The Python Programming Language Matt Campbell | Steve Losh

From the Creators… “The language is named after the BBC show ``Monty Python's Flying Circus'' and has nothing to do with nasty reptiles. Making references to Monty Python skits in documentation is not only allowed, it is encouraged! “

Origins Created in the early 1990s by Guido van Rossum at Stichting Mathematisch Centrum (CWI ) in the Netherlands Successor language to ABC Rossum remains the principle author of the language today

Overview of the Language Python is an interpreted language Like Scheme, it is an interactive language Very high-level data types Code is very human readable

Extensibility Python is a very extensible language You can write modules in C to link python to other binary libraries You can even link the interpreter itself into an application written in C and use python as an extension or command language for that application

Lexical Aspects Input Format: –Line oriented –White space is not ignored Comments: –Denoted by hash mark (#) to end of line Delimiters: –End of line Keywords: –Reserved Names: –Case sensitive –Variable names can consist of letters, numbers, and/or underscores –Underscores sometimes have special meaning, so their use is not highly recommended

Data Types Scalars: –Integer, Float, Boolean Aggregate Types –Complex Number, String, List, Dictionary, Tuple, File, Set Python is not strongly typed Python does not require declaration of variables before their use

Literals Integers: 2, 4, -3 Floats: 2.0e10, 3.5,.03 Boolean: True, False Strings: ‘cat’, “cat” Lists: [12, 3.4, ‘cat’, lambda x: x+3] Sets: set([12, 3.4, ‘cat’, lambda x: x+3]) Dictionaries: dict = {‘cat': 2, 6: ‘dog’} Functions: Can be mapped to names via ‘def’ and ‘lambda’ just as in Scheme. They can be returned by functions, placed in lists, etc. Files: open('/path/file', ‘r+') Null: None ‘_’: holds the most recently returned value

Variable Typing Variables in Python do not need to be declared as a specific type –Example: A, B = 3, ‘cat’ A variable’s type is dynamic, and will changed whenever it is reassigned –Example: a, b = 1, ‘cat’ a, b =.3, lambda x: x*x No such thing as “const” in Python

Quick & Dirty Input >>> x = int(raw_input("Please enter an integer: "))

Slicing Aggregate slicing syntax is similar to ICON Think of indices as pointing between elements in a list. [ ‘cat’, ‘dog’, 3, 4.5 ] >>> animals = [‘cat’, ‘dog’, ‘mouse’, ‘bird’] >>> print animals[0:1] [‘cat’, ‘dog’] >> print animals[1:] [‘dog’, ‘mouse’, ‘bird’] >>> tmp = list(“Shrubbery”) >>> tmp[:1] = tmp[-7:] >>> tmp [‘r’, ’u’, ’b’, ’b’, ’e’, ’r’, ’y’, ’S’, ’h’, ’r’, ’u’, ’b’, ’b’, ’e’, ’r’, ’y’]

Ranges Python has a range function to easily form lists of integers. >>> range(5) [0, 1, 2, 3, 4] >>> range(2,5) [2, 3, 4] >>> range(0, 10, 2) [0, 2, 4, 6, 8] >>> range(5, 0, -1) [5, 4, 3, 2, 1]

in The in keyword checks if the given object is contained within the aggregate. >>> p = “cat” >>> j = [‘cat’, ‘dog’] >>> p in j True >>> ‘a’ in p True >>> ‘t’ in p[:2] False

Subroutines Python supports both procedures and functions –Procedure: def proc1(): print ‘Hi!’ –Function: def func1(): return ‘Hi!’

Subroutines (continued) Python does not support name mangling as in C++ Anything can be returned from a function, including None and other functions Recursion is allowed Python has support for calling subroutines in modules written in C Parameters are passed by value

Scope Lexical Global/local scope Similar to Scheme No names need to be declared before use

Lifetime / Actions Variables are alive as long as they can be referenced, similar to Scheme Python supports standard arithmetic precedence and association with ()’s Result type is defined the more descriptive of the operands

Control Structures if statements work as expected >>> if x < 0: …print ‘Negative’ … elif x == 0: …print ‘Zero’ … else: …print “Positive” …

Control Structures continued for loops differ from c++ and/or java. They iterate over an aggregate. >>> animals = [‘cat’, ‘dog’, ‘horse’] >>> for x in animals: …print x …

Control Structures Continued for loops can iterate over multiple lists at the same time >>> questions = ['name', 'quest', 'favorite color'] >>> answers = ['lancelot', 'the holy grail', 'blue'] >>> for q, a in zip (questions, answers):... print 'What is your %s? It is %s.' % (q, a)... What is your name? It is lancelot. What is your quest? It is the holy grail. What is your favorite color? It is blue.

Pass The pass command does nothing.

Functions >>> def fib(n):...a, b = 0, 1... while b < n:... print b,... a, b = b, a+b...

Functions continued >>> def makeIncFunc ( n = 1 ) …return lambda x: x + n … >>> tmp = makeIncFunc() >>> print tmp(3) 4 >>> tmp = makeIncFunc(2) >>> print tmp(3) 5

Default Value Side Effects >>> def f(a, L=[]): …L.append(a) …return L … >>> print f(1) [1] >>> print f(2) [1, 2] >>> print f(3) [1, 2, 3]

Classes Python implements classes in a similar way to Java and C++ >>> class Complex:...def __init__(self, realpart, imagpart):... self.r = realpart... self.i = imagpart... >>> x = Complex(3.0, -4.5) >>> x.r, x.i (3.0, -4.5)

Inheritance “Of course, a language feature would not be worthy of the name ``class'' without supporting inheritance. “ class DerivedClassName(BaseClassName):...

Multiple Inheritance! class DerivedClassName(Base1, Base2, Base3):...

Odds and Ends class Employee: pass john = Employee() john.name = 'John Doe‘ john.dept = 'computer lab‘ john.salary = 1000

Pickling Python’s equivalent to Serialization >>> pickle.dump( anyobject, fileopenedforwriting ) >>> objecttoloadto = pickle.load( fileopenedforreading )

What this has to do with Legos A python library calls Pylnp which allows remote control of your robot through the IR tower import lnp lnp.iwrite('hello') lnp.iread() 'world'