What's the Pythonic way to store a data block in a Python script?

Question

Perl allows me to use the __DATA__ token in a script to mark the start of a data block. I can read the data using the DATA filehandle. What\'s the Pythonic wa

Answer 1

Not being familiar with Perl's __DATA__ variable Google is telling me that it's often used for testing. Assuming you are also looking into testing your code you may want to consider doctest (http://docs.python.org/library/doctest.html). For example, instead of

import StringIO

__DATA__ = StringIO.StringIO("""lines
of data
from a file
""")

Assuming you wanted DATA to be a file object that's now what you've got and you can use it like most other file objects going forward. For example:

if __name__=="__main__":
    # test myfunc with test data:
    lines = __DATA__.readlines()
    myfunc(lines)

But if the only use of DATA is for testing you are probably better off creating a doctest or writing a test case in PyUnit / Nose.

For example:

import StringIO

def myfunc(lines):
    r"""Do something to each line

    Here's an example:

    >>> data = StringIO.StringIO("line 1\nline 2\n")
    >>> myfunc(data)
    ['1', '2']
    """
    return [line[-2] for line in lines]

if __name__ == "__main__":
    import doctest
    doctest.testmod()

Running those tests like this:

$ python ~/doctest_example.py -v
Trying:
    data = StringIO.StringIO("line 1\nline 2\n")
Expecting nothing
ok
Trying:
    myfunc(data)
Expecting:
    ['1', '2']
ok
1 items had no tests:
    __main__
1 items passed all tests:
   2 tests in __main__.myfunc
2 tests in 2 items.
2 passed and 0 failed.
Test passed.

Doctest does a lot of different things including finding python tests in plain text files and running them. Personally, I'm not a big fan and prefer more structured testing approaches (import unittest) but it is unequivocally a pythonic way to test ones code.