mirror of
https://github.com/ansible-collections/community.general.git
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245 lines
6.8 KiB
Python
245 lines
6.8 KiB
Python
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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# Copyright: (c) 2018, Dag Wieers (@dagwieers) <dag@wieers.com>
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# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
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from __future__ import absolute_import, division, print_function
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__metaclass__ = type
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ANSIBLE_METADATA = {'metadata_version': '1.1',
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'status': ['preview'],
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'supported_by': 'community'}
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DOCUMENTATION = r'''
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---
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module: read_csv
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short_description: Read a CSV file
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description:
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- Read a CSV file and return a list or a dictionary, containing one dictionary per row.
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author:
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- Dag Wieers (@dagwieers)
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options:
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path:
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description:
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- The CSV filename to read data from.
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type: path
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required: yes
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aliases: [ filename ]
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key:
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description:
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- The column name used as a key for the resulting dictionary.
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- If C(key) is unset, the module returns a list of dictionaries,
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where each dictionary is a row in the CSV file.
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type: str
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dialect:
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description:
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- The CSV dialect to use when parsing the CSV file.
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- Possible values include C(excel), C(excel-tab) or C(unix).
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type: str
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default: excel
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fieldnames:
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description:
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- A list of field names for every column.
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- This is needed if the CSV does not have a header.
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type: list
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unique:
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description:
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- Whether the C(key) used is expected to be unique.
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type: bool
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default: yes
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delimiter:
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description:
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- A one-character string used to separate fields.
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- When using this parameter, you change the default value used by C(dialect).
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- The default value depends on the dialect used.
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type: str
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skipinitialspace:
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description:
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- Whether to ignore any whitespaces immediately following the delimiter.
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- When using this parameter, you change the default value used by C(dialect).
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- The default value depends on the dialect used.
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type: bool
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strict:
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description:
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- Whether to raise an exception on bad CSV input.
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- When using this parameter, you change the default value used by C(dialect).
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- The default value depends on the dialect used.
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type: bool
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notes:
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- Ansible also ships with the C(csvfile) lookup plugin, which can be used to do selective lookups in CSV files from Jinja.
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'''
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EXAMPLES = r'''
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# Example CSV file with header
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#
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# name,uid,gid
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# dag,500,500
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# jeroen,501,500
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# Read a CSV file and access user 'dag'
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- name: Read users from CSV file and return a dictionary
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read_csv:
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path: users.csv
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key: name
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register: users
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delegate_to: localhost
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- debug:
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msg: 'User {{ users.dict.dag.name }} has UID {{ users.dict.dag.uid }} and GID {{ users.dict.dag.gid }}'
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# Read a CSV file and access the first item
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- name: Read users from CSV file and return a list
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read_csv:
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path: users.csv
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register: users
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delegate_to: localhost
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- debug:
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msg: 'User {{ users.list.1.name }} has UID {{ users.list.1.uid }} and GID {{ users.list.1.gid }}'
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# Example CSV file without header and semi-colon delimiter
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#
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# dag;500;500
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# jeroen;501;500
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# Read a CSV file without headers
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- name: Read users from CSV file and return a list
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read_csv:
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path: users.csv
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fieldnames: name,uid,gid
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delimiter: ';'
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register: users
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delegate_to: localhost
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'''
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RETURN = r'''
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dict:
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description: The CSV content as a dictionary.
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returned: success
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type: dict
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sample:
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dag:
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name: dag
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uid: 500
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gid: 500
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jeroen:
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name: jeroen
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uid: 501
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gid: 500
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list:
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description: The CSV content as a list.
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returned: success
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type: list
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sample:
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- name: dag
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uid: 500
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gid: 500
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- name: jeroen
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uid: 501
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gid: 500
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'''
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import csv
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from io import BytesIO, StringIO
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from ansible.module_utils.basic import AnsibleModule
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from ansible.module_utils._text import to_text
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from ansible.module_utils.six import PY3
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# Add Unix dialect from Python 3
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class unix_dialect(csv.Dialect):
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"""Describe the usual properties of Unix-generated CSV files."""
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delimiter = ','
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quotechar = '"'
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doublequote = True
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skipinitialspace = False
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lineterminator = '\n'
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quoting = csv.QUOTE_ALL
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csv.register_dialect("unix", unix_dialect)
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def main():
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module = AnsibleModule(
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argument_spec=dict(
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path=dict(type='path', required=True, aliases=['filename']),
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dialect=dict(type='str', default='excel'),
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key=dict(type='str'),
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fieldnames=dict(type='list'),
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unique=dict(type='bool', default=True),
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delimiter=dict(type='str'),
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skipinitialspace=dict(type='bool'),
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strict=dict(type='bool'),
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),
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supports_check_mode=True,
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)
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path = module.params['path']
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dialect = module.params['dialect']
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key = module.params['key']
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fieldnames = module.params['fieldnames']
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unique = module.params['unique']
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if dialect not in csv.list_dialects():
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module.fail_json(msg="Dialect '%s' is not supported by your version of python." % dialect)
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dialect_options = dict(
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delimiter=module.params['delimiter'],
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skipinitialspace=module.params['skipinitialspace'],
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strict=module.params['strict'],
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)
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# Create a dictionary from only set options
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dialect_params = dict((k, v) for k, v in dialect_options.items() if v is not None)
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if dialect_params:
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try:
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csv.register_dialect('custom', dialect, **dialect_params)
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except TypeError as e:
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module.fail_json(msg="Unable to create custom dialect: %s" % to_text(e))
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dialect = 'custom'
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try:
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with open(path, 'rb') as f:
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data = f.read()
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except (IOError, OSError) as e:
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module.fail_json(msg="Unable to open file: %s" % to_text(e))
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if PY3:
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# Manually decode on Python3 so that we can use the surrogateescape error handler
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data = to_text(data, errors='surrogate_or_strict')
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fake_fh = StringIO(data)
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else:
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fake_fh = BytesIO(data)
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reader = csv.DictReader(fake_fh, fieldnames=fieldnames, dialect=dialect)
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if key and key not in reader.fieldnames:
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module.fail_json(msg="Key '%s' was not found in the CSV header fields: %s" % (key, ', '.join(reader.fieldnames)))
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data_dict = dict()
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data_list = list()
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if key is None:
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try:
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for row in reader:
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data_list.append(row)
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except csv.Error as e:
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module.fail_json(msg="Unable to process file: %s" % to_text(e))
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else:
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try:
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for row in reader:
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if unique and row[key] in data_dict:
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module.fail_json(msg="Key '%s' is not unique for value '%s'" % (key, row[key]))
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data_dict[row[key]] = row
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except csv.Error as e:
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module.fail_json(msg="Unable to process file: %s" % to_text(e))
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module.exit_json(dict=data_dict, list=data_list)
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if __name__ == '__main__':
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main()
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