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问题:
I've been struggling with this simple problem for too long, so I thought I'd ask for help. I am trying to read a list of journal articles from National Library of Medicine ftp site into Python 3.3.2 (on Windows 7). The journal articles are in a .csv file.
I have tried the following code:
import csv
import urllib.request
url = "ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/file_list.csv"
ftpstream = urllib.request.urlopen(url)
csvfile = csv.reader(ftpstream)
data = [row for row in csvfile]
It results in the following error:
Traceback (most recent call last):
File "<pyshell#4>", line 1, in <module>
data = [row for row in csvfile]
File "<pyshell#4>", line 1, in <listcomp>
data = [row for row in csvfile]
_csv.Error: iterator should return strings, not bytes (did you open the file in text mode?)
I presume I should be working with strings not bytes? Any help with the simple problem, and an explanation as to what is going wrong would be greatly appreciated.
回答1:
The problem relies on urllib
returning bytes. As a proof, you can try to download the csv file with your browser and opening it as a regular file and the problem is gone.
A similar problem was addressed here.
It can be solved decoding bytes to strings with the appropriate encoding. For example:
import csv
import urllib.request
url = "ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/file_list.csv"
ftpstream = urllib.request.urlopen(url)
csvfile = csv.reader(ftpstream.read().decode('utf-8')) # with the appropriate encoding
data = [row for row in csvfile]
The last line could also be: data = list(csvfile)
which can be easier to read.
By the way, since the csv file is very big, it can slow and memory-consuming. Maybe it would be preferable to use a generator.
EDIT:
Using codecs as proposed by Steven Rumbalski so it's not necessary to read the whole file to decode. Memory consumption reduced and speed increased.
import csv
import urllib.request
import codecs
url = "ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/file_list.csv"
ftpstream = urllib.request.urlopen(url)
csvfile = csv.reader(codecs.iterdecode(ftpstream, 'utf-8'))
for line in csvfile:
print(line) # do something with line
Note that the list is not created either for the same reason.
回答2:
Even though there is already an accepted answer, I thought I'd add to the body of knowledge by showing how I achieved something similar using the requests
package (which is sometimes seen as an alternative to urlib.request
).
The basis of using codecs.itercode()
to solve the original problem is still the same as in the accepted answer.
import codecs
from contextlib import closing
import csv
import requests
url = "ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/file_list.csv"
with closing(requests.get(url, stream=True)) as r:
reader = csv.reader(codecs.iterdecode(r.iter_lines(), 'utf-8'))
for row in reader:
print row
Here we also see the use of streaming provided through the requests
package in order to avoid having to load the entire file over the network into memory first (which could take long if the file is large).
I thought it might be useful since it helped me, as I was using requests
rather than urllib.request
in Python 3.6.
Some of the ideas (e.g using closing()
) are picked from this similar post
回答3:
urlopen
will return a urllib.response.addinfourl
instance for an ftp request.
For ftp, file, and data urls and requests explicity handled by legacy
URLopener and FancyURLopener classes, this function returns a
urllib.response.addinfourl object which can work as context manager...
>>> urllib2.urlopen(url)
<addinfourl at 48868168L whose fp = <addclosehook at 48777416L whose fp = <socket._fileobject object at 0x0000000002E52B88>>>
At this point ftpstream
is a file like object, using .read()
would return the contents however csv.reader
requires an iterable in this case:
Defining a generator like so:
def to_lines(f):
line = f.readline()
while line:
yield line
line = f.readline()
We can create our csv reader like so:
reader = csv.reader(to_lines(ftps))
And with a url
url = "http://pic.dhe.ibm.com/infocenter/tivihelp/v41r1/topic/com.ibm.ismsaas.doc/reference/CIsImportMinimumSample.csv"
The code:
for row in reader: print row
Prints
>>>
['simpleci']
['SCI.APPSERVER']
['SRM_SaaS_ES', 'MXCIImport', 'AddChange', 'EN']
['CI_CINUM']
['unique_identifier1']
['unique_identifier2']