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。

这是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

和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）你问“为什么win32com比xlrd慢得多？” ......这个问题有点像“你有没有停止殴打你的妻子？” ---它基于一个可能不正确的预设; win32com是由一位优秀的程序员用C语言编写的，但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您知道谁编写，而xlrd直接读取Excel文件。此外，场景中还有第四方：你。请继续阅读。

（1）您没有向我们展示您在COM代码中重复使用的find_last_col()函数的来源。在xlrd代码中，您很乐意一直使用相同的值（ws.ncols）。因此，在COM代码中，您应该调用find_last_col(ws) ONCE，然后使用返回的结果。更新请参阅answer to your separate question，了解如何从COM中获取xlrd Sheet.ncols的等效内容。

（2）访问每个单元格值TWICE正在减慢两个代码。而不是

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

试

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

注意：每个代码段中都有两种情况。

（3）你的嵌套循环的目的是什么并不明显，但似乎有一些冗余计算，涉及来自COM的冗余提取。如果您想通过示例告诉我们您要实现的目标，我们可以帮助您提高运行速度。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 与此同时，小精灵们使用直肠镜检查您的代码，并提出以下脚本：

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

输出：

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需要与另一个实际处理请求的进程通信。 xlrd在数据结构本身上进行处理。

Answer 3

在我昨晚睡觉的时候想到了它，最后还是用了这个。比原版更优越的版本：

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

为什么win32com比xlrd慢得多？

3 个答案: