csv.reader vs csv.dictReader

[mepyyeti]

I'm having a lot of difficulty understanding the difference between csv.reader and csv.dictReader. The Python docs didn't shed much light for me on this point...
Basically when would I elect to use csv.reader and where is csv.dictReader the better choice (I feel the answer must relate to fieldnames?

So my questions are :
1) what is the difference between the two methods?
2) my code reprints the fieldnames when I use csv.dictReader
3) rightnow my fieldnames are in my csv file...how do I attach them to print with csv methods
(for example with csv.dictWriter it is fieldnames=['id','a','b','c','d']; somefile = csv.DictWriter(someotherfile, fieldnames=fieldnames];somefile.writeheader() what is csv.reader/csv.dictReader alternative?

here is my csv:

Output:
id-a-b-c-d
1-foo-1-2-0
2-bar-10-20-0
3-moo-2-3-0

here is my code:

opened_file = open('foo0.csv')
print(opened_file.read())#this prints out fine

with open('foo0.csv') as openme:
#also, how do I implement fieldnames with csv.reader OR csv.dictReader (the docs show me how to do this with csv.dictWriter only)
	readme = csv.DictReader(openme, delimiter='-')#this refuses to work...it simply reprint my 'fieldnames'
	for x in readme:
		print(' '.join(x))

my output:

Output:
id-a-b-c-d
1-foo-1-2-0
2-bar-10-20-0
3-moo-2-3-0

id a b c d
id a b c d
id a b c d

[buran]

In simple terms csv.reader and csv.writer work with list/tuple, while csv.DictReader and csv.DictWriter work with dict.
csv.DictReader and csv.DictWriter take additional argument fieldnames that are used as dict keys.

---

scores.csv

Output:
id,name,score
1,John,10
2,Annie,25
3,Jane,15

import csv

with open('scores.csv') as f:
    rdr = csv.reader(f)
    for line in rdr:
        print(type(line))
        print(line)
        
print ('\n\nusing DictReader \n')

with open('scores.csv') as f:
    rdr = csv.DictReader(f)
    print 'fieldnames:', rdr.fieldnames
    for line in rdr:
        print(type(line))
        print(line)

output

Output:
<type 'list'>
['id', 'name', 'score']
<type 'list'>
['1', 'John', '10']
<type 'list'>
['2', 'Annie', '25']
<type 'list'>
['3', 'Jane', '15']


using DictReader

fieldnames: ['id', 'name', 'score']
<type 'dict'>
{'score': '10', 'id': '1', 'name': 'John'}
<type 'dict'>
{'score': '25', 'id': '2', 'name': 'Annie'}
<type 'dict'>
{'score': '15', 'id': '3', 'name': 'Jane'}
>>>

[mepyyeti]

readme = csv.DictReader(openme, delimiter='-')#this refuses to work...it simply reprint my 'fieldnames'

So the line above won't work b/c I'm missing fieldnames statement...the python docs aren't quite clear on this.

Also for a bare knuckles inventory system which is be better dictReader/Writer or Reader/Writer. If those are your only options... I'm leaning toward the use of dictionaries only because I can use the 'column'/fieldnames names as keys...

[buran]

So the line above won't work b/c I'm missing fieldnames statement...the python docs aren't quite clear on this.

This is not True. Both with respect to working and documentation being not clear. From the docs

The fieldnames parameter is a sequence. If fieldnames is omitted, the values in the first row of file f will be used as the fieldnames. Regardless of how the fieldnames are determined, the ordered dictionary preserves their original ordering.

As to which one is better - I would not put it this way (better/worse). It depends on the particular setup and your preferences. I tend to prefer DictReader/DictWriter. However if your data comes from a database it will be list of tuples, so writer could be handy. On other hand you can easily turn list/tuple into dict usizng dict(zip(keys, values)) given you have the fieldnames as list/tuple (keys) and values as list too.