import re

from copy import deepcopy

from dataclasses import dataclass, field

from http import HTTPStatus

from typing import Any, Dict, Iterator, List, Optional, Protocol, Set, Tuple, Union

from pydantic import ValidationError

from .. import schema as oai

from .. import utils

from ..config import Config

from ..utils import PythonIdentifier

from .bodies import Body, body_from_data

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 = "..."

class RequestBodyParser(Protocol):

__name__: str = "RequestBodyParser"

def __call__(

self, *, body: oai.RequestBody, schemas: Schemas, parent_name: str, config: Config

) -> Tuple[Union[Property, PropertyError, None], Schemas]: ... # pragma: no cover

@dataclass

class Endpoint:

"""

Describes a single endpoint on the server

"""

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: List[Property] = field(default_factory=list)

path_parameters: List[Property] = field(default_factory=list)

header_parameters: List[Property] = field(default_factory=list)

cookie_parameters: List[Property] = field(default_factory=list)

responses: List[Response] = field(default_factory=list)

bodies: List[Body] = field(default_factory=list)

errors: List[ParseError] = field(default_factory=list)

@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

@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/

"""

# 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: Dict[str, List[Property]] = {

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 # noqa: PLW2901

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)

if any(

other_param for other_param in parameters_by_location[param.param_in] if other_param.name == param.name

):

# Defined at the operation level, ignore it here

continue

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}: {prop.detail}",

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

# 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))

parameters_by_location[param.param_in].append(prop)

return endpoint._check_parameters_for_conflicts(config=config), schemas, parameters

def _check_parameters_for_conflicts(

self,

*,

config: Config,

previously_modified_params: Optional[Set[Tuple[oai.ParameterLocation, str]]] = None,

) -> Union["Endpoint", ParseError]:

"""Check for conflicting parameters

For parameters that have the same python_name but are in different locations, append the location to the

python_name. For parameters that have the same name but are in the same location, use their raw name without

snake casing instead.

Function stops when there's a conflict that can't be resolved or all parameters are guaranteed to have a

unique python_name.

"""

modified_params = previously_modified_params or set()

used_python_names: Dict[PythonIdentifier, Tuple[oai.ParameterLocation, Property]] = {}

reserved_names = ["client", "url"]

for parameter in self.iter_all_parameters():

location, prop = parameter

if prop.python_name in reserved_names:

prop.set_python_name(new_name=f"{prop.python_name}_{location}", config=config)

modified_params.add((location, prop.name))

continue

conflicting = used_python_names.pop(prop.python_name, None)

if conflicting is None:

used_python_names[prop.python_name] = parameter

continue

conflicting_location, conflicting_prop = conflicting

if (conflicting_location, conflicting_prop.name) in modified_params or (

location,

prop.name,

) in modified_params:

return ParseError(

detail=f"Parameters with same Python identifier {conflicting_prop.python_name} detected",

)

if location != conflicting_location:

conflicting_prop.set_python_name(

new_name=f"{conflicting_prop.python_name}_{conflicting_location}", config=config

)

prop.set_python_name(new_name=f"{prop.python_name}_{location}", config=config)

elif conflicting_prop.name != prop.name: # Use the name to differentiate

conflicting_prop.set_python_name(new_name=conflicting_prop.name, config=config, skip_snake_case=True)

prop.set_python_name(new_name=prop.name, config=config, skip_snake_case=True)

modified_params.add((location, conflicting_prop.name))

modified_params.add((conflicting_location, conflicting_prop.name))

used_python_names[prop.python_name] = parameter

used_python_names[conflicting_prop.python_name] = conflicting

if len(modified_params) > 0 and modified_params != previously_modified_params:

return self._check_parameters_for_conflicts(config=config, previously_modified_params=modified_params)

return self

@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:

endpoint.path_parameters.sort(

key=lambda param: parameters_from_path.index(param.name),

)

except ValueError:

pass # We're going to catch the difference down below

if parameters_from_path != [param.name for param in 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,

)

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)

if isinstance(result, ParseError):

return result, schemas, parameters

bodies, schemas = body_from_data(data=data, schemas=schemas, config=config, endpoint_name=result.name)

body_errors = []

for body in bodies:

if isinstance(body, ParseError):

body_errors.append(body)

continue

result.bodies.append(body)

result.relative_imports.update(body.prop.get_imports(prefix=models_relative_prefix))

result.relative_imports.update(body.prop.get_lazy_imports(prefix=models_relative_prefix))

if len(result.bodies) > 0:

result.errors.extend(body_errors)

elif len(body_errors) > 0:

return (

ParseError(

header="Endpoint requires a body, but none were parseable.",

detail="\n".join(error.detail or "" for error in body_errors),

),

schemas,

parameters,

)

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[Tuple[oai.ParameterLocation, Property]]:

"""Iterate through all the parameters of this endpoint"""

yield from ((oai.ParameterLocation.PATH, param) for param in self.path_parameters)

yield from ((oai.ParameterLocation.QUERY, param) for param in self.query_parameters)

yield from ((oai.ParameterLocation.HEADER, param) for param in self.header_parameters)

yield from ((oai.ParameterLocation.COOKIE, param) for param in self.cookie_parameters)

def list_all_parameters(self) -> List[Property]:

"""Return a List of all the parameters of this endpoint"""

return (

self.path_parameters

+ self.query_parameters

+ self.header_parameters

+ self.cookie_parameters

+ [body.prop for body in self.bodies]

)

@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.model_validate(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,

config=config,

)

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,

)