如何在Python中将文本文件导入数组（金字塔）

Question

嗨，所以我想做一些非常简单的事情

我有一个Array，其中有大量的句子被随机用于slideDown通知div。由于我不想在PyCharm中有一个非常长的1行，我想我可以将txt文件中的句子导入我的Array。

我找到了this和this，因此我导入了 numpy ，然后使用下面的代码，它中断了（ <{1}}行上跳过我的错误消息，我也没有收到错误。

success_msgs

有什么想法？ ：（

我的文本文件（与py文件位于同一文件夹中：

def create_request(self):
    # text_file = open("success_requests.txt", "r")
    # lines = text_file.readlines()
    # print lines

    success_msgs = loadtxt("success_request.txt", comments="#", delimiter="_", unpack=False)
    #success_msgs = ['The intro request was sent successfully', "Request sent off, let's see what happens!", "Request Sent. Good luck, may the force be with you.", "Request sent, that was great! Like Bacon."]

调试器

我的def genfromtxt

The intro request was sent successfully_
Request sent off, let's see what happens!_
Request Sent. Good luck, may the force be with you._
Request sent, that was great! Like Bacon._

genfromtxt debug：

Answer 1

首先，告诉它使用带有dtype='S72'的字符串dtype（或者您期望的任何最大字符数）。

In [368]: np.genfromtxt("success_request.txt", delimiter='\n', dtype='S72')
Out[368]: 
array(['The intro request was sent successfully_',
       "Request sent off, let's see what happens!_",
       'Request Sent. Good luck, may the force be with you._',
       'Request sent, that was great! Like Bacon._'], 
      dtype='|S72')

或者，如果每一行以下划线结尾，并且您不想包含下划线，则可以设置delimiter='_'和usecols=0以仅获取第一列：

In [372]: np.genfromtxt("success_request.txt", delimiter='_', usecols=0, dtype='S72')
Out[372]: 
array(['The intro request was sent successfully',
       "Request sent off, let's see what happens!",
       'Request Sent. Good luck, may the force be with you.',
       'Request sent, that was great! Like Bacon.'], 
      dtype='|S72')

但是没有理由不在不使用numpy和

的情况下加载文件

In [369]: s = open("success_request.txt",'r')

In [379]: [line.strip().strip('_') for line in s.readlines()]
Out[379]: 
['The intro request was sent successfully',
 "Request sent off, let's see what happens!",
 'Request Sent. Good luck, may the force be with you.',
 'Request sent, that was great! Like Bacon.']