from_path.index(param.name)
)
endpoint.path_parameters = OrderedDict((param.name, param) for param in sorted_params)
except ValueError:
pass # We're going to catch the difference down below
if parameters_from_path != list(endpoint.path_parameters):
return ParseError(
detail=f"Incorrect path templating for {endpoint.path} (Path parameters do not match with path)",
)
return endpoint
@staticmethod
def from_data(
*,
data: oai.Operation,
path: str,
method: str,
tag: str,
schemas: Schemas,
parameters: Parameters,
config: Config,
) -> Tuple[Union["Endpoint", ParseError], Schemas, Parameters]:
"""Construct an endpoint from the OpenAPI data"""
if data.operationId is None:
name = generate_operation_id(path=path, method=method)
else:
name = data.operationId
endpoint = Endpoint(
path=path,
method=method,
summary=utils.remove_string_escapes(data.summary) if data.summary else "",
description=utils.remove_string_escapes(data.description) if data.description else "",
name=name,
requires_security=bool(data.security),
tag=tag,
data=data,
)
result, schemas, parameters = Endpoint.add_parameters(
endpoint=endpoint, data=data, schemas=schemas, parameters=parameters, config=config
)
if isinstance(result, ParseError):
return result, schemas, parameters
result, schemas = Endpoint._add_responses(endpoint=result, data=data.responses, schemas=schemas, config=config)
result, schemas = Endpoint._add_body(endpoint=result, data=data, schemas=schemas, config=config)
return result, schemas, parameters
def response_type(self) -> str:
"""Get the Python type of any response from this endpoint"""
types = sorted({response.prop.get_type_string(quoted=False) for response in self.responses})
if len(types) == 0:
return "Any"
if len(types) == 1:
return self.responses[0].prop.get_type_string(quoted=False)
return f"Union[{', '.join(types)}]"
def iter_all_parameters(self) -> Iterator[Property]:
"""Iterate through all the parameters of this endpoint"""
yield from self.path_parameters.values()
yield from self.query_parameters.values()
yield from self.header_parameters.values()
yield from self.cookie_parameters.values()
if self.multipart_body:
yield self.multipart_body
if self.json_body:
yield self.json_body
def list_all_parameters(self) -> List[Property]:
"""Return a List of all the parameters of this endpoint"""
return list(self.iter_all_parameters())
@dataclass
class GeneratorData:
"""All the data needed to generate a client"""
title: str
description: Optional[str]
version: str
models: Iterator[ModelProperty]
errors: List[ParseError]
endpoint_collections_by_tag: Dict[utils.PythonIdentifier, EndpointCollection]
enums: Iterator[EnumProperty]
@staticmethod
def from_dict(data: Dict[str, Any], *, config: Config) -> Union["GeneratorData", GeneratorError]:
"""Create an OpenAPI from dict"""
try:
openapi = oai.OpenAPI.parse_obj(data)
except ValidationError as err:
detail = str(err)
if "swagger" in data:
detail = (
"You may be trying to use a Swagger document; this is not supported by this project.\n\n" + detail
)
return GeneratorError(header="Failed to parse OpenAPI document", detail=detail)
schemas = Schemas()
parameters = Parameters()
if openapi.components and openapi.components.schemas:
schemas = build_schemas(components=openapi.components.schemas, schemas=schemas, config=config)
if openapi.components and openapi.components.parameters:
parameters = build_parameters(components=openapi.components.parameters, parameters=parameters)
endpoint_collections_by_tag, schemas, parameters = EndpointCollection.from_data(
data=openapi.paths, schemas=schemas, parameters=parameters, config=config
)
enums = (prop for prop in schemas.classes_by_name.values() if isinstance(prop, EnumProperty))
models = (prop for prop in schemas.classes_by_name.values() if isinstance(prop, ModelProperty))
return GeneratorData(
title=openapi.info.title,
description=openapi.info.description,
version=openapi.info.version,
endpoint_collections_by_tag=endpoint_collections_by_tag,
models=models,
errors=schemas.errors + parameters.errors,
enums=enums,
)