from numpy_lru_cache_decorator import np_cache
@np_cache()
def function(array):
...
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======= | |
Modules | |
======= | |
This is an in-depth dive into understanding how Ansible makes use of modules. | |
It will be of use to people working on the portions of the Core Ansible Engine | |
that execute a module, it may be of interest to people writing Ansible Modules, | |
and people simply wanting to use Ansible Modules will likely want to read | |
a different paper. |
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--- | |
hosts: all | |
tasks: | |
- name: add github ssh key | |
copy: > | |
src=files/id_rsa.github | |
dest=/root/.ssh/id_rsa.github | |
owner=root | |
group=root |
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1. Setup a project | |
2. Add groovy SDK support: | |
https://www.bonusbits.com/wiki/HowTo:Add_Groovy_SDK_to_IntelliJ_IDEA | |
3. Download http://(yourjenkinsurl)/job/(yourpipelinejob)/pipeline-syntax/gdsl | |
- this will give you the .gdsl file - download this to the src folder of your project. | |
4. Finally follow this step - right click on the src folder -> Mark directory as -> Sources Root |
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def manager = org.jenkins.plugins.lockableresources.LockableResourcesManager.get() | |
def resources = manager.getResources().findAll{ | |
!it.locked | |
} | |
resources.each{ | |
manager.getResources().remove(it) | |
} | |
manager.save() |
I am assuming you are here because like me, you installed a bazillion different python interpreters on mac and the whole thing is a spagetti. Today, I finally fixed my python installation. Whatever I install for python2 or python3 using pip JUST.WORKS.. My god! finally.
Here is what I had messed up, which you also probably did:
- I had too many different python interpreters
- Too many different symlinks which I lost track of
- almost no package I installed with pip worked without a headache
- any attempt to fix using online resources made it worse.
Not KVM bound. The VFIO API deconstructs a device into regions, irqs, etc. The userspace application (QEMU, cloud-hypervisor, etc..) is responsible for reconstructing it into a device for e.g. a guest VM to consume.
Boot with intel_iommu=on
.
Devices are bound together for isolation, IOMMU capabilities and platform topology reasons. It is not configurable.