CS61A Lecture 11 Immutable Trees - University of California ...

CS61A Lecture 11 Immutable Trees - University of California ...

CS61A Lecture 20 Object-Oriented Programming: Implementation Jom Magrotker UC Berkeley EECS July 23, 2012 COMPUTER SCIENCE IN THE NEWS http://www.theengineer.co.uk/sectors/electronics/news/researchers-create-memory-with-one-bit-per-molecule/1013215.article 2 COMPUTER SCIENCE IN THE NEWS http://news.stanford.edu/news/2012/july/computer-model-organism-071812.html

3 TODAY Review: Dispatch Functions Dispatch Dictionaries OOP Implementation 4 REVIEW: DISPATCH FUNCTIONS We saw that we do not need data structures to store information: we can use functions to accomplish the storage and retrieval of data. 5

REVIEW: DISPATCH FUNCTIONS def make_pair(first, second): def pair(msg, arg=None): nonlocal first, second if msg == first: return first elif msg == second: return second elif msg == set-first: first = arg elif msg == set-second: second = arg else: return "Message not understood. return pair

6 REVIEW: DISPATCH FUNCTIONS The inner function pair, returned by every call to make-pair, represents the pair object. It receives a message as an argument, and responds by dispatching the appropriate piece of code. The function pair is called the dispatch function; this programming style is called message passing. 7 MESSAGE PASSING Enumerating different messages in a conditional statement is not very convenient. Equality tests can be repetitive. We need to write new code for new messages.

Can we use something that will take care of the message lookup and code dispatch for us? 8 DISPATCH DICTIONARIES Idea: We will allow ourselves one kind of data structure. In particular, we will represent an object by a dispatch dictionary, where the messages are the keys. 9 DISPATCH DICTIONARIES def make_pair(first, second): pair_dict = { first : first,

second: second } return pair_dict How do we create and use pair objects now? 10 DISPATCH DICTIONARIES >>> def make_pair(first, second): ... >>> p = make_pair(1, 2) G make_pai r p

E1 pair_dic t first 1 secon d 2 params: (first, second) body: pair_dict = { ... } first second

1 2 11 DISPATCH DICTIONARIES >>> p[first] 1 G make_pai r p

E1 pair_dic t first 1 secon d 2 params: (first, second) body: pair_dict = { ... } first second

1 2 12 DISPATCH DICTIONARIES >>> p[first] = 3 G make_pai r p

E1 pair_dic t first 1 secon d 2 params: (first, second) body: pair_dict = { ... } first second

1 3 2 13 ANNOUNCEMENTS: MIDTERM 2 Midterm 2 is on Wednesday, July 25. Where? 2050 VLSB. When? 7PM to 9PM. How much? Material covered until, and including, July 19.

Closed book and closed electronic devices. One 8.5 x 11 cheat sheet allowed. Group portion is 15 minutes long. If you have a conflict, please let us know by the end of today, July 23. 14 ANNOUNCEMENTS Homework 10 is due Tuesday, July 24. Project 3 is due Thursday, July 26. Homework 11 is due Friday, July 27. Please ask for help if you need to. There is a lot of work in the weeks ahead, so if you are ever confused, consult (in order of preference) your

study group and Piazza, your TAs, and Jom. Dont be clueless! 15 OOP IMPLEMENTATION: PREFACE We have discovered how we can create a pair object using just functions and dictionaries. We will now use many of the same ideas to explore how an object-oriented programming system can be constructed from scratch. 16 OOP IMPLEMENTATION: PREFACE Things we will implement: Classes and objects

Class variables Instance variables Methods Inheritance 17 OOP IMPLEMENTATION: PREFACE Things we will not implement: Dot notation (We will see similar notation though.) Class methods Multiple inheritance Introspection (What class does this object belong to? What attributes does it have?)

18 OOP IMPLEMENTATION We know that everything in Python is an object. Classes and objects have attributes, which map names to values. These values can either be data or functions. Main idea: We represent classes and objects as dictionaries that map attribute names to values. 19 OOP IMPLEMENTATION We start simple and first implement class variables. For example, we want to mimic class Pokemon: total_pokemon = 0

total_pokemon is a class variable. We access its value using the expression Pokemon.total_pokemon. 20 OOP IMPLEMENTATION: CLASS VARIABLES First solution: def make_class(attributes={}, base_class=None): return attributes def make_pokemon_class(): return make_class({total_pokemon: 0}) Dictionary of class variables 21

OOP IMPLEMENTATION: CLASS VARIABLES def make_class(attributes={}, base_class=None): return attributes def make_pokemon_class(): return make_class({ total_pokemon: 0 }) >>> Pokemon = make_pokemon_class() >>> Pokemon[total_pokemon] 0 22 OOP IMPLEMENTATION: INHERITANCE The current solution works. However, we need to modify it to include support for inheritance.

Why? If the current class does not have the class variable, its parent classes might have the variable. We need to specify a way to recursively retrieve values for variables that may be defined in parent classes. 23 OOP IMPLEMENTATION: INHERITANCE Idea: We create two inner functions, one that deals with locating the value for the class variable, and another that deals with setting new values for class attributes. Our class now becomes a dispatch dictionary of at least two keys: get and set. 24 OOP IMPLEMENTATION: INHERITANCE Modified solution:

def make_class(attributes={}, base_class=None): def get_value(name): To find the value of a class attribute if name in attributes: check if it is already in the return attributes[name] dictionary of attributes. elif base_class is not None: return base_class[get](name) def set_value(name, value): attributes[name] = value Otherwise, if there is a parent class, check if the parent class has the class attribute.

cls = {get: get_value, set: set_value} return cls A class is still a dictionary! The two new messages get and set allow us to use the general getter and setter functions. 25 OOP IMPLEMENTATION: INHERITANCE How do we use this new definition of a class? >>> Pokemon = make_pokemon_class() >>> Pokemon[get](total_pokemon) 0 Find the general getter function in the dispatch dictionary

and use it to find the value of a certain class variable. >>> Pokemon[set](total_pokemon, 1) Find the general setter function in the dispatch dictionary and use it to set or update the value of a certain class variable. 26 OOP IMPLEMENTATION: INHERITANCE Pokemon[get](total_pokemon)

is equivalent to Pokemon.total_pokemon Pokemon[set](total_pokemon, 1) is equivalent to Pokemon.total_pokemon = 1 We are passing messages to our classes. 27 OOP IMPLEMENTATION: INHERITANCE The new syntax is (unfortunately) more clunky. However, we can now access class variables from parent classes. >>> Pokemon = make_pokemon_class() >>> def make_water_pokemon_class(): return make_class({}, Pokemon)

>>> WaterPokemon = make_water_pokemon_class() >>> WaterPokemon[get](total_pokemon) 0 28 OOP IMPLEMENTATION: OBJECTS Just as we did with classes, we use dictionaries to represent objects: def make_instance(cls): What class is this object an instance of? def get_value(name): if name in attributes: return attributes[name] else: return cls[get](name)

def set_value(name, value): attributes[name] = value To find the value of an instance attribute check if it is already in the dictionary of attributes. Otherwise, check if the class has a value for the attribute. Dictionary of instance attributes attributes = {} instance = {get: get_value, set: set_value} return instance

An instance is a dictionary! The two messages get and set allow us to use the general getter and setter functions. 29 OOP IMPLEMENTATION: OBJECTS Just as we did with classes, we use dictionaries to represent objects: def make_instance(cls): def get_value(name): if name in attributes: return attributes[name] else: return cls[get](name) def set_value(name, value): attributes[name] = value

Every instance gets its own dictionary of instance attributes. attributes = {} instance = {get: get_value, set: set_value} return instance 30 OOP IMPLEMENTATION: OBJECTS How do we use this definition of an object? >>> Pokemon = make_pokemon_class() >>> pikachu = make_instance(Pokemon) >>> pikachu[set](hp, 300) Find the general setter function in the dispatch dictionary

and use it to set or update the value of a certain instance variable. >>> pikachu[get](hp) 300 Find the general getter function in the dispatch dictionary and use it to find the value of a certain instance variable. 31 BREAK http://thedoghousediaries.com/4432

http://thedoghousediaries.com/4400 32 REVIEW: BOUND METHODS A method is bound to an instance. Use the increase_hp method defined for objects of the Pokemon class with self being the ashs_pikachu object and amount being

150. Pokemon.increase_hp(ashs_pikachu, 150) of is equivalent to ashs_pikachu.increase_hp(150) Use the increase_hp method of (or bound to) the ashs_pikachu object with amount being 150. 33 BOUND METHODS

ashs_pikachu.increase_hp(150) In the expression above, we do not pass in an object as the first argument, even though the definition of increase_hp seems to need it. The first argument to the method increase_hp is already bound to the object ashs_pikachu. 34 BOUND METHODS We have seen a variant of this idea before, during functional programming: def sum_of_squares(a, b): t need return a*a + b*b Notice thatthweefirdost no argument to provide the

anymore! a is bound to 5. def sum_with_25(b): return sum_of_squares(5, b) 35 OOP IMPLEMENTATION: LOOKING AHEAD We would like to eventually have the following (revised) definition of the Pokemon class: def make_pokemon_class(): def __init__(self, name, owner, hp): ... def increase_hp(self, amount): ... arguments need

These self arg object on e th to d n u o b e to b d is called. which the metho 36

OOP IMPLEMENTATION: OBJECTS def make_instance(cls): def get_value(name): if name in attributes: return attributes[name] else: value = cls[get](name) return bind_method(value, instance) ass. We might get one cl e th in ed fin

de e ar ds All the metho t to the current en m gu ar st fir e th nd bi

, of these: if we do instance. e fo th d r ho et m d un bo a instance to produce

37 OOP IMPLEMENTATION: OBJECTS def bind_method(value, instance): if callable(value): callable is a predicate that checks if the argument provided can be called with arguments. If the value provided is callable (for example, a function), ...

def method(*args): make the new bound method return value(instance, *args) return method else: where the first argument is bound to the instance given, and all the other arguments remain the same

and return this bound method. return value If the value provided is not callable, return it as is. 38 OOP IMPLEMENTATION: INSTANTIATION AND INITIALIZATION We have seen how we can implement instance variables, class variables, and methods. We are almost done! In Pythons OOP system, the expression Pokemon(Pikachu, Ash, 300) both instantiated a new object and initialized its attributes with

appropriate values. The constructor method __init__ initialized the object. 39 OOP IMPLEMENTATION: INSTANTIATION AND INITIALIZATION We write a function init_instance that allows us to easily instantiate and initialize objects. def init_instance(cls, *args): instance = make_instance(cls) Make an instance of the class. init = cls[get](__init__) Find the constructor method.

if init is not None: init(instance, *args) return instance If the constructor exists... ... use it to initialize the object. Return the new instance. 40 OOP IMPLEMENTATION: INSTANTIATION AND INITIALIZATION We write a function init_instance that allows us to easily instantiate and initialize objects. def init_instance(cls, *args): instance = make_instance(cls)

init = cls[get](__init__) The constructor name is fixed here. if init is not None: init(instance, *args) return instance 41 OOP IMPLEMENTATION: INSTANTIATION AND INITIALIZATION We add an extra message that our classes can understand, which will allow us to create new objects: def make_class(attributes={}, base_class=None): ...

def new(*args): return init_instance(cls, *args) cls = {get: get_value, set: set_value, new: new} return cls 42 OOP IMPLEMENTATION: USAGE def make_pokemon_class(): def __init__(self, name, owner, hp): self[set](name, name) self[set](owner, owner) self[set](hp, hp) def increase_hp(self, amount): old_hp = self[get](hp)

self[set](hp, old_hp + amount) ... return make_class({__init__: __init__, increase_hp: increase_hp, ...}) 43 OOP IMPLEMENTATION: USAGE >>> Pokemon = make_pokemon_class() >>> ashs_pikachu = Pokemon[new](Pikachu, Ash, 300) >>> ashs_pikachu[get](hp) 300 >>> ashs_pikachu[get](owner) Ash >>> ashs_pikachu[get](increase_hp)(50) >>> ashs_pikachu[get](hp)

350 44 CONCLUSION Today, after five weeks of studying two major programming paradigms, we designed an OOP system from scratch using only dictionaries and functions! Main idea: Classes and objects are dispatch dictionaries, which are passed messages, and which run code and assign (or update) variables as needed. 45

Recently Viewed Presentations

  • Key Budget Assumptions

    Key Budget Assumptions

    1 - continuous cannabis use and elected to transfer care ~Gon, 2016~ ... "I don't like this…watching my kid withdrawal. I don't have a choice. I feel selfish. It is hard for me to agree to be on Subutex, but...
  • Primary PD Lead Support Programme

    Primary PD Lead Support Programme

    The structure of division as sharing needs to be developed and not left at 1 for you, 1 for you. 1 for you..... The new curriculum mentions scaling several times, particularly in the context of problem solving. An image for...
  • Higher physical education

    Higher physical education

    Higher physical education. Revision Questions. Cycle of Analysis. Wednesday 22nd March 2017. ... Revision - how much am I prepared to do between now and the exam? What resources can I use? Today's Task ...
  • Starter - shortcutstv.com

    Starter - shortcutstv.com

    'Vocationalism' In the 1976, James Callaghan, a Labour Prime Minister made a famous speech in Ruskin College, Oxford, where he said that Britain was falling behind its industrial competitors because the education system failed to produce skilled and motivated workers....
  • Forensic DNA Fingerprinting: Using Restriction Enzymes Learning targets

    Forensic DNA Fingerprinting: Using Restriction Enzymes Learning targets

    Uses of DNA fingerprinting. DNA structure. DNA restriction analysis (RFLP) Agarose gel electrophoresis. Molecular weight determination. Simulation of DNA Fingerprinting. Plasmid mapping.
  • STRESS MANAGEMENT - miningquiz.com

    STRESS MANAGEMENT - miningquiz.com

    RECOGNISE THE PROBLEM STRESS CONTROL ABC STRATEGY ABC STRATEGY ABC STRATEGY Stress Management Techniques Change your Thinking Re-framing Positive Thinking Change your Behaviour Be Assertive Equality and Basic Rights PowerPoint Presentation Being Assertive Assertive People Assertive Skills Benefits Get Organised...
  • Welcome to Woodmancote

    Welcome to Woodmancote

    Welcome to Woodmancote School . Reception Information Evening. Stages at Woodmancote School. Early Years Foundation Stage - Pre-school and Reception. ... This is a continuation of the records that pre school settings kept and passed on to school.
  • Go To DreamSpark.com Upper Left Click On Students

    Go To DreamSpark.com Upper Left Click On Students

    Go To DreamSpark.com. Upper Left Click On Students. Sign In (upper left), or Middle of Page Create New Account. If new: Create An Account and Proceed To Verify. Verify Using DreamSpark Key. Mapping Is *Optional* (see notes)