Ansible Pilot

Automating File Extension Validation with Ansible

How to use the regular expression within an Ansible Playbook.

April 11, 2024
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In the age of automation, managing file integrity across diverse environments is crucial for ensuring data consistency and security. Ansible, a powerful IT automation tool, offers an efficient way to automate tasks and ensure that files meet specified criteria, such as having correct file extensions. This article presents a detailed guide on using Ansible to validate file extensions within a system.

Understanding the Playbook Structure

The given Ansible playbook is designed to validate file extensions to ensure that each file ends with specified formats (e.g., .csv or .txt). Here’s a breakdown of the playbook’s components:

- name: Validate file extensions
  hosts: all
    my_dicts: [
      { file_name: 'data1.csv' },
      { file_name: 'report.txt' },
      { file_name: 'summary.json' }

    - name: Check file extensions
        that: item is match('.*\.(csv|txt)$')
        fail_msg: "File with invalid extension detected: {{ item }}"
        success_msg: "Valid file extension for file: {{ item }}"
      loop: "{{ my_dicts | map(attribute='file_name') | list }}"
        label: "{{ item }}"

Key Components Explained

  1. Hosts: The playbook targets localhost, meaning it runs on the local machine. This setup is ideal for scripts that manage local files or perform tests without affecting remote systems.

  2. Variables: The my_dicts variable is a list of dictionaries, each representing a file with a file_name key. This structure is flexible and can be expanded to include more files or metadata as needed.

  3. Tasks:

    • Check file extensions: This task utilizes the assert module, which checks conditions and fails if the conditions are not met. The condition here ensures each file name matches the regex pattern '.*\.(csv|txt)$', confirming it ends with .csv or .txt.

    • Loop: The playbook iterates over each filename extracted from my_dicts, applying the validation condition to each.

    • Loop Control: The label control improves the readability of loop outputs by customizing how looped items are displayed.

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Execution Flow and Output

When executed, the playbook performs the following steps:

  1. Gathering Facts: Collects the system facts from localhost.
  2. Check File Extensions: Validates each file’s extension. If a file does not meet the criteria, the playbook fails for that file, indicating which file has an invalid extension.

The output snippet below illustrates the playbook’s execution results:

PLAY [Validate file extensions] ******************************************************************************************************************

TASK [Gathering Facts] ***************************************************************************************************************************
ok: [localhost]

TASK [Check file extensions] *********************************************************************************************************************
ok: [localhost] => (item=data1.csv) => {
    "ansible_loop_var": "item",
    "changed": false,
    "item": "data1.csv",
    "msg": "Valid file extension for file: data1.csv"
ok: [localhost] => (item=report.txt) => {
    "ansible_loop_var": "item",
    "changed": false,
    "item": "report.txt",
    "msg": "Valid file extension for file: report.txt"
failed: [localhost] (item=summary.json) => {
    "ansible_loop_var": "item",
    "assertion": "item is match('.*\\.(csv|txt)$')",
    "changed": false,
    "evaluated_to": false,
    "item": "summary.json",
    "msg": "File with invalid extension detected: summary.json"

PLAY RECAP ***************************************************************************************************************************************
localhost                  : ok=1    changed=0    unreachable=0    failed=1    skipped=0    rescued=0    ignored=0

In this output:


Automating file validation with Ansible not only streamlines the process of maintaining file standards across systems but also enhances security by ensuring that only files with correct formats are processed or moved forward in workflows. By adapting the playbook provided, organizations can enforce data quality and integrity standards efficiently, reducing manual oversight and the potential for errors.

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