CSV-Compare

import csv, datetime

def _headers_count(csv_reader):
    return len(list(csv_reader)[0])

def _get_headers(csv_reader):
	return list(csv_reader)[0]

def _records_count(csv_reader):
	return len(list(csv_reader))

def _header_is_repeated(csv_reader):
	# print 'csv_reader: ', csv_reader
	return len(list(csv_reader)[0]) != len(set(list(csv_reader)[0]))

def _identifier_is_repeated(csv_reader):
	identifiers = [e[0] for e in list(csv_reader)[1:]]
	return len(identifiers) != len( set(identifiers) )

def parse(csv_reader):
	return list(csv_reader)


def compare_csv(file1, file2, generated_file_path):
    csv_file1 = file1
    csv_file2 = file2

    generated_file_name = 'results-{timestamp}.csv'.format( timestamp=str(datetime.datetime.utcnow()) )
    generated_file = open(generated_file_path + '/' +generated_file_name, 'wb')

    writer = csv.writer(generated_file, delimiter=',',
                            quotechar='|', quoting=csv.QUOTE_MINIMAL)
    
    reader1 = csv.reader(csv_file1, delimiter=',', quotechar='|')
    reader2 = csv.reader(csv_file2, delimiter=',', quotechar='|')

    csv_content1 = parse(reader1)
    csv_content2 = parse(reader2)
	
    #---------------
    # Run Tests
    #---------------
    errors_count = 0
	# Checks if each header name is unique
    if _header_is_repeated(csv_content1) or _header_is_repeated(csv_content2):
		errors_count+= 1

	# Checks if a identifier is repeated at column1
    if _identifier_is_repeated(csv_content1) or _identifier_is_repeated(csv_content2):
        errors_count+= 1

	# Checks if Count of Rows in CSV1 match count of rows in CSV2
	if _records_count(csv_content1) != _records_count(csv_content2):
		errors_count+= 1

    if errors_count == 0:		
		result_list = []
		# Set headers
		result_list.append( [(_get_headers(csv_content1)[0])] )		
		for item in csv_content1[1:]:
			result = []
			item_id = item[0]
			result = [e for e in csv_content2[1:] if e[0] == item_id]
			if result:
				result_list.append(result[0][0:1])
		writer.writerows(result_list)
		return {
            'data': result_list,
            'file': generated_file_name,
            'errors': None
        }
    else:
		print 'errors_count: ', errors_count
		return False