Builder pattern equivalent in Python


In Java, you can use the builder pattern to provide a more readable means to instantiating a class with many parameters. In the builder pattern, one constructs a configuration object with methods to set named attributes, and then uses it to construct another object.

What is the equivalent in Python? Is the best way to mimic the same implementation?

5/23/2017 10:31:16 AM

Accepted Answer

Design patterns can often be replaced with built-in language features.

Your use case

You say "I wanted to have a more readable "means" to instantiating a class with many parameters.". In Java's case:

[A] use case for the builder pattern is when the constructor of the object to be built must take very many parameters. In such cases, it is often more convenient to lump such configuration parameters in a builder object (setMaxTemperature(int t), setMinTemperature(int t), set.. , etc. ) than to burden the caller with a long list of arguments to pass in the class's constructor..

Builder pattern not needed

But Python supports named parameters, so this is not necessary. You can just define a class's constructor:

class SomeClass(object):
    def __init__(self, foo="default foo", bar="default bar", baz="default baz"):
        # do something

and call it using named parameters:

s = SomeClass(bar=1, foo=0)

Note that you can freely reorder and omit arguments, just as with a builder in Java you can omit or reorder calls to the set methods on the builder object.

Also worth stating is that Python's dynamic nature gives you more freedom over construction of objects (using __new__ etc.), which can replace other uses of the builder pattern.

But if you really want to use it

you can use collections.namedtuple as your config object. namedtuple() returns a new type representing a tuple, each of whose parameters has a given name, without having to write a boilerplate class. You can use objects of the resulting type in a similar way to Java builders. (Thanks to Paul McGuire for suggesting this.)


A related pattern is Java's StringBuilder, which is used to efficiently construct an (immutable) String in stages. In Python, this can be replaced with str.join. For example:

final StringBuilder sb = new StringBuilder();
for(int i = 0; i < 100; i++)
    sb.append("Hello(" + i + ")");
return sb.toString();

can be replaced with

return "".join("Hello({})".format(i) for i in range(100))
5/23/2017 12:18:11 PM

The OP set themselves up for a fall by casting the Builder pattern as Java specific. It's not. It's in the Gang of Four's book and is potentially relevant to any object oriented language.

Unfortunately, even the Wikipedia article on the Builder pattern doesn't give it enough credit. It's not simply useful for code elegance. Builder patterns are a great way to create immutable objects that need to be mutable until they're used. Immutable state is especially critical in functional paradigms, making the Builder an excellent object-oriented pattern for python.

I've provided an an example Builder + ImmutableObject implementation below using the collections.namedtuple, borrowed and modified from "How to make an immutable object in python". I've kept the Builder fairly simple. However, setter functions could be provided that return the Builder itself to allow call chaining. Or @property syntax could be used in the Builder to provide attribute setters that check attribute validity prior to setting.

from collections import namedtuple

IMMUTABLE_OBJECT_FIELDS = ['required_function_result', 'required_parameter', 'default_parameter']

class ImmutableObjectBuilder(object):
    def __init__(self, required_function, required_parameter, default_parameter="foo"):
        self.required_function = required_function
        self.required_parameter = required_parameter
        self.default_parameter = default_parameter

    def build(self):
        return ImmutableObject(self.required_function(self.required_parameter),

class ImmutableObject(namedtuple('ImmutableObject', IMMUTABLE_OBJECT_FIELDS)):
    __slots__ = ()

    def foo_property(self):
        return self.required_function_result + self.required_parameter

    def foo_function(self):
        return self.required_function_result - self.required_parameter

    def __str__(self):
        return str(self.__dict__)

Example usage:

my_builder = ImmutableObjectBuilder(lambda x: x+1, 2)
obj1 =
my_builder.default_parameter = "bar"
my_builder.required_parameter = 1
obj2 =
my_builder.required_function = lambda x: x-1
obj3 =

print obj1
# prints "OrderedDict([('required_function_result', 3), ('required_parameter', 2), ('default_parameter', 'foo')])"
print obj1.required_function_result
# prints 3
print obj1.foo_property
# prints 5
print obj1.foo_function()
# prints 1
print obj2
# prints "OrderedDict([('required_function_result', 2), ('required_parameter', 1), ('default_parameter', 'bar')])"
print obj3
# prints "OrderedDict([('required_function_result', 0), ('required_parameter', 1), ('default_parameter', 'bar')])"

In this example, I created three ImmutableObjects, all with different parameters. I've given the caller the ability to copy, modify, and pass around a mutable configuration in the form of the builder while still guaranteeing immutability of the built objects. Setting and deleting attributes on the ImmutableObjects will raise errors.

Bottom line: Builders are a great way to pass around something with mutable state that provides an object with immutable state when you're ready to use it. Or, stated differently, Builders are a great way to provide attribute setters while still ensuring immutable state. This is especially valuable in functional paradigms.

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