Create a pool of Mechanical servers

The LocalMechanicalPool class simplifies creating and connecting to multiple servers of the Mechanical class for batch processing. You can use this class for batch processing a set of input files or other batch-related processes.

This code shows how to create a pool with 10 instances:

>>> from ansys.mechanical.core import LocalMechanicalPool
>>> pool = LocalMechanicalPool(10, version="242")
'Mechanical Pool with 10 active instances'

When you are creating a pool, you can supply additional keyword arguments. For example, to restart failed instances, you can set restart_failed=True:

>>> import os
>>> my_path = os.getcmd()
>>> pool = LocalMechanicalPool(10, version="242", restart_failed=True)
Creating Pool: 100%|########| 10/10 [00:01<00:00,  1.43it/s]

You can access each individual instance of Mechanical with this code:

>>> pool[0]
<ansys.mechanical.core.mechanical.Mechanical at 0x7fabf0230d90>

Because this is a self-healing pool, if an instance of Mechanical stops during a batch process, this instance is automatically restarted. When creating the pool, you can disable this behavior by setting restart_failed=False.

Run a set of input files

You can use the pool to run a set of pre-generated input files using the run_batch() method.

For example, you can run the first set of 20 verification files with this code:

>>>>>> from ansys.mechanical.core import examples
>>> files = [f"test{index}.py" for index in range(1, 21)]
>>> outputs = pool.run_batch(files)
>>> len(outputs)
20

Run a user-defined function

While the previous example uses the run_batch() method to run a set of inputs files, you can also use the map() method to run a custom user-defined function on each instance of Mechanical over a set of input files.

>>> completed_indices = []
>>> def func(mechanical, input_file, index):
...     # input_file, index = args
...     mechanical.clear()
...     output = mechanical.run_python_script_from_file(input_file)
...     completed_indices.append(index)
...     return output
...
>>> inputs = [("test{index}.py", i) for i in range(1, 10)]
>>> output = pool.map(func, inputs, progress_bar=True, wait=True)
['result1',
 'result2',
 'result3',
 'result4',
 'result5',
 'result6',
 'result7',
 'result8',
 'result9']