如何使用regex / python将顺序组织的多行字符串解析为数据结构？

Question

我需要将多行字符串解析为包含（1）标识符和（2）标识符后面的文本（但在下一个>符号之前）的数据结构。 标识符总是在它自己的行上，但文本可以占用多行。

>identifier1
lalalalalalalalalalalalalalalalala
>identifier2 
bababababababababababababababababa
>identifier3
wawawawawawawawawawawawawawawawawa

执行后我可能有这样的数据结构：

id = ['identifier1', 'identifier2', 'identifier3']

和

txt = 
['lalalalalalalalalalalalalalalalala',
 'bababababababababababababababababa', 
 'wawawawawawawawawawawawawawawawawa']

似乎我想使用正则表达式来查找（1）之后的东西，但在回车之前，以及（2）之间的事情，暂时删除标识符字符串和EOL，替换为“”。

问题是我将拥有数百个这样的标识符，所以我需要按顺序运行正则表达式。 关于如何解决这个问题的任何想法？ 我在python中工作，但随时可以在您的回复中使用您想要的任何语言。

* 更新1：来自slater的代码越来越接近，但事情仍未按顺序分为id，text，id，text等*

teststring = '''>identifier1
lalalalalalalalalalalalalalalalala
>identifier2
bababababababababababababababababa
>identifier3
wawawawawawawawawawawawawawawawawa'''

# First, split the text into relevant chunks
split_text = teststring.split('>')

#see where we are after split
print split_text

#remove spaces that will mess up the partitioning
while '' in split_text:
    split_text.remove('')

#see where we are after removing '', before partitioning
print split_text

id = [text.partition(r'\n')[0] for text in split_text]
txt = [text.partition(r'\n')[0] for text in split_text]

#see where we are after partition
print id
print txt
print len(split_text)
print len(id)

但输出是：

['', 'identifier1\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa']
['identifier1\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa']
['identifier1\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa']
['identifier1\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa']
3
3

注意：它需要为多行字符串工作，处理所有\\ n的。 一个更好的测试用例可能是：

teststring = '''
>identifier1
lalalalalalalalalalalalalalalalala
lalalalalalalalalalalalalalalalala
>identifier2
bababababababababababababababababa
bababababababababababababababababa
>identifier3
wawawawawawawawawawawawawawawawawa
wawawawawawawawawawawawawawawawawa'''

# First, split the text into relevant chunks
split_text = teststring.split('>')

#see where we are after split
print split_text

#remove spaces that will mess up the partitioning
while '' in split_text:
    split_text.remove('')

#see where we are after removing '', before partitioning
print split_text

id = [text.partition(r'\n')[0] for text in split_text]
txt = [text.partition(r'\n')[0] for text in split_text]

#see where we are after partition
print id
print txt
print len(split_text)
print len(id)

电流输出：

['\n', 'identifier1\nlalalalalalalalalalalalalalalalala\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa\nwawawawawawawawawawawawawawawawawa']
['\n', 'identifier1\nlalalalalalalalalalalalalalalalala\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa\nwawawawawawawawawawawawawawawawawa']
['\n', 'identifier1\nlalalalalalalalalalalalalalalalala\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa\nwawawawawawawawawawawawawawawawawa']
['\n', 'identifier1\nlalalalalalalalalalalalalalalalala\nlalalalalalalalalalalalalalalalala\n', 'identifier2\nbababababababababababababababababa\nbababababababababababababababababa\n', 'identifier3\nwawawawawawawawawawawawawawawawawa\nwawawawawawawawawawawawawawawawawa']
4
4

Answer 1

就个人而言，我觉得你应该尽可能少地使用正则表达式。 它很慢，难以维护，而且通常难以理解。

也就是说，在python中解决这个问题非常简单。 通过“按顺序”运行，我有点不清楚你究竟是什么意思，但请告诉我这个解决方案是否符合您的需求。

# First, split the text into relevant chunks
split_text = text.split('>')
id = [text.partition('\n')[0] for text in split_text]
txt = [text.partition('\n')[2] for text in split_text]

显然，您可以使代码更有效，但如果您只处理数百个标识符，则实际上不需要它。

如果要删除可能出现的任何空白条目，可以执行以下操作：

list_with_blanks = ['', 'hello', '', '', 'world']
filter(None, list_with_blanks)
>>> ['hello', 'world']

如果您还有其他问题，请与我们联系。

Answer 2

除非我误解了这个问题，否则它就像

for line in your_file:
    if line.startswith('>'):
        id.append(line[1:].strip())
    else:
        text.append(line.strip())

编辑：连接多行：

ids, text = [], []
for line in teststring.splitlines():
    if line.startswith('>'):
        ids.append(line[1:])
        text.append('')
    elif text:
        text[-1] += line

Answer 3

我找到了解决方案。 它肯定不是非常pythonic但它的工作原理。

================================================== ====================

================================================== ====================

teststring = '''
>identifier1
lalalalalalalalalalalalalalalalala\n
lalalalalalalalalalalalalalalalala\n
>identifier2
bababababababababababababababababa\n
bababababababababababababababababa\n
>identifier3
wawawawawawawawawawawawawawawawawa\n
wawawawawawawawawawawawawawawawawa\n'''

i = 0
j = 0

#split the multiline string by line
dsplit = teststring.split('\n')

#the indicies of identifiers
index = list()

for line in dsplit:
    if line.startswith('>'):
        print line
        index.append(i)
        j = j + 1
    i = i+1
index.append(i)  #add this so you get the last block of text

#the text corresponding to each index
thetext = list()
#the names corresponding to each gene
thenames = list()
for n in range(0, len(index)-1):
    thetext.append("")
    for k in range(index[n]+1, index[n+1]):
        thetext[n] = thetext[n] + dsplit[k]
    thenames.append(dsplit[index[n]][1:]) # the [1:] removes the first character (>) from the line
print "the indicies", index
print "the text: ", thetext
print "the names", thenames
print "this many text entries: ", len(thetext)
print "this many index entries: ", j

这给出了以下输出：

>identifier1
>identifier2
>identifier3
the indicies [1, 6, 11, 16]
the text:  ['lalalalalalalalalalalalalalalalalalalalalalalalalalalalalalalalalala', 'babababababababababababababababababababababababababababababababababa', 'wawawawawawawawawawawawawawawawawawawawawawawawawawawawawawawawawawa']
the names ['identifier1', 'identifier2', 'identifier3']
this many text entries:  3
this many index entries:  3