CSC 508 – Theory of Programming Languages, Spring, 2009 Week 3: Data Abstraction and Object Orientation

Review of Object-Oriented Programming – Encapsulation A module encapsulates implementation code and data, exposing abstract interfaces to client code while hiding implementation details. Also called information hiding, this approach does not necessarily entail using objects. C++ namespaces, Java packages, Python packages and modules. It reduces conceptual load, provides fault containment, and provides component independence.

Interface Inheritance An interface defines operations and symbolic constants that specify operation signatures and semantics. C++ abstract class consisting of pure virtual functions and constant definitions, Java interface, Python class with method declarations that throw exceptions. Derived concrete classes implement the operations of a base class interface while hiding implementation details.

sequence_interface (ADT) – sequence of string objects cp ~parson/JavaLang/sequence_adt ~/JavaLang/sequence_adt > sequence_interface.java sequence_interface insert(value : string, offset : integer) : boolean remove(offset : integer) : boolean get(offset : integer) : string size() : integer

Concrete class sequence_arrayimpl implements sequence_interface > sequence_interface sequence_arrayimpl insert(), remove() get(), size() private String [] array ; private int count ; // number of array elements actually used

Class sequence_linkedlistimpl implements sequence_interface > sequence_interface sequence_linkedlistimpl insert(), remove() get(), size() private static class listelement { // private local helper class String content ; // string stored at this element listelement next ; // next element, higher in number than this one } private listelement first ; private int count ; // number of linked list nodes actually used

Implementation Inheritance An abstract or concrete base class provides fields, public methods and protected methods used in common by alternative implementations in derived classes. Protected fields and methods are accessible only to derived classes. They are part of shared implementation. They eliminate duplicate code. Public fields and methods are accessible to client code, and methods can be redefined or extended by derived classes.

Package sequence_aclass class sequence_abstract_baseclass > sequence_interface > sequence_abstract_baseclass size() : int protected int getRealOffset(int offset, boolean isinsert) : int (helper method to convert an offset parameter to a real offset) protected int count sequence_arrayimpl sequence_linkedlistimpl sequence_arraylistimpl

Subtype Polymorphism Derived classes that implement a common interface can take various forms. Each class can provide an implementation that is extended, customized or optimized for some class of client applications. Once object construction is complete, client access occurs via a pointer or reference to a base class or interface object. The concrete run-time objects accessed via such a pointer or reference have many forms.

Module encapsulation in Python A package takes the form of a directory containing one or more Python modules. The package name is a “.”-separated path name below a directory on PYTHONPATH. A module is a Python source file within a package directory with related data and code definitions. Clients must import components of a module.

Python Packages Assuming $HOME/ProcLang is on my PYTHONPATH, package mysort corresponds to directory $HOME/ProcLang/mysort. File __init__.py contains a list of every module name in the package in its __all__ variable. ~parson/ProcLang/mysort/__init__.py contains the assignment __all__ = ["mysort"] for module mysort.py. Most packages contain multiple modules. This list provides support for “from mysort import *” from other modules. It tells Python what modules to import.

Importing Python Modules Importing a module without importing explicit symbols requires using the module name as a prefix. >>> import sys ; sys.exit(1) Importing distinct names restricts the import and makes those name first class objects. from sys import exit ; exit(1) from sys import exit as byebye ; byebye(1) Importing “*” imports all modules in a package or all symbols in a module. Python does not report symbol collisions from multiple modules. It uses the most recent import.

Python Classes Classes are dynamic constructs in Python, like everything else. There is no compiler check to ensure definition of “abstract methods” in concrete derived classes (there are no abstract methods) or method signature compatibility between base and derived classes. Inherited symbol access is a series of dictionary lookups from derived to base classes. All fields and methods are public. Naming conventions document intended access limitations.

Classy Examples >>> class baseclass(object):... """ baseclass is an example def statmethod(): …print "statmethod in baseclass"... def __init__(self, val):... self.value = val... def f(self, newval):... oldval = self.value... self.value = newval... return oldval >>> class def statmethod(): print "statmethod in d1"... def __init__(self, val):... return super(d1, self).__init__(val) >>> D1 = d1(3) >>> D1.f(5) 3 >>> D1.f(7) 5

More Classy Examples >>> class d2(baseclass):... def f(self, newval):... oldval = self.value... self.value = newval return oldval >>> D2 = d2(5) >>> D2.f(1) 5 >>> D2.f(3) 11.0 >>> isinstance(D2, d2) True >>> isinstance(D2, baseclass) True >>> isinstance(D2, d1) False >>> issubclass(d1, baseclass) True >>> issubclass(d1, d1) True >>> issubclass(d1, d2) False

No method name overloading Both the constructor method, called __init__, and other methods within the class, must have unique names. There is no name overloading in Python. Calls to superclass __init__ are explicit in explicit order. The class determines construction order. You can supply default parameter values. Methods can test for argument types. Methods can use variable number of *positional and **keyword arguments. There are no destructors in Python. The garbage collector invokes __del__(self) on an object being recovered, but most classes do not redefine __del__.

Operator overloading and extension of built-in types You can overload Python operators such as + by defining special methods such as __add_ and __radd__ -- see PY Chapter 3. You can extend built-in types. >>> class coercive_int(int):... def __init__(self, value):... super(coercive_int,self).__init__(self, value)... def __add__(self, value):... print "Inside method __add__"... return int(self) + int(value)... def __radd__(self, value):... print "Inside method __radd__"... return int(self) + int(value)

User-extended types in expressions >>> ci = coercive_int(3) >>> ci 3 >>> ci Inside method __add__ 7 >>> int(ci) >>> coercive_int(ci) Inside method __add__ 7 >>> ci 7.0 >>> "12345" + ci Inside method __radd__ >>> "12345" + 3 Traceback (most recent call last): File " ", line 1, in ? TypeError: cannot concatenate 'str' and 'int' objects

Multiple Inheritance uses Mixins Each base class can be a fragment of a class that refers to symbols defined in other fragmentary or complete classes. Combining fragmentary classes via multiple inheritance supplies their missing parts. Python’s SocketServer module has both UDPServer and TCPServer classes, and threading and forking mixin classes. You can define derived classes like this: ThreadingTCPServer(ThreadingMixIn, TCPServer) ForkingUDPServer(ForkingMixIn, UDPServer)

Mixin Inheritance Mixin inheritance requires application-specific names for methods and possibly fields contributed by mixin component classes. Multiple implementation inheritance of complete base classes is also possible. Python walks a class’ inheritance graph in left-to- right order, from most-to-least derived, backing up before shared base classes, to search for symbols and to resolve conflicts. Print CLASSNAME.__mro__ shows the class ordering.

Deciphering multiple inheritance >>> class d11(d1): pass >>> class d12(d1) : pass >>> class d21(d2) : pass >>> class d22(d2) : pass >>> class multi(d11, d12, d21, d22): pass >>> multi.__mro__ (,,, <clas s '__main__.d1'>,,, <class '__main __.d2'>,, ) multi(d11, d12, d21, d22):

All method bindings are either object-dynamic or class-static. The Python bytecode interpreter looks for field and method symbols within class objects using the __mro__ class ordering graph. All lookup is dynamic. There is nothing like a C++ non-virtual member function that is bound statically by the methods require no object. They can be invoked using a class name or an object of that class as a prefix. Resolution of static methods also uses __mro__ for an object prefix.

Python metaclasses (end of PY Ch. 7) Derive a class from type or class and define or redefine the appropriate methods. This new type can create alternatives to “class” for creating user-defined types. pymeta.html pymeta.html sses.html?page=1 sses.html?page=1