运行delphi客户端自动化程序后excel.exe保持加载的原因？

Question

我编写了一个Delphi程序，它将单个.XLS文件的几个不同电子表格中的数据提取并合并到一个文本文件中，以便以后处理。这是一个Delphi 7 控制台程序。

最相关的代码段的摘录将向您展示，显然，我的程序表现得非常好，或者至少与它需要的程序一样多。

uses ...  ActiveX, ComObj ... ;

procedure Fatal(s:string);
  ...
  Halt(1);

var ExcelApp:Variant; (* global var *)

begin (* main program block *)
  coInitialize(nil);
  ExcelApp:=CreateOleObject('Excel.Application');
  try
    ExcelApp.Visible:=False;
    ExcelApp.WorkBooks.Open(ExcelFileName);
  ...
    XLSSheet := ExcelApp.Worksheets[ExcelSheetName];
  ...
    try
      XLSRange := XLSSheet.Range[ExcelRangeName];
    except
      Fatal('Range "'+ExcelRangeName+'" not found');
    end;
    if VarIsNull(XLSRange) then Fatal('Range '+ExcelRangeName+' not found');
    for row:=XLSRange.Row to XLSRange.Rows[XLSRange.Rows.Count].Row do
      for col:=XLSRange.Column to XLSRange.Columns[XLSRange.Columns.Count].Column do
        CellValue:=XLSSheet.Cells[Row,Col].Value;
        ...
        if CellValue<>'' then ...
        ...
    ExcelApp.Workbooks.Close;
    ...
  finally
    ExcelApp.Quit;
    coUninitialize;
  end;   
end.

有时，当程序退出时，XLS仍然处于锁定状态。查看任务管理器，我看到客户端程序运行时启动的Excel.exe进程仍在运行，客户端程序已退出并成功卸载。

你碰巧知道这种行为的常见嫌疑人是什么？想知道在客户端执行时总是在哪里寻找excel？

Answer 1

您需要发布ExcelApp变体。它仍然保持引用计数为1，因此Excel不会完全关闭。

将此添加到您的代码（标记的行）：

finally
  ExcelApp.Quit;
  ExcelApp := Unassigned;        // Add this line
  coUninitialize;
end;  

以下是一些重现问题的简单代码，并测试解决方案：

// Add two buttons to a form, and declare a private form field. 
// Add OnClick handlers to the two buttons, and use the code provided. 
// Run the app, and click Button1. Wait until Excel is shown, and then click
// Button2 to close it. See the comments in the Button2Click event handler.
type
  TForm1=class(TForm)
    Button1: TButton;
    Button2: TButton;
    procedure Button1Click(Sender: TObject);
    procedure Button2Click(Sender: TObject);
  private
    ExcelApp: Variant;
  end;

implementation

uses
  ComObj;

procedure TForm1.Button1Click(Sender: TObject);
begin
  ExcelApp := CreateOleObject('Excel.Application');
  ExcelApp.Visible := True;
end;

procedure TForm1.Button2Click(Sender: TObject);
begin
  ExcelApp.Visible := False;
  ExcelApp.Quit;

  // Leave the next line commented, run the app, and click the button.
  // After exiting your app NORMALLY, check Task Manager processes, and you'll
  // see an instance of Excel.exe still running, even though it's not
  // in the Applications tab. 
  //
  // Do an "end process" in Task Manager to remove the orphaned instance 
  // of Excel.exe left from the above. Uncomment the next line of code
  // and repeat the process, again closing your app normally after clicking
  // Button2. You'll note that Excel.exe is no longer in
  // Task Manager Processes after closing your app.

  // ExcelApp := Unassigned;
end;

end.

Answer 2

我在XE2中遇到了同样的问题，我的解决方案是替换这样的代码示例：

fExcel.ActiveWorkBook.ActiveSheet.Range[
    fExcel.ActiveWorkBook.ActiveSheet.Cells[3, 2],
    fExcel.ActiveWorkBook.ActiveSheet.Cells[3+i,1+XL_PT_Tip_FieldCount]
].Formula := VarArr;

使用：

cl := fExcel.ActiveWorkBook.ActiveSheet.Cells[3, 2];
ch := fExcel.ActiveWorkBook.ActiveSheet.Cells[3+i,1+XL_PT_Tip_FieldCount];
fExcel.ActiveWorkBook.ActiveSheet.Range[cl, ch].Formula := VarArr;

在这种情况下也会发生相同的情况，其中使用了工作表变量：

sheetDynamicHb := fExcel.ActiveWorkBook.Sheets['Dynamics Hb'];
cl := sheetDynamicHb.Cells[52, 2];
ch := sheetDynamicHb.Cells[52+i, 2+3];
sheetDynamicHb.Range[cl, ch].Formula := VarArr;

以某种方式引入临时变量（cl,ch: Variant）就可以了。似乎嵌套的Excel变量访问做了一些奇怪的事情。我无法解释为什么会这样，但确实有效..

Answer 3

我在试图关闭＆＃34; zombie＆＃34;时遇到了同样的问题。 Excel进程（如果我从我的应用程序启动它们然后强制终止应用程序，则保持运行）我尝试了所有建议的行动而没有​​运气。最后，我创建了一个组合杀手程序，如果通常的COM方法没有帮助，可以使用WinApi强有力地完成这个技巧。

library(grid)
library(ggplot2)


sensor.data <- read.csv("/home/oskar/Downloads/Sample_Dataset.csv - Sample_Dataset.csv.csv") 

# Create position -> coord conversion 
pos.names <- names(sensor.data)[ grep("*Pos",names(sensor.data)) ] # Get column names with "Pos" in them 
mock.coords <- list ("Position1"=data.frame("x"=0.1,"y"=0.2), 
                     "Position2"=data.frame("x"=0.2,"y"=0.4), 
                     "Position3"=data.frame("x"=0.3,"y"=0.6), 
                     "Position4"=data.frame("x"=0.4,"y"=0.65), 
                     "Position5"=data.frame("x"=0.5,"y"=0.75), 
                     "Position6"=data.frame("x"=0.6,"y"=0.6), 
                     "Position7"=data.frame("x"=0.7,"y"=0.6), 
                     "Position8"=data.frame("x"=0.8,"y"=0.43), 
                     "Position8.1"=data.frame("x"=0.85,"y"=0.49), 
                     "Position9"=data.frame("x"=0.9,"y"=0.27), 
                     "Position10"=data.frame("x"=0.75,"y"=0.12))

# Change format of your data matrix 
df.l <- list() 
cnt <- 1 

for (i in 1:nrow(sensor.data)){ 
  for (j in 1:length(pos.names)){ 
    name <- pos.names[j] 
    curr.coords <- mock.coords[[name]] 
    df.l[[cnt]] <- data.frame("x.pos"=curr.coords$x, 
                              "y.pos"=curr.coords$y, 
                              "heat" =sensor.data[i,j]) 
    cnt <- cnt + 1 
  } 
} 

df <- do.call(rbind, df.l) 

# Load image 
library(jpeg)
download.file("http://www.expresspcb.com/wp-content/uploads/2015/06/PhotoProductionPCB_TL_800.jpg","pcb.jpg")
img <- readJPEG("/home/oskar/pcb.jpg")
g <- rasterGrob(img, interpolate=TRUE,width=1,height=1) 

# Manually set number of rows and columns in the matrix containing max of heat for each square in grid
nrows <- 50
ncols <- 50

# Define image coordinate ranges
x.range <- c(0,1) # x-coord range
y.range <- c(0,1) # x-coord range

x.bounds <- seq(from=min(x.range),to=max(x.range),length.out = ncols + 1)
y.bounds <- seq(from=min(y.range),to=max(y.range),length.out = nrows + 1)

# Create matrix and set all entries to 0
heat.max.dat <<- matrix(nrow=nrows,ncol=ncols)

lapply(1:length(mock.coords), function(i){
  c <- mock.coords[[i]]
  # calculate where in matrix this fits
  x <- c$x; y <- c$y
  x.ind <- findInterval(x, x.bounds)
  y.ind <- findInterval(y, y.bounds)
  heat.max.dat[x.ind,y.ind] <<- max(sensor.data[names(mock.coords)[i]])
})
heat.max.dat[is.na(heat.max.dat)]<-0

require(fields)
# Look at the image plots to see how the smoothing works
#image(heat.max.dat)
h.mat.interp <- image.smooth(heat.max.dat)
#image(h.mat.interp$z)

mat <- h.mat.interp$z

require(reshape2)
m.dat <- melt(mat)
# Change to propper coors, image is assumed to have coors between 0-1
m.dat$Var1 <-  seq(from=min(x.range),to=max(x.range),length.out=ncols)[m.dat$Var1]
m.dat$Var2 <-  seq(from=min(y.range),to=max(y.range),length.out=ncols)[m.dat$Var2]

# Show where max temperature is 
heat.dat <- sensor.data[pos.names] 

# Get max for each position 
max.df <- apply(heat.dat,2,max) 
dat.max.l <- lapply(1:length(max.df), function(i){ 
  h.val <- max.df[i] 
  c.name <- names(h.val) 
  c.coords <- mock.coords[[c.name]] 
  data.frame("x.pos"=c.coords$x, "y.pos"=c.coords$y,"heat"=h.val) 
}) 

dat.max <- do.call(rbind,dat.max.l) 

coords <- data.frame("x"=c(0,1),"y"=c(0,1)) 
ggplot(data=coords,aes(x=x,y=y)) + 
  annotation_custom(g, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
  geom_raster(data=m.dat,aes(x=Var1,y=Var2,fill=value), interpolate = TRUE, alpha=0.5) + 
  scale_fill_gradientn(colours = rev( rainbow(3) ),guide=FALSE) +
  geom_text(data=dat.max,aes(x=x.pos,y=y.pos,label=round(heat,3)),vjust=0,color="white",size=5) +
  scale_x_continuous(expand=c(0,0)) + 
  scale_y_continuous(expand=c(0,0))