import glob
path = '/Documents/Data/*'
read_files = glob.glob(path)
with open("result.txt", "wb") as outfile:
    for f in read_files:
        with open(f, "rb") as infile:
            outfile.write(infile.read())

import glob
import csv
from collections import OrderedDict

# make an ordered dict for the fields
# for each field add
#(FIELD, (start, end))
# note that index starts at 0
FIELDS_MAP = OrderedDict([('NBR', (0, 40)),
                          ('DT', (40,72)),
                          ('TYP', (72, 112)),
                          ('POST', (112, 113)),
                          ('CURR', (113, 116)),
                          ('DECI', (116, 156)),
                          ('ORIG', (156, ))]) # last field has no end index


def parse_line(line):
    my_data = {}
    for key, value in FIELDS_MAP.items():
        if len(value) == 2:
            start, end = value
            my_data[key] = line[start:end] # slice from index start to index end-1
        else:
            start = value[0]
            my_data[key] = line[start:] # slice from index start to the end
    return my_data


path = '/Documents/Data/*'
read_files = glob.glob(path)
with open("result.txt", "wb") as outfile:
    wrtr = csv.DictWriter(outfile, fieldnames = FIELDS_MAP.keys())
    wrtr.writeheader()
    for f in read_files:
        with open(f, "rb") as infile:
            for line in infile:
                wrtr.writerow(parse_line(line))