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 WITH DATAFRAMES
#
#INPUT IS NOW ONLY A FILE PATH. COULD OPTIONALLY GET OTHER TYPE OBJECTS...
#
#OUTPUT IS AN ITERABLE, DEPENDING ON CHUNKSIZE BEING SET:
#    - a single dataframe in a list
#    - a pd.io.parsers.textfilereader
#
#
#WITH BASICALLY 1 RECORD (ONE OR MULTIPLE REPORTS) IN ONE LINE
#
#delimiter="\t" option in pandas.read_fwf avoids white spaces at tails
#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 .. import properties

def main(source,chunksize = None, skiprows = None):
    """

    Returns an iterable object with a pandas dataframe from
    an input data source. The pandas dataframe has a report
    per row and a single column with the full report as a
    block string.
    Currently only supports a data file path as source data,
    but could be easily extended to accept a different
    source object.
    
    Parameters
    ----------
    source : str
        Path to data file
        
    Keyword Arguments
    -----------------
    chunksize : int, opt
        Number of lines to chunk the input data into
    skiprows : int, opt
        Number of lines to skip from input file


    Returns
    -------
    iterable 
        List of with a single pandas dataframe
        or pandas.io.parsers.textfilereader
    

    """
    
    if os.path.isfile(source):
        TextParser = pd.read_fwf(source,widths=[properties.MAX_FULL_REPORT_WIDTH],header = None, delimiter="\t", skiprows = skiprows, chunksize = chunksize, quotechar='\0',escapechar='\0')
        if not chunksize:
            TextParser = [TextParser]
        return TextParser
    else:
        print('Error')
        return