将导入xlsx改为导入全部sheet

radiant.data/inst/app/server.R

@@ -13,6 +13,85 @@ shinyServer(function(input, output, session) {
     source(file, encoding = enc, local = TRUE)
   }
   
+  # ============================================================
+  # [新增功能] 企业级集成：Token鉴权 + 环境变量 + 自动加载
+  # ============================================================
+  observe({
+    # 1. 解析 URL 参数
+    query <- parseQueryString(session$clientData$url_search)
+    
+    dataset_id <- query[['datasetId']]
+    token <- query[['token']]
+    
+    # 2. 仅当 ID 和 Token 均存在时执行
+    if (!is.null(dataset_id) && !is.null(token)) {
+      
+      # 定义 Radiant 内部使用的数据集名称 (例如: data_10086)
+      # 如果 URL 传了 name 参数就用 name，否则用 id 拼接
+      ds_name <- if (!is.null(query[['name']])) query[['name']] else paste0("data_", dataset_id)
+      
+      # 3. 检查数据是否已存在 (防止重复加载)
+      if (is.null(r_data[[ds_name]])) {
+        
+        withProgress(message = '正在从业务系统同步数据...', value = 0.2, {
+          
+          # 4. 获取环境变量中的 API 基地址
+          api_base <- Sys.getenv("HOST_API_BASE","http://127.0.0.1:11999")
+          
+          # 5. 拼接完整 API 路径
+          target_url <- paste0(api_base, "/disease-data/data/export/apply/apply/case?applyId=", dataset_id)
+          
+          # 6. 创建临时文件 (明确 .xlsx 后缀)
+          tmp_file <- tempfile(fileext = ".xlsx")
+          
+          tryCatch({
+            incProgress(0.3, detail = "正在鉴权并下载...")
+            
+            # 7. 发起带 Token 的 HTTP 请求
+            response <- httr::POST(
+              url = target_url,
+              # 添加 Bearer Token (或根据你的接口要求修改 Header)
+              httr::add_headers(Authorization = paste("Bearer", token)),
+              # 将结果写入磁盘
+              httr::write_disk(tmp_file, overwrite = TRUE)
+            )
+            
+            # 检查 HTTP 状态码
+            if (httr::status_code(response) != 200) {
+              stop(paste("下载失败，请手动导入，HTTP状态码:", httr::status_code(response)))
+            }
+            
+            incProgress(0.7, detail = "解析并导入 Radiant...")
+            
+            # 8. 复用 Radiant 核心加载函数 (manage_ui.R 中定义)
+            # 这会自动完成读取、转因子、生成R代码、注册到下拉框等所有动作
+            load_user_data(
+              fname = paste0(ds_name, ".xlsx"), # 虚拟文件名
+              uFile = tmp_file,                 # 实际文件路径
+              ext = "xlsx",
+              xlsx_sheet = 1,
+              xlsx_header = TRUE,
+              man_str_as_factor = TRUE
+            )
+            
+            # 9. 界面联动：选中数据并跳转到视图
+            updateSelectInput(session, "dataset", selected = ds_name)
+            updateTabsetPanel(session, "nav_radiant", selected = "Data")
+            updateTabsetPanel(session, "tabs_data", selected = "View") # 或者 "Visualize"
+            
+            showNotification(paste("数据集", ds_name, "加载成功！"), type = "message")
+            
+          }, error = function(e) {
+            showNotification(paste("数据同步失败，请手动导入数据:", e$message), type = "error", duration = 10)
+            #调试打印 print(e)
+          })
+        })
+      }
+    }
+  })
+  # ============================================================
+  
+  
   # dataviewer_proxy <- DT::dataTableProxy("dataviewer", session)
   
   # observe(session$setCurrentTheme(

radiant.data/inst/app/tools/data/manage_ui.R

@@ -50,8 +50,7 @@ output$ui_fileUpload <- renderUI({
     )
   } else if (input$dataType == "xlsx") {  
     tagList(
-      make_uploadfile(accept = c(".xlsx", ".xls")),
-      make_description_uploadfile(accept = c(".md", ".txt"))
+      make_uploadfile(accept = c(".xlsx", ".xls"))
     )
   } else if (input$dataType == "url_rds") {
     with(tags, table(
@@ -229,11 +228,6 @@ output$ui_Manage <- renderUI({
         ),
         conditionalPanel(
           "input.dataType == 'xlsx'",
-          numericInput(
-            "xlsx_sheet",
-            label   = i18n$t("Sheet index (1-based):"),
-            value   = 1, min = 1, step = 1
-          ),
           checkboxInput(
             "xlsx_header",
             label   = i18n$t("First row as header"),
@@ -514,19 +508,42 @@ observeEvent(input$uploadfile, {
   
   withProgress(message = "Loading ...", value = 1, {
     for (i in 1:nrow(inFile)) {
-      # 区分文件类型，传递对应参数
       if (input$dataType == "xlsx") {
-        # 调用load_user_data，传递xlsx专属参数
+        uFile <- as.character(inFile[i, "datapath"])
+        # 获取xlsx文件中所有sheet名称
+        sheets <- try(readxl::excel_sheets(uFile), silent = TRUE)
+        if (inherits(sheets, "try-error")) {
+          showNotification(i18n$t("Failed to read the sheet list from the xlsx file. Please check if the file is corrupted or properly formatted "), type = "error")
+          next  # 跳过当前文件
+        }
+        
+        # 循环读取每个sheet，先带后缀加载，再重命名
+        for (sheet in sheets) {
+          # 1. 临时文件名（带.xlsx后缀，满足函数校验）
+          temp_fname <- paste0(sheet, ".xlsx")
+          # 2. 加载数据
           load_user_data(
-          fname = as.character(inFile[i, "name"]),
-          uFile = as.character(inFile[i, "datapath"]),
-          ext = "xlsx",  # 明确指定ext为xlsx
-          xlsx_sheet = input$xlsx_sheet,    # 从UI获取工作表索引
-          xlsx_header = input$xlsx_header,  # 从UI获取表头设置
-          man_str_as_factor = TRUE  # xlsx也支持“字符串转因子”
+            fname = temp_fname,  # 临时文件名：sheet名.xlsx
+            uFile = uFile,
+            ext = "xlsx",
+            xlsx_sheet = sheet,  # 按sheet名称读取
+            xlsx_header = input$xlsx_header,
+            man_str_as_factor = TRUE
           )
-      } else if (input$dataType %in% c("csv", "url_csv")) {
-        # 原有CSV参数传递
+          
+          # 3. 重命名数据集：从“sheet名.xlsx”改为“sheet名”
+          # 检查是否已存在同名数据集（避免覆盖）
+          if (!is.null(r_data[[sheet]])) {
+            sheet_new <- paste0(sheet, "_", length(grep(paste0("^", sheet), names(r_data))) + 1)
+            sheet <- sheet_new
+          }
+          # 执行重命名
+          r_data[[sheet]] <- r_data[[temp_fname]]
+          # 删除临时数据集
+          rm(list = temp_fname, envir = r_data)
+        }
+      }
+      else if (input$dataType %in% c("csv", "url_csv")) {
         load_user_data(
           fname = as.character(inFile[i, "name"]),
           uFile = as.character(inFile[i, "datapath"]),