小编alv*_*vas的帖子

在过去,有codecs被取代的io.虽然看起来它更适合使用io.open,但大多数入门级python类仍在教授open.

在Python中open和codecs.open之间有区别的问题,但它open只是一种鸭子类型io.open？

如果没有,为什么使用更好io.open？为什么教学更容易open？

在这篇文章中(http://code.activestate.com/lists/python-list/681909/),Steven DAprano说内置的open是io.open在后端使用.那么我们是否应该重构我们的代码open而不是io.open？

除了py2.x的向后兼容性之外,是否有任何理由io.open而不是open在py3.0中使用？

Lucene有一个默认的stopfilter(http://lucene.apache.org/core/4_0_0/analyzers-common/org/apache/lucene/analysis/core/StopFilter.html),有谁知道列表中哪些是单词？

哪一个会更好:

sed -e '/^$/d' *.txt
sed 'g/^$/d' -i *.txt

另外,如何从文本文件中每行的开头和结尾删除空格？

这个问题与来自python中的基类的Inherit namedtuple相反,其目的是从namedtuple继承子类,反之亦然.

在正常继承中,这有效:

class Y(object):
    def __init__(self, a, b, c):
        self.a = a
        self.b = b
        self.c = c


class Z(Y):
    def __init__(self, a, b, c, d):
        super(Z, self).__init__(a, b, c)
        self.d = d

[OUT]:

>>> Z(1,2,3,4)
<__main__.Z object at 0x10fcad950>

但如果基类是namedtuple:

from collections import namedtuple

X = namedtuple('X', 'a b c')

class Z(X):
    def __init__(self, a, b, c, d):
        super(Z, self).__init__(a, b, c)
        self.d = d

[OUT]:

>>> Z(1,2,3,4)
Traceback (most recent call …

现在我一直在尝试在字符串列表上执行strip(),我这样做了:

i = 0
for j in alist:
    alist[i] = j.strip()
    i+=1

有没有更好的方法呢？

如果元素与子字符串匹配,如何从列表中删除元素？

我尝试使用pop()和enumerate方法从列表中删除元素,但似乎我缺少一些需要删除的连续项:

sents = ['@$\tthis sentences needs to be removed', 'this doesnt',
     '@$\tthis sentences also needs to be removed',
     '@$\tthis sentences must be removed', 'this shouldnt',
     '# this needs to be removed', 'this isnt',
     '# this must', 'this musnt']

for i, j in enumerate(sents):
  if j[0:3] == "@$\t":
    sents.pop(i)
    continue
  if j[0] == "#":
    sents.pop(i)

for i in sents:
  print i

输出:

this doesnt
@$  this sentences must be removed
this shouldnt
this isnt
#this should …

使用gensim我能够从LSA中的一组文档中提取主题但是如何访问从LDA模型生成的主题？

打印lda.print_topics(10)代码时出现以下错误,因为print_topics()返回a NoneType:

Traceback (most recent call last):
  File "/home/alvas/workspace/XLINGTOP/xlingtop.py", line 93, in <module>
    for top in lda.print_topics(2):
TypeError: 'NoneType' object is not iterable

代码:

from gensim import corpora, models, similarities
from gensim.models import hdpmodel, ldamodel
from itertools import izip

documents = ["Human machine interface for lab abc computer applications",
              "A survey of user opinion of computer system response time",
              "The EPS user interface management system",
              "System and human system engineering testing of …

我正在使用Vader SentimentAnalyzer获取极性分数.之前我使用了正/负/中性的概率分数,但我刚刚意识到"复合"分数,范围从-1(大多数负)到1(大多数pos)将提供单一的极性测量.我想知道如何计算"复合"分数.这是从[pos,neu,neg]向量计算的吗？

当我分块文本时,我在输出中得到了很多代码 NN, VBD, IN, DT, NNS, RB.是否有某个列表记录在哪里告诉我这些的含义？我试过谷歌搜索nltk chunk code nltk chunk grammar nltk chunk tokens.

但我无法找到任何解释这些代码含义的文档.

首先,让我们每个文档每个术语提取TF-IDF分数:

from gensim import corpora, models, similarities
documents = ["Human machine interface for lab abc computer applications",
              "A survey of user opinion of computer system response time",
              "The EPS user interface management system",
              "System and human system engineering testing of EPS",
              "Relation of user perceived response time to error measurement",
              "The generation of random binary unordered trees",
              "The intersection graph of paths in trees",
              "Graph minors IV Widths of trees and well quasi ordering",
              "Graph minors A survey"]
stoplist = …