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DPF Framework 2026 R1

utility:split in for each range

Last update: 31.07.2026

Version: 0.0.0

Description

Split a scoping into several pieces so you can iterate it with a for_each loop.

Inputs

This table lists the input pins for this operator. Input pins define the data that the operator requires to perform its operation. Some inputs are required, while others are optional and provide additional configuration. Each parameter is detailed in the sections that follow the table.

Pin number Name Status Expected type(s)
0 iterable
1 operator_to_iterate Required operator
2 pin_index Required int32
3 scoping Required scoping
4 chunk_size Required int32

iterable (Pin 0)

  • Required: No
  • Expected type(s):

Iterable that can be combined with the one currently generated.

operator_to_iterate (Pin 1)

  • Required: Yes
  • Expected type(s): operator

Operator that must be reconnected with the range values.

pin_index (Pin 2)

  • Required: Yes
  • Expected type(s): int32

scoping (Pin 3)

  • Required: Yes
  • Expected type(s): scoping

chunk_size (Pin 4)

  • Required: Yes
  • Expected type(s): int32

Outputs

This table lists the output pins for this operator. Output pins provide the results of the operator's computation and can be connected to inputs of other operators or retrieved for further processing. Each output is detailed in the sections that follow the table.

Pin number Name Expected type(s)
0 output

output (Pin 0)

  • Expected type(s):

Configurations

This operator supports configuration options that modify its behavior.

mutex

  • Expected type(s): bool
  • Default value: false

If this option is set to true, the shared memory is prevented from being simultaneously accessed by multiple threads.

Scripting

This operator can be accessed through scripting interfaces using these identifiers.

Category: utility

Plugin: core

Scripting name: split_in_for_each_range

Full name: utility.split_in_for_each_range

Internal name: chunk_in_for_each_range

License: None

Examples

These examples demonstrate how to use this operator in different programming environments. Each example shows how to instantiate the operator, connect the required inputs, and retrieve the output.

C++
#include "dpf_api.h"

ansys::dpf::Operator op("chunk_in_for_each_range"); // operator instantiation
op.connect(0, my_iterable);
op.connect(1, my_operator_to_iterate);
op.connect(2, my_pin_index);
op.connect(3, my_scoping);
op.connect(4, my_chunk_size);
 my_output = op.getOutput<>(0);
CPython
import ansys.dpf.core as dpf

op = dpf.operators.utility.split_in_for_each_range() # operator instantiation
op.inputs.iterable.connect(my_iterable)
op.inputs.operator_to_iterate.connect(my_operator_to_iterate)
op.inputs.pin_index.connect(my_pin_index)
op.inputs.scoping.connect(my_scoping)
op.inputs.chunk_size.connect(my_chunk_size)
my_output = op.outputs.output()
IPython
import mech_dpf
import Ans.DataProcessing as dpf

op = dpf.operators.utility.split_in_for_each_range() # operator instantiation
op.inputs.iterable.Connect(my_iterable)
op.inputs.operator_to_iterate.Connect(my_operator_to_iterate)
op.inputs.pin_index.Connect(my_pin_index)
op.inputs.scoping.Connect(my_scoping)
op.inputs.chunk_size.Connect(my_chunk_size)
my_output = op.outputs.output.GetData()

Changelog

  • Version 0.0.0: Initial release.

Connect with Ansys