# Using Standard Data Types¶

## Defining Constant Values¶

In many cases, Pyomo models can be constructed without Set and Param data components. Native Python data types class can be simply used to define constant values in Pyomo expressions. Consequently, Python sets, lists and dictionaries can be used to construct Pyomo models, as well as a wide range of other Python classes.

TODO

More examples here: set, list, dict, numpy, pandas.

## Initializing Set and Parameter Components¶

The Set and Param components used in a Pyomo model can also be initialized with standard Python data types. This enables some modeling efficiencies when manipulating sets (e.g. when re-using sets for indices), and it supports validation of set and parameter data values. The Set and Param components are initialized with Python data using the initialize option.

### Set Components¶

In general, Set components can be initialized with iterable data. For example, simple sets can be initialized with:

• list, set and tuple data:

model.A = Set(initialize=[2,3,5])
model.B = Set(initialize=set([2,3,5]))
model.C = Set(initialize=(2,3,5))

• generators:

model.D = Set(initialize=range(9))
model.E = Set(initialize=(i for i in model.B if i%2 == 0))

• numpy arrays:

f = numpy.array([2, 3, 5])
model.F = Set(initialize=f)


Sets can also be indirectly initialized with functions that return native Python data:

def g(model):
return [2,3,5]
model.G = Set(initialize=g)


Indexed sets can be initialized with dictionary data where the dictionary values are iterable data:

H_init = {}
H_init[2] = [1,3,5]
H_init[3] = [2,4,6]
H_init[4] = [3,5,7]
model.H = Set([2,3,4],initialize=H_init)


### Parameter Components¶

When a parameter is a single value, then a Param component can be simply initialized with a value:

model.a = Param(initialize=1.1)


More generally, Param components can be initialized with dictionary data where the dictionary values are single values:

model.b = Param([1,2,3], initialize={1:1, 2:2, 3:3})


Parameters can also be indirectly initialized with functions that return native Python data:

def c(model):
return {1:1, 2:2, 3:3}
model.c = Param([1,2,3], initialize=c)