#!/usr/bin/python # -*- coding: utf-8 -*- # Copyright (c) 2018, Dag Wieers (@dagwieers) # GNU General Public License v3.0+ (see LICENSES/GPL-3.0-or-later.txt or https://www.gnu.org/licenses/gpl-3.0.txt) # SPDX-License-Identifier: GPL-3.0-or-later from __future__ import absolute_import, division, print_function __metaclass__ = type DOCUMENTATION = r''' --- module: read_csv short_description: Read a CSV file description: - Read a CSV file and return a list or a dictionary, containing one dictionary per row. author: - Dag Wieers (@dagwieers) extends_documentation_fragment: - community.general.attributes attributes: check_mode: support: full diff_mode: support: none options: path: description: - The CSV filename to read data from. type: path required: true aliases: [ filename ] key: description: - The column name used as a key for the resulting dictionary. - If O(key) is unset, the module returns a list of dictionaries, where each dictionary is a row in the CSV file. type: str dialect: description: - The CSV dialect to use when parsing the CSV file. - Possible values include V(excel), V(excel-tab) or V(unix). type: str default: excel fieldnames: description: - A list of field names for every column. - This is needed if the CSV does not have a header. type: list elements: str unique: description: - Whether the O(key) used is expected to be unique. type: bool default: true delimiter: description: - A one-character string used to separate fields. - When using this parameter, you change the default value used by O(dialect). - The default value depends on the dialect used. type: str skipinitialspace: description: - Whether to ignore any whitespaces immediately following the delimiter. - When using this parameter, you change the default value used by O(dialect). - The default value depends on the dialect used. type: bool strict: description: - Whether to raise an exception on bad CSV input. - When using this parameter, you change the default value used by O(dialect). - The default value depends on the dialect used. type: bool seealso: - plugin: community.general.csvfile plugin_type: lookup description: Can be used to do selective lookups in CSV files from Jinja. ''' EXAMPLES = r''' # Example CSV file with header # # name,uid,gid # dag,500,500 # jeroen,501,500 # Read a CSV file and access user 'dag' - name: Read users from CSV file and return a dictionary community.general.read_csv: path: users.csv key: name register: users delegate_to: localhost - ansible.builtin.debug: msg: 'User {{ users.dict.dag.name }} has UID {{ users.dict.dag.uid }} and GID {{ users.dict.dag.gid }}' # Read a CSV file and access the first item - name: Read users from CSV file and return a list community.general.read_csv: path: users.csv register: users delegate_to: localhost - ansible.builtin.debug: msg: 'User {{ users.list.1.name }} has UID {{ users.list.1.uid }} and GID {{ users.list.1.gid }}' # Example CSV file without header and semi-colon delimiter # # dag;500;500 # jeroen;501;500 # Read a CSV file without headers - name: Read users from CSV file and return a list community.general.read_csv: path: users.csv fieldnames: name,uid,gid delimiter: ';' register: users delegate_to: localhost ''' RETURN = r''' dict: description: The CSV content as a dictionary. returned: success type: dict sample: dag: name: dag uid: 500 gid: 500 jeroen: name: jeroen uid: 501 gid: 500 list: description: The CSV content as a list. returned: success type: list sample: - name: dag uid: 500 gid: 500 - name: jeroen uid: 501 gid: 500 ''' from ansible.module_utils.basic import AnsibleModule from ansible.module_utils.common.text.converters import to_native from ansible_collections.community.general.plugins.module_utils.csv import (initialize_dialect, read_csv, CSVError, DialectNotAvailableError, CustomDialectFailureError) def main(): module = AnsibleModule( argument_spec=dict( path=dict(type='path', required=True, aliases=['filename']), dialect=dict(type='str', default='excel'), key=dict(type='str', no_log=False), fieldnames=dict(type='list', elements='str'), unique=dict(type='bool', default=True), delimiter=dict(type='str'), skipinitialspace=dict(type='bool'), strict=dict(type='bool'), ), supports_check_mode=True, ) path = module.params['path'] dialect = module.params['dialect'] key = module.params['key'] fieldnames = module.params['fieldnames'] unique = module.params['unique'] dialect_params = { "delimiter": module.params['delimiter'], "skipinitialspace": module.params['skipinitialspace'], "strict": module.params['strict'], } try: dialect = initialize_dialect(dialect, **dialect_params) except (CustomDialectFailureError, DialectNotAvailableError) as e: module.fail_json(msg=to_native(e)) try: with open(path, 'rb') as f: data = f.read() except (IOError, OSError) as e: module.fail_json(msg="Unable to open file: %s" % to_native(e)) reader = read_csv(data, dialect, fieldnames) if key and key not in reader.fieldnames: module.fail_json(msg="Key '%s' was not found in the CSV header fields: %s" % (key, ', '.join(reader.fieldnames))) data_dict = dict() data_list = list() if key is None: try: for row in reader: data_list.append(row) except CSVError as e: module.fail_json(msg="Unable to process file: %s" % to_native(e)) else: try: for row in reader: if unique and row[key] in data_dict: module.fail_json(msg="Key '%s' is not unique for value '%s'" % (key, row[key])) data_dict[row[key]] = row except CSVError as e: module.fail_json(msg="Unable to process file: %s" % to_native(e)) module.exit_json(dict=data_dict, list=data_list) if __name__ == '__main__': main()