如何将Python元组转换为.csv文件？

Question

I would like to transform a Python tuple to a .csv file. Let's say I have a retrive() function and when I print it with pprint it looks like this:

test = tuple(retrive(directory))
pprint(test, width=1)

Then:

("opinion_1.txt, I am an amateur photographer and own three DSLR c.... purchase",
 "opinion_2.txt, This my second Sony Digital Came.... good camera for a good price!',
 'opinion_3.txt, \'I ordered this camera with high hopes after  couldn\\\'t find.\'')

So, I tried this with the csv module:

with open('/Users/user/Downloads/output.csv','w') as out:
    csv_out=csv.writer(out)
    csv_out.writerow(['id','content'])
    for row in test:
        csv_out.writerow(row)

The problem is that I get a weird output which looks like this:

id,content
o,p,i,n,i,o,n,_,1,.,t,x,t,",", ,I, ,a,m, ,a,n, ,a,m,a,t,e,u,r, ,p,h,o,t,o,g,r,a,p,h,e,r, ,a,n,d, ,o,w,n, ,t,h,r,e,e, ,D,S,L,R, ,c,a,m,e,r,a,s, ,w,i,t,h, ,a, ,s,e,l,e,c,t,i,o,n, ,o,f, ,l,e,n,s,e,s,., ,H,o,w,e,v,e,r, ,t,h,a,t, ,c,o,l,l,e,c,t,i,o,n, 

How can I get something like this:

opinion_1.txt,I am an amateur photographer and own three DSLR c.... purchase
opinion_2.txt,This my second Sony Digital Came.... good camera for a good price!
opinion_3.txt,I ordered this camera with high hopes after  couldn\\\'t find.

Answer 1

CSV trying to iterate over string you pass from the tuple. Change your code to:

for row in test:
    csv_out.writerow(row.split(', ', 1))

It means you split each string in the tuple by first occurrence of ', ' . It produces two elements for each row and it is what csv writer is need is.

Answer 2

If you need Pandas solution, use DataFrame constructor and to_csv :

import pandas as pd

df = pd.DataFrame([ x.split(',') for x in test ])
df.columns = ["id","content"]
print df
#              id                                            content
#0  opinion_1.txt   I am an amateur photographer and own three DS...
#1  opinion_2.txt   This my second Sony Digital Came.... good cam...
#2  opinion_3.txt   'I ordered this camera with high hopes after ...

#for testing
#print df.to_csv(index=False)
df.to_csv("/Users/user/Downloads/output.csv", index=False)
#id,content
#opinion_1.txt, I am an amateur photographer and own three DSLR c.... purchase
#opinion_2.txt, This my second Sony Digital Came.... good camera for a good price!
#opinion_3.txt, 'I ordered this camera with hig

If there is multiple , , you can use split by first occurence of , :

import pandas as pd

test = ("opinion_1.txt,a","opinion_2.txt,b","opinion_3.txt,c",  "opinion_3.txt,b,c,k")
print test

print [ x.split(',', 1) for x in test ]
[['opinion_1.txt', 'a'], 
 ['opinion_2.txt', 'b'], 
 ['opinion_3.txt', 'c'], 
 ['opinion_3.txt', 'b,c,k']]

df = pd.DataFrame([ x.split(',', 1) for x in test ])
df.columns = ["id","content"]
print df
              id content
0  opinion_1.txt       a
1  opinion_2.txt       b
2  opinion_3.txt       c
3  opinion_3.txt   b,c,k

print df.to_csv(index=False)
id,content
opinion_1.txt,a
opinion_2.txt,b
opinion_3.txt,c
opinion_3.txt,"b,c,k"

Answer 3

Your parsing is destroyed if one of your sentences has multiple commas like this:

s = "opinion_4.txt, Oh my, what happens with really, really long sentences?"

>>> s.split(", ")
['opinion_4.txt',
 'Oh my',
 'what happens with really',
 'really long sentences?']

A better approach would be to find the first comma and then split the sentence using slicing at this location:

for line in text:
    comma_idx = line.find(', ')
    csvout.writerow(line[:comma_idx], line[comma_idx+2:])

For the sentence above, it would result in this:

('opinion_4.txt', 'Oh my, what happens with really, really long sentences?')