fix:yapi
This commit is contained in:
gongwenxin
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@@ -1,355 +1,481 @@
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"""Input Parser Module"""
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import json
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import os
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from typing import Any, Dict, Optional, List, Union
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from pydantic import BaseModel # For defining the structure of parsed inputs
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from dataclasses import dataclass, field
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import logging
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from typing import List, Dict, Any, Optional, Union # Ensure Union is imported
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logger = logging.getLogger("InputParser")
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logger = logging.getLogger(__name__)
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class ParsedOpenAPISpec(BaseModel):
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# Placeholder for OpenAPI spec details relevant to the compliance suite
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spec: Dict[str, Any]
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info: Dict[str, Any] # Swagger 'info' object with title, version, etc.
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paths: Dict[str, Dict[str, Any]] # API paths and their operations
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tags: Optional[List[Dict[str, str]]] = None # API tags
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basePath: Optional[str] = None # Base path for all APIs
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swagger_version: str # Swagger specification version
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class BaseEndpoint:
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"""所有端点对象的基类，可以包含一些通用属性或方法。"""
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def __init__(self, method: str, path: str):
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self.method = method
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self.path = path
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@dataclass
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class YAPIEndpoint:
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"""YAPI API端点信息"""
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path: str
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method: str
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title: str = ""
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description: str = ""
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category_name: str = ""
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req_params: List[Dict[str, Any]] = field(default_factory=list)
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req_query: List[Dict[str, Any]] = field(default_factory=list)
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req_headers: List[Dict[str, Any]] = field(default_factory=list)
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req_body_type: str = ""
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req_body_other: str = ""
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res_body_type: str = ""
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res_body: str = ""
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def to_dict(self) -> Dict[str, Any]:
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# 基类可以提供一个默认的 to_dict 实现或要求子类实现
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raise NotImplementedError("Subclasses must implement to_dict")
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@dataclass
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class ParsedYAPISpec:
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class YAPIEndpoint(BaseEndpoint): # Inherit from BaseEndpoint
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def __init__(self, data: Dict[str, Any], category_name: Optional[str] = None, category_id: Optional[int] = None):
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super().__init__(method=data.get("method", "GET").upper(), path=data.get("path", ""))
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self._raw_data = data
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self.title: str = data.get("title", "")
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self.desc: Optional[str] = data.get("desc")
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self._id: int = data.get("_id")
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self.project_id: int = data.get("project_id")
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self.catid: int = data.get("catid")
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self.req_params: List[Dict[str, Any]] = data.get("req_params", [])
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self.req_query: List[Dict[str, Any]] = data.get("req_query", [])
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self.req_headers: List[Dict[str, Any]] = data.get("req_headers", [])
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self.req_body_form: List[Dict[str, Any]] = data.get("req_body_form", [])
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self.req_body_type: Optional[str] = data.get("req_body_type")
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self.req_body_is_json_schema: bool = data.get("req_body_is_json_schema", False)
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self.req_body_other: Optional[str] = data.get("req_body_other")
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self.res_body_type: Optional[str] = data.get("res_body_type")
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self.res_body_is_json_schema: bool = data.get("res_body_is_json_schema", False)
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self.res_body: Optional[str] = data.get("res_body")
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self.status: str = data.get("status", "undone")
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self.api_opened: bool = data.get("api_opened", False)
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self.uid: int = data.get("uid")
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self.category_name = category_name
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self.category_id = category_id if category_id is not None else self.catid
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self._parsed_req_body_schema: Optional[Dict[str, Any]] = None
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if self.req_body_type == "json" and self.req_body_other and self.req_body_is_json_schema:
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try:
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self._parsed_req_body_schema = json.loads(self.req_body_other)
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except json.JSONDecodeError as e:
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logger.error(f"YAPIEndpoint (ID: {self._id}, Title: {self.title}): Failed to parse req_body_other as JSON during init: {e}. Content: {self.req_body_other[:200]}")
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self._parsed_res_body_schema: Optional[Dict[str, Any]] = None
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if self.res_body_type == "json" and self.res_body and self.res_body_is_json_schema:
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try:
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self._parsed_res_body_schema = json.loads(self.res_body)
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except json.JSONDecodeError as e:
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logger.error(f"YAPIEndpoint (ID: {self._id}, Title: {self.title}): Failed to parse res_body as JSON during init: {e}. Content: {self.res_body[:200]}")
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def to_dict(self) -> Dict[str, Any]:
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endpoint_dict = {
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"method": self.method,
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"path": self.path,
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"title": self.title,
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"summary": self.title,
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"description": self.desc or "",
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"operationId": f"{self.method.lower()}_{self.path.replace('/', '_').replace('{', '').replace('}', '')}_{self._id}",
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"tags": [self.category_name or str(self.catid)],
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"parameters": [],
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"requestBody": None,
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"responses": {},
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"_source_format": "yapi",
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"_yapi_id": self._id,
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"_yapi_raw_data": self._raw_data # Keep raw data for debugging or deeper inspection if needed
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}
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# Path parameters from req_params
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for p_spec in self.req_params:
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param_name = p_spec.get("name")
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if not param_name: continue
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endpoint_dict["parameters"].append({
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"name": param_name,
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"in": "path",
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"required": True, # Path parameters are always required
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"description": p_spec.get("desc", ""),
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"schema": {"type": "string", "example": p_spec.get("example", f"example_{param_name}")}
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})
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# Query parameters from req_query
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for q_spec in self.req_query:
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param_name = q_spec.get("name")
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if not param_name: continue
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is_required = q_spec.get("required") == "1" # YAPI uses "1" for true
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param_schema = {"type": "string"} # Default to string, YAPI doesn't specify types well here
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if "example" in q_spec: param_schema["example"] = q_spec["example"]
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# Add other fields from YAPI query spec if needed (e.g., desc)
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endpoint_dict["parameters"].append({
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"name": param_name,
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"in": "query",
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"required": is_required,
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"description": q_spec.get("desc", ""),
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"schema": param_schema
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})
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# Header parameters from req_headers
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for h_spec in self.req_headers:
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param_name = h_spec.get("name")
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if not param_name or param_name.lower() == 'content-type': continue # Content-Type is handled by requestBody
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is_required = h_spec.get("required") == "1"
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default_value = h_spec.get("value") # YAPI uses 'value' for default/example header value
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param_schema = {"type": "string"}
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if default_value:
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if is_required: # If required, it's more like an example of what's expected
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param_schema["example"] = default_value
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else: # If not required, it's a default value
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param_schema["default"] = default_value
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endpoint_dict["parameters"].append({
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"name": param_name,
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"in": "header",
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"required": is_required,
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"description": h_spec.get("desc", ""),
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"schema": param_schema
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})
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# Request body
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if self.req_body_type == "json" and self._parsed_req_body_schema:
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endpoint_dict["requestBody"] = {
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"content": {
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"application/json": {
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"schema": self._parsed_req_body_schema
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}
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}
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}
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elif self.req_body_type == "form" and self.req_body_form:
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properties = {}
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required_form_params = []
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for form_param in self.req_body_form:
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name = form_param.get("name")
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if not name: continue
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properties[name] = {
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"type": "string", # YAPI form params are typically strings, file uploads are different
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"description": form_param.get("desc","")
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}
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if form_param.get("example"): properties[name]["example"] = form_param.get("example")
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if form_param.get("required") == "1": required_form_params.append(name)
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endpoint_dict["requestBody"] = {
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"content": {
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"application/x-www-form-urlencoded": {
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"schema": {
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"type": "object",
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"properties": properties,
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"required": required_form_params if required_form_params else None # OpenAPI: omit if empty
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}
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}
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# YAPI also supports req_body_type = 'file', which would map to multipart/form-data
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# This example focuses on json and basic form.
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}
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}
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# Add other req_body_types if necessary (e.g., raw, file)
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# Responses
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# YAPI has a simpler response structure. We'll map its res_body to a default success response (e.g., 200 or 201).
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default_success_status = "200"
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if self.method == "POST": default_success_status = "201" # Common practice for POST success
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if self.res_body_type == "json" and self._parsed_res_body_schema:
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endpoint_dict["responses"][default_success_status] = {
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"description": "Successful Operation (from YAPI res_body)",
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"content": {
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"application/json": {
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"schema": self._parsed_res_body_schema
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}
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}
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}
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elif self.res_body_type == "json" and not self._parsed_res_body_schema and self.res_body: # Schema parsing failed but text exists
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endpoint_dict["responses"][default_success_status] = {
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"description": "Successful Operation (Schema parsing error, raw text might be available)",
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"content": {"application/json": {"schema": {"type": "object", "description": "Schema parsing failed for YAPI res_body."}}} # Placeholder
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}
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else: # No JSON schema, or other res_body_type
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endpoint_dict["responses"][default_success_status] = {
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"description": "Successful Operation (No specific schema provided in YAPI for this response)"
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}
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# Ensure there's always a default response if nothing specific was added
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if not endpoint_dict["responses"]:
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endpoint_dict["responses"]["default"] = {"description": "Default response from YAPI definition"}
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return endpoint_dict
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def __repr__(self):
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return f"<YAPIEndpoint ID:{self._id} Method:{self.method} Path:{self.path} Title:'{self.title}'>"
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class SwaggerEndpoint(BaseEndpoint): # Inherit from BaseEndpoint
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def __init__(self, path: str, method: str, data: Dict[str, Any], global_spec: Dict[str, Any]):
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super().__init__(method=method.upper(), path=path)
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self._raw_data = data
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self._global_spec = global_spec # Store for $ref resolution
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self.summary: Optional[str] = data.get("summary")
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self.description: Optional[str] = data.get("description")
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self.operation_id: Optional[str] = data.get("operationId")
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self.tags: List[str] = data.get("tags", [])
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# Parameters, requestBody, responses are processed by to_dict
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def _resolve_ref(self, ref_path: str) -> Optional[Dict[str, Any]]:
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"""Resolves a $ref path within the global OpenAPI/Swagger spec."""
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if not ref_path.startswith("#/"):
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logger.warning(f"Unsupported $ref path: {ref_path}. Only local refs '#/...' are currently supported.")
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return None
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parts = ref_path[2:].split('/') # Remove '#/' and split
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current_level = self._global_spec
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try:
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for part in parts:
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# Decode URI component encoding if present (e.g. "~0" for "~", "~1" for "/")
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part = part.replace("~1", "/").replace("~0", "~")
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current_level = current_level[part]
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# It's crucial to return a copy if the resolved ref will be modified,
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# or ensure modifications happen on copies later.
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# For now, returning as is, assuming downstream processing is careful or uses copies.
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if isinstance(current_level, dict):
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return current_level # Potentially json.loads(json.dumps(current_level)) for a deep copy
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else: # Resolved to a non-dict, which might be valid for some simple refs but unusual for schemas
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logger.warning(f"$ref '{ref_path}' resolved to a non-dictionary type: {type(current_level)}. Value: {str(current_level)[:100]}")
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return {"type": "string", "description": f"Resolved $ref '{ref_path}' to non-dict: {str(current_level)[:100]}"} # Placeholder
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except (KeyError, TypeError, AttributeError) as e:
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logger.error(f"Failed to resolve $ref '{ref_path}': {e}", exc_info=True)
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return None
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def _process_schema_or_ref(self, schema_like: Any) -> Optional[Dict[str, Any]]:
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"""
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Processes a schema part, resolving $refs and recursively processing nested structures.
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Returns a new dictionary with resolved refs, or None if resolution fails badly.
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"""
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if not isinstance(schema_like, dict):
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if schema_like is None: return None
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logger.warning(f"Expected a dictionary for schema processing, got {type(schema_like)}. Value: {str(schema_like)[:100]}")
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return {"type": "string", "description": f"Schema was not a dict: {str(schema_like)[:100]}"} # Placeholder for non-dict schema
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# If it's a $ref, resolve it.
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if "$ref" in schema_like:
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return self._resolve_ref(schema_like["$ref"]) # This will be the new base schema_like
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# Create a copy to avoid modifying the original spec during processing
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processed_schema = schema_like.copy()
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# Recursively process 'properties' for object schemas
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if "properties" in processed_schema and isinstance(processed_schema["properties"], dict):
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new_properties = {}
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for prop_name, prop_schema in processed_schema["properties"].items():
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resolved_prop = self._process_schema_or_ref(prop_schema)
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if resolved_prop is not None: # Only add if resolution was successful
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new_properties[prop_name] = resolved_prop
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# else: logger.warning(f"Failed to process property '{prop_name}' in {self.operation_id or self.path}")
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processed_schema["properties"] = new_properties
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# Recursively process 'items' for array schemas
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if "items" in processed_schema and isinstance(processed_schema["items"], dict): # 'items' should be a schema object
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resolved_items = self._process_schema_or_ref(processed_schema["items"])
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if resolved_items is not None:
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processed_schema["items"] = resolved_items
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# else: logger.warning(f"Failed to process 'items' schema in {self.operation_id or self.path}")
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# Handle allOf, anyOf, oneOf by trying to merge or process them (simplistic merge for allOf)
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# This is a complex area of JSON Schema. This is a very basic attempt.
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if "allOf" in processed_schema and isinstance(processed_schema["allOf"], list):
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merged_all_of_props = {}
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merged_all_of_required = set()
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temp_schema_for_all_of = {"type": processed_schema.get("type", "object"), "properties": {}, "required": []}
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for sub_schema_data in processed_schema["allOf"]:
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resolved_sub_schema = self._process_schema_or_ref(sub_schema_data)
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if resolved_sub_schema and isinstance(resolved_sub_schema, dict):
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if "properties" in resolved_sub_schema:
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temp_schema_for_all_of["properties"].update(resolved_sub_schema["properties"])
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if "required" in resolved_sub_schema and isinstance(resolved_sub_schema["required"], list):
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merged_all_of_required.update(resolved_sub_schema["required"])
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# Copy other top-level keywords from the resolved_sub_schema if needed, e.g. description
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for key, value in resolved_sub_schema.items():
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if key not in ["properties", "required", "type", "$ref", "allOf", "anyOf", "oneOf"]:
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if key not in temp_schema_for_all_of or temp_schema_for_all_of[key] is None: # prioritize existing
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temp_schema_for_all_of[key] = value
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if temp_schema_for_all_of["properties"]:
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processed_schema["properties"] = {**processed_schema.get("properties",{}), **temp_schema_for_all_of["properties"]}
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if merged_all_of_required:
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current_required = set(processed_schema.get("required", []))
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current_required.update(merged_all_of_required)
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processed_schema["required"] = sorted(list(current_required))
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del processed_schema["allOf"] # Remove allOf after processing
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# Copy other merged attributes back to processed_schema
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for key, value in temp_schema_for_all_of.items():
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if key not in ["properties", "required", "type", "$ref", "allOf", "anyOf", "oneOf"]:
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if key not in processed_schema or processed_schema[key] is None:
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processed_schema[key] = value
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# anyOf, oneOf are harder as they represent choices. For now, we might just list them or pick first.
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# For simplicity in to_dict, we might not fully expand them but ensure refs inside are resolved.
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for keyword in ["anyOf", "oneOf"]:
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if keyword in processed_schema and isinstance(processed_schema[keyword], list):
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processed_sub_list = []
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for sub_item in processed_schema[keyword]:
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resolved_sub = self._process_schema_or_ref(sub_item)
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if resolved_sub:
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processed_sub_list.append(resolved_sub)
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if processed_sub_list: # only update if some were resolved
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processed_schema[keyword] = processed_sub_list
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return processed_schema
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def to_dict(self) -> Dict[str, Any]:
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endpoint_data = {
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"method": self.method,
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"path": self.path,
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"summary": self.summary or "",
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"title": self.summary or self.operation_id or "", # Fallback for title
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"description": self.description or "",
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"operationId": self.operation_id or f"{self.method.lower()}_{self.path.replace('/', '_').replace('{', '').replace('}', '')}",
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"tags": self.tags,
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"parameters": [],
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"requestBody": None,
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"responses": {},
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"_source_format": "swagger/openapi",
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"_swagger_raw_data": self._raw_data, # Keep raw for debugging
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"_global_api_spec_for_resolution": self._global_spec # For test cases that might need to resolve further
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}
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# Process parameters
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if "parameters" in self._raw_data and isinstance(self._raw_data["parameters"], list):
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for param_data_raw in self._raw_data["parameters"]:
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# Each param_data_raw could itself be a $ref or contain a schema that is a $ref
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processed_param_container = self._process_schema_or_ref(param_data_raw)
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if processed_param_container and isinstance(processed_param_container, dict):
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# If the parameter itself was a $ref, processed_param_container is the resolved object.
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# If it contained a schema that was a $ref, that nested schema should be resolved.
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# We need to ensure 'schema' key exists if 'in' is path, query, header
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if "schema" in processed_param_container and isinstance(processed_param_container["schema"], dict):
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# schema was present, process it further (it might have been already by _process_schema_or_ref if it was a complex object)
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# but if _process_schema_or_ref was called on param_data_raw which wasn't a ref itself,
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# the internal 'schema' ref might not have been re-processed with full context.
|
||||
# However, the recursive nature of _process_schema_or_ref should handle nested $refs.
|
||||
pass # Assume it's processed by the main call to _process_schema_or_ref on param_data_raw
|
||||
elif "content" in processed_param_container: # Parameter described by Content Object (OpenAPI 3.x)
|
||||
pass # Content object schemas should have been resolved by _process_schema_or_ref
|
||||
|
||||
endpoint_data["parameters"].append(processed_param_container)
|
||||
|
||||
# Process requestBody
|
||||
if "requestBody" in self._raw_data and isinstance(self._raw_data["requestBody"], dict):
|
||||
processed_rb = self._process_schema_or_ref(self._raw_data["requestBody"])
|
||||
if processed_rb:
|
||||
endpoint_data["requestBody"] = processed_rb
|
||||
|
||||
# Process responses
|
||||
if "responses" in self._raw_data and isinstance(self._raw_data["responses"], dict):
|
||||
for status_code, resp_data_raw in self._raw_data["responses"].items():
|
||||
processed_resp = self._process_schema_or_ref(resp_data_raw)
|
||||
if processed_resp:
|
||||
endpoint_data["responses"][status_code] = processed_resp
|
||||
elif resp_data_raw: # If processing failed but raw exists, keep raw (though this is less ideal)
|
||||
endpoint_data["responses"][status_code] = resp_data_raw
|
||||
logger.warning(f"Kept raw response data for {status_code} due to processing failure for {self.operation_id or self.path}")
|
||||
|
||||
if not endpoint_data["responses"]: # Ensure default response if none processed
|
||||
endpoint_data["responses"]["default"] = {"description": "Default response from Swagger/OpenAPI definition"}
|
||||
|
||||
return endpoint_data
|
||||
|
||||
def __repr__(self):
|
||||
return f"<SwaggerEndpoint Method:{self.method} Path:{self.path} Summary:'{self.summary}'>"
|
||||
|
||||
class ParsedAPISpec:
|
||||
"""解析后的API规范的通用基类"""
|
||||
def __init__(self, spec_type: str, endpoints: List[Union[YAPIEndpoint, SwaggerEndpoint]], spec: Dict[str, Any]):
|
||||
self.spec_type = spec_type
|
||||
self.endpoints = endpoints
|
||||
self.spec = spec # Store the original full spec dictionary, useful for $ref resolution if not pre-resolved
|
||||
|
||||
class ParsedYAPISpec(ParsedAPISpec):
|
||||
"""解析后的YAPI规范"""
|
||||
endpoints: List[YAPIEndpoint]
|
||||
categories: List[Dict[str, Any]]
|
||||
total_count: int
|
||||
def __init__(self, endpoints: List[YAPIEndpoint], categories: List[Dict[str, Any]], spec: Dict[str, Any]):
|
||||
super().__init__(spec_type="yapi", endpoints=endpoints, spec=spec)
|
||||
self.categories = categories
|
||||
|
||||
@dataclass
|
||||
class SwaggerEndpoint:
|
||||
"""Swagger API端点信息"""
|
||||
path: str
|
||||
method: str
|
||||
summary: str = ""
|
||||
description: str = ""
|
||||
operation_id: str = ""
|
||||
tags: List[str] = field(default_factory=list)
|
||||
parameters: List[Dict[str, Any]] = field(default_factory=list)
|
||||
responses: Dict[str, Any] = field(default_factory=dict)
|
||||
consumes: List[str] = field(default_factory=list)
|
||||
produces: List[str] = field(default_factory=list)
|
||||
request_body: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
@dataclass
|
||||
class ParsedSwaggerSpec:
|
||||
"""解析后的Swagger规范"""
|
||||
endpoints: List[SwaggerEndpoint]
|
||||
info: Dict[str, Any]
|
||||
swagger_version: str
|
||||
host: str = ""
|
||||
base_path: str = ""
|
||||
schemes: List[str] = field(default_factory=list)
|
||||
tags: List[Dict[str, Any]] = field(default_factory=list)
|
||||
categories: List[Dict[str, Any]] = field(default_factory=list)
|
||||
|
||||
class ParsedBusinessLogic(BaseModel):
|
||||
# Placeholder for parsed business logic flow
|
||||
name: str
|
||||
steps: list # List of steps, each could be another Pydantic model
|
||||
class ParsedSwaggerSpec(ParsedAPISpec):
|
||||
"""解析后的Swagger/OpenAPI规范"""
|
||||
def __init__(self, endpoints: List[SwaggerEndpoint], tags: List[Dict[str, Any]], spec: Dict[str, Any]):
|
||||
super().__init__(spec_type="swagger", endpoints=endpoints, spec=spec)
|
||||
self.tags = tags
|
||||
|
||||
class InputParser:
|
||||
"""
|
||||
Responsible for parsing DDMS supplier's input materials like API specs, etc.
|
||||
"""
|
||||
|
||||
"""负责解析输入（如YAPI JSON）并提取API端点信息"""
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def parse_openapi_spec(self, spec_path: str) -> Optional[ParsedOpenAPISpec]:
|
||||
"""
|
||||
Parses an OpenAPI specification from a file path.
|
||||
|
||||
Args:
|
||||
spec_path: The file path of the OpenAPI specification.
|
||||
|
||||
Returns:
|
||||
A ParsedOpenAPISpec object containing the parsed specification,
|
||||
or None if parsing fails.
|
||||
"""
|
||||
try:
|
||||
# Check if file exists
|
||||
if not os.path.exists(spec_path):
|
||||
print(f"Error: File not found: {spec_path}")
|
||||
return None
|
||||
|
||||
# Read and parse JSON file
|
||||
with open(spec_path, 'r', encoding='utf-8') as f:
|
||||
swagger_data = json.load(f)
|
||||
|
||||
# Extract basic information
|
||||
swagger_version = swagger_data.get('swagger', swagger_data.get('openapi', 'Unknown'))
|
||||
info = swagger_data.get('info', {})
|
||||
paths = swagger_data.get('paths', {})
|
||||
tags = swagger_data.get('tags', [])
|
||||
base_path = swagger_data.get('basePath', '')
|
||||
|
||||
# Create and return ParsedOpenAPISpec
|
||||
return ParsedOpenAPISpec(
|
||||
spec=swagger_data,
|
||||
info=info,
|
||||
paths=paths,
|
||||
tags=tags,
|
||||
basePath=base_path,
|
||||
swagger_version=swagger_version
|
||||
)
|
||||
|
||||
except FileNotFoundError:
|
||||
print(f"File not found: {spec_path}")
|
||||
return None
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"Error parsing JSON from {spec_path}: {e}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"Error parsing OpenAPI spec from {spec_path}: {e}")
|
||||
return None
|
||||
self.logger = logging.getLogger(__name__)
|
||||
|
||||
def parse_yapi_spec(self, file_path: str) -> Optional[ParsedYAPISpec]:
|
||||
"""
|
||||
解析YAPI规范文件
|
||||
|
||||
Args:
|
||||
file_path: YAPI JSON文件路径
|
||||
|
||||
Returns:
|
||||
Optional[ParsedYAPISpec]: 解析后的YAPI规范，如果解析失败则返回None
|
||||
"""
|
||||
if not os.path.isfile(file_path):
|
||||
logger.error(f"文件不存在: {file_path}")
|
||||
return None
|
||||
|
||||
self.logger.info(f"Parsing YAPI spec from: {file_path}")
|
||||
all_endpoints: List[YAPIEndpoint] = []
|
||||
yapi_categories: List[Dict[str, Any]] = []
|
||||
raw_spec_data_list: Optional[List[Dict[str, Any]]] = None # YAPI export is a list of categories
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
yapi_data = json.load(f)
|
||||
|
||||
if not isinstance(yapi_data, list):
|
||||
logger.error(f"无效的YAPI文件格式: 顶层元素应该是数组")
|
||||
raw_spec_data_list = json.load(f)
|
||||
|
||||
if not isinstance(raw_spec_data_list, list):
|
||||
self.logger.error(f"YAPI spec file {file_path} does not contain a JSON list as expected for categories.")
|
||||
return None
|
||||
|
||||
endpoints = []
|
||||
categories = []
|
||||
|
||||
# 处理分类
|
||||
for category_data in yapi_data:
|
||||
|
||||
for category_data in raw_spec_data_list:
|
||||
if not isinstance(category_data, dict):
|
||||
logger.warning(f"YAPI 分类条目格式不正确，应为字典类型，已跳过: {category_data}")
|
||||
self.logger.warning(f"Skipping non-dictionary item in YAPI spec list: {str(category_data)[:100]}")
|
||||
continue
|
||||
cat_name = category_data.get("name")
|
||||
cat_id = category_data.get("_id", category_data.get("id")) # YAPI uses _id
|
||||
yapi_categories.append({"name": cat_name, "description": category_data.get("desc"), "id": cat_id})
|
||||
|
||||
category_name = category_data.get('name', '')
|
||||
category_desc = category_data.get('desc', '')
|
||||
|
||||
# 添加到分类列表
|
||||
categories.append({
|
||||
'name': category_name,
|
||||
'desc': category_desc
|
||||
})
|
||||
|
||||
# 处理API接口
|
||||
api_list = category_data.get('list', [])
|
||||
if not isinstance(api_list, list):
|
||||
logger.warning(f"分类 '{category_name}' 中的 API列表 (list) 格式不正确，应为数组类型，已跳过。")
|
||||
continue
|
||||
|
||||
for api_item in api_list:
|
||||
if not isinstance(api_item, dict):
|
||||
logger.warning(f"分类 '{category_name}' 中的 API条目格式不正确，应为字典类型，已跳过: {api_item}")
|
||||
for endpoint_data in category_data.get("list", []):
|
||||
if not isinstance(endpoint_data, dict):
|
||||
self.logger.warning(f"Skipping non-dictionary endpoint item in category '{cat_name}': {str(endpoint_data)[:100]}")
|
||||
continue
|
||||
|
||||
# 提取API信息
|
||||
path = api_item.get('path', '')
|
||||
if not path:
|
||||
logger.info(f"分类 '{category_name}' 中的 API条目缺少 'path'，使用空字符串。 API: {api_item.get('title', '未命名')}")
|
||||
method = api_item.get('method', 'GET')
|
||||
if api_item.get('method') is None: # 仅当原始数据中完全没有 method 字段时记录
|
||||
logger.info(f"分类 '{category_name}' 中的 API条目 '{path}' 缺少 'method'，使用默认值 'GET'。")
|
||||
title = api_item.get('title', '')
|
||||
if not title:
|
||||
logger.info(f"分类 '{category_name}' 中的 API条目 '{path}' ({method}) 缺少 'title'，使用空字符串。")
|
||||
description = api_item.get('desc', '')
|
||||
|
||||
# 提取请求参数
|
||||
req_params = api_item.get('req_params', [])
|
||||
req_query = api_item.get('req_query', [])
|
||||
req_headers = api_item.get('req_headers', [])
|
||||
|
||||
# 提取请求体信息
|
||||
req_body_type = api_item.get('req_body_type', '')
|
||||
req_body_other = api_item.get('req_body_other', '')
|
||||
|
||||
# 提取响应体信息
|
||||
res_body_type = api_item.get('res_body_type', '')
|
||||
res_body = api_item.get('res_body', '')
|
||||
|
||||
# 创建端点对象
|
||||
endpoint = YAPIEndpoint(
|
||||
path=path,
|
||||
method=method,
|
||||
title=title,
|
||||
description=description,
|
||||
category_name=category_name,
|
||||
req_params=req_params,
|
||||
req_query=req_query,
|
||||
req_headers=req_headers,
|
||||
req_body_type=req_body_type,
|
||||
req_body_other=req_body_other,
|
||||
res_body_type=res_body_type,
|
||||
res_body=res_body
|
||||
)
|
||||
|
||||
endpoints.append(endpoint)
|
||||
|
||||
return ParsedYAPISpec(
|
||||
endpoints=endpoints,
|
||||
categories=categories,
|
||||
total_count=len(endpoints)
|
||||
)
|
||||
try:
|
||||
yapi_endpoint = YAPIEndpoint(endpoint_data, category_name=cat_name, category_id=cat_id)
|
||||
all_endpoints.append(yapi_endpoint)
|
||||
except Exception as e_ep:
|
||||
self.logger.error(f"Error processing YAPI endpoint data (ID: {endpoint_data.get('_id', 'N/A')}, Title: {endpoint_data.get('title', 'N/A')}). Error: {e_ep}", exc_info=True)
|
||||
|
||||
# The 'spec' for ParsedYAPISpec should be a dict representing the whole document.
|
||||
# Since YAPI export is a list of categories, we wrap it.
|
||||
yapi_full_spec_dict = {"yapi_categories": raw_spec_data_list}
|
||||
return ParsedYAPISpec(endpoints=all_endpoints, categories=yapi_categories, spec=yapi_full_spec_dict)
|
||||
except FileNotFoundError:
|
||||
self.logger.error(f"YAPI spec file not found: {file_path}")
|
||||
except json.JSONDecodeError as e:
|
||||
self.logger.error(f"Error decoding JSON from YAPI spec file {file_path}: {e}")
|
||||
except Exception as e:
|
||||
logger.error(f"解析YAPI文件时出错: {str(e)}")
|
||||
return None
|
||||
self.logger.error(f"An unexpected error occurred while parsing YAPI spec {file_path}: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
def parse_swagger_spec(self, file_path: str) -> Optional[ParsedSwaggerSpec]:
|
||||
"""
|
||||
解析Swagger规范文件
|
||||
|
||||
Args:
|
||||
file_path: Swagger JSON文件路径
|
||||
|
||||
Returns:
|
||||
Optional[ParsedSwaggerSpec]: 解析后的Swagger规范，如果解析失败则返回None
|
||||
"""
|
||||
if not os.path.isfile(file_path):
|
||||
logger.error(f"文件不存在: {file_path}")
|
||||
return None
|
||||
|
||||
self.logger.info(f"Parsing Swagger/OpenAPI spec from: {file_path}")
|
||||
all_endpoints: List[SwaggerEndpoint] = []
|
||||
swagger_tags: List[Dict[str, Any]] = []
|
||||
raw_spec_data_dict: Optional[Dict[str, Any]] = None # Swagger/OpenAPI is a single root object
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
swagger_data = json.load(f)
|
||||
|
||||
if not isinstance(swagger_data, dict):
|
||||
logger.error(f"无效的Swagger文件格式: 顶层元素应该是对象")
|
||||
# TODO: Add YAML support if needed, e.g., using PyYAML
|
||||
raw_spec_data_dict = json.load(f)
|
||||
|
||||
if not isinstance(raw_spec_data_dict, dict):
|
||||
self.logger.error(f"Swagger spec file {file_path} does not contain a JSON object as expected.")
|
||||
return None
|
||||
|
||||
# 提取基本信息
|
||||
swagger_version = swagger_data.get('swagger', swagger_data.get('openapi', ''))
|
||||
info = swagger_data.get('info', {})
|
||||
host = swagger_data.get('host', '')
|
||||
base_path = swagger_data.get('basePath', '')
|
||||
schemes = swagger_data.get('schemes', [])
|
||||
tags = swagger_data.get('tags', [])
|
||||
|
||||
swagger_tags = raw_spec_data_dict.get("tags", [])
|
||||
paths = raw_spec_data_dict.get("paths", {})
|
||||
|
||||
# 创建分类列表
|
||||
categories = []
|
||||
for tag in tags:
|
||||
categories.append({
|
||||
'name': tag.get('name', ''),
|
||||
'desc': tag.get('description', '')
|
||||
})
|
||||
|
||||
# 处理API路径
|
||||
paths = swagger_data.get('paths', {})
|
||||
endpoints = []
|
||||
|
||||
for path, path_item in paths.items():
|
||||
if not isinstance(path_item, dict):
|
||||
continue
|
||||
|
||||
# 处理每个HTTP方法 (GET, POST, PUT, DELETE等)
|
||||
for method, operation in path_item.items():
|
||||
if method in ['get', 'post', 'put', 'delete', 'patch', 'options', 'head', 'trace']:
|
||||
if not isinstance(operation, dict):
|
||||
continue
|
||||
|
||||
# 提取操作信息
|
||||
summary = operation.get('summary', '')
|
||||
description = operation.get('description', '')
|
||||
operation_id = operation.get('operationId', '')
|
||||
operation_tags = operation.get('tags', [])
|
||||
|
||||
# 提取参数信息
|
||||
parameters = operation.get('parameters', [])
|
||||
|
||||
# 提取响应信息
|
||||
responses = operation.get('responses', {})
|
||||
|
||||
# 提取请求和响应的内容类型
|
||||
consumes = operation.get('consumes', swagger_data.get('consumes', []))
|
||||
produces = operation.get('produces', swagger_data.get('produces', []))
|
||||
|
||||
# 提取请求体信息 (OpenAPI 3.0 格式)
|
||||
request_body = operation.get('requestBody', {})
|
||||
|
||||
# 创建端点对象
|
||||
endpoint = SwaggerEndpoint(
|
||||
path=path,
|
||||
method=method.upper(),
|
||||
summary=summary,
|
||||
description=description,
|
||||
operation_id=operation_id,
|
||||
tags=operation_tags,
|
||||
parameters=parameters,
|
||||
responses=responses,
|
||||
consumes=consumes,
|
||||
produces=produces,
|
||||
request_body=request_body
|
||||
)
|
||||
|
||||
endpoints.append(endpoint)
|
||||
|
||||
# 创建返回对象
|
||||
return ParsedSwaggerSpec(
|
||||
endpoints=endpoints,
|
||||
info=info,
|
||||
swagger_version=swagger_version,
|
||||
host=host,
|
||||
base_path=base_path,
|
||||
schemes=schemes,
|
||||
tags=tags,
|
||||
categories=categories
|
||||
)
|
||||
for path, path_item_obj in paths.items():
|
||||
if not isinstance(path_item_obj, dict): continue
|
||||
for method, operation_obj in path_item_obj.items():
|
||||
# Common methods, can be extended
|
||||
if method.lower() not in ["get", "post", "put", "delete", "patch", "options", "head", "trace"]:
|
||||
continue # Skip non-standard HTTP methods or extensions like 'parameters' at path level
|
||||
if not isinstance(operation_obj, dict): continue
|
||||
try:
|
||||
# Pass the full raw_spec_data_dict for $ref resolution within SwaggerEndpoint
|
||||
swagger_endpoint = SwaggerEndpoint(path, method, operation_obj, global_spec=raw_spec_data_dict)
|
||||
all_endpoints.append(swagger_endpoint)
|
||||
except Exception as e_ep:
|
||||
self.logger.error(f"Error processing Swagger endpoint: {method.upper()} {path}. Error: {e_ep}", exc_info=True)
|
||||
|
||||
return ParsedSwaggerSpec(endpoints=all_endpoints, tags=swagger_tags, spec=raw_spec_data_dict)
|
||||
except FileNotFoundError:
|
||||
self.logger.error(f"Swagger spec file not found: {file_path}")
|
||||
except json.JSONDecodeError as e:
|
||||
self.logger.error(f"Error decoding JSON from Swagger spec file {file_path}: {e}")
|
||||
except Exception as e:
|
||||
logger.error(f"解析Swagger文件时出错: {str(e)}")
|
||||
return None
|
||||
|
||||
def parse_business_logic_flow(self, flow_description: str) -> Optional[ParsedBusinessLogic]:
|
||||
"""
|
||||
Parses a business logic flow description.
|
||||
The format of this description is TBD and this parser would need to be built accordingly.
|
||||
|
||||
Args:
|
||||
flow_description: The string content describing the business logic flow.
|
||||
|
||||
Returns:
|
||||
A ParsedBusinessLogic object or None if parsing fails.
|
||||
"""
|
||||
print(f"[InputParser] Placeholder: Parsing business logic flow. Content: {flow_description[:100]}...")
|
||||
# Placeholder: Actual parsing logic will depend on the defined format.
|
||||
return ParsedBusinessLogic(name="Example Flow", steps=["Step 1 API call", "Step 2 Validate Response"])
|
||||
|
||||
# Add other parsers as needed (e.g., for data object definitions)
|
||||
self.logger.error(f"An unexpected error occurred while parsing Swagger spec {file_path}: {e}", exc_info=True)
|
||||
return None
|
||||
Binary file not shown.
@@ -20,22 +20,22 @@ logger = logging.getLogger(__name__)
|
||||
class ValidationResult:
|
||||
"""Validation result container"""
|
||||
|
||||
def __init__(self, is_valid: bool, errors: List[str] = None, warnings: List[str] = None):
|
||||
def __init__(self, passed: bool, errors: List[str] = None, warnings: List[str] = None):
|
||||
"""
|
||||
Initialize a validation result
|
||||
|
||||
Args:
|
||||
is_valid: Whether the data is valid according to the schema
|
||||
passed: Whether the data is valid according to the schema
|
||||
errors: List of error messages (if any)
|
||||
warnings: List of warning messages (if any)
|
||||
"""
|
||||
self.is_valid = is_valid
|
||||
self.passed = passed
|
||||
self.errors = errors or []
|
||||
self.warnings = warnings or []
|
||||
|
||||
def __str__(self) -> str:
|
||||
"""String representation of validation result"""
|
||||
status = "Valid" if self.is_valid else "Invalid"
|
||||
status = "Valid" if self.passed else "Invalid"
|
||||
result = f"Validation Result: {status}\n"
|
||||
|
||||
if self.errors:
|
||||
|
||||
@@ -93,18 +93,20 @@ class BaseAPITestCase:
|
||||
use_llm_for_query_params: bool = False
|
||||
use_llm_for_headers: bool = False
|
||||
|
||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||
"""
|
||||
初始化测试用例。
|
||||
Args:
|
||||
endpoint_spec: 当前被测API端点的详细定义 (来自YAPI/Swagger解析结果)。
|
||||
global_api_spec: 完整的API规范文档 (来自YAPI/Swagger解析结果)。
|
||||
json_schema_validator: APITestOrchestrator 传入的 JSONSchemaValidator 实例 (可选)。
|
||||
llm_service: APITestOrchestrator 传入的 LLMService 实例 (可选)。
|
||||
"""
|
||||
self.endpoint_spec = endpoint_spec
|
||||
self.global_api_spec = global_api_spec
|
||||
self.logger = logging.getLogger(f"testcase.{self.id}")
|
||||
self.json_schema_validator = json_schema_validator # 存储传入的校验器实例
|
||||
self.llm_service = llm_service # 存储注入的 LLMService 实例
|
||||
self.logger.debug(f"Test case '{self.id}' initialized for endpoint: {self.endpoint_spec.get('method', '')} {self.endpoint_spec.get('path', '')}")
|
||||
|
||||
# --- 1. 请求生成与修改阶段 ---
|
||||
@@ -120,6 +122,20 @@ class BaseAPITestCase:
|
||||
self.logger.debug(f"Hook: generate_request_body, current body type: {type(current_body)}")
|
||||
return current_body
|
||||
|
||||
def generate_path_params(self, current_path_params: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""
|
||||
允许测试用例修改或生成路径参数。
|
||||
这些参数将用于替换URL中的占位符，例如 /users/{userId}。
|
||||
|
||||
Args:
|
||||
current_path_params: 从API规范或编排器默认逻辑生成的初始路径参数。
|
||||
|
||||
Returns:
|
||||
最终要使用的路径参数字典。
|
||||
"""
|
||||
self.logger.debug(f"Hook: generate_path_params, current: {current_path_params}")
|
||||
return current_path_params
|
||||
|
||||
# --- 1.5. 请求URL修改阶段 (新增钩子) ---
|
||||
def modify_request_url(self, current_url: str) -> str:
|
||||
"""
|
||||
@@ -180,26 +196,40 @@ class BaseAPITestCase:
|
||||
results.append(self.failed(f"{context_message_prefix} schema validation skipped: Validator not available."))
|
||||
return results
|
||||
|
||||
is_valid, errors = self.json_schema_validator.validate(data_to_validate, schema_definition)
|
||||
# validator_result 是 JSONSchemaValidator 内部定义的 ValidationResult 对象
|
||||
validator_result = self.json_schema_validator.validate(data_to_validate, schema_definition)
|
||||
|
||||
if is_valid:
|
||||
results.append(self.passed(f"{context_message_prefix} conforms to the JSON schema."))
|
||||
if validator_result.passed:
|
||||
success_message = f"{context_message_prefix} conforms to the JSON schema."
|
||||
# 可以选择性地将 validator 的警告信息添加到 details
|
||||
current_details = {}
|
||||
if validator_result.warnings:
|
||||
current_details["schema_warnings"] = validator_result.warnings
|
||||
# 如果 validator_result 有其他有用的成功信息，也可以加入 message 或 details
|
||||
results.append(self.passed(success_message, details=current_details if current_details else None))
|
||||
else:
|
||||
error_messages = []
|
||||
if isinstance(errors, list):
|
||||
for error in errors: # jsonschema.exceptions.ValidationError 对象
|
||||
error_messages.append(f"- Path: '{list(error.path)}', Message: {error.message}") # error.path 是一个deque
|
||||
elif isinstance(errors, str): # 兼容旧版或简单错误字符串
|
||||
error_messages.append(errors)
|
||||
# 从 validator_result.errors 构建 message 和 details
|
||||
error_reason = "Validation failed."
|
||||
if validator_result.errors:
|
||||
error_reason = "Errors:\n" + "\n".join([f"- {e}" for e in validator_result.errors])
|
||||
|
||||
full_message = f"{context_message_prefix} does not conform to the JSON schema. Errors:\n" + "\n".join(error_messages)
|
||||
full_message = f"{context_message_prefix} does not conform to the JSON schema. {error_reason}"
|
||||
|
||||
current_details = {
|
||||
"schema_errors": validator_result.errors,
|
||||
"validated_data_sample": str(data_to_validate)[:200]
|
||||
}
|
||||
if validator_result.warnings:
|
||||
current_details["schema_warnings"] = validator_result.warnings
|
||||
|
||||
results.append(self.failed(
|
||||
message=full_message,
|
||||
details={"schema_errors": error_messages, "validated_data_sample": str(data_to_validate)[:200]}
|
||||
details=current_details
|
||||
))
|
||||
self.logger.warning(f"{context_message_prefix} schema validation failed: {full_message}")
|
||||
return results
|
||||
|
||||
|
||||
# --- Helper to easily create a passed ValidationResult ---
|
||||
@staticmethod
|
||||
def passed(message: str, details: Optional[Dict[str, Any]] = None) -> ValidationResult:
|
||||
|
||||
@@ -640,21 +640,22 @@ class APITestOrchestrator:
|
||||
validation_results: List[ValidationResult] = []
|
||||
overall_status: ExecutedTestCaseResult.Status
|
||||
execution_message = ""
|
||||
test_case_instance: Optional[BaseAPITestCase] = None # Initialize to None
|
||||
|
||||
# 将 endpoint_spec 转换为字典，如果它还不是的话
|
||||
endpoint_spec_dict: Dict[str, Any]
|
||||
if isinstance(endpoint_spec, dict):
|
||||
endpoint_spec_dict = endpoint_spec
|
||||
self.logger.debug(f"endpoint_spec 已经是字典类型。")
|
||||
# self.logger.debug(f"endpoint_spec 已经是字典类型。")
|
||||
elif hasattr(endpoint_spec, 'to_dict') and callable(endpoint_spec.to_dict):
|
||||
try:
|
||||
endpoint_spec_dict = endpoint_spec.to_dict()
|
||||
self.logger.debug(f"成功通过 to_dict() 方法将类型为 {type(endpoint_spec)} 的 endpoint_spec 转换为字典。")
|
||||
# self.logger.debug(f"成功通过 to_dict() 方法将类型为 {type(endpoint_spec)} 的 endpoint_spec 转换为字典。")
|
||||
if not endpoint_spec_dict: # 如果 to_dict() 返回空字典
|
||||
self.logger.warning(f"endpoint_spec.to_dict() (类型: {type(endpoint_spec)}) 返回了一个空字典。")
|
||||
# self.logger.warning(f"endpoint_spec.to_dict() (类型: {type(endpoint_spec)}) 返回了一个空字典。")
|
||||
# 尝试备用转换
|
||||
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
||||
self.logger.debug(f"尝试从 {type(endpoint_spec).__name__} 对象的属性手动构建 endpoint_spec_dict。")
|
||||
# self.logger.debug(f"尝试从 {type(endpoint_spec).__name__} 对象的属性手动构建 endpoint_spec_dict。")
|
||||
endpoint_spec_dict = {
|
||||
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
||||
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
||||
@@ -667,7 +668,7 @@ class APITestOrchestrator:
|
||||
"_original_object_type": type(endpoint_spec).__name__
|
||||
}
|
||||
if not any(endpoint_spec_dict.values()): # 如果手动构建后仍基本为空
|
||||
self.logger.error(f"手动从属性构建 endpoint_spec_dict (类型: {type(endpoint_spec)}) 后仍然为空或无效。")
|
||||
# self.logger.error(f"手动从属性构建 endpoint_spec_dict (类型: {type(endpoint_spec)}) 后仍然为空或无效。")
|
||||
endpoint_spec_dict = {} # 重置为空，触发下方错误处理
|
||||
except Exception as e:
|
||||
self.logger.error(f"调用 endpoint_spec (类型: {type(endpoint_spec)}) 的 to_dict() 方法时出错: {e}。尝试备用转换。")
|
||||
@@ -691,10 +692,10 @@ class APITestOrchestrator:
|
||||
endpoint_spec_dict = {} # 转换失败
|
||||
elif hasattr(endpoint_spec, 'data') and isinstance(getattr(endpoint_spec, 'data'), dict): # 兼容 YAPIEndpoint 结构
|
||||
endpoint_spec_dict = getattr(endpoint_spec, 'data')
|
||||
self.logger.debug(f"使用了类型为 {type(endpoint_spec)} 的 endpoint_spec 的 .data 属性。")
|
||||
# self.logger.debug(f"使用了类型为 {type(endpoint_spec)} 的 endpoint_spec 的 .data 属性。")
|
||||
else: # 如果没有 to_dict, 也不是已知可直接访问 .data 的类型，则尝试最后的通用转换或手动构建
|
||||
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
||||
self.logger.debug(f"类型为 {type(endpoint_spec).__name__} 的 endpoint_spec 没有 to_dict() 或 data，尝试从属性手动构建。")
|
||||
# self.logger.debug(f"类型为 {type(endpoint_spec).__name__} 的 endpoint_spec 没有 to_dict() 或 data，尝试从属性手动构建。")
|
||||
endpoint_spec_dict = {
|
||||
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
||||
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
||||
@@ -795,7 +796,8 @@ class APITestOrchestrator:
|
||||
test_case_instance = test_case_class(
|
||||
endpoint_spec=endpoint_spec_dict,
|
||||
global_api_spec=global_spec_dict,
|
||||
json_schema_validator=self.validator
|
||||
json_schema_validator=self.validator,
|
||||
llm_service=self.llm_service # Pass the orchestrator's LLM service instance
|
||||
)
|
||||
self.logger.info(f"开始执行测试用例 '{test_case_instance.id}' ({test_case_instance.name}) for endpoint '{endpoint_spec_dict.get('method', 'N/A')} {endpoint_spec_dict.get('path', 'N/A')}'")
|
||||
|
||||
@@ -928,226 +930,199 @@ class APITestOrchestrator:
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
self.logger.error(f"执行测试用例 '{test_case_class.id if test_case_instance else test_case_class.__name__}' 时发生严重错误: {e}", exc_info=True)
|
||||
self.logger.error(f"执行测试用例 '{test_case_class.id if hasattr(test_case_class, 'id') else test_case_class.__name__}' (在实例化阶段或之前) 时发生严重错误: {e}", exc_info=True)
|
||||
# 如果 test_case_instance 在实例化时失败，它将是 None
|
||||
tc_id_for_log = test_case_instance.id if test_case_instance else (test_case_class.id if hasattr(test_case_class, 'id') else "unknown_tc_id_instantiation_error")
|
||||
tc_name_for_log = test_case_instance.name if test_case_instance else (test_case_class.name if hasattr(test_case_class, 'name') else test_case_class.__name__)
|
||||
# 实例化失败，严重性默认为CRITICAL
|
||||
tc_severity_for_log = test_case_instance.severity if test_case_instance else TestSeverity.CRITICAL
|
||||
|
||||
tc_duration = time.monotonic() - start_time
|
||||
# validation_results 可能在此阶段为空，或包含来自先前步骤的条目（如果错误发生在实例化之后）
|
||||
return ExecutedTestCaseResult(
|
||||
test_case_id=test_case_instance.id if test_case_instance else test_case_class.id if hasattr(test_case_class, 'id') else "unknown_tc_id",
|
||||
test_case_name=test_case_instance.name if test_case_instance else test_case_class.name if hasattr(test_case_class, 'name') else "Unknown Test Case Name",
|
||||
test_case_severity=test_case_instance.severity if test_case_instance else TestSeverity.CRITICAL,
|
||||
test_case_id=tc_id_for_log,
|
||||
test_case_name=tc_name_for_log,
|
||||
test_case_severity=tc_severity_for_log,
|
||||
status=ExecutedTestCaseResult.Status.ERROR,
|
||||
validation_points=validation_results,
|
||||
message=f"测试用例执行时发生内部错误: {str(e)}",
|
||||
validation_points=validation_results, # Ensure validation_results is defined (it is, at the start of the function)
|
||||
message=f"测试用例执行时发生内部错误 (可能在实例化期间): {str(e)}",
|
||||
duration=tc_duration
|
||||
)
|
||||
|
||||
def _prepare_initial_request_data(
|
||||
self,
|
||||
endpoint_spec: Dict[str, Any],
|
||||
test_case_instance: Optional[BaseAPITestCase] = None
|
||||
) -> Tuple[str, Dict[str, Any], Dict[str, Any], Dict[str, Any], Optional[Any]]:
|
||||
endpoint_spec: Dict[str, Any], # 已经转换为字典
|
||||
test_case_instance: Optional[BaseAPITestCase] = None # 传入测试用例实例以便访问其LLM配置
|
||||
) -> APIRequestContext: # 返回 APIRequestContext 对象
|
||||
"""
|
||||
根据OpenAPI端点规格和测试用例实例准备初始请求数据。
|
||||
包含端点级别的LLM参数缓存逻辑。
|
||||
根据API端点规范，准备初始的请求数据，包括URL（模板）、路径参数、查询参数、头部和请求体。
|
||||
这些数据将作为测试用例中 generate_* 方法的输入。
|
||||
"""
|
||||
method = endpoint_spec.get("method", "get").upper()
|
||||
operation_id = endpoint_spec.get("operationId", f"{method}_{endpoint_spec.get('path', '')}")
|
||||
endpoint_cache_key = f"{method}_{endpoint_spec.get('path', '')}"
|
||||
|
||||
self.logger.info(f"[{operation_id}] 开始为端点 {endpoint_cache_key} 准备初始请求数据 (TC: {test_case_instance.id if test_case_instance else 'N/A'})")
|
||||
method = endpoint_spec.get('method', 'GET').upper()
|
||||
path_template = endpoint_spec.get('path', '/') # 这是路径模板, e.g., /users/{id}
|
||||
operation_id = endpoint_spec.get('operationId') or f"{method}_{path_template.replace('/', '_').replace('{', '_').replace('}','')}"
|
||||
|
||||
# 尝试从缓存加载参数
|
||||
if endpoint_cache_key in self.llm_endpoint_params_cache:
|
||||
cached_params = self.llm_endpoint_params_cache[endpoint_cache_key]
|
||||
self.logger.info(f"[{operation_id}] 从缓存加载了端点 '{endpoint_cache_key}' 的LLM参数。")
|
||||
# 直接从缓存中获取各类参数，如果存在的话
|
||||
path_params_data = cached_params.get("path_params", {})
|
||||
query_params_data = cached_params.get("query_params", {})
|
||||
headers_data = cached_params.get("headers", {})
|
||||
body_data = cached_params.get("body") # Body可能是None
|
||||
initial_path_params: Dict[str, Any] = {}
|
||||
initial_query_params: Dict[str, Any] = {}
|
||||
initial_headers: Dict[str, str] = {}
|
||||
initial_body: Optional[Any] = None
|
||||
|
||||
parameters = endpoint_spec.get('parameters', [])
|
||||
|
||||
# 1. 处理路径参数
|
||||
path_param_specs = [p for p in parameters if p.get('in') == 'path']
|
||||
for param_spec in path_param_specs:
|
||||
name = param_spec.get('name')
|
||||
if not name: continue
|
||||
|
||||
# 即使从缓存加载，仍需确保默认头部（如Accept, Content-Type）存在或被正确设置
|
||||
# Content-Type应基于body_data是否存在来决定
|
||||
default_headers = {"Accept": "application/json"}
|
||||
if body_data is not None and method not in ["GET", "DELETE", "HEAD", "OPTIONS"]:
|
||||
default_headers["Content-Type"] = "application/json"
|
||||
should_use_llm = self._should_use_llm_for_param_type("path_params", test_case_instance)
|
||||
if should_use_llm and self.llm_service:
|
||||
self.logger.info(f"Attempting LLM generation for path parameter '{name}' in '{operation_id}'")
|
||||
# generated_value = self.llm_service.generate_data_for_parameter(param_spec, endpoint_spec, "path")
|
||||
# initial_path_params[name] = generated_value if generated_value is not None else f"llm_placeholder_for_{name}"
|
||||
initial_path_params[name] = f"llm_path_{name}" # Placeholder
|
||||
else:
|
||||
if 'example' in param_spec:
|
||||
initial_path_params[name] = param_spec['example']
|
||||
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||
initial_path_params[name] = param_spec['schema']['example'] # OpenAPI 3.0 `parameter.schema.example`
|
||||
elif 'default' in param_spec.get('schema', {}):
|
||||
initial_path_params[name] = param_spec['schema']['default']
|
||||
elif 'default' in param_spec: # OpenAPI 2.0 `parameter.default`
|
||||
initial_path_params[name] = param_spec['default']
|
||||
else:
|
||||
schema = param_spec.get('schema', {})
|
||||
param_type = schema.get('type', 'string')
|
||||
if param_type == 'integer': initial_path_params[name] = 123
|
||||
elif param_type == 'number': initial_path_params[name] = 1.23
|
||||
elif param_type == 'boolean': initial_path_params[name] = True
|
||||
elif param_type == 'string' and schema.get('format') == 'uuid': initial_path_params[name] = str(UUID(int=0)) # Example UUID
|
||||
elif param_type == 'string' and schema.get('format') == 'date': initial_path_params[name] = dt.date.today().isoformat()
|
||||
elif param_type == 'string' and schema.get('format') == 'date-time': initial_path_params[name] = dt.datetime.now().isoformat()
|
||||
else: initial_path_params[name] = f"param_{name}"
|
||||
self.logger.debug(f"Initial path param for '{operation_id}': {name} = {initial_path_params.get(name)}")
|
||||
|
||||
# 2. 处理查询参数
|
||||
query_param_specs = [p for p in parameters if p.get('in') == 'query']
|
||||
for param_spec in query_param_specs:
|
||||
name = param_spec.get('name')
|
||||
if not name: continue
|
||||
should_use_llm = self._should_use_llm_for_param_type("query_params", test_case_instance)
|
||||
if should_use_llm and self.llm_service:
|
||||
self.logger.info(f"Attempting LLM generation for query parameter '{name}' in '{operation_id}'")
|
||||
initial_query_params[name] = f"llm_query_{name}" # Placeholder
|
||||
else:
|
||||
if 'example' in param_spec:
|
||||
initial_query_params[name] = param_spec['example']
|
||||
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||
initial_query_params[name] = param_spec['schema']['example']
|
||||
elif 'default' in param_spec.get('schema', {}):
|
||||
initial_query_params[name] = param_spec['schema']['default']
|
||||
elif 'default' in param_spec:
|
||||
initial_query_params[name] = param_spec['default']
|
||||
else:
|
||||
initial_query_params[name] = f"query_val_{name}" # Simplified default
|
||||
self.logger.debug(f"Initial query param for '{operation_id}': {name} = {initial_query_params.get(name)}")
|
||||
|
||||
# 3. 处理请求头参数 (包括规范定义的和标准的 Content-Type/Accept)
|
||||
header_param_specs = [p for p in parameters if p.get('in') == 'header']
|
||||
for param_spec in header_param_specs:
|
||||
name = param_spec.get('name')
|
||||
if not name: continue
|
||||
# 标准头 Content-Type 和 Accept 会在后面专门处理
|
||||
if name.lower() in ['content-type', 'accept', 'authorization']:
|
||||
self.logger.debug(f"Skipping standard header '{name}' in parameter processing for '{operation_id}'. It will be handled separately.")
|
||||
continue
|
||||
|
||||
headers_data = {**default_headers, **headers_data} # 合并，缓存中的优先
|
||||
|
||||
self.logger.debug(f"[{operation_id}] (缓存加载) 准备的请求数据: method={method}, path_params={path_params_data}, query_params={query_params_data}, headers={list(headers_data.keys())}, body_type={type(body_data).__name__}")
|
||||
return method, path_params_data, query_params_data, headers_data, body_data
|
||||
should_use_llm = self._should_use_llm_for_param_type("headers", test_case_instance)
|
||||
if should_use_llm and self.llm_service:
|
||||
self.logger.info(f"Attempting LLM generation for header '{name}' in '{operation_id}'")
|
||||
initial_headers[name] = f"llm_header_{name}" # Placeholder
|
||||
else:
|
||||
if 'example' in param_spec:
|
||||
initial_headers[name] = str(param_spec['example'])
|
||||
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||
initial_headers[name] = str(param_spec['schema']['example'])
|
||||
elif 'default' in param_spec.get('schema', {}):
|
||||
initial_headers[name] = str(param_spec['schema']['default'])
|
||||
elif 'default' in param_spec:
|
||||
initial_headers[name] = str(param_spec['default'])
|
||||
else:
|
||||
initial_headers[name] = f"header_val_{name}"
|
||||
self.logger.debug(f"Initial custom header param for '{operation_id}': {name} = {initial_headers.get(name)}")
|
||||
|
||||
# 缓存未命中，需要生成参数
|
||||
self.logger.info(f"[{operation_id}] 端点 '{endpoint_cache_key}' 的参数未在缓存中找到，开始生成。")
|
||||
generated_params_for_endpoint: Dict[str, Any] = {}
|
||||
|
||||
path_params_data: Dict[str, Any] = {}
|
||||
query_params_data: Dict[str, Any] = {}
|
||||
headers_data_generated: Dict[str, Any] = {} # LLM或常规生成的，不含默认
|
||||
body_data: Optional[Any] = None
|
||||
# 3.1 设置 Content-Type
|
||||
# 优先从 requestBody.content 获取 (OpenAPI 3.x)
|
||||
request_body_spec = endpoint_spec.get('requestBody', {})
|
||||
if 'content' in request_body_spec:
|
||||
content_types = list(request_body_spec['content'].keys())
|
||||
if content_types:
|
||||
# 优先选择 application/json 如果存在
|
||||
initial_headers['Content-Type'] = next((ct for ct in content_types if 'json' in ct.lower()), content_types[0])
|
||||
elif 'consumes' in endpoint_spec: # 然后是 consumes (OpenAPI 2.0)
|
||||
consumes = endpoint_spec['consumes']
|
||||
if consumes:
|
||||
initial_headers['Content-Type'] = next((c for c in consumes if 'json' in c.lower()), consumes[0])
|
||||
elif method in ['POST', 'PUT', 'PATCH'] and not initial_headers.get('Content-Type'):
|
||||
initial_headers['Content-Type'] = 'application/json' # 默认对于这些方法
|
||||
self.logger.debug(f"Initial Content-Type for '{operation_id}': {initial_headers.get('Content-Type')}")
|
||||
|
||||
# 提取各类参数的定义列表
|
||||
path_params_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "path"]
|
||||
query_params_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "query"]
|
||||
headers_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "header"]
|
||||
request_body_spec = endpoint_spec.get("requestBody", {}).get("content", {}).get("application/json", {}).get("schema")
|
||||
# 3.2 设置 Accept
|
||||
# 优先从 responses.<code>.content 获取 (OpenAPI 3.x)
|
||||
responses_spec = endpoint_spec.get('responses', {})
|
||||
accept_header_set = False
|
||||
for code, response_def in responses_spec.items():
|
||||
if 'content' in response_def:
|
||||
accept_types = list(response_def['content'].keys())
|
||||
if accept_types:
|
||||
initial_headers['Accept'] = next((at for at in accept_types if 'json' in at.lower() or '*/*' in at), accept_types[0])
|
||||
accept_header_set = True
|
||||
break
|
||||
if not accept_header_set and 'produces' in endpoint_spec: # 然后是 produces (OpenAPI 2.0)
|
||||
produces = endpoint_spec['produces']
|
||||
if produces:
|
||||
initial_headers['Accept'] = next((p for p in produces if 'json' in p.lower() or '*/*' in p), produces[0])
|
||||
accept_header_set = True
|
||||
if not accept_header_set and not initial_headers.get('Accept'):
|
||||
initial_headers['Accept'] = 'application/json, */*' # 更通用的默认值
|
||||
self.logger.debug(f"Initial Accept header for '{operation_id}': {initial_headers.get('Accept')}")
|
||||
|
||||
# --- 1. 处理路径参数 ---
|
||||
param_type_key = "path_params"
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and path_params_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成路径参数。")
|
||||
object_schema, model_name = self._build_object_schema_for_params(path_params_spec_list, f"DynamicPathParamsFor_{operation_id}")
|
||||
if object_schema and model_name:
|
||||
try:
|
||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
||||
if PydanticModel:
|
||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
||||
PydanticModel,
|
||||
prompt_instruction=f"Generate valid path parameters for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
||||
)
|
||||
if isinstance(llm_generated, dict):
|
||||
path_params_data = llm_generated
|
||||
self.logger.info(f"[{operation_id}] LLM成功生成路径参数: {path_params_data}")
|
||||
else:
|
||||
self.logger.warning(f"[{operation_id}] LLM为路径参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
||||
else:
|
||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
||||
except Exception as e:
|
||||
self.logger.error(f"[{operation_id}] LLM生成路径参数失败: {e}。回退到常规生成。", exc_info=True)
|
||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
||||
else: # _build_object_schema_for_params 返回 None
|
||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
||||
else: # 不使用LLM或LLM服务不可用，或者 path_params_spec_list 为空但仍需确保path_params_data被赋值
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not path_params_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 配置为路径参数使用LLM，但没有定义路径参数规格。")
|
||||
# 对于不使用LLM或LLM不适用的情况，或者 spec_list 为空的情况，都执行常规生成（如果 spec_list 非空则会记录）
|
||||
if path_params_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为路径参数。")
|
||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
||||
generated_params_for_endpoint[param_type_key] = path_params_data
|
||||
# 4. 处理请求体 (Body)
|
||||
request_body_schema: Optional[Dict[str, Any]] = None
|
||||
# 确定请求体 schema 的来源，优先 OpenAPI 3.x 的 requestBody
|
||||
content_type_for_body_schema = initial_headers.get('Content-Type', 'application/json').split(';')[0].strip()
|
||||
|
||||
# --- 2. 处理查询参数 ---
|
||||
param_type_key = "query_params"
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and query_params_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成查询参数。")
|
||||
object_schema, model_name = self._build_object_schema_for_params(query_params_spec_list, f"DynamicQueryParamsFor_{operation_id}")
|
||||
if object_schema and model_name:
|
||||
try:
|
||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
||||
if PydanticModel:
|
||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
||||
PydanticModel,
|
||||
prompt_instruction=f"Generate valid query parameters for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
||||
)
|
||||
if isinstance(llm_generated, dict):
|
||||
query_params_data = llm_generated
|
||||
self.logger.info(f"[{operation_id}] LLM成功生成查询参数: {query_params_data}")
|
||||
else:
|
||||
self.logger.warning(f"[{operation_id}] LLM为查询参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
||||
else:
|
||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
||||
except Exception as e:
|
||||
self.logger.error(f"[{operation_id}] LLM生成查询参数失败: {e}。回退到常规生成。", exc_info=True)
|
||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
||||
else: # _build_object_schema_for_params 返回 None
|
||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
||||
else: # 不使用LLM或LLM服务不可用，或者 query_params_spec_list 为空
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not query_params_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 配置为查询参数使用LLM，但没有定义查询参数规格。")
|
||||
if query_params_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为查询参数。")
|
||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
||||
generated_params_for_endpoint[param_type_key] = query_params_data
|
||||
if 'content' in request_body_spec and content_type_for_body_schema in request_body_spec['content']:
|
||||
request_body_schema = request_body_spec['content'][content_type_for_body_schema].get('schema')
|
||||
elif 'parameters' in endpoint_spec: # OpenAPI 2.0 (Swagger) body parameter
|
||||
body_param = next((p for p in parameters if p.get('in') == 'body'), None)
|
||||
if body_param and 'schema' in body_param:
|
||||
request_body_schema = body_param['schema']
|
||||
|
||||
# --- 3. 处理头部参数 ---
|
||||
param_type_key = "headers"
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and headers_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成头部参数。")
|
||||
object_schema, model_name = self._build_object_schema_for_params(headers_spec_list, f"DynamicHeadersFor_{operation_id}")
|
||||
if object_schema and model_name:
|
||||
try:
|
||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
||||
if PydanticModel:
|
||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
||||
PydanticModel,
|
||||
prompt_instruction=f"Generate valid HTTP headers for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
||||
)
|
||||
if isinstance(llm_generated, dict):
|
||||
headers_data_generated = llm_generated # Store LLM generated ones separately first
|
||||
self.logger.info(f"[{operation_id}] LLM成功生成头部参数: {headers_data_generated}")
|
||||
else:
|
||||
self.logger.warning(f"[{operation_id}] LLM为头部参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
||||
else:
|
||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
||||
except Exception as e:
|
||||
self.logger.error(f"[{operation_id}] LLM生成头部参数失败: {e}。回退到常规生成。", exc_info=True)
|
||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
||||
else: # _build_object_schema_for_params 返回 None
|
||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
||||
else: # 不使用LLM或LLM服务不可用，或者 headers_spec_list 为空
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not headers_spec_list:
|
||||
self.logger.info(f"[{operation_id}] 配置为头部参数使用LLM，但没有定义头部参数规格。")
|
||||
if headers_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为头部参数。")
|
||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
||||
generated_params_for_endpoint[param_type_key] = headers_data_generated
|
||||
|
||||
# --- 4. 处理请求体 ---
|
||||
param_type_key = "body"
|
||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and request_body_spec:
|
||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成请求体。")
|
||||
model_name = f"DynamicBodyFor_{operation_id}"
|
||||
try:
|
||||
PydanticModel = self._create_pydantic_model_from_schema(request_body_spec, model_name)
|
||||
if PydanticModel:
|
||||
llm_generated_body = self.llm_service.generate_parameters_from_schema(
|
||||
PydanticModel,
|
||||
prompt_instruction=f"Generate a valid JSON request body for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}. Schema: {json.dumps(request_body_spec, indent=2)}"
|
||||
)
|
||||
if isinstance(llm_generated_body, dict):
|
||||
try:
|
||||
body_data = PydanticModel(**llm_generated_body).model_dump(by_alias=True)
|
||||
self.logger.info(f"[{operation_id}] LLM成功生成并验证请求体。")
|
||||
except ValidationError as ve:
|
||||
self.logger.error(f"[{operation_id}] LLM生成的请求体未能通过Pydantic模型验证: {ve}。回退到常规生成。")
|
||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
||||
elif isinstance(llm_generated_body, BaseModel): # LLM直接返回模型实例
|
||||
body_data = llm_generated_body.model_dump(by_alias=True)
|
||||
self.logger.info(f"[{operation_id}] LLM成功生成请求体 (模型实例)。")
|
||||
else:
|
||||
self.logger.warning(f"[{operation_id}] LLM为请求体返回了非预期类型: {type(llm_generated_body)}。回退到常规生成。")
|
||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
||||
else: # _create_pydantic_model_from_schema 返回 None
|
||||
self.logger.warning(f"[{operation_id}] 未能为请求体创建Pydantic模型。回退到常规生成。")
|
||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
||||
except Exception as e:
|
||||
self.logger.error(f"[{operation_id}] LLM生成请求体失败: {e}。回退到常规生成。", exc_info=True)
|
||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
||||
elif request_body_spec: # 不使用LLM但有body spec
|
||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用/不适用，为请求体。")
|
||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
||||
else: # 没有requestBody定义
|
||||
self.logger.info(f"[{operation_id}] 端点没有定义请求体。")
|
||||
body_data = None # 明确设为None
|
||||
generated_params_for_endpoint[param_type_key] = body_data
|
||||
if request_body_schema:
|
||||
should_use_llm_for_body = self._should_use_llm_for_param_type("body", test_case_instance)
|
||||
if should_use_llm_for_body and self.llm_service:
|
||||
self.logger.info(f"Attempting LLM generation for request body of '{operation_id}' with schema...")
|
||||
initial_body = self.llm_service.generate_data_from_schema(request_body_schema, endpoint_spec, "requestBody")
|
||||
if initial_body is None:
|
||||
self.logger.warning(f"LLM failed to generate request body for '{operation_id}'. Falling back to default schema generator.")
|
||||
initial_body = self._generate_data_from_schema(request_body_schema, context_name=f"{operation_id}_body", operation_id=operation_id)
|
||||
else:
|
||||
initial_body = self._generate_data_from_schema(request_body_schema, context_name=f"{operation_id}_body", operation_id=operation_id)
|
||||
self.logger.debug(f"Initial request body generated for '{operation_id}' (type: {type(initial_body)})")
|
||||
else:
|
||||
self.logger.debug(f"No request body schema found or applicable for '{operation_id}' with Content-Type '{content_type_for_body_schema}'. Initial body is None.")
|
||||
|
||||
# 合并最终的头部 (默认头部 + 生成的头部)
|
||||
final_headers = {"Accept": "application/json"}
|
||||
if body_data is not None and method not in ["GET", "DELETE", "HEAD", "OPTIONS"]:
|
||||
final_headers["Content-Type"] = "application/json"
|
||||
final_headers.update(headers_data_generated) # headers_data_generated 是从LLM或常规生成的
|
||||
|
||||
# 将本次生成的所有参数存入缓存
|
||||
self.llm_endpoint_params_cache[endpoint_cache_key] = generated_params_for_endpoint
|
||||
self.logger.info(f"[{operation_id}] 端点 '{endpoint_cache_key}' 的参数已生成并存入缓存。")
|
||||
|
||||
# 确保路径参数中的值都是字符串 (URL部分必须是字符串)
|
||||
path_params_data_str = {k: str(v) if v is not None else "" for k, v in path_params_data.items()}
|
||||
|
||||
self.logger.debug(f"[{operation_id}] (新生成) 准备的请求数据: method={method}, path_params={path_params_data_str}, query_params={query_params_data}, headers={list(final_headers.keys())}, body_type={type(body_data).__name__}")
|
||||
return method, path_params_data_str, query_params_data, final_headers, body_data
|
||||
# 构造并返回APIRequestContext
|
||||
return APIRequestContext(
|
||||
method=method,
|
||||
url=path_template, # 传递路径模板, e.g. /items/{itemId}
|
||||
path_params=initial_path_params,
|
||||
query_params=initial_query_params,
|
||||
headers=initial_headers,
|
||||
body=initial_body,
|
||||
endpoint_spec=endpoint_spec # 传递原始的 endpoint_spec 字典
|
||||
)
|
||||
|
||||
def _build_object_schema_for_params(self, params_spec_list: List[Dict[str, Any]], model_name_base: str) -> Tuple[Optional[Dict[str, Any]], str]:
|
||||
"""
|
||||
@@ -1490,4 +1465,34 @@ class APITestOrchestrator:
|
||||
self.logger.debug(f"{log_prefix}_generate_data_from_schema: 未知或不支持的 schema 类型 '{schema_type}' for{context_log}. Schema: {schema}")
|
||||
return None
|
||||
|
||||
def _format_url_with_path_params(self, path_template: str, path_params: Dict[str, Any]) -> str:
|
||||
"""
|
||||
使用提供的路径参数格式化URL路径模板。
|
||||
例如: path_template='/users/{userId}/items/{itemId}', path_params={'userId': 123, 'itemId': 'abc'}
|
||||
会返回 '/users/123/items/abc'
|
||||
同时处理 base_url.
|
||||
"""
|
||||
# 首先确保 path_template 不以 '/' 开头，如果 self.base_url 已经以 '/' 结尾
|
||||
# 或者确保它们之间只有一个 '/'
|
||||
formatted_path = path_template
|
||||
for key, value in path_params.items():
|
||||
placeholder = f"{{{key}}}"
|
||||
if placeholder in formatted_path:
|
||||
formatted_path = formatted_path.replace(placeholder, str(value))
|
||||
else:
|
||||
self.logger.warning(f"路径参数 '{key}' 在路径模板 '{path_template}' 中未找到占位符。")
|
||||
|
||||
# 拼接 base_url 和格式化后的路径
|
||||
# 确保 base_url 和 path 之间只有一个斜杠
|
||||
if self.base_url.endswith('/') and formatted_path.startswith('/'):
|
||||
url = self.base_url + formatted_path[1:]
|
||||
elif not self.base_url.endswith('/') and not formatted_path.startswith('/'):
|
||||
if formatted_path: # 避免在 base_url 后添加不必要的 '/' (如果 formatted_path 为空)
|
||||
url = self.base_url + '/' + formatted_path
|
||||
else:
|
||||
url = self.base_url
|
||||
else:
|
||||
url = self.base_url + formatted_path
|
||||
return url
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user