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ansible_custom_module__replace_string_in_csv.py
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ansible_custom_module__replace_string_in_csv.py
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#!/usr/bin/python
# - name: replace dot by comma in money-amount columns of {{ rapporto_filename }}
# ansible_custom_module__replace_string_in_csv:
# path: "{{ log_base_path }}/{{ rapporto_filename }}"
# columns_to_process: "{{ [ 'ammontare' ] }}"
# string_to_be_replaced: "."
# string_to_replace_with: ","
# delimiter: ";"
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
from ansible.module_utils.basic import AnsibleModule
def run_module():
module_args = dict(
# inputs to the module
# path of the csv file where to do the replacement
path = dict(type='str', required=True),
# list with the titles the columns of the csv where you want to have the replacement done
columns_to_process = dict(type='list', required=True),
string_to_be_replaced = dict(type='str', required=True),
string_to_replace_with = dict(type='str', required=True),
delimiter = dict(type='str', required=True),
# the csv must have the first line as header
)
# this is the output of the playbook for each host
result = dict(
changed=False,
warning_messages=[],
source_csv_number_of_raw_lines=None,
source_csv_number_of_lines=None,
number_of_modified_cells=None,
# found_lines='',
# found=False
)
# options which state syntax rules for calling the module
module = AnsibleModule(
argument_spec=module_args,
supports_check_mode=True
)
# # this snippet was to access the file at indicated path, search a astring and retrun true if it was found
# with open(module.params['path'], 'r') as f:
# for line in f.readlines():
# if module.params['search_string'] in line:
# result['found_lines'] = result['found_lines'] + line
# result['found'] = True
# # define the output of the playbook for each hosts, according to what happens into the play
# result['changed'] = False
# python is calledon the target machine
#---------------------------------------
csv_file_path = module.params['path']
columns_to_process = module.params['columns_to_process']
# columns_to_order_by = ['idm', 'idc']
string_to_be_replaced = module.params['string_to_be_replaced']
string_to_replace_with = module.params['string_to_replace_with']
mydelimiter = module.params['delimiter']
#------------
# specific import for csv
import csv, io
# import operator
import shutil
# specific import to manage errors
import os, traceback
# check file existence
if not os.path.isfile(csv_file_path):
raise IOError("csv_file_path is not valid or does not exists: {}".format(csv_file_path))
# check the delimiter existence
with open(csv_file_path, 'r') as csvfile:
first_line = csvfile.readline()
# print("first_line", first_line)
if mydelimiter not in first_line:
delimiter_warning_message = "No delimiter found in file first line."
result['warning_messages'].append(delimiter_warning_message)
# count the lines in the source file
NOL = sum(1 for _ in io.open(csv_file_path, "r"))
# print("NOL:", NOL)
# if NOL = 0 -> void file
# if NOL = 1 -> header-only file
if NOL > 0:
# just get the columns names, then close the file
#-----------------------------------------------------
with open(csv_file_path, 'r') as csvfile:
columnslist = csv.DictReader(csvfile, delimiter=mydelimiter)
list_of_dictcolumns = []
# loop to iterate through the rows of csv
for row in columnslist:
# adding the first row
list_of_dictcolumns.append(row)
# breaking the loop after the
# first iteration itself
break
# transform the colum names into a list
first_dictcolumn = list_of_dictcolumns[0]
list_of_column_names = list(first_dictcolumn.keys())
number_of_columns = len(list_of_column_names)
# check columns existence
#------------------------
column_existence = [ (column_name in list_of_column_names ) for column_name in columns_to_process ]
if not all(column_existence):
raise ValueError("File {} does not contains all the columns given in input for processing:\nFile columns names: {}\nInput columns names: {}".format(csv_file_path, list_of_column_names, columns_to_process))
# determine the indexes of the columns to process
indexes_of_columns_to_process = [i for i, column_name in enumerate(list_of_column_names) if column_name in columns_to_process]
# print("indexes_of_columns_to_process: ", indexes_of_columns_to_process)
# build the path of a to-be-generated duplicate file to be used as output
inputcsv_absname, inputcsv_extension = os.path.splitext(csv_file_path)
csv_output_file_path = inputcsv_absname + '__output' + inputcsv_extension
# define the processing function
def replace_string_in_columns(input_csv, output_csv, indexes_of_columns_to_process, string_to_be_replaced, string_to_replace_with):
number_of_replacements = 0
with open(input_csv, 'r', newline='') as infile, open(output_csv, 'w', newline='') as outfile:
reader = csv.reader(infile, quoting=csv.QUOTE_NONE, delimiter=mydelimiter, quotechar='',escapechar='\\')
writer = csv.writer(outfile, quoting=csv.QUOTE_NONE, delimiter=mydelimiter, quotechar='',escapechar='\\')
# writer = csv.writer(outfile, delimiter=mydelimiter, escapechar='\\', quoting=csv.QUOTE_NONE)
row_index=0
for row in reader:
for col_index in indexes_of_columns_to_process:
# break the processing when empty lines at the end of the file are reached
if len(row) == 0:
break
cell = row[col_index]
columns_before = row[:col_index]
columns_after = row[(col_index + 1):]
# print("col_index: ", col_index)
# print("row: ", row)
# # print("list_of_cells: ", list_of_cells)
# print("cell: ", cell)
# # print("columns_before: ", columns_before)
# # print("columns_after: ", columns_after)
if string_to_be_replaced in cell and row_index != 0:
# do the substitution in the cell
cell = cell.replace(string_to_be_replaced, string_to_replace_with)
number_of_replacements = number_of_replacements + 1
# print("number_of_replacements: ", number_of_replacements)
# # sew the row up agian
row_replaced = columns_before + [ cell ] + columns_after
row = row_replaced
# write / copy the row in the new file
writer.writerow(row)
# print("written row: ", row, "index: ", row_index)
row_index=row_index+1
return number_of_replacements
# launch the function
result['number_of_modified_cells'] = replace_string_in_columns(csv_file_path, csv_output_file_path, indexes_of_columns_to_process, string_to_be_replaced, string_to_replace_with)
# replace the old csv with the new one
shutil.copyfile(csv_output_file_path, csv_file_path)
os.remove(csv_output_file_path)
if result['number_of_modified_cells'] > 0:
result['changed'] = True
else:
result['changed'] = False
else:
result['changed'] = False
result['source_csv_number_of_raw_lines'] = NOL
result['source_csv_number_of_lines'] = NOL - 1
#-------------
module.exit_json(**result)
def main():
run_module()
if __name__ == '__main__':
main()