Author: Florent Hivert <florent.hivert@univrouen.fr>
This tutorial is an introduction to objectoriented programming in Python and Sage. It requires basic knowledge about imperative/procedural programming (the most common programming style) – that is, conditional instructions, loops, functions (see the “Programming” section of the Sage tutorial) – but no further knowledge about objects and classes is assumed. It is designed as an alternating sequence of formal introduction and exercises. Solutions to the exercises are given at the end.
As an objectoriented language, Python’s ‘’variables’’ behavior may be surprising for people used to imperative languages like C or Maple. The reason is that they are not variables but names.
The following explanation is borrowed from David Goodger.
int a = 1;

Box “a” now contains an integer 1.
Assigning another value to the same variable replaces the contents of the box:
a = 2;

Now box “a” contains an integer 2.
Assigning one variable to another makes a copy of the value and puts it in the new box:
int b = a;

a = 1

Here, an integer 1 object has a tag labelled “a”.
If we reassign to “a”, we just move the tag to another object:
a = 2

Now the name “a” is attached to an integer 2 object.
The original integer 1 object no longer has a tag “a”. It may live on, but we can’t get to it through the name “a”. (When an object has no more references or tags, it is removed from memory.)
If we assign one name to another, we’re just attaching another nametag to an existing object:
b = a

The name “b” is just a second tag bound to the same object as “a”.
Although we commonly refer to “variables” even in Python (because it’s common terminology), we really mean “names” or “identifiers”. In Python, “variables” are nametags for values, not labelled boxes.
Warning
As a consequence, when there are two tags “a” and “b” on the same object, modifying the object tagged “b” also modifies the object tagged “a”:
sage: a = [1,2,3]
sage: b = a
sage: b[1] = 0
sage: a
[1, 0, 3]
Note that reassigning the tag “b” (rather than modifying the object with that tag) doesn’t affect the object tagged “a”:
sage: b = 7
sage: b
7
sage: a
[1, 0, 3]
The objectoriented programming paradigm relies on the two following fundamental rules:
At this point, those two rules are a little meaningless, so let’s give some more or less precise definitions of the terms:
Let’s start with some examples: We consider the vector space over \(\QQ\) whose basis is indexed by permutations, and a particular element in it:
sage: F = CombinatorialFreeModule(QQ, Permutations())
sage: el = 3*F([1,3,2])+ F([1,2,3])
sage: el
B[[1, 2, 3]] + 3*B[[1, 3, 2]]
(For each permutation, say [1, 3, 2], the corresponding element in F is denoted by B[[1, 3, 2]] – in a CombinatorialFreeModule, if an element is indexed by x, then by default its print representation is B[x].)
In Python, everything is an object so there isn’t any difference between types and classes. One can get the class of the object el by:
sage: type(el)
<class 'sage.combinat.free_module.CombinatorialFreeModule_with_category.element_class'>
As such, this is not very informative. We’ll come back to it later. The data associated to objects are stored in socalled attributes. They are accessed through the syntax obj.attribute_name. For an element of a combinatorial free module, the main attribute is called _monomial_coefficients. It is a dictionary associating coefficients to indices:
sage: el._monomial_coefficients
{[1, 2, 3]: 1, [1, 3, 2]: 3}
Modifying the attribute modifies the objects:
sage: el._monomial_coefficients[Permutation([3,2,1])] = 1/2
sage: el
B[[1, 2, 3]] + 3*B[[1, 3, 2]] + 1/2*B[[3, 2, 1]]
Warning
as a user, you are not supposed to do such a modification by yourself (see note on private attributes below).
As an element of a vector space, el has a particular behavior:
sage: 2*el
2*B[[1, 2, 3]] + 6*B[[1, 3, 2]] + B[[3, 2, 1]]
sage: el.support()
[[1, 2, 3], [1, 3, 2], [3, 2, 1]]
sage: el.coefficient([1, 2, 3])
1
The behavior is defined through methods (support, coefficient). Note that this is true even for equality, printing or mathematical operations. For example, the call a == b actually is translated to the method call a.__eq__(b). The names of those special methods which are usually called through operators are fixed by the Python language and are of the form __name__. Examples include __eq__ and __le__ for operators == and <=, __repr__ (see Sage specifics about classes) for printing, __add__ and __mult__ for operators + and *. See http://docs.python.org/library/ for a complete list.
sage: el.__eq__(F([1,3,2]))
False
sage: el.__repr__()
'B[[1, 2, 3]] + 3*B[[1, 3, 2]] + 1/2*B[[3, 2, 1]]'
sage: el.__mul__(2)
2*B[[1, 2, 3]] + 6*B[[1, 3, 2]] + B[[3, 2, 1]]
Some particular actions modify the data structure of el:
sage: el.rename("bla")
sage: el
bla
Note
The class is stored in a particular attribute called __class__, and the normal attributes are stored in a dictionary called __dict__:
sage: F = CombinatorialFreeModule(QQ, Permutations())
sage: el = 3*F([1,3,2])+ F([1,2,3])
sage: el.rename("foo")
sage: el.__class__
<class 'sage.combinat.free_module.CombinatorialFreeModule_with_category.element_class'>
sage: el.__dict__
{'_monomial_coefficients': {[1, 2, 3]: 1, [1, 3, 2]: 3}, '__custom_name': 'foo'}
Lots of Sage objects are not Python objects but compiled Cython objects. Python sees them as builtin objects and you don’t have access to the data structure. Examples include integers and permutation group elements:
sage: e = Integer(9)
sage: type(e)
<type 'sage.rings.integer.Integer'>
sage: e.__dict__
dict_proxy({'__module__': 'sage.categories.euclidean_domains',
'_reduction': (<builtin function getattr>, (Category of
euclidean domains, 'element_class')), '__doc__': None,
'_sage_src_lines_': <staticmethod object at 0x...>})
sage: e.__dict__.keys()
['__module__', '_reduction', '__doc__', '_sage_src_lines_']
sage: id4 = SymmetricGroup(4).one()
sage: type(id4)
<type 'sage.groups.perm_gps.permgroup_element.PermutationGroupElement'>
sage: id4.__dict__
dict_proxy({'__module__': 'sage.categories.category',
'_reduction': (<builtin function getattr>, (Join of Category
of finite permutation groups and Category of finite weyl
groups, 'element_class')), '__doc__': '\n Put methods for
elements here.\n ', '_sage_src_lines_': <staticmethod object
at 0x...>})
Note
Each object corresponds to a portion of memory called its identity in Python. You can get the identity using id:
sage: el = Integer(9)
sage: id(el) # random
139813642977744
sage: el1 = el; id(el1) == id(el)
True
sage: el1 is el
True
In Python (and therefore in Sage), two objects with the same identity will be equal, but the converse is not true in general. Thus the identity function is different from mathematical identity:
sage: el2 = Integer(9)
sage: el2 == el1
True
sage: el2 is el1
False
sage: id(el2) == id(el)
False
To define some object, you first have to write a class. The class will define the methods and the attributes of the object.
Let’s write a small class about glasses in a restaurant:
sage: class Glass(object):
... def __init__(self, size):
... assert size > 0
... self._size = float(size) # an attribute
... self._content = float(0.0) # another attribute
... def __repr__(self):
... if self._content == 0.0:
... return "An empty glass of size %s"%(self._size)
... else:
... return "A glass of size %s cl containing %s cl of water"%(
... self._size, self._content)
... def fill(self):
... self._content = self._size
... def empty(self):
... self._content = float(0.0)
Let’s create a small glass:
sage: myGlass = Glass(10); myGlass
An empty glass of size 10.0
sage: myGlass.fill(); myGlass
A glass of size 10.0 cl containing 10.0 cl of water
sage: myGlass.empty(); myGlass
An empty glass of size 10.0
Some comments:
Note
Private Attributes
The problem: objects of different classes may share a common behavior.
For example, if one wants to deal with different dishes (forks, spoons, ...), then there is common behavior (becoming dirty and being washed). So the different classes associated to the different kinds of dishes should have the same clean, is_clean and wash methods. But copying and pasting code is very bad for maintenance: mistakes are copied, and to change anything one has to remember the location of all the copies. So there is a need for a mechanism which allows the programmer to factorize the common behavior. It is called inheritance or subclassing: one writes a base class which factorizes the common behavior and then reuses the methods from this class.
We first write a small class ‘’AbstractDish’’ which implements the “cleandirtywash” behavior:
sage: class AbstractDish(object):
... def __init__(self):
... self._clean = True
... def is_clean(self):
... return self._clean
... def state(self):
... return "clean" if self.is_clean() else "dirty"
... def __repr__(self):
... return "An unspecified %s dish"%self.state()
... def _make_dirty(self):
... self._clean = False
... def wash(self):
... self._clean = True
Now one can reuse this behavior within a class Spoon:
sage: class Spoon(AbstractDish): # Spoon inherits from AbstractDish
... def __repr__(self):
... return "A %s spoon"%self.state()
... def eat_with(self):
... self._make_dirty()
Let’s test it:
sage: s = Spoon(); s
A clean spoon
sage: s.is_clean()
True
sage: s.eat_with(); s
A dirty spoon
sage: s.is_clean()
False
sage: s.wash(); s
A clean spoon
Any class can reuse the behavior of another class. One says that the subclass inherits from the superclass or that it derives from it.
Any instance of the subclass is also an instance of its superclass:
sage: type(s)
<class '__main__.Spoon'>
sage: isinstance(s, Spoon)
True
sage: isinstance(s, AbstractDish)
True
If a subclass redefines a method, then it replaces the former one. One says that the subclass overloads the method. One can nevertheless explicitly call the hidden superclass method.
sage: s.__repr__()
'A clean spoon'
sage: Spoon.__repr__(s)
'A clean spoon'
sage: AbstractDish.__repr__(s)
'An unspecified clean dish'
Note
Advanced superclass method call
Sometimes one wants to call an overloaded method without knowing in which class it is defined. To do this, use the super operator:
sage: super(Spoon, s).__repr__()
'An unspecified clean dish'
A very common usage of this construct is to call the __init__ method of the superclass:
sage: class Spoon(AbstractDish):
... def __init__(self):
... print "Building a spoon"
... super(Spoon, self).__init__()
... def __repr__(self):
... return "A %s spoon"%self.state()
... def eat_with(self):
... self._make_dirty()
sage: s = Spoon()
Building a spoon
sage: s
A clean spoon
Compared to Python, Sage has particular ways to handle objects:
For more details, see the Sage Developer’s Guide.
Here is a solution to the first exercise:
sage: class Glass(object):
... def __init__(self, size):
... assert size > 0
... self._size = float(size)
... self.wash()
... def __repr__(self):
... if self._content == 0.0:
... return "An empty glass of size %s"%(self._size)
... else:
... return "A glass of size %s cl containing %s cl of %s"%(
... self._size, self._content, self._beverage)
... def content(self):
... return self._content
... def beverage(self):
... return self._beverage
... def fill(self, beverage = "water"):
... if not self.is_clean():
... raise ValueError("Don't want to fill a dirty glass")
... self._clean = False
... self._content = self._size
... self._beverage = beverage
... def empty(self):
... self._content = float(0.0)
... def is_empty(self):
... return self._content == 0.0
... def drink(self, amount):
... if amount <= 0.0:
... raise ValueError("amount must be positive")
... elif amount > self._content:
... raise ValueError("not enough beverage in the glass")
... else:
... self._content = float(amount)
... def is_clean(self):
... return self._clean
... def wash(self):
... self._content = float(0.0)
... self._beverage = None
... self._clean = True
Let’s check that everything is working as expected:
sage: G = Glass(10.0)
sage: G
An empty glass of size 10.0
sage: G.is_empty()
True
sage: G.drink(2)
Traceback (most recent call last):
...
ValueError: not enough beverage in the glass
sage: G.fill("beer")
sage: G
A glass of size 10.0 cl containing 10.0 cl of beer
sage: G.is_empty()
False
sage: G.is_clean()
False
sage: G.drink(5.0)
sage: G
A glass of size 10.0 cl containing 5.0 cl of beer
sage: G.is_empty()
False
sage: G.is_clean()
False
sage: G.drink(5)
sage: G
An empty glass of size 10.0
sage: G.is_clean()
False
sage: G.fill("orange juice")
Traceback (most recent call last):
...
ValueError: Don't want to fill a dirty glass
sage: G.wash()
sage: G
An empty glass of size 10.0
sage: G.fill("orange juice")
sage: G
A glass of size 10.0 cl containing 10.0 cl of orange juice
Here is the solution to the second exercice:
sage: class AbstractDish(object):
... def __init__(self):
... self._clean = True
... def is_clean(self):
... return self._clean
... def state(self):
... return "clean" if self.is_clean() else "dirty"
... def __repr__(self):
... return "An unspecified %s dish"%self.state()
... def _make_dirty(self):
... self._clean = False
... def wash(self):
... self._clean = True
sage: class ContainerDish(AbstractDish):
... def __init__(self, size):
... assert size > 0
... self._size = float(size)
... self._content = float(0)
... super(ContainerDish, self).__init__()
... def content(self):
... return self._content
... def empty(self):
... self._content = float(0.0)
... def is_empty(self):
... return self._content == 0.0
... def wash(self):
... self._content = float(0.0)
... super(ContainerDish, self).wash()
sage: class Glass(ContainerDish):
... def __repr__(self):
... if self._content == 0.0:
... return "An empty glass of size %s"%(self._size)
... else:
... return "A glass of size %s cl containing %s cl of %s"%(
... self._size, self._content, self._beverage)
... def beverage(self):
... return self._beverage
... def fill(self, beverage = "water"):
... if not self.is_clean():
... raise ValueError("Don't want to fill a dirty glass")
... self._make_dirty()
... self._content = self._size
... self._beverage = beverage
... def drink(self, amount):
... if amount <= 0.0:
... raise ValueError("amount must be positive")
... elif amount > self._content:
... raise ValueError("not enough beverage in the glass")
... else:
... self._content = float(amount)
... def wash(self):
... self._beverage = None
... super(Glass, self).wash()
Let’s check that everything is working as expected:
sage: G = Glass(10.0)
sage: G
An empty glass of size 10.0
sage: G.is_empty()
True
sage: G.drink(2)
Traceback (most recent call last):
...
ValueError: not enough beverage in the glass
sage: G.fill("beer")
sage: G
A glass of size 10.0 cl containing 10.0 cl of beer
sage: G.is_empty()
False
sage: G.is_clean()
False
sage: G.drink(5.0)
sage: G
A glass of size 10.0 cl containing 5.0 cl of beer
sage: G.is_empty()
False
sage: G.is_clean()
False
sage: G.drink(5)
sage: G
An empty glass of size 10.0
sage: G.is_clean()
False
sage: G.fill("orange juice")
Traceback (most recent call last):
...
ValueError: Don't want to fill a dirty glass
sage: G.wash()
sage: G
An empty glass of size 10.0
sage: G.fill("orange juice")
sage: G
A glass of size 10.0 cl containing 10.0 cl of orange juice
Todo
give the example of the class Plate.
That all folks !