为什么win32com比xlrd慢得多？

Question

我有相同的代码，使用win32com和xlrd编写。 xlrd在不到一秒的时间内完成算法，而win32com需要几分钟的时间。

这里是win32com：

def makeDict(ws): 
"""makes dict with key as header name, 
    value as tuple of column begin and column end (inclusive)""" 
wsHeaders = {} # key is header name, value is column begin and end inclusive 
for cnum in xrange(9, find_last_col(ws)): 
    if ws.Cells(7, cnum).Value: 
     wsHeaders[str(ws.Cells(7, cnum).Value)] = (cnum, find_last_col(ws)) 
     for cend in xrange(cnum + 1, find_last_col(ws)): #finds end column 
      if ws.Cells(7, cend).Value: 
       wsHeaders[str(ws.Cells(7, cnum).Value)] = (cnum, cend - 1) 
       break 
return wsHeaders 

而且xlrd

def makeDict(ws): 
"""makes dict with key as header name, 
    value as tuple of column begin and column end (inclusive)""" 
wsHeaders = {} # key is header name, value is column begin and end inclusive 
for cnum in xrange(8, ws.ncols): 
    if ws.cell_value(6, cnum): 
     wsHeaders[str(ws.cell_value(6, cnum))] = (cnum, ws.ncols) 
     for cend in xrange(cnum + 1, ws.ncols):#finds end column 
      if ws.cell_value(6, cend): 
       wsHeaders[str(ws.cell_value(6, cnum))] = (cnum, cend - 1) 
       break 
return wsHeaders 

Answer 1

（0）您问“为什么win32com比xlrd慢得多？” ......这个问题有点像“你不再殴打你的妻子吗？” ---它是基于一个可能不是真的假设; win32com由一位出色的程序员用C语言编写，但是xlrd是由普通程序员用纯Python编写的。真正的区别在于win32com必须调用COM，其中涉及进程间通信和由you-know-who编写，而xlrd则直接读取Excel文件。此外，场景中还有第四方：您。请继续阅读。

（1）您不会向我们展示在COM代码中重复使用的find_last_col()函数的来源。在xlrd代码中，您总是乐意使用相同的值（ws.ncols）。所以在COM代码中，你应该调用find_last_col(ws) ONCE，然后使用返回的结果。 更新请参阅answer to your separate question关于如何从COM获取xlrd的Sheet.ncols的等效项。 （2）访问每个单元值TWICE正在减慢两个代码的速度。取而代之的

if ws.cell_value(6, cnum): 
    wsHeaders[str(ws.cell_value(6, cnum))] = (cnum, ws.ncols) 

尝试

value = ws.cell_value(6, cnum) 
if value: 
    wsHeaders[str(value)] = (cnum, ws.ncols) 

注：有每个代码片断2案件这一点。

（3）你的嵌套循环的目的并不明显，但似乎有一些冗余计算，涉及从COM冗余提取。如果你想通过例子告诉我们你想要达到的目标，我们可以帮助你使其运行得更快。至少，从COM中提取值然后在Python中嵌套循环中处理它们应该更快。有多少列？

更新2同时，小精灵走上与直肠镜你的代码，并与下面的脚本上来：

tests= [ 
    "A/B/C/D", 
    "A//C//", 
    "A//C//E", 
    "A///D", 
    "///D", 
    ] 
for test in tests: 
    print "\nTest:", test 
    row = test.split("/") 
    ncols = len(row) 
    # modelling the OP's code 
    # (using xlrd-style 0-relative column indexes) 
    d = {} 
    for cnum in xrange(ncols): 
     if row[cnum]: 
      k = row[cnum] 
      v = (cnum, ncols) #### BUG; should be ncols - 1 ("inclusive") 
      print "outer", cnum, k, '=>', v 
      d[k] = v 
      for cend in xrange(cnum + 1, ncols): 
       if row[cend]: 
        k = row[cnum] 
        v = (cnum, cend - 1) 
        print "inner", cnum, cend, k, '=>', v 
        d[k] = v 
        break 
    print d 
    # modelling a slightly better algorithm 
    d = {} 
    prev = None 
    for cnum in xrange(ncols): 
     key = row[cnum] 
     if key: 
      d[key] = [cnum, cnum] 
      prev = key 
     elif prev: 
      d[prev][1] = cnum 
    print d 
    # if tuples are really needed (can't imagine why) 
    for k in d: 
     d[k] = tuple(d[k]) 
    print d 

它输出这样的：因为它

Test: A/B/C/D 
outer 0 A => (0, 4) 
inner 0 1 A => (0, 0) 
outer 1 B => (1, 4) 
inner 1 2 B => (1, 1) 
outer 2 C => (2, 4) 
inner 2 3 C => (2, 2) 
outer 3 D => (3, 4) 
{'A': (0, 0), 'C': (2, 2), 'B': (1, 1), 'D': (3, 4)} 
{'A': [0, 0], 'C': [2, 2], 'B': [1, 1], 'D': [3, 3]} 
{'A': (0, 0), 'C': (2, 2), 'B': (1, 1), 'D': (3, 3)} 

Test: A//C// 
outer 0 A => (0, 5) 
inner 0 2 A => (0, 1) 
outer 2 C => (2, 5) 
{'A': (0, 1), 'C': (2, 5)} 
{'A': [0, 1], 'C': [2, 4]} 
{'A': (0, 1), 'C': (2, 4)} 

Test: A//C//E 
outer 0 A => (0, 5) 
inner 0 2 A => (0, 1) 
outer 2 C => (2, 5) 
inner 2 4 C => (2, 3) 
outer 4 E => (4, 5) 
{'A': (0, 1), 'C': (2, 3), 'E': (4, 5)} 
{'A': [0, 1], 'C': [2, 3], 'E': [4, 4]} 
{'A': (0, 1), 'C': (2, 3), 'E': (4, 4)} 

Test: A///D 
outer 0 A => (0, 4) 
inner 0 3 A => (0, 2) 
outer 3 D => (3, 4) 
{'A': (0, 2), 'D': (3, 4)} 
{'A': [0, 2], 'D': [3, 3]} 
{'A': (0, 2), 'D': (3, 3)} 

Test: ///D 
outer 3 D => (3, 4) 
{'D': (3, 4)} 
{'D': [3, 3]} 
{'D': (3, 3)} 

Answer 2

COM需要谈论其实际处理请求的另一个过程。 xlrd在数据结构本身上正在进行工作。

Answer 3

思想我昨晚要睡觉，并最终使用这个。一个远远超出我的原始版本：

def makeDict(ws): 
"""makes dict with key as header name, 
    value as tuple of column begin and column end (inclusive)""" 
wsHeaders = {} # key is header name, value is column begin and end inclusive 
last_col = find_last_col(ws) 

for cnum in xrange(9, last_col): 
    if ws.Cells(7, cnum).Value: 
     value = ws.Cells(7, cnum).Value 
     cstart = cnum 
    if ws.Cells(7, cnum + 1).Value: 
     wsHeaders[str(value)] = (cstart, cnum) #cnum is last in range 
return wsHeaders