我正在尝试清理这个网站并获取每一个字。但使用生成器比使用列表给我更多的单词。而且，这些词是不一致的。有时我有1个单词，有时没有，有时超过30个单词。我已经阅读了有关python文档的生成器，并查找了有关生成器的一些问题。我的理解是它不应该有所不同。我不明白引擎盖下面发生了什么。我正在使用python 3.6。我也读过Generator Comprehension different output from list comprehension?，但我无法理解这种情况。
这是发电机的第一个功能。
def text_cleaner1(website):
'''
This function just cleans up the raw html so that I can look at it.
Inputs: a URL to investigate
Outputs: Cleaned text only
'''
try:
site = requests.get(url).text # Connect to the job posting
except:
return # Need this in case the website isn't there anymore or some other weird connection problem
soup_obj = BeautifulSoup(site, "lxml") # Get the html from the site
for script in soup_obj(["script", "style"]):
script.extract() # Remove these two elements from the BS4 object
text = soup_obj.get_text() # Get the text from this
lines = (line.strip() for line in text.splitlines()) # break into lines
print(type(lines))
chunks = (phrase.strip() for line in lines for phrase in line.split(" ")) # break multi-headlines into a line each
print(type(chunks))
def chunk_space(chunk):
chunk_out = chunk + ' ' # Need to fix spacing issue
return chunk_out
text = ''.join(chunk_space(chunk) for chunk in chunks if chunk).encode('utf-8') # Get rid of all blank lines and ends of line
# Now clean out all of the unicode junk (this line works great!!!)
try:
text = text.decode('unicode_escape').encode('ascii', 'ignore') # Need this as some websites aren't formatted
except: # in a way that this works, can occasionally throw
return # an exception
text = str(text)
text = re.sub("[^a-zA-Z.+3]"," ", text) # Now get rid of any terms that aren't words (include 3 for d3.js)
# Also include + for C++
text = text.lower().split() # Go to lower case and split them apart
stop_words = set(stopwords.words("english")) # Filter out any stop words
text = [w for w in text if not w in stop_words]
text = set(text) # Last, just get the set of these. Ignore counts (we are just looking at whether a term existed
# or not on the website)
return text
这是列表推导的第二个功能。
def text_cleaner2(website):
'''
This function just cleans up the raw html so that I can look at it.
Inputs: a URL to investigate
Outputs: Cleaned text only
'''
try:
site = requests.get(url).text # Connect to the job posting
except:
return # Need this in case the website isn't there anymore or some other weird connection problem
soup_obj = BeautifulSoup(site, "lxml") # Get the html from the site
for script in soup_obj(["script", "style"]):
script.extract() # Remove these two elements from the BS4 object
text = soup_obj.get_text() # Get the text from this
lines = [line.strip() for line in text.splitlines()] # break into lines
chunks = [phrase.strip() for line in lines for phrase in line.split(" ")] # break multi-headlines into a line each
def chunk_space(chunk):
chunk_out = chunk + ' ' # Need to fix spacing issue
return chunk_out
text = ''.join(chunk_space(chunk) for chunk in chunks if chunk).encode('utf-8') # Get rid of all blank lines and ends of line
# Now clean out all of the unicode junk (this line works great!!!)
try:
text = text.decode('unicode_escape').encode('ascii', 'ignore') # Need this as some websites aren't formatted
except: # in a way that this works, can occasionally throw
return # an exception
text = str(text)
text = re.sub("[^a-zA-Z.+3]"," ", text) # Now get rid of any terms that aren't words (include 3 for d3.js)
# Also include + for C++
text = text.lower().split() # Go to lower case and split them apart
stop_words = set(stopwords.words("english")) # Filter out any stop words
text = [w for w in text if not w in stop_words]
text = set(text) # Last, just get the set of these. Ignore counts (we are just looking at whether a term existed
# or not on the website)
return text
这段代码随机给我不同的结果。
text_cleaner1("https://www.indeed.com/rc/clk?jk=02ecc871f377f959&fccid=c46d0116f6e69eae") - text_cleaner2("https://www.indeed.com/rc/clk?jk=02ecc871f377f959&fccid=c46d0116f6e69eae")
答案 0 :(得分：0)
生成器是"lazy" - 它不会立即执行代码，但是稍后在需要结果时执行它。这意味着它不会立即从变量或函数中获取值，但它会保留对变量和函数的引用。
链接示例
all_configs = [
{'a': 1, 'b':3},
{'a': 2, 'b':2}
]
unique_keys = ['a','b']
for x in zip( *([c[k] for k in unique_keys] for c in all_configs) ):
print(x)
print('---')
for x in zip( *((c[k] for k in unique_keys) for c in all_configs) ):
print(list(x))
在生成器中，另一个for循环内部有for个循环。
内部生成器会引用c而非c中的值，并且稍后会获得值。
稍后（当它必须从生成器获得结果时）它开始使用外部生成器for c in all_configs执行。当外部生成器被执行时，它循环并生成两个内部生成器，它们使用c的引用，而不是来自c的值，但是当它循环时它也会改变c中的值 - 所以最后你有＆＃34;列表＆＃34;在{'a': 2, 'b':2}中有两个内部生成器和c。
之后它执行内部生成器，最终从c获得值，但此时c已经有{'a': 2, 'b':2}。
顺便说一句：当lambda中的按钮与for循环使用时，tkinter循环中存在<meta http-equiv="refresh" content="40" >类似的问题。