203 lines
5.6 KiB
R
203 lines
5.6 KiB
R
# plumber.R
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# SSA-Pro R Statistics Service 入口文件
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#
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# 安全与性能优化：
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# - 生产环境预加载所有工具脚本
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# - tool_code 白名单正则校验（防止路径遍历攻击）
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library(plumber)
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library(jsonlite)
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# 环境配置
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DEV_MODE <- Sys.getenv("DEV_MODE", "false") == "true"
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# 加载公共函数
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source("utils/error_codes.R")
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source("utils/data_loader.R")
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source("utils/guardrails.R")
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source("utils/result_formatter.R")
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# 工具目录
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tools_dir <- "tools"
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tool_files <- list.files(tools_dir, pattern = "\\.R$", full.names = TRUE)
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# ========== 生产环境预加载优化 ==========
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# 在服务启动时预加载所有工具脚本到独立环境
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# 避免每次请求都从磁盘读取和解析
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# 工具缓存环境
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TOOL_CACHE <- new.env(parent = emptyenv())
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# 预加载函数
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preload_tools <- function() {
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message("[Init] 预加载工具脚本...")
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for (f in tool_files) {
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tool_name <- tools::file_path_sans_ext(basename(f))
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# 创建独立环境加载工具
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tool_env <- new.env(parent = globalenv())
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source(f, local = tool_env)
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# 检查是否实现了 run_analysis
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if (exists("run_analysis", envir = tool_env, mode = "function")) {
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TOOL_CACHE[[tool_name]] <- tool_env$run_analysis
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message(paste("[Init] 已加载:", tool_name))
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} else {
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warning(paste("[Init] 工具缺少 run_analysis 函数:", tool_name))
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}
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}
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message(paste("[Init] 预加载完成，共", length(ls(TOOL_CACHE)), "个工具"))
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}
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# 生产环境：启动时预加载
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# 开发环境：跳过（支持热重载）
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if (!DEV_MODE) {
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preload_tools()
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} else {
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message("[Init] DEV_MODE 启用，跳过预加载（支持热重载）")
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# 开发模式仍需首次加载
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for (f in tool_files) source(f)
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}
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# ========== 安全校验函数 ==========
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#' 校验 tool_code 格式（防止路径遍历攻击）
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#' @param tool_code 工具代码
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#' @return TRUE 如果格式合法，否则 FALSE
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validate_tool_code <- function(tool_code) {
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# 只允许：大写字母、数字、下划线
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# 有效示例：ST_T_TEST_IND, ST_ANOVA, T_TEST_IND
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# 无效示例：../etc/passwd, ST_TEST;rm -rf
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pattern <- "^[A-Z][A-Z0-9_]*$"
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return(grepl(pattern, tool_code))
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}
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#' 将 tool_code 转换为工具名（小写，去除 ST_ 前缀）
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#' @param tool_code 例如 "ST_T_TEST_IND"
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#' @return 例如 "t_test_ind"
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normalize_tool_name <- function(tool_code) {
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name <- tolower(gsub("^ST_", "", tool_code))
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return(name)
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}
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# ========== API 定义 ==========
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#* @apiTitle SSA-Pro R Statistics Service
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#* @apiDescription 严谨型统计分析 R 引擎
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#* 健康检查
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#* @get /health
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function() {
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list(
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status = "ok",
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timestamp = Sys.time(),
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version = "1.0.1",
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dev_mode = DEV_MODE,
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tools_loaded = if (DEV_MODE) length(tool_files) else length(ls(TOOL_CACHE))
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)
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}
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#* 列出已加载的工具
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#* @get /api/v1/tools
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function() {
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if (DEV_MODE) {
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tools <- gsub("\\.R$", "", basename(tool_files))
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} else {
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tools <- ls(TOOL_CACHE)
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}
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list(
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status = "ok",
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tools = tools,
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count = length(tools)
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)
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}
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#* 执行统计工具
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#* @post /api/v1/skills/<tool_code>
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#* @param tool_code:str 工具代码（如 ST_T_TEST_IND）
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#* @serializer unboxedJSON
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function(req, tool_code) {
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tryCatch({
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# ===== 安全校验：tool_code 白名单 =====
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if (!validate_tool_code(tool_code)) {
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return(list(
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status = "error",
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error_code = "E400",
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message = "Invalid tool code format",
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user_hint = "工具代码格式错误，只允许大写字母、数字和下划线"
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))
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}
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# 解析请求体
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input <- jsonlite::fromJSON(req$postBody, simplifyVector = FALSE)
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# Debug 模式：保留临时文件用于排查
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debug_mode <- isTRUE(input$debug)
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# 统一入口函数名
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func_name <- "run_analysis"
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# 标准化工具名
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tool_name <- normalize_tool_name(tool_code)
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tool_file <- file.path("tools", paste0(tool_name, ".R"))
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# ===== 根据环境选择加载策略 =====
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if (DEV_MODE) {
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# 开发环境：每次请求重新加载（支持热重载）
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if (!file.exists(tool_file)) {
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return(list(
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status = "error",
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error_code = "E100",
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message = paste("Unknown tool:", tool_code),
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user_hint = "请检查工具代码是否正确"
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))
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}
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source(tool_file)
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if (!exists(func_name, mode = "function")) {
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return(list(
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status = "error",
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error_code = "E100",
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message = paste("Tool", tool_code, "does not implement run_analysis()"),
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user_hint = "工具脚本格式错误，请联系管理员"
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))
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}
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# 执行分析
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result <- do.call(func_name, list(input))
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} else {
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# 生产环境：从缓存加载
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if (!exists(tool_name, envir = TOOL_CACHE)) {
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return(list(
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status = "error",
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error_code = "E100",
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message = paste("Unknown tool:", tool_code),
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user_hint = "请检查工具代码是否正确，或联系管理员确认工具已部署"
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))
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}
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# 从缓存获取函数并执行
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cached_func <- TOOL_CACHE[[tool_name]]
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result <- cached_func(input)
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}
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# Debug 模式：附加临时文件路径
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if (debug_mode && !is.null(result$tmp_files)) {
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result$debug_files <- result$tmp_files
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message("[DEBUG] 临时文件已保留: ", paste(result$tmp_files, collapse = ", "))
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}
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return(result)
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}, error = function(e) {
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# 使用友好错误映射
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return(map_r_error(e$message))
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})
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}
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