http://ibmdecisionoptimization.github.io/docplex-doc/mp/docplex.mp.model.html

In above link it provides some information about how to define an optimization model using docplex.
I have solved optimization model as follows.

mymodel = Model("demo_model")

I noted that a model can be defined as following method as well.

mymodel = Model(name="demo_model",checker='on');

I see in the link above it explains the usage checker,,Can someone explain with an example how we can use this feature in optimization models.How we can enhance modeling by using this 'checker' feature.

Thanks.

------------------------------
Suresh Abeyweera
------------------------------

#DecisionOptimization

The `checker` argument lets you control the amount of type-checking that DOcplex performs on method arguments.
By default(checker='on'), DOcplex checks the type of _all_ argument methods, issuing message that are relevant to modeling;
of course this comes with a runtime cost, in the modeling phase (the solve time itself is unchanged)

Setting checker='off' disables all type-checking. Use this option only when your model has been completely tuned and debugged.
On one hand, this might speed up model build time, but unexpected arguments might well print hard-to-understand messages.
At least this option let you switch type-checking on and off

------------------------------
Philippe Couronne
------------------------------

Original Message:
Sent: Tue October 20, 2020 06:06 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

http://ibmdecisionoptimization.github.io/docplex-doc/mp/docplex.mp.model.html

In above link it provides some information about how to define an optimization model using docplex.
I have solved optimization model as follows.

mymodel = Model("demo_model")

I noted that a model can be defined as following method as well.

mymodel = Model(name="demo_model",checker='on');

I see in the link above it explains the usage checker,,Can someone explain with an example how we can use this feature in optimization models.How we can enhance modeling by using this 'checker' feature.

Thanks.

------------------------------
Suresh Abeyweera
------------------------------

#DecisionOptimization

Hi Philippe, Thanks for your prompt reply. By refereing your answer I understand that I am not well familiar with what is meant by 'all type-checking' in your reply .Is there anyplace that I can understand this concept.Thanks

------------------------------
Suresh Abeyweera
------------------------------

Original Message:
Sent: Tue October 20, 2020 06:29 AM
From: Philippe Couronne
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

The `checker` argument lets you control the amount of type-checking that DOcplex performs on method arguments.
By default(checker='on'), DOcplex checks the type of _all_ argument methods, issuing message that are relevant to modeling;
of course this comes with a runtime cost, in the modeling phase (the solve time itself is unchanged)

Setting checker='off' disables all type-checking. Use this option only when your model has been completely tuned and debugged.
On one hand, this might speed up model build time, but unexpected arguments might well print hard-to-understand messages.
At least this option let you switch type-checking on and off

------------------------------
Philippe Couronne

Original Message:
Sent: Tue October 20, 2020 06:06 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

http://ibmdecisionoptimization.github.io/docplex-doc/mp/docplex.mp.model.html

In above link it provides some information about how to define an optimization model using docplex.
I have solved optimization model as follows.

mymodel = Model("demo_model")

I noted that a model can be defined as following method as well.

mymodel = Model(name="demo_model",checker='on');

I see in the link above it explains the usage checker,,Can someone explain with an example how we can use this feature in optimization models.How we can enhance modeling by using this 'checker' feature.

Thanks.

------------------------------
Suresh Abeyweera
------------------------------

#DecisionOptimization

Type checking means checking the _type_ of the arguments passed to DOcplex methods. Let's take an example with `Model.add_constraint`, 
which expects a constraint. If I pass a string instead, with checker='on' , as below

Model(checker='on').add_constraint("foo")

I get this message:

>>> docplex.mp.utils.DOcplexException: Expecting constraint, got: 'foo' with type: <class 'str'>

With typechecking disabled, I get:


Model(checker='off').add_constraint("foo")
>>> AttributeError: 'str' object has no attribute '_index'

Which is a lot more cryptic. The rule of thumb is: do not bother with `checker' until you have serious model building performance issues,
for which you might look here for general ideas:

https://github.com/IBMDecisionOptimization/docplex-examples/blob/master/examples/mp/jupyter/efficient.ipynb






------------------------------
Philippe Couronne
------------------------------

Original Message:
Sent: Tue October 20, 2020 06:52 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

Hi Philippe, Thanks for your prompt reply. By refereing your answer I understand that I am not well familiar with what is meant by 'all type-checking' in your reply .Is there anyplace that I can understand this concept.Thanks

------------------------------
Suresh Abeyweera

Original Message:
Sent: Tue October 20, 2020 06:29 AM
From: Philippe Couronne
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

The `checker` argument lets you control the amount of type-checking that DOcplex performs on method arguments.
By default(checker='on'), DOcplex checks the type of _all_ argument methods, issuing message that are relevant to modeling;
of course this comes with a runtime cost, in the modeling phase (the solve time itself is unchanged)

Setting checker='off' disables all type-checking. Use this option only when your model has been completely tuned and debugged.
On one hand, this might speed up model build time, but unexpected arguments might well print hard-to-understand messages.
At least this option let you switch type-checking on and off

------------------------------
Philippe Couronne

Original Message:
Sent: Tue October 20, 2020 06:06 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

http://ibmdecisionoptimization.github.io/docplex-doc/mp/docplex.mp.model.html

In above link it provides some information about how to define an optimization model using docplex.
I have solved optimization model as follows.

mymodel = Model("demo_model")

I noted that a model can be defined as following method as well.

mymodel = Model(name="demo_model",checker='on');

I see in the link above it explains the usage checker,,Can someone explain with an example how we can use this feature in optimization models.How we can enhance modeling by using this 'checker' feature.

Thanks.

------------------------------
Suresh Abeyweera
------------------------------

#DecisionOptimization

This is super Philippe.I understood the concept clearly. Thanks for the update.

------------------------------
Suresh Abeyweera
------------------------------

Original Message:
Sent: Tue October 20, 2020 08:50 AM
From: Philippe Couronne
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

Type checking means checking the _type_ of the arguments passed to DOcplex methods. Let's take an example with `Model.add_constraint`, 
which expects a constraint. If I pass a string instead, with checker='on' , as below

Model(checker='on').add_constraint("foo")

I get this message:

>>> docplex.mp.utils.DOcplexException: Expecting constraint, got: 'foo' with type: <class 'str'>

With typechecking disabled, I get:


Model(checker='off').add_constraint("foo")
>>> AttributeError: 'str' object has no attribute '_index'

Which is a lot more cryptic. The rule of thumb is: do not bother with `checker' until you have serious model building performance issues,
for which you might look here for general ideas:

https://github.com/IBMDecisionOptimization/docplex-examples/blob/master/examples/mp/jupyter/efficient.ipynb






------------------------------
Philippe Couronne

Original Message:
Sent: Tue October 20, 2020 06:52 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

Hi Philippe, Thanks for your prompt reply. By refereing your answer I understand that I am not well familiar with what is meant by 'all type-checking' in your reply .Is there anyplace that I can understand this concept.Thanks

------------------------------
Suresh Abeyweera

Original Message:
Sent: Tue October 20, 2020 06:29 AM
From: Philippe Couronne
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

The `checker` argument lets you control the amount of type-checking that DOcplex performs on method arguments.
By default(checker='on'), DOcplex checks the type of _all_ argument methods, issuing message that are relevant to modeling;
of course this comes with a runtime cost, in the modeling phase (the solve time itself is unchanged)

Setting checker='off' disables all type-checking. Use this option only when your model has been completely tuned and debugged.
On one hand, this might speed up model build time, but unexpected arguments might well print hard-to-understand messages.
At least this option let you switch type-checking on and off

------------------------------
Philippe Couronne

Original Message:
Sent: Tue October 20, 2020 06:06 AM
From: Suresh Abeyweera
Subject: class docplex.mp.model.Model(name=None, checker = "on") what is checker

http://ibmdecisionoptimization.github.io/docplex-doc/mp/docplex.mp.model.html

In above link it provides some information about how to define an optimization model using docplex.
I have solved optimization model as follows.

mymodel = Model("demo_model")

I noted that a model can be defined as following method as well.

mymodel = Model(name="demo_model",checker='on');

I see in the link above it explains the usage checker,,Can someone explain with an example how we can use this feature in optimization models.How we can enhance modeling by using this 'checker' feature.

Thanks.

------------------------------
Suresh Abeyweera
------------------------------

#DecisionOptimization