I'm getting different results when using loop vs with_items when trying to iterate over a list of dictionaries.
I've tried using loop|dict2items (the structure isn't a dictionary, & it tells me as much. heh) and loop with the flatten filter.
Here is the list of dictionaries:
"msg": [
{
"id": "id1",
"ip": "ip1",
"name": "name1"
},
{
"id": "id2",
"ip": "ip2",
"name": "name2"
},
{
"id": "id3",
"ip": "ip3",
"name": "name3"
},
{
"id": "id4",
"ip": "ip4",
"name": "name4"
}
]
}
Here is the task in the playbook:
- name: Add privateIp windows_instances to inventory
add_host:
name: "{{ item.ip }}"
aws_name: "{{ item.name }}"
groups: windows_instances
aws_instanceid: "{{ item.id }}"
ansible_user: "{{ windows_user }}"
ansible_password: "{{ windows_password }}"
ansible_port: 5985
ansible_connection: winrm
ansible_winrm_server_cert_validation: ignore
loop:
- "{{ list1 | flatten(levels=1) }}"
When attempting to run the above code, I get the "list object has no attribute" error. I've tried different flatten levels to no avail.
HOWEVER...
If I simply replace the loop above with:
with_items:
- "{{ list1 }}"
Everything works perfectly. I'm missing something in the with_items > loop translation here...
The with_ keywords rely on Lookup Plugins - even items is a lookup. The loop keyword is equivalent to with_list, and is the best choice for simple loops. The loop keyword will not accept a string as input, see Ensuring list input for loop: query vs. lookup.
Ansible's syntax also supports the idea of nested looping. Nested loops in many ways are similar in nature to a set of arrays that would be iterated over using the with_nested operator. Nested loops provide us with a succinct way of iterating over multiple lists within a single task.
Ansible loop is used to repeat any task or a part of code multiple times in an Ansible-playbook. It includes the creation of multiple users using the user module, installing multiple packages using apt or yum module or changing permissions on several files or folders using the file module.
When creating loops, Ansible provides these two directives: loop and with_* keyword. The loop keyword was recently added to Ansible 2.5. The loop keyword is usually used to create simple and standard loops that iterate through several items.
Don't put a -
before your list.
And here, you have a list of dicts, so you don't need to flatten neither.
This playbook:
- hosts: localhost
gather_facts: no
vars:
demo_list:
- ip: 1.2.3.4
id: 1
name: demo1
- ip: 2.2.3.4
id: 2
name: demo2
- ip: 3.2.3.4
id: 3
name: demo3
tasks:
- name: the list
debug:
msg: "{{ demo_list }}"
- name: unflattened list
debug:
msg: "{{ item.id }} {{ item.ip }} {{ item.name }}"
loop:
"{{ demo_list }}"
- name: flattened list == unflattened list in this case
debug:
msg: "{{ item.id }} {{ item.ip }} {{ item.name }}"
loop:
"{{ demo_list | flatten(levels=1) }}"
gives this result:
PLAY [localhost] ***************************************************************************************
TASK [the list] ****************************************************************************************
ok: [localhost] => {
"msg": [
{
"id": 1,
"ip": "1.2.3.4",
"name": "demo1"
},
{
"id": 2,
"ip": "2.2.3.4",
"name": "demo2"
},
{
"id": 3,
"ip": "3.2.3.4",
"name": "demo3"
}
]
}
TASK [unflattened list] ********************************************************************************
ok: [localhost] => (item=None) => {
"msg": "1 1.2.3.4 demo1"
}
ok: [localhost] => (item=None) => {
"msg": "2 2.2.3.4 demo2"
}
ok: [localhost] => (item=None) => {
"msg": "3 3.2.3.4 demo3"
}
TASK [flattened list == unflattened list in this case] *************************************************
ok: [localhost] => (item=None) => {
"msg": "1 1.2.3.4 demo1"
}
ok: [localhost] => (item=None) => {
"msg": "2 2.2.3.4 demo2"
}
ok: [localhost] => (item=None) => {
"msg": "3 3.2.3.4 demo3"
}
PLAY RECAP *********************************************************************************************
localhost : ok=3 changed=0 unreachable=0 failed=0
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With