481 lines
27 KiB
Python
481 lines
27 KiB
Python
import json
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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(__name__)
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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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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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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.
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# However, the recursive nature of _process_schema_or_ref should handle nested $refs.
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pass # Assume it's processed by the main call to _process_schema_or_ref on param_data_raw
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elif "content" in processed_param_container: # Parameter described by Content Object (OpenAPI 3.x)
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pass # Content object schemas should have been resolved by _process_schema_or_ref
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endpoint_data["parameters"].append(processed_param_container)
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# Process requestBody
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if "requestBody" in self._raw_data and isinstance(self._raw_data["requestBody"], dict):
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processed_rb = self._process_schema_or_ref(self._raw_data["requestBody"])
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if processed_rb:
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endpoint_data["requestBody"] = processed_rb
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# Process responses
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if "responses" in self._raw_data and isinstance(self._raw_data["responses"], dict):
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for status_code, resp_data_raw in self._raw_data["responses"].items():
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processed_resp = self._process_schema_or_ref(resp_data_raw)
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if processed_resp:
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endpoint_data["responses"][status_code] = processed_resp
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elif resp_data_raw: # If processing failed but raw exists, keep raw (though this is less ideal)
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endpoint_data["responses"][status_code] = resp_data_raw
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logger.warning(f"Kept raw response data for {status_code} due to processing failure for {self.operation_id or self.path}")
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if not endpoint_data["responses"]: # Ensure default response if none processed
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endpoint_data["responses"]["default"] = {"description": "Default response from Swagger/OpenAPI definition"}
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return endpoint_data
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def __repr__(self):
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return f"<SwaggerEndpoint Method:{self.method} Path:{self.path} Summary:'{self.summary}'>"
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class ParsedAPISpec:
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"""解析后的API规范的通用基类"""
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def __init__(self, spec_type: str, endpoints: List[Union[YAPIEndpoint, SwaggerEndpoint]], spec: Dict[str, Any]):
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self.spec_type = spec_type
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self.endpoints = endpoints
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self.spec = spec # Store the original full spec dictionary, useful for $ref resolution if not pre-resolved
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class ParsedYAPISpec(ParsedAPISpec):
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"""解析后的YAPI规范"""
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def __init__(self, endpoints: List[YAPIEndpoint], categories: List[Dict[str, Any]], spec: Dict[str, Any]):
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super().__init__(spec_type="yapi", endpoints=endpoints, spec=spec)
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self.categories = categories
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class ParsedSwaggerSpec(ParsedAPISpec):
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"""解析后的Swagger/OpenAPI规范"""
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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:
|
||
"""负责解析输入（如YAPI JSON）并提取API端点信息"""
|
||
def __init__(self):
|
||
self.logger = logging.getLogger(__name__)
|
||
|
||
def parse_yapi_spec(self, file_path: str) -> Optional[ParsedYAPISpec]:
|
||
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:
|
||
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
|
||
|
||
for category_data in raw_spec_data_list:
|
||
if not isinstance(category_data, dict):
|
||
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})
|
||
|
||
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
|
||
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:
|
||
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]:
|
||
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:
|
||
# 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
|
||
|
||
swagger_tags = raw_spec_data_dict.get("tags", [])
|
||
paths = raw_spec_data_dict.get("paths", {})
|
||
|
||
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:
|
||
self.logger.error(f"An unexpected error occurred while parsing Swagger spec {file_path}: {e}", exc_info=True)
|
||
return None |