def __init__(self):

self.dict = None

self.paper_ID = None

self.proteins = None

self.protein1 = None

self.protein2 = None

def get_paper_ID(self, data):

for key, value in data.iteritems() :

data = {}

data[dir_entry] = my_file.read()

a1_file = A1_File()

a1_file.dict = data

a1_file.paper_ID = a1_file.get_paper_ID(data)

a1_file.proteins = first_two_proteins

a1_file.protein1 = first_two_proteins[0]

a1_file.protein2 = first_two_proteins[1]

path = r'C:\Users\Adam\workspace\Wiki Pi NLP\Test_Set_Files_BIONLP09\dot_a1_files'

count = 0

for dir_entry in os.listdir(path):

count += 1

if count > size_of_test_set:

break

dir_entry_path = os.path.join(path, dir_entry)

if os.path.isfile(dir_entry_path):

with open(dir_entry_path, 'r') as my_file:

reader=csv.reader(my_file,delimiter='\t')

rows = []

for row in reader:

rows.append(row)

first_two_proteins = []

for lst in rows[:2]:

first_two_proteins.append(lst[2])

if len(first_two_proteins) != 2:

continue

first_two_proteins = [x.lower() for x in first_two_proteins]

#first_two_proteins = [x.replace('-',' ') for x in first_two_proteins]

if first_two_proteins[0] == first_two_proteins[1]:

continue

a1_file = make_a1_file_object(my_file, dir_entry,first_two_proteins)

print a1_file.proteins, count