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Lets say I wish to make a page that can query the desired object with type(string) and id(int).
/query?type=people&id=1
would fetch me
Person.find(1)
whereas
/query?type=cities&id=123
would fetch me
City.find(123)
However, I have problems as to how to translate strings into the desired model class.
The only way I can think of is
case params[:type]
when 'people'
@object = Person.find(params[:id])
when 'cities'
@object = City.find(params[:id])
end
However, this method will be quite problematic if I have more types of models.
Is there a better way?
Thank you in advance,
269
Like libraries, model references allow you to define a set of blocks once and use it repeatedly. Model references provide several advantages that are unavailable with subsystems and libraries.
tf.keras.Model() Model groups layers into an object with training and inference features. Arguments. inputs: The input (s) of the model: a keras.Input object or list of keras.Input objects. outputs: The output (s) of the model. See Functional API example below. name: String, the name of the model. There are two ways to instantiate a Model:
You can simulate a referenced model either interpretively (in normal mode) or by compiling the referenced model to code and executing the code (in accelerator mode). For details, see Choose Simulation Modes for Model Hierarchies.
Model References. You can include one model in another by using a Model block. Each instance of a Model block is a model reference. For simulation and code generation, blocks within a referenced model execute together as a unit. The model that contains a referenced model is a parent model.
Try:
klass = params[:type]
klass.singularize.classify.constantize.find(params[:id])
Edit:
@object = params[:type].singularize.classify.constantize.find(params[:id])
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