import_data.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 10 13:17:43 2020

FUNCTION TO PREPARE SOURCE DATA TO WHAT GET_SECTIONS() EXPECTS, AN ITERABLE:
EITHER A PD.IO.PARSERS.TEXTFILEREADER OR A LIST, DEPENDING ON
SOURCE TYPE AND CHUNKSIZE ARGUMENT
BASICALLY 1 RECORD (ONE OR MULTIPLE REPORTS) IN ONE LINE

delimiter="\t" option in pandas.read_fwf avoids white spaces at taild 
to be stripped

@author: iregon

OPTIONS IN OLD DEVELOPMENT:
    1. DLMT: delimiter = ',' default
        names = [ (x,y) for x in schema['sections'].keys() for y in schema['sections'][x]['elements'].keys()]
        missing = { x:schema['sections'][x[0]]['elements'][x[1]].get('missing_value') for x in names }
        TextParser = pd.read_csv(source,header = None, delimiter = delimiter, encoding = 'utf-8',
                                 dtype = 'object', skip_blank_lines = False, chunksize = chunksize,
                                 skiprows = skiprows, names = names, na_values = missing)

    2. FWF:# delimiter = '\t' so that it reads blanks as blanks, otherwise reads as empty: NaN
    this applies mainly when reading elements from sections, but we leave it also here
    TextParser = pd.read_fwf(source,widths=[FULL_WIDTH],header = None, skiprows = skiprows, delimiter="\t", chunksize = chunksize)

"""

import pandas as pd
import os
from mdf_reader import properties

def import_data(source,chunksize = None, skiprows = None):

    if isinstance(source,pd.io.parsers.TextFileReader):
        TextParser = source
    elif os.path.isfile(source):
        TextParser = pd.read_fwf(source,widths=[properties.MAX_FULL_REPORT_WIDTH],header = None, delimiter="\t", skiprows = skiprows, chunksize = chunksize)
        if not chunksize:
            TextParser = [TextParser]
    else:
        print('Error')
    return TextParser