For Python 3

Remove the rb argument and use either r or don't pass argument (default read mode).

with open( <path-to-file>, 'r' ) as theFile:
    reader = csv.DictReader(theFile)
    for line in reader:
        # line is { 'workers': 'w0', 'constant': 7.334, 'age': -1.406, ... }
        # e.g. print( line[ 'workers' ] ) yields 'w0'
        print(line)

For Python 2

import csv
with open( <path-to-file>, "rb" ) as theFile:
    reader = csv.DictReader( theFile )
    for line in reader:
        # line is { 'workers': 'w0', 'constant': 7.334, 'age': -1.406, ... }
        # e.g. print( line[ 'workers' ] ) yields 'w0'

Python has a powerful built-in CSV handler. In fact, most things are already built in to the standard library.

Expanding on the answer given by Jeff It is now possbile to use pandas without actually reading any rows.

In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: pd.DataFrame(np.random.randn(10, 4), columns=list('abcd')).to_csv('test.csv', mode='w')

In [4]: pd.read_csv('test.csv', index_col=0, nrows=0).columns.tolist()
Out[4]: ['a', 'b', 'c', 'd']

pandas can have the advantage that it deals more gracefully with CSV encodings.

Though you already have an accepted answer, I figured I'd add this for anyone else interested in a different solution-

• The csv module's DictReader object has a public attribute called fieldnames (as of Python 2.6 and above). https://docs.python.org/3.4/library/csv.html#csv.csvreader.fieldnames

An implementation could be as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    dict_reader = csv.DictReader(f)

    #get header fieldnames from DictReader and store in list
    headers = dict_reader.fieldnames

    #sample file reading logic
    for line in dict_reader:
        print(line[headers[0]])
        

In the above, dict_reader.fieldnames returns a list of your headers (assuming the headers are in the top row). Which allows...

>>> print(headers)
['MyColumn1', 'MyColumn2', 'MyColumn3']

If your headers are in, say the 2nd row (with the very top row being row 1), you could do as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    #you can eat the first line before creating DictReader.
    #if no "fieldnames" param is passed into
    #DictReader object upon creation, DictReader
    #will read the upper-most line as the headers
    f.readline()
    
    dict_reader = csv.DictReader(f)
    headers = dict_reader.fieldnames

    #sample file reading logic
    for line in dict_reader:
        print(line[headers[0]])