http://www.reddit.com/r/learnpython/comments/22i7oq/problem_with_logic_and_formatting/

fasta.txt

>Rosalind_8980
CACCCCCTAAGTTAGACAGCTACAAGTCACTATGATTTTTTAGCTGCCTAGCACTATTGT
TTGAAACTCAGCGTCACACACAGCCAACATCTACCGGACGACCAGTTTTAATTCGTAAAG
ACGTGCGGGCTACTGTGATCTAATGTAACCGCACTCTCGCGGAACGCCTTTTGTCTCGGG
TCGGCCTATGTCCTTAGGAATGTCCGGTGAATTACAACTAAGAACGGCCTTGGTATCGCG
GGTACACCTGTCTATTTTGCATGGTGTGTGTTAACGGTGGCTGCGAGGGGACGAAATCAA
TGACCAAGGCAGGAAGTAGGTTAGCGGGCTAGTCGCACACTTTGTTGTCGGTCAAGTGAA
TACCCTCAGGACCTGTGCGGTTACGGGTCACGGGAGATCCGCGAAGCTGCCAATTGTATT
GACTTTGGCCACGGTATAGGTGTTCAGGTATCCTTGTCATCAACGATACCCTCAGGTCCT
TTGAGGCCTCTACTGCCTAGGTGTTAGGCGCATTTTCGCTGAGTCCTAAAACAGTATTAC
CAAGGCTACTTAACGTATGGAAATCATCCCCCATTTCCCGTTTTTGTCGAGAGATACGCT
CTTTAGGTTATAAGGATAAATAATGAGAACTCATCGAATACCGCGTAAACAATAGCGTGC
AGGTCGTGATATAGGACACGATCAGCAAATGCGAGAGTCGAGTCAAGGACCTAGGCTGAT
TTGTACCGGAAGTTTCTCTCTCTTCAAAATAGCCTTACTGCCGCGAACCGAGGTGACGTT
AGTAGCATCTGCATTGGTTTTGGACGTCTGCTATTGCTATGTCGCCACCCATAGTGTAAA
ATACTAGTGGCGAAGTGCTCAGTGAATGCGATTGAGCCAATGACGAACCAGACTAACTTG
AACCGTGTGCTCCAATTGGTAAGATATGCTAC
>Rosalind_1203
ACCACTTTGTTTCAGTAACCGTTCCTGATGACTCTACTCCCACCACAACGGACACAAGCG
GAGTAGGTGGCGGAGTGGTGACGTTTGTTCCAGAGACGGTACCATTAGTCCCCGCGACAA
AAATTCCCCTACAAATCCGGTTAGGTGATCTGCACCGGCTTTGAGGCAACCATACCCCTA
TAGCCCAAACGTTGGATTGGAGATTGGATTGCCCTCTAGTCCGGACAACCACAGGAGACG
GGATCTTATGACAATACGAGCACGAACAGTTCGTTCATGCTTTCCCATTCGAGCGCCCAA
CTAATCAACACTTCTATCTGCGACCTTAAATATGACTCGCGAATCAACGAGGGACGCCAT
TTAACGCAGAATTTATTTGTTTCGCGACCCGCGTTTTGTACGAGACAGATGCACCGATAT
ACGGTTTATCTTTACGCTAGGCCAATTCACCATAGTTCGTCCGCCGTATCGGGCGATTAG
TGCGACTCGTATCTGAACATAAATATACGCCACTCGAATATTACATACCCTCTTAGGATG
GAGACCTGTTTGTGCCAAGAAGATGTTCGCATTGGAGGTCGTACGTGGACTGGTATGGCT
GTGCATCCTATGCCCGACCAACGAGTCACGGTCCCCGAGAGATGGACTACCACATAAAAT
TAAGTAGGCAGACAATGGGCCAAGAGAACATGATAATCACGACGTGTCCAGGTAGCGTAG
CCCTTTTGAACTTCTCCGGATCGACCCCCAGCGCTGCGGTAGCGGTTATTATTAGAGCTT
TAAGTTTCCCTGCCGCCCGGTTAAAAGTCTGTGTGGAGCGGAAGCATAGAATTGCATAGT
TTCGGCGAAGGCTTCCCACACACCGTCCGTCAATAAAAACACGATTGACGGTATTGTATC
GTCATGCAGCCGCATGCCCTAAAAGTCCGGCC
>Rosalind_6922
CTCTGGGTCAACGCAGGAGGGGTGGGAAGTGCCACACGGTCCGATAGACGCTCATTAATA
AATCTACGCATCCGCCTCGGACTCTCGTGACATCCTTTTAAACCGCCAGCAACGGTGACC
ATGAAAAATCGGTAAGTTTTTCTGGCTAGGGCCCTAAAAAATCCATTTCTCTGTTGAGTG
GTTCTTAATGCATCTCTAGCGCACGTGCGAGCGTGCATAGATACGTTCGACGTGTAGACT
AACTTCACACCTTTTGAAACGCATAAGTAGCCCAACATAATCCACATGCGCTACGTAATG
ATTCTCGGTGATTGCACGGTCATCCCCAAAACAGTACAGGCCGGCTTCTCTATTGGCCGT
ATTGAATCTTTGTTATGTCGGTGGATAATAGTTCATTGGAGCACGAGGGCTAGACCCGGT
TAGGTAGGTTTTCTCGTCATTTGTTACATAGATAACAACCGCTAAGCGAGGGGGCACTAG
ACCTTCTACCGCCGTCATACGTGGCCGGGATACCGAAGTAACTAATCTCTGTTACATACT
CTGTTGCAGTCTATGTGCATTCCGCGTTTTACAACGAGTTCGGGGCGAGCACGAACAGCC
AAAAGTTTTCCGCACCGCTATTAATTTTGTGGGGAATATCCGTAGGACGTGGGCTGCTAC
TCAGGTGAACGACGCGACGCACCAACAACATCACGATGTGCCATTTTCGGTCATTGGATT
ACGTCCCCCGCAGCATTAGGCTGTGCACCTAGCCGATAGTTCATGCTATGTCACGAGGTT
ACCGCAGGGGCCACAGTCACTTCTGCGTATGAGACACAGAGTATAGTAAAGCTATAGAAA
TAAGTCGAGACAGGAGAACCGCGTGTCGTCTCCCCACGGCGGCCTCCCCCGGCGTTAAGC
GCTCTTATGATGTGTCGTCGCCATCACCAGCT
>Rosalind_7678
GGTCTCCCGAGATGGTTTGTACTTGACTGAAACAGGACGGCATGCCATATTTCGGAAAAT
AATACATCGGTCTTCTCAACGCGTCAACCTTGGCCTGGAGATGTGACCCCATAGTTGAGT
TATCGGGAAGATTAGTTCCAGCGAACACCCAGGGGCCTAAAAGAGGGGAGCGGGATCAGA
CCACTGAATGGTGGCTATCGCTGCCATGCTCCCATCAAAGGTTGTAAGCATAAATTTATC
CGATGCGGTGTATATTTGTCGATTTCCTCGAACTTCGTGAACGATTTTTTTAATTAGAAC
CAATGCTACGCCAACCTAGATTTTCGTTAGATCCAGTGCATAAGCTACAACGGTGCTCCC
AGCGTAGTATTCATCATACCGGGATCTGTAAAAGACCGGCGGTTCTTCGTATGTGCTTTC
TAAGAAGGTGAGGCTTAAACTTTTCCCTTATTTGCCCGCGAACGACACCGCAGTGTGAAG
CCAGCAGTCAGGGTCTCGACCTGTTGACGAGCCACGTAGTGATTTATACCAGTGGTGCTC
TCGGTTGTTGTGACTAGAACGCTGTAAACGACGGCCCTTTAGGGGGATCACGGGCACGCT
TGCGTAGGGACACTATATGGAAAGGTCACGTAGACGTCTCGCCGCCGAGCTTACAATATC
TATGGACTCGATTTCTGAGGGGGTTTCACATCCGGGTTTTGTGCCGAGCTCTTCTCATCA
TTCTATCCTTACAACCCAACCATACCATAACCTCGGTTGTAAGAACTTTATAAACACGGT
AGCCCCAGCTTTTACTGGCCAACGTCTCACTCTCTGGCACGTAGTGTGTACTAGGCCGGA
TCCGCCATTGGATGTCTAAAGGAGTGTCTCCTAAGCCCTGTGTGACTTAGTCGAACTGGT
CGAAGGTAATTATACAAGGAGCATCTGATTCC
>Rosalind_4630
CGCGGAGGTCAGAGGGGTTGGTGCGTTCCCGGGTGGGCATAGGGCGCGCACCACGGTTAG
GGGAACATGGCAGGAATACTGTTATCTAATGACGCAATCGTGCGTGCCTGGCTTACACGT
CTTCGTTGGCATGGCCATAAACCTCCACGTACGTCCTAGAGTCTTTAACTTAAGTGCTAA
CGACCTACCAAAGTCCAATAAGACCAGCAGGAATATGGGACTATAGTATACAACTGATCG
GACACTTGAGCATATTAGGGAAATAAGATCAGGGCGGAGGGACCTAGCAAGCCTGGCTGA
ACCCCAAGTGGCTTGCAAACCACTCGCCCATCCACGGGCACAATCACGTCAAGGAACTCG
GGGGTGTCTTCGTGGCGTATGGTTGCGTCAGAGTACAAAATGCTAGCCCTTAGGCTACTA
AATACTTACCACCCTACTTGGCCTACATGACGTGACCGACCTATCAGTGAAGTAGTAGAA
TTTACCCGAATCACACCTGGCAAATGAAAGGTTGGAACTCATCGGCGTGGTTCCGCCCCC
AAGGGGTTATTTCTGTAAGCACCGAAAGACTCAAGTTATAAGTAGGAACTGCGTAGACAC
AGGCGCAAGAGGATAACGTACACCAAACATCCCATGTTCTACGTTAGGATAATTTGGGTC
TCAACGCCCCGGAGATCTGTCATCTGTAATGCAATGTATGATGTTTAGACGTTCAGCCGA
GATGGGTTTGGCATCTAAACGTAACTGGTAAGTACTACAAATGGCTGCGATAGCTTACTC
TCGACCCACTCTCAGAATCCCCGAGATCCGGACATTTCTTTTCTTGGTCACTTATATTGT
GCCACAAGAAAGCTTTCACGAGTAAGAAATGTTAAAAGGTGTATACTCGTCGGGGCCGGA
AAATCATGATGGGACGTAGATCCACATTTGTC
>Rosalind_6816
AACCAGGGTCAGGTACCGGGCGTAGGGGTGAAATCGGCTTCTGGAGATCACCTCGTATTT
AGCATGCAGCTTATTGGGCGCGCTGCTGTGTACCGCGCCGCGGGGATATTGTAATATAAG
GCATTGCAGGTAGCGGTCGGGGCGATGCACTCAACGATCCCCCACCATTCAGATGAGCGG
ATGTTAAGTTGTCATCCGTATCACGCATGGGGCACCTCGTGGAACGACTGTCGACACTTT
TTTTATAGGTAGGCCATGATCGGTCGTAGCTCCGACATAGGCGCCAATCTCTCTATTCAC
CTATTCGACCCGCGCCAAATAAGTCGGGGTGCAAGTGAGCCCTGAAGACTGGGGTGCTCC
GATCCTGCCTGTGCAACTCCCTCGCATTTTGCGCCGCTCACGATGATGCAGTCTACCCTG
GTGTAGTCTACTCCCGGGCATGCTTCCTCGCCCCCTATACGGACCCGTAGCGGTGGCACG
GGGCGGAATCAAGCAGTGTTAGTGACACACAGTGGCGCCCATGCATCAGTCCTCGGTGAC
AGCGATGGTGTCGCTGCGAGCCTTCCATCATCAACTCTACGATATAGCGGGATAAACAAA
CTTTTGGGTTACGCGCTATATTCAGACTCAGCGCAGGATCGGGATGATCGATAAGATTAG
CGCGGGCTTACGTCGCTTTCATGCGGGGTACTCCGCAGTCTATGCGAATGCATTCCACAT
GAACGGTGTTTTTTCAAATGAGTCCTCATTGCCACGCTGCGCACAGATGCCGTCATAGCG
AATACCAGCTTGCAGCTTACTCCGGGTGTTATCGGCTCAACGGGCGGTTTCGACGGTCTC
CCGAAATGTCATTCCATGGCTTAGCTCTAAATTCACGGTTGCATTTTGCATCCTATAGTG
CGTTGACAACATGAACCATTTCACCGCTTAAA
>Rosalind_6912
TGCGTCCAGCCCTGATCAGTGGTCCCGTTATTTAGTTGCGCGGACGTCTACGTCAGCGAC
ACGATTGCAAGAATCTGTATCACTCCGGTAAGCTTCAACTCCACGCTTCGAGTATGCTCG
TCTACTGGCAGGGTGAGATATAATAATCAGTAAAGATTGTCCTCACACGACTGTATCATA
CAACTAGCATGATAGGTGATGCCACGGCGGCTCTGATGTCCCAGTGGAACCACTTATAAA
CGCAAGAGGCGGGACGCGCCGATGTCTTAGACCTATGGGCTCCTCTAACGTAAAAAGTGA
TGGGATAGTGGCTTCGTCAATGATCATTACGGATCCGTACATCCGCGCAAGGCTCTTCCG
GATAGTGCCCTGGGAGGAGTCTGTTAGTTGGAAATTTGCTCGCCATGTTAGTGGGGTCAC
GCTTACAGCTACGGTGGGAACCGTTTGATGATCAATCTACGAGATAGCCTTCGCTGTCCA
TTGGTGTTCATTTGTACAACGGGCGTTGGGCGCGTAGCAAAAACCAGACTTAGAGCCTAA
TTCATGAGGCCATTATAATGACTACAGGCGTTCTTTAACCGGTCTGATTACGACAGCTAG
TGTAGGACACGCAAATTTCCTCATAAAGGAGGGACGTGAACCAAGCTGAGGCCGTGCAAA
TCCCACTGGGGGACTCAGGCTACGGACAGGGGCATATACTCGTGGCTGTCATAGAAACGG
GGAAGTTCGTTTGCATCGCAAGAGCTCACGCTACCAGTTCGGTGGGGAGGTGACCGGTTA
AGATGGTAGACGGGGGAACGCACTAAGCCGGCCGTGTAGGGCTACCGATTTAACTACCTC
AGATTAATTAGTTCGTCGGTTCTAGTTCGGTTTCCAAGGTTTTAGCGGAGTGACCAGACA
TAGTCCGGGCACGCATCTTGCGGTTTAAACAC
>Rosalind_7593
TATCAATGGCCGTGTGGATATCAGACTGTCTCCCGGCCCCCACCGACGCATTCGCGTCGC
CCCGTTATGCTACAGTAATGACAGCGATGATCCCCTGAAATCTTGACACAGTGTTGAGCC
GAAACTACGTCTATGCGCGTGTCGCCCTTACACCTACACCTAGAGGCTTCCTTCGTGATA
CGCGCATTTGCGCCGCGATCTACCTCTCATCTGGTGCCATTTTCGTCGCCTTCTGCTGAA
GAGAGCTTGCCGGACCGAAGGTTTTGAACCAAGGAGCAGAAGGCTTGCGCAGAGACTAGT
GTACTTTGTACGGGCAAGGGACTTCGATGTAAGGACATTGACATTCATAGAATTCATGGT
CCAACGCAATGTGATCTAGAGGCCAGCATGGAACGTGCAACACGTGCACAGTGTCTTAGA
GCAATCCGATTAGTTAGACCGTAGCGATTCGATGGGCCGCGCGGTTCACGGCTATGGCAC
ATTCTATACTAGAAGTAAGTCCTGTTAATCAAGAGGATCGATATTGGGCACAAAAATTAA
CACAGTGAGACAAGGGACCAAGGGTTGCGTAGAATTTACAACGTAGTCGCGTAGTATCAC
CCTATCCGTGCAATTCTGGCGCGGCTCGTTTCCGACCAGTGGCTAGCACTATTACAGCCG
ACGCGCCGGAGTTGTCTAGCGTCCTGCCAGGCATAATTGAGGGTGTAACCCAATTTACGA
ATTGCGCAAATGTACGGCCACTATTAGCTAGCTAATCTGATGTCGGCGCCCACACGCCAT
AAGACGCTACACACGAGCAACGCCCAAAGAGCATAGCCGCTCCATCTGCATAGCATCGCC
GGTACAACATTATCGAACACGCGATATCCCCCATTAATCTGCGTAGGCATTACTCCACTA
TCAAGAGCGTCTCCAGGTTGACTTGTCGTATT
>Rosalind_1598
ACGAACATGGAGGTACCATAGCCGGCGAGCATTATCACCAAACAGTCGGCCCGCAGGGGG
GGGTATGAAGCATCCGAGTTAAGGCGCCTGGGCGTTACACTGTCACTCCATTGGTGTCTG
TCCTAGTGCCCCCAGTATCCGGGTAGTTGGAAGATCACGGCAGGGGAGCTACTGATCCTT
GGAACCTTGCTCATACAACATCGTCGACGAATATAGAAAGGGCAGACGGGGCTTGCAATG
CTGTTATTGCGTAGTTTGATAACATACAGCATTTCTGGAATGGCACCATACGAAACTCGC
AATTCTACTACAGCAGGGACGGACCAACAATCTAGCCACAGAGAAATAGCATTTTTACTG
ACCCCCTTCCTCAAAATTTTGTGACGGACAACGCTACCAGGAGCGAAACCCCTTGGTCCA
AGATGATCGGCTTGCCTAAGTTTTTAAGGCTAAGGATAGATTCGAGCTCATGGCAAGTCA
GGCATAAAACTCCATCTGACCGGCTTAAAATAAGAGTGTAATCACGTGCAATTGCCGGGT
TGGCTCTAAACATCCGCTGCTGTTGTCCCAGGGTATATGGTCCTCTCCGAACTCGAGTGA
ACCAGTAACCAAGAGCACCATGTCGCACTGAAACTAGGCCGCTTGGCGGCTAACCTCGAC
CGCCCTTATCCACATCGTCCTGGGCTACGTTTATCTGGCAAAATTGCTAATAAGCCTCGC
CATAGGCGTTCATCAAGTCAGCAAGTACCTCACGGGAATATGAGTTTTAACCTGCCTGAG
GCTAGTTCCTAACTATGCTGTCTTCCACAAGGAACAGTCCTAAGCCCATGTGCAGAAAGG
AGGACCTTGCACCGGTTCGGTTGGCCACTAAGAACAGTCAAAAGCCACCTCTCATGACTC
TACCAAGTATCCGGATAGCGTGCGCGACTGGG
>Rosalind_6195
ATGCATTCGCGTTGTTTCTGCCGAGAATATACCTCCATTAAGATGCCGACTAGTAGGTAG
CGAAAGAGCCCAGCCGACGGGGGAATCCTGTTGAAATGTTAGTATCTAACTAATATTGGA
GAACAAGGTGCCTACTCGATGTCTTAAGTTGTTCAGTGTTTGGGTACATACAAGACAACC
AAGATATCTCTAGGTGTGGACCCAACGAACATTCACTTTGAAACATGAGGGGTCCTACCA
ACTCTCCTTCCTATACCTGACTTGTGCCGAGTCTCGATCGGCCTCATGGGCCTACTTCGT
AATCCAGCAAGACCTTGCAAGGAGCCGTTACAAGTGCGCACACGATCGAACGTAGACTTT
TGTACCTATGAGTAGCCACTGGCTACGGTCCTGCTGATCGGGCTCGACGGACGGAATGCT
GGGTCAACTATTCTTATGGGGGTGATACATGCTCTCGGTCAGCGACAACGTAAGGCCCAT
TACTCGGATGAAGGCTCTCCAAACGGAAGGATCTACTGGTGCCAAAGCCTGTAACTCGTC
TCGGTAGTGCCGTGTTGGACCGAGTTTTACTGGCCCGGACCACAAGTCAAAAGGAGTGTT
GTTATCAGCATACCGTGAGGGAGGCGCCGATCCCCCGGATTACGAGTGACCGTACTTAGC
TGTTGATGTATCAAATGGACAGGACCCTGCTGCCTGACTATTGCGGACGGCCCTCCCTAA
AATCAGACCTCCAGCATATCTTTGATCCGCTCCATGGCCGCCCGTCATGAGGAGGGTGGA
ACGAGTGATTTGTTCCTTATAAGATTCGTTATCGGAATGTGTCACAACTGGGTCCTGGGC
TAGTGGCAGCCGACCAGAGTTCGAGTGCGCTCACTAGTCTGTTAGTGGCGTGGGGAACAC
GAGCCGATTTGATGGAAGCACGAGACGATAGG

sample.txt

>Rosalind_1
ATCCAGCT
>Rosalind_2
GGGCAACT
>Rosalind_3
ATGGATCT
>Rosalind_4
AAGCAACC
>Rosalind_5
TTGGAACT
>Rosalind_6
ATGCCATT
>Rosalind_7
ATGGCACT

solver.py

#!/usr/bin/env python3
import sys
from collections import OrderedDict


# this is a "generator function"
# it'll create an iterable when invoked
def fastaseq_gen(filename):
    """ iterator yielding entire sequences from fasta-formatted input file """

    # open the file with a context manager so it closes automaticaly
    with open(filename) as f:
        # the idea here is that we'll scan each line and create groups
        # with everything that is within lines starting with >
        # then the lines of each group will be concatenated with ''.join()
        # so they produce a single string not the wrapped blocks from FASTA

        # initialize variable to hold grouped lines with a value we recognize
        parts = None

        # this loop is controlled manually
        # (i.e. iterates infinitely until we "break" out of it)
        while True:

            # read the next entire line from the file (it ends with \n)
            line = f.readline()

            # at the end of the file f.readline() will return an empty string
            if not line:
                # yield last group (if it exists)
                if parts is not None:
                    yield ''.join(parts)
                # manually break from while loop to exit function
                break

            # lines starting with > are headers, we ignore them
            if line.startswith('>'):
                # yield previous group if it exists
                if parts is not None:
                    yield ''.join(parts)
                # reset the group variable to a container (list)
                parts = []
            else:
                # if the line isn't a header we add it to the group
                # previously removing trailing newlines with .strip()
                parts.append(line.strip())


def get_profile_matrix(fastaseqs):
    """ convert fasta sequences into profile matrix """

    # create an empty data structure to hold the counts
    # normal dicts don't mainatain the order of the keys
    profile_matrix = OrderedDict.fromkeys(
        ('A', 'C', 'G', 'T',)
    )

    # iterate the sequences
    for fastaseq in fastaseqs:
        # the first time we run the loop we need to initialize the matrix
        # assuming all fasta seqs are of the same length, we take a random key
        # and if it's empty we replace all entries with a list of the same
        # length of the chars in the sequnece filled with zeroes
        # we can do this because numbers are inmutable
        # otherwise there would be reference issues
        if not profile_matrix['A']:
            for key in profile_matrix:
                profile_matrix[key] = [0] * len(fastaseq)

        # use enumerate to index the position of the chars in the string
        for index, char in enumerate(fastaseq):

            # update counts for given char
            profile_matrix[char][index] += 1

    # at the end we return the contructed matrix with the counts per char
    return profile_matrix


def get_concensus_string(profile_matrix):
    """ given a profile matrix return one of the concensus strings """

    # accumulator for the result chars
    result = []

    # we'll iterate thru the positions of the sequence and check each entry
    for index in range(len(profile_matrix['A'])):

        # initialize/reset counters
        max_repeats, max_char = 0, ''

        # now cycle over the keys for this index
        for char in profile_matrix:

            # update counters
            if profile_matrix[char][index] >= max_repeats:
                max_repeats = profile_matrix[char][index]
                max_char = char

        # append largest-counted char to result
        result.append(max_char)

    # return all the chars as a single string
    return ''.join(result)


# this check prevents the code from running when the file is imported as module
if __name__ == '__main__':
    try:
        # read filename from commandline arguments
        filename = sys.argv[1]
    except IndexError:
        # if the argument is missing sys.argv will only contain one element
        # print the error to stderr and exit with failed statuscode
        print('Missing filename', file=sys.stderr)
        sys.exit(1)

    # process input file and calculate profile matrix
    fastaseqs = fastaseq_gen(filename)
    profile_matrix = get_profile_matrix(fastaseqs)

    # calculate a concensus string
    concensus_string = get_concensus_string(profile_matrix)

    # format output
    print(concensus_string)
    for key, chars in profile_matrix.items():
        print('{}: {}'.format(key, ' '.join(str(char) for char in chars)))