The .csv format

The .csv format

Call the functions of this format:

import pulling.Csv as csv

csv.function(arguments)

Possible methods:

get_data( path ) is a function that returns data from a file as a list, where each sublist is a row from the file and the sublist elements are columns in a row.

• path is the path to the required file.

find_data( path, pattern_list ) - a function that returns matches from file data as a dictionary, where the key is a search pattern and the value is a list with found matches.

• path - is the path to the required file.

• pattern_list - a list with templates, where each template is a separate list element.

write_data( path, data_list, mode='w' ) is a function that writes data to a file and saves it.

• path - the path of the file to which the data should be written.

• data_list - a list, where each sublist is a string to be saved to the file. And sublist elements are columns in a row.

• mode - file opening mode. The default reading mode is 'w'.

replace_data( path, new_path, replacement_dict ) - a function that accepts dictionary with data, replaces data and saves these changes in a new file.

• path - file path from which data should be taken.

• new_path - path of the file, in which the changes should be written. If you enter the same path, the changes will be saved in this file.

• replacement_dict - dictionary with data, where dictionary keys are data to be replaced, and dictionary element value is data to be replaced.

Code sample

import pulling.Avro as avro

path = 'path\file.csv'.

data = [ ['Name', 'Age'] , ['Seraphim', '16'] , ['Nikolas', '13'] ].

csv.write_data(path, data)

Writing complete.

found_data = csv.find_data(path, ['16', 'Nikolas']).

print(found_data)

{

'16': ['Seraphim', '16'],

'Nikolai': ['Nicholas', '13']

}

csv.replace_data(path, path, {'Nikolas': 'Kolya', '16': '17' }).

Writing complete.

result_data = csv.get_data(path)

print(result_data)

[ ['Name', 'Age'], ['Seraphim', '17'], ['Kolya', '13'] ].