我有一个文件,其中我提供了步骤,然后根据要遵循的内容的步骤。 这是我读到的文本文件:
[Steps]
step1 = WebAddress
step2 = Tab
step3 = SecurityType
step4 = Criteria
step5 = Date
step6 = Click1
step7 = Results
step8 = Download
[data]
WebAddress___________________________ Destination___________ Tab_____________ SecurityType___________________________________________________ Criteria___ Date_______ Click1_ Results_ Download
https://mbsdisclosure.fanniemae.com/ q:\\%s\\raw\\fnmapool Advanced Search Interim MBS: Single-Family Issue Date 09/01/2012 Search 100 CSV XML
https://mbsdisclosure.fanniemae.com/ q:\\%s\\raw\\fnmapool Advanced Search Preliminary Mega: Fannie Mae/Ginnie Mae backed Adjustable Rate Issue Date 09/01/2012 Search 100 CSV XML
https://mbsdisclosure.fanniemae.com/ q:\\%s\\raw\\fnmapool Advanced Search Preliminary Mega: Fannie Mae/Ginnie Mae backed Fixed Rate Issue Date 09/01/2012 Search 100 CSV XML
我已经有了一个工作模型来读取文件,然后将正确的内容分配给正确的标题(例如标题WebAdress的URL)。但是,我想要做的是遵循基于步骤的循环。 处理数据的代码:
from itertools import groupby
count =0
file_name = "FNMA.tbl"
with open(file_name) as f:
pre_data,post_data =[s.strip() for s in (f.read()).split("[data]")]
post_data_lines = post_data.splitlines()
headers = post_data_lines[0].split()
headers2 = [s.replace("_"," ").strip() for s in headers]
for line in post_data_lines[1:]:
tmpline = []
pos = 0
for itm in headers:
tmpline.append(line[pos:pos+len(itm)])
pos += len(itm)+1
myDict= dict(zip(headers2,tmpline))
count += 1
for key, group in groupby(myDict.iteritems(), lambda x: x[0]):
for thing in group:
print "step: %s header: %s" % (thing[1], key)
print "Finished processing row %s" % count
答案 0 :(得分:0)
首先,创建一个将步骤名称映射到数字的字典,如下所示:
steps = dict((step.split()[2], pos)
for (pos, step) in enumerate(pre_data.splitlines()[1:]))
(当然,这是一个非常丑陋的Python系列,但似乎有效)
现在,您可以按照以下步骤对词典中的项目进行排序:
sorted_items = sorted(myDict.items(),
key=lambda item: steps[item[0]] if item[0] in steps else 999)
迭代这些项目:
for key, thing in sorted_items:
print "step: %s header: %s" % (thing, key)