Output Settings

The user can control several aspects of the generated code. The options can be accessed via the hamburger icon ≡ in the top right corner of the Python API Recording dialog.

Figure 1. Output settings.

Option	Description
Code destination	Defines where the generated code is output. Valid options are Python Console, Python File, and Pulse Task.
Function name	Defines the name of the Python function.
Generate verbose code	Expands the code by creating individual variables for every argument.
Show equivalent Tcl commands	Includes equivalent Tcl commands as comments.
Include all functions	Includes view, undo/redo, and similar functions.
Enable deprecated functions	Creates a debug model object that provides access to the deprecated functions.
Append collections	Appends collections when creating collections by attached/adjacent.
Ignore popups	Inserts model.hm_answernext(“yes”) before functions that can trigger a popup.
Use ranges for ID lists	Compresses full ID lists using range function.
Include all split entity classes	Generalizes the code to act on all split entity classes.
Include tips in the comments	Includes tips about available options in the comments.
Include header comments	Includes comments at the top of the code with the information about HyperMesh version, model file, solver interface, data, time, and username.
Use list comprehension for entity lists	Compresses full list of entity objects using list comprehension.

The code destination option Pulse Task lets the user automatically generate a Pulse Task from the recorded code. It requires a Pulse installation which is used to generate the task JSON files and to output them into the Pulse Library. The function arguments are recognized and defined as Task inputs.

Figure 2. Generating a Pulse Task.

The following code snippets demonstrate how various output settings impact the generated code:

Generate verbose code

Generate verbose code - OFF

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[80, 82, 84, 90, 103, 105, 107, 113]))
model.normalsreverse(collection=collection, size=0)

Generate verbose code - ON

ids = [80, 82, 84, 90, 103, 105, 107, 113]
filterByEnumeration = hm.FilterByEnumeration(ent.Element, ids=ids)
collection = hm.Collection(model, filterByEnumeration)
size = 0
model.normalsreverse(collection=collection, size=size)

Show equivalent Tcl commands

Show equivalent Tcl commands - OFF

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[17, 18, 19, 20]))
model.maskentitymark(collection=collection, flag=0)

Show equivalent Tcl commands - ON

# [TCL]: *createmark elements 1 17-20
# [TCL]: *maskentitymark elements 1 0
collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[17, 18, 19, 20]))
model.maskentitymark(collection=collection, flag=0)

Include all functions

Include all functions - OFF

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[35, 36, 54, 56, 77, 78, 101, 249]))
model.normalsreverse(collection=collection, size=0)

Include all functions - ON

model.rotateabout(overridedefault=1, x=865, y=200, z=475)

model.viewset(a00=-0.161329937, a01=-0.986833866, a02=-0.0114705461, a03=0, a10=-0.553105123, a11=0.100036611, a12=-0.827083671, a13=0, a20=0.817341651, a21=-0.127088938, a22=-0.561961767, a23=0, a30=425.411852, a31=23.7688757, a32=333.19761, a33=1, minx=-92.2937276, miny=-1003.27125, maxx=1200.87036, maxy=-693.592482)

model.startnotehistorystate(name="Reverse Normals")

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[35, 36, 54, 56, 77, 78, 101, 249]))
model.normalsreverse(collection=collection, size=0)

model.endnotehistorystate(name="Reverse Normals")

Enable deprecated functions

Enable deprecated functions - OFF

import hm
import hm.entities as ent

model = hm.Model()

def main():
    component = ent.Component(model, 1)
    propertyid = ent.Property(model, 1)
    component.propertyid = propertyid
    component.materialid = None

    components_collection = hm.Collection(model, hm.FilterByEnumeration(ent.Component, ids=[component.id]))
    collection = hm.Collection(model, hm.FilterByCollection(ent.Element, ent.Component), components_collection)
    # [ERROR]: model.propertyupdate(collection=collection, property_name="property1")

Enable deprecated functions - ON

import hm
import hm.entities as ent

from hm.mdi import apis
model = apis.HmModelDebug()

def main():
   component = ent.Component(model, 1)
   propertyid = ent.Property(model, 1)
   component.propertyid = propertyid
   component.materialid = None

   components_collection = hm.Collection(model, hm.FilterByEnumeration(ent.Component, ids=[component.id]))
   collection = hm.Collection(model, hm.FilterByCollection(ent.Element, ent.Component), components_collection)
   model.propertyupdate(collection=collection, property_name="property1")

Append collections

Append collections - OFF

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[78]))
collection_1 = hm.CollectionByAdjacent(model, collection)
model.normalsreverse(collection=collection_1, size=0)

Append collections - ON

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[78]))
collection = hm.CollectionByAdjacent(model, collection)
model.normalsreverse(collection=collection, size=0)

Ignore popups

Ignore popups - OFF

# [TIP]: Command triggers popup window. Enable 'Ignore popups' to ignore it when running the script.
model.deletemodel()

Ignore popups - ON

model.hm_answernext('yes')
model.deletemodel()

Use ranges for ID lists

Use ranges for ID lists - OFF

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[77, 78, 79, 80, 81, 82]))
model.normalsreverse(collection=collection, size=0)

Use ranges for ID lists - ON

collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[*range(77,83)]))
model.normalsreverse(collection=collection, size=0)

Inlcude all split entity classes

Inlcude all split entity classes - OFF

loadforce_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadForce, ids=[1]))
loadforce_collection.set_items('magnitude', 100)

Inlcude all split entity classes - ON

loadforce_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadForce, ids=[1]))
loadforce_collection.set_items('magnitude', 100)
loadmoment_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadMoment, ids=hm.hwUIntList([])))
loadmoment_collection.set_items('magnitude', 100)
loadconstraint_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadConstraint, ids=hm.hwUIntList([])))
loadconstraint_collection.set_items('magnitude', 100)
loadpressure_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadPressure, ids=hm.hwUIntList([])))
loadpressure_collection.set_items('magnitude', 100)
loadtemperature_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadTemperature, ids=hm.hwUIntList([])))
loadtemperature_collection.set_items('magnitude', 100)
loadflux_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadFlux, ids=hm.hwUIntList([])))
loadflux_collection.set_items('magnitude', 100)
loadvelocity_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadVelocity, ids=hm.hwUIntList([])))
loadvelocity_collection.set_items('magnitude', 100)
loadacceleration_collection = hm.Collection(model, hm.FilterByEnumeration(ent.LoadAcceleration, ids=hm.hwUIntList([])))
loadacceleration_collection.set_items('magnitude', 100)

Include tips in the comments

Include tips in the comments - OFF

model.readfile(filename="C:/Users/Temp/my_model.hm", load_cad_geometry_as_graphics=0)

model.deletemodel()

Include tips in the comments - ON

# [TIP]: Command triggers popup window. Enable 'Ignore popups' to ignore it when running the script.
model.readfile(filename="C:/Users/Temp/my_model.hm", load_cad_geometry_as_graphics=0)

# [TIP]: Command triggers popup window. Enable 'Ignore popups' to ignore it when running the script.
model.deletemodel()

Include header comments

Include header comments - OFF

 import hm
 import hm.entities as ent

 model = hm.Model()

 def main():
    collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[81, 82, 83, 84]))
    model.normalsreverse(collection=collection, size=0)

Include header comments - ON

 # HyperMesh Python API Code Generator
 # HyperMesh Version: 2025.1
 # Model File: C:/Users/Temp/my_model.hm
 # Solver Interface: OptiStruct
 # Date: April 02, 2025
 # Time: 13:27:47
 # Author: username

 import hm
 import hm.entities as ent

 model = hm.Model()

 def main():
    collection = hm.Collection(model, hm.FilterByEnumeration(ent.Element, ids=[81, 82, 83, 84]))
    model.normalsreverse(collection=collection, size=0)

Use list comprehension for entity lists

Use list comprehension for entity lists - OFF

list = [ent.Node(model, 114), ent.Node(model, 118), ent.Node(model, 119), ent.Node(model, 138)]
direction_vector = [0.999402583,0.0343760811,0.00357038225]
model.dragnodestoformsurface(list=list, direction_vector=direction_vector, distance=40)

Use list comprehension for entity lists - ON

 list = [ent.Node(model, id) for id in [114, 118, 119, 138]]
 direction_vector = [0.999402583,0.0343760811,0.00357038225]
 model.dragnodestoformsurface(list=list, direction_vector=direction_vector, distance=40)