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Python的CSV阅读器和迭代

[英]Python's CSV reader and iteration

I have a CSV file that looks like this: 我有一个CSV文件,看起来像这样:

"Company, Inc.",,,,,,,,,,,,10/30/09
A/R Summary Aged Analysis Report,,,,,,,,,,,,10:35:01
All Clients,,,,,,,,,,,,USER

Client Account,Customer Name,15-Jan,16 - 30,31 - 60,61 - 90,91 - 120,120 - Over,Total,Status,Credit Limit
1000001111,CLIENT A,0,0,"3,711.32",0,0,"18,629.64","22,340.96",COD,"20,000.00"
1000002222,CLIENT B,0,0,0,"3,591.27",0,0,"3,591.27",COD,0
1000003333,CLIENT C,536.78,0,0,0,0,"11,216.60","11,753.38",COD,0
1000004444,CLIENT D,0,514.94,"3,147.45",690,0,0,"4,352.39",COD,0

Grand Total,,"139,203,856.06","84,607,749.30","110,746,640.18","58,474,379.45","52,025,869.06","292,653,734.82","737,712,228.87",,,,

But I only want to process the lines after the line "Client Account..." and before "Grand Total..." Here's the code that I'm using now: 但是我只想处理“客户帐户...”行之后和“总计...”行之前的行,这是我现在正在使用的代码:

inputFile = csv.reader(open(filename), dialect='excel')
records = [line for line in inputFile if line and line[0].isdigit()]

Via generators. 通过发电机。 You can build all kinds of complexity from simple generator-filter functions. 您可以从简单的生成器过滤器函数构建各种复杂性。 While considerably more complex than your filter, this is more extensible and can easily handle really complex spreadsheets. 尽管它比过滤器复杂得多,但它具有更高的可扩展性,可以轻松处理真正复杂的电子表格。

def skip_blank( rdr ):
    for row in rdr:
        if len(row) == 0: continue
        if all(len(col)==0 for col in row): continue
        yield row

def after_heading( text, rdr ):
    i= iter(rdr)
    for row in i:
        if any( column == text for column in row ):
            break
    for row in i:
        yield row

def before_footing( text, rdr ):
    for row in rdr:
        if any( column == text for column in row ):
            break
        yield row

def between( start, end, rdr ):
    for row in before_footing( end, after_heading( start, rdr ) ):
        yield row

for row in between( 'Grand Total', 'Client Account', skip_blank( inputFile ) ):
    print row

you can do it like this, by setting flag 您可以通过设置标志来做到这一点

import csv
file = "file"
f=0
reader = csv.reader(open(file),delimiter=',')
for row in reader:
    if "Grand Total" in row: break
    if "Client Account" in row: f=1;continue
    if f:
        if row[0].isdigit():
            print row
import re
import StringIO

data=re.search("Client Account[^\r\n]+[\r\n]+(.*)(?=Grand Total)",open(filename).read(),re.DOTALL).group(1)
datafile=StringIO.StringIO(data)

inputFile = csv.reader(datafile, dialect='excel')
records = [line for line in inputFile if line and line[0].isdigit()]

Use a nice little generator for something like this. 使用一个不错的小型生成器来处理类似这样的事情。 This one could be generalized a little more if your requirements change: 如果您的需求有所变化,则可以将其概括为:

def lines_between(source, first, second):
    for line in source:
        if line and line[0] == first:
            break

    for line in source:
        if line: and line[0] == second:
            break

        if line:  # only non-empty lines
            yield line

for record in lines_between(inputFile, 'Client Account', 'Grand Total'):
    # process record

You didn't ask explicitly for the "non-empty lines" filter, but your own approach was doing this so I assume you wanted it. 您没有明确要求使用“非空行”过滤器,但是您自己的方法正在执行此操作,因此我认为您需要这样做。 If you don't want to process the rows "lazily" like that, but just want a list with everything built in advance, do this: 如果您不想像这样“懒惰”地处理行,而只想要一个包含所有预先构建的内容的列表,请执行以下操作:

records = list(lines_between(inputFile, 'Client Account', 'Grand Total'))

By the way, on Windows, be sure to open the real source file using binary mode , with csv.reader(open(filename, 'rb'), dialect='excel') as the csv docs note . 顺便说一句,在Windows上,请确保使用二进制模式打开真实的源文件,并将csv.reader(open(filename, 'rb'), dialect='excel')作为csv docs note

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