Introduction to Python

Presentation on theme: "Introduction to Python"— Presentation transcript:

1 Introduction to Python
Based on material for the course Programming with Python by Chad Haynes. Modified at Kasetsart University by Chaiporn Jaokaew and James Brucker.

2 Outline Overview Built-in objects Functions and scopes
Object-oriented programming Functional programming Exercise

3 Import a library module
Python At First Glance Import a library module import math def showArea(shape): print("Area = ", shape.area()‏ ) def widthOfSquare(area): return math.sqrt(area)‏ class Rectangle(object): def __init__(self, width, height): self.width = width self.height = height def area(self): return self.width * self.height ###### Main Program ###### r = Rectangle(10, 20)‏ showArea(r)‏ Function definition Class definition Comment Object instantiation Calling a function

4 Why use Python? Simple syntax: easy to learn and remember Portable
Flexible Large standard library Short development time Lots of 3rd party tools/add-ons Many good implementations: CPython, PyPy, IronPython, Jython Active open-source community

5 Similarities to Java Everything inherits from "object"
Has numbers, functions, classes, … Everything is first-class Large standard library Garbage collection Introspection, serialization, threads, net,…

6 Python vs. Java/C++/C Typing: strong, but dynamic Names have no type
Objects have type No name declarations Sparse syntax No { } for blocks, just indentation No ( ) for if/while conditions Interactive interpreter # for comments (like Perl) // this is Java if (x < 10)‏ { x = x + tmp; y = y * x; } System.out.println(y); Java # this is Python if x < 10: x = x + tmp y = y * x print( y ) Python

7 Getting Started Download from: http://python.org/
Add python to PATH to run scripts from command line Python is available for most platforms, even mobile. Most Linux distributions have Python as package(s)

8 Python 3: print( "hello" ) There are some differences between Python 2.x and Python 3 syntax. print is a function in Python 3, which uses parenthesis: Python 3.x: Python 2.x: print("hello") print "hello"

9 Hello, World! C# Python using System; class Hello {
static void Main()‏ Console.WriteLine("Hello, World"); } print("Hello, World")

10 Variables >>> x = 23 name x means 23 >>> print(x) 23
>>> x = 'foo' foo >>> del x Traceback (most recent call last): File "<stdin>", line 1, in <module> NameError: name 'x' is not defined >>> name x means 23 now it means 'foo' x is undefined

11 Variables Variable is a reference to an object not a value
more than one variable can refer to the same object Var1 Var1_copy Var2

12 Numeric Types Integers Generally signed, 32-bit Long Integers
Unlimited size Format: <number>L Example: L Float Platform dependant “double” precision Complex Format: <real>+<imag>j Example: 6+3j

13 Strings A sequence of characters enclosed in quotes
3 ways to quote strings: 'Single Quotes' "Double Quotes" """Triple Quotes""" or '''triple quotes''' Triple quotes can span multiple lines Examples >>> print('This string may contain a "') This string may contain a " >>> print("A ' is allowed") A ' is allowed >>> print("""Either " or ' are OK""") Either " or ' are OK

14 raw_input for reading input
raw_input( [prompt] )‏ Print prompt and return user's input as a string a built-in function Example >>> reply = raw_input('Are you awake? ')‏ Are you awake? not sure >>> print( reply ) not sure

15 Arithmetic Operations
operators: * / // ** % abs Examples: >>> # Addition 8 >>> 2 ** # Exponentiation 256 >>> 13 / # Integer (Truncating) Division* 3 >>> float(13) / 4 # Float Division 3.25 >>> 13 % # Remainder 1 >>> abs(-3.5) # Absolute Value 3.5 * 13/4 performs float division in Python 3.x

16 Boolean comparisons Comparison: < <= > >= == != <>
Results in 1 (true) or 0 (false)‏ Example >>> 4 > 1.5 1 >>> 'this' != 'that' >>> 4+3j == 4-2j >>> '5' == 5 >>> 0 < 10 < 20

17 Boolean Operations Operators: and or not Standard Boolean Algebra i1
not i1 1 i1 i2 i1 and i2 i1 or i2 1 1 1 1 1 1 1 1

18 Boolean values True: any non-zero, non-null value. False: None (null)
empty string empty list s = "hello" if s: print("true") lst = [] if lst: print("list is not empty")

19 Boolean Expressions >>> 1 == 1 and 2 >= 3 False
>>> 1 == 1 or 2 >= 3 True >>> not 5.3 != # same as: not (5.3 != 2.2)‏ >>> 2 and '23' > '11' or 0

20 Building strings Concatenation (+)‏: string1 + string2 Example:
>>> 'Rockefeller' + 'University' 'RockefellerUniversity' Repetition (*)‏: string * number >>> 'dog' * 5 'dogdogdogdogdog'

21 "format string" % (arg1, arg2, ...)
String Formatting C-Style formatting (extended printf)‏: "format string" % (arg1, arg2, ...) >>> "%i %s in the basket" % (2, "eggs")‏ '2 eggs in the basket' >>> x = 2.0/9.0 >>> "%f to 2 dec places is %.2f" % (x, x)‏ ' to 2 decimal places is 0.22' >>> length = 5 >>> obj = "fence" >>> "Length of %(obj)s is %(length)i" % vars()‏ 'Length of the fence is 5'

22 String Format Codes Format codes begin with "%": import math x = 10
"x is %f" % x "pi is %.8f" % math.pi "pi is %12.6f" % math.pi eps = 1.0E-17 "eps is %f (%g)" % (eps, eps)

23 String Formatting using .format
>>> "{0} {1} in the basket".format(2, "eggs")‏ '2 eggs in the basket' >>> x = 2.0/9.0 >>> "{0} to 2 dec places is {0:.2f}".format(x)‏ ' to 2 decimal places is 0.22' "{0} to {1} dec places is {0:.{1}f}".format(x,3)‏ ' to 3 decimal places is 0.222' >>> name = "James Bond" >>> id = 7 >>> "{0:12s} is {1:03d}".format‏(name,id) 'James Bond is 007' Python format mini-language reference:

24 split a String Syntax: string.split([seperator])‏
Returns a list of substrings >>> text = " " >>> text.split()‏ ['1', '2', '4', '5', '1'] >>> test = "a, b, c, d, e" >>> test.split(',')‏ ['a', ' b', ' c', ' d', ' e'] # notice the space before b c d e

25 strip leading/trailing whitespace
string.strip()‏ Remove leading and trailing white space (tab, new line, etc)‏ >>> padded = " stuff " >>> unpadded = padded.strip()‏ >>> unpadded 'stuff' >>> padded ' stuff ' # strings are immutable

26 String functions s = '''Now is the time for all good men'''
Multi-line strings (triple quote) list = s.splitlines() return list of lines in string s.lower() to lowercase s.upper() to uppercase s.title() title case s.index('me') index of first occurrence, throw exception if substring not found s.count('me') count occurrences s[1:10] slice, just like list slice s.replace("men","people") replace substring.

27 String format functions
>>> "Hello".ljust(8) "Hello " Left justify to given length. >>> "Hello".rjust(8) " Hello" Right justify. >>> "Hello".center(8) " Hello " Center, of course. >>> u = "Bird" >>> "Hello {0}".format(u) 'Hello Bird' Format using template.

28 type determines type of Object
Determine the type of an object Syntax: type(object)‏ Examples >>> type(2.45)‏ <type 'float'> >>> type('x')‏ <type 'str'> >>> type(2**34)‏ <type 'long'> >>> type(3+2j)‏ <type 'complex'>

29 Testing the type if type(x) is int: print("x is an integer")

30 Type Conversions Functions to convert between types:
str() int() float() complex() bool()‏ >>> str(0.5)‏ '0.5' >>> float('-1.32e-3')‏ >>> int('0243')‏ 243 >>> int(2**100)‏ >>> bool('hi')‏ True >>> bool('False')‏ # any non-zero, non-null is true

31 Built-in Data Structures
List l = [ 2, 3, 5, 8 ] Tuple (read-only list) t = ( 2, 3, 5, 8 ) Set s = { 2, 5, 3, 8 } Dictionary (key-value map) d = {"two":2, "three": 3, ...}

32 Lists Syntax: [elem1, elem2, ...]
Ordered sequence of any type (mixed types ok) Mutable >>> list1 = [1, 'hello', 4+2j, ] >>> list1 [1, 'hello', (4+2j), ] >>> list1[0] = 'a' ['a', 'hello', (4+2j), ]

33 Joining and Repeating Lists
Concatenation: list1 + list2 >>> [1, 'a', 'b'] + [3, 4, 5] [1, 'a', 'b', 3, 4, 5] Repetition: list * count >>> [23, 'x'] * 4 [23, 'x', 23, 'x', 23, 'x', 23, 'x']

34 Adding Elements to a List
>>> list = [ "apple", "banana" ] Append item to end >>> list.append( "durian" ) Append another list >>> list.extend( list2 ) Same as list + list2 Insert item anywhere >>> list.insert( 0, "artichoke" ) >>> list.insert( 2, "carrot" ) Like Java list.add( n, item)

35 Not so object-oriented len( )
len( ) returns length of a list >>> list = [ "a", "b", "c" ] >>> len( list ) 3

36 Removing Elements from a List
>>> list = [ "a" "b", "c", "b" ] Remove a matching element (w/o returning it) >>> list.remove( "b" ) Throws exception if argument is not in the list Remove last element and return it >>> list.pop( ) 'b' Remove by position >>> list.pop( 1 ) # 'b' removed already 'c'

37 Indexing Syntax: list[n] Positive indices count from the left: list[0]
Negative indices count from the right: list[-1] a b c d e f g list[0] == a sequence[-1] == g list[2] == c sequence[-2] == f list[6] == g sequence[-7] == a

38 List Slicing: get a sublist
list[m:n] return elements m up to n (exclusive) syntax for both strings and lists >>> x = [0, 1, 2, 3, 4, 5, 6, 7] >>> x[1:4] [1, 2, 3] >>> x[2:-1] [2, 3, 4, 5, 6] # Missing Index means start or end of list >>> x[:2] [0, 1] >>> "Hello nerd"[3:] lo Nerd

39 Remove element from a list
list.remove(element)‏ Removes the first occurrence of element in list Example: >>> list2 = [0, 1, 3, 4, 3, 5] >>> list2.remove(3)‏ >>> list2 [0, 1, 4, 3, 5] del list[ index ] Delete element by index. Nominated for "Python Worst Syntax Award"

40 Remove & return an element
Syntax: list.pop([index])‏ Remove and return item at position index from list Without an argument: remove last item Example: >>> list1 = [1, 'hi', 2, 9, 'the end'] >>> list1.pop(1)‏ hi >>> list1.pop()‏ the end >>> list1 [1, 2, 9]

41 Sorting a list List.sort( [comparator] )
Sort List in place. Result is applied to the list! Example: >>> list3 = [4, 12, 3, 9] >>> list3.sort()‏ >>> list3 [3, 4, 9, 12]

42 Reverse order of elements
list.reverse( ) Reverse elements of list in place. Example: >>> list3 = [4, 12, 3, 9] >>> list3.reverse()‏ >>> list3 [9, 3, 12, 4]

43 Count or find elements in a list
list.count( element ) count number of occurences of element. n = list.index( element ) return index of first occurence of element. Throws ValueError if element is not in list.

44 Tuples Immutable list Syntax: (elem1, elem2, …)‏
A tuple cannot be changed. Example: >>> tuple1 = (1, 5, 10)‏ >>> tuple1[2] = 2 Traceback (most recent call last): File "<pyshell#136>", line 1, in ? tuple1[2] = 2 TypeError: object doesn't support item assignment

45 Converting between list and tuple
>>> list1 = ['a', 'b', 'c'] >>> tuple1 = tuple( list1 ) >>> type( tuple1 ) <class 'tuple'> >>> tuple2 = ('cat', 'dog') >>> list2 = list(tuple2)

46 len - Length of an object
n = len(object)‏ Return the length of object Examples >>> list1 = [1, 2, 3, 4, 5] >>> len(list1)‏ 5 >>> string1 = "length of a string" >>> len(string1)‏ 18 len is not object-oriented.

47 Multiple assignment using tuples
(a,b,c) = (10, 20, 50) >>> b 20‏ This can be used in for loops. points = [ (1,0), (0.2,0.9), (1,2) ] for (x,y) in points: r = math.hypot(x,y) print("radius of (%f,%f) is %f" % (x,y,r) )

48 Dictionary: mapping key to value
A mapping of keys to values Associate a key with a value Each key must be unique 'z' 'ab' 2.1 3 keys 10 [2] (3,8)‏ 'hello' values

49 Using Dictionaries Syntax: dict = {key1: value1, key2: value2, ...}
>>> dict = {'a': 1, 'b': 2} >>> dict {'a': 1, 'b': 2} >>> dict['a'] 1 >>> dict['b'] 2 >>> dict[3] = 'three' {'a': 1, 'b': 2, 3: 'three'}

50 Dictionary Methods dict = {'a': 1, 'b':2, 'c':30} Example dict.keys()
list of keys dict.values( ) [1, 2, 30] list of values dict.has_key('d') False Test for key in dictionary

51 Set An unordered collection, without duplicates (like Java).
Syntax is like dictionary, but no ":" between key-value. >>> aset = { 'a', 'b', 'c' } >>> aset {'a', 'c', 'b'} >>> aset.add('c") # no effect, 'c' already in set

52 Set Methods set.discard('cat') remove cat. No error if not in set.
set.remove('cat') remove cat. Error if not in set. set3 = set1.union(set2) doesn't change set1. set4 = set1.intersection(set2) set2.issubset( set1 ) set2.issuperset( set1 ) set1.difference( set2 ) element in set1 not set2 set1.symmetric_difference(set2) xor set1.clear( ) remove everything

53 Test for element in Set item in set
>>> aset = { 'a', 'b', 'c' } >>> 'a' in aset True >>> 'A' in aset False

54 Flow Control if condition : body elif condition : else: if x%2 == 0:
y = y + x else: y = y - x while condition: body while count < 10: count = 2*count for name in iterable: body for x in [1,2,3]: sum = sum + x

55 range: create a sequence
range([start,] stop[, step])‏ Generate a list of numbers from start to stop stepping every step start defaults to 0, step defaults to 1 Example >>> range(5)‏ [0, 1, 2, 3, 4] >>> range(1, 9)‏ [1, 2, 3, 4, 5, 6, 7, 8] >>> range(2, 20, 5)‏ [2, 7, 12, 17]

56 for loop using range( ) Use range to generate values to use in for loop >>> for i in range(1,4): print i 1 2 3

57 loop iteration using continue
skip to next iteration of a loop for x in range(10): if x%2 == 0: continue print x 1 3 5 7

58 break break out of the inner-most loop 1 2 3 Breaking
for number in range(10): if number == 4: print 'Breaking' break else: print number 1 2 3 Breaking

59 dir: show all methods & attributes
dir returns all methods for a class or object >>> lst = [1, 3, 2] >>> dir(lst)‏ ['__add__', '__class__', '__contains__', '__delattr__', '__delitem__', '__delslice__', '__doc__', '__eq__', '__ge__', '__getattribute__', '__getitem__', '__getslice__', ... '__setitem__', '__setslice__', '__str__', 'append', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort' >>> dir( math ) # import math first ['__doc__', '__name__', '__package__', 'acos', 'asin", 'atan', 'atan2', 'ceil', 'copysoign', 'cos', 'degrees', 'e', 'exp', 'factorial', 'floor', 'fmod', 'frexp', 'fsum', 'hypot', ...

60 The help function gives help for a module or function.
Getting Help The help function gives help for a module or function. >>> help(str)‏ Help on class str in module __builtin__: class str(basestring)‏ | str(object) -> string | | Return a nice string representation of the object. | Method resolution order: | str | basestring | object | Methods defined here: | ...

61 Functions and Scope

62 Defining Functions Syntax: def func(arg1, …):
body Body of function must be indented If no value is returned explicitly, function will return None def average(num1, num2, num3): sum = num1 + num2 + num3 avg = sum / 3.0 return avg

63 Function Parameters Parameters can be any type
A function can take any number of parameters or none at all def usage(programName, version): print("%s Version %i" % (programName, version))‏ print("Usage: %s arg1 arg2" % programName)‏ >>> usage('Test', 1.0)‏ Test Version 1.0 Usage: Test arg1 arg2

64 Function Default Parameter values
Parameters can be given a default values split(string, substr=' ') The function can be called with fewer arguments than there are parameters Parameters with default values must come last >>> def printName(last, first, mi=""): print("%s, %s %s" % (last, first, mi)‏) >>> printName("Smith", "John")‏ Smith, John >>> printName("Smith", "John", "Q")‏ Smith, John Q

65 Keyword Arguments Functions can be invoked using the name of the parameter and a value func(param=value, ...)‏ The order of values passed by keyword does not matter def fun(key1="X", key2="X", key3="X", key4="X"): '''function with keywords and default values''' print(key1, key2, key3, key4) >>> fun(key3="O", key2="O")‏ X O O X >>> fun(key4='Z')‏ X X X Z

66 Functions at Values Functions can be used just like any other data type Functions can be assigned to variables def sub(a, b): return a-b >>> op = sub >>> print op(3, 5)‏ -2 >>> type(op)‏ <type 'function'>

67 Functions as Parameters
Functions can be passed to other functions def convert(data, convertFunc): for i in range(len(data)): data[i] = convertFunc(data[i])‏ return data >>> convert(['1', '5', '10', '53'], int)‏ [1, 5, 10, 53] >>> convert(['1', 'nerd', '10', 'hi!'], len)‏ [1.0, 5.0, 10.0, 53.0] >>> convert(['1', '5', '10', '53'], complex)‏ [(1+0j), (5+0j), (10+0j), (53+0j)]

68 Functions can return multiple values
Return a tuple of values. Example: string.split( ) returns a tuple of substrings. def separate(text, size=3): '''divide a string into two parts''' head = text[:size] tail = text[size:] return (head,tail)‏ # ok to omit parens: start,last = separate(...) >>> (start,last) = separate('GOODBYE', 4)‏ >>> start GOOD >>> last BYE

69 Generators Generators are functions that generate a sequence of items, but only when requested Generated sequence can be infinite def fibonacci(): a = b = 1 while True: yield a a, b = b, a+b for rabbits in fibonacci(): print( rabbits ) if rabbits > 100: break

70 Generators Generator invokes yield to "yield" control.
Receiver calls next(generator) to invoke generator. def filereader( filename ): with open(filename) as infile: line = infile.read() yield line gen = filereader( "readme.txt" ) s = next(gen) process_line(s) ...

71 Namespaces and Scopes Namespace A mapping from names to objects
(Currently) implemented as Python dictionaries Scope A region of program where a namespace is accessible Name references search at most 3 scopes: local, global, built-in Assignments create or change local names by default Can force names to be global with global command

72 Scope Example X = 99 def func(Y):
Z = X+Y # X not assigned, so it's global return Z >>> func(1)‏ X = 99 def func(Y): X = 10 Z = X+Y # X is local return Z >>> func(1)‏ >>> X # still 99

73 Modules A file containing Python definitions and statements
Modules can be “imported” Module file name must end in .py Used to divide code between files math.py string.py import math import string …

74 import Statement import <module name>
module name is the file name without .py extension You must use the module name to call functions >>> import math >>> dir(math)‏ ['__doc__', '__name__', 'acos', 'asin', 'atan', 'atan2', 'ceil', 'cos', 'cosh', 'e', 'exp', 'fabs', 'floor', 'fmod', 'frexp', ...] >>> math.e >>> math.sqrt(2.3)

75 import specific names from <module> import <name>
Import a specific name from a module into global namespace Module name is not required to access imported name(s) >>> from math import sqrt >>> sqrt(16)‏ 4 >>> dir(math)‏ Traceback (most recent call last): File "<stdin>", line 1, in <module> NameError: name 'math' is not defined

76 import all names from module
from <module> import * Import everything into global namespace >>> dir()‏ ['__builtins__', '__doc__', '__name__'] >>> from time import * ['__builtins__', '__doc__', '__name__', 'accept2dyear', 'altzone', 'asctime', 'clock', 'ctime', 'daylight', 'gmtime', 'localtime', 'mktime', 'sleep', 'strftime', 'time', ... ] >>> time()‏

77 Python Standard Libraries
sys System-specific parameters and functions time Time access and conversions thread Multiple threads of control re Regular expression operations and MIME handling httplib HTTP protocol client tkinter GUI package based on TCL/Tk (in Python 2.x this is named Tkinter) See

78 Operating System related functions
The os Module Operating System related functions import os os.getcwd( ) Get current working directory os.chdir("/temp/somedir") Change dir. Use forward slash on MS Windows. os.getenv('JAVA_HOME') Get environment variable. os.unlink('filename') Remove regular file os.removedirs('dirname') Remove directory(s) stats = os.stat('file') Get file metadata: ctime, mtime, atime, uid, gid

79 os.path Module for manipulating paths > dir '/some/path' > file
> (dir, file) = os.path.split("/some/path/test.py") > dir '/some/path' > file 'test.py' > (name,ext) = os.path.splitext(file) > ext 'py' # Test absolute path to file > os.chdir('/Temp/examples') > os.path.realpath('readme.txt') C:\\Temp\\examples\\readme.txt

80 glob Module for getting files in directory > import glob
> glob.glob('*.txt') ['help.txt', 'install.txt', 'readme.txt', 'zzz.txt']

81 File Objects - open a file
open(filename, mode)‏ mode is one of: 'r' : Read 'w' : Write 'a' : Append If a file opened for 'w' does not exist it will be created Example >>> inFile = open('input.txt', 'r')‏ >>> type(infile)‏ <type 'file'>

82 File Methods read([size])‏
Read at most size bytes and return as a string readlines([size])‏ Read the lines of the file into a list of strings. Use size as an approximate bound on the number of bytes returned

83 File Methods for output
write(text)‏ Write text to the file writelines(string_sequence)‏ Write each string in the sequence to the file New lines are not added to the end of the strings

84 with to define a block for open
File is automatically closed at end of "with" block, even if an exception occurs. with open("students.csv",'r') as student_file: # read each line of file for line in student_file: (id,name, ) = split(',', 3) print("%s has id %s" % (name,id))

85 Errors or unexpected conditions during execution.
Exceptions Errors or unexpected conditions during execution. Example: division by zero >>> 1 / 0 Traceback (most recent call last): File "<pyshell#0>", line 1, in ? 1 / 0 ZeroDivisionError: integer division or modulo by zero

86 Exceptions Motivation Move error handling code away from main code
Deal with “exceptional” cases separately How it works Exceptions are thrown (or raised) and caught An exception is caught by a catch code block When exception occurs, control jumps to a surrounding "catch" block. May propagate from function to caller.

87 Throwing Exceptions Some common operations may throw an exception:
List index out of bounds Invalid type conversions Invalid arithmetic operation, e.g. math.sqrt(-1) Exceptions can be thrown manually using the raise keyword >>> raise ValueError, "Bad Value“

88 Catching an Exception If an exception is not caught, the program will terminate. try: <code block> except <Exception List1>: <exception handling code block> except <Exception List2>: except: <exception handler for all other exceptions> else: <code to execute if no exception occurs>

89 Exception Example try: x = 1 / 0 except ZeroDivisionError:
print('Division by zero') else: print("x =", x)

90 First matching except block is used
try: x = 1 / 0 except IOError: print 'Input/Output error' except: print 'Unknown error' Unknown error

91 Types of Exceptions There is a hierarchy of exceptions
All built-in exceptions are subclasses of Exception An exception can be caught by any type higher up in the hierarchy Exception StandardError ArithmeticError ZeroDivisionError SystemExit ValueError OverflowError StopIteration LookupError IndexError KeyError

92 Example of Hierarchical Exception
try: x = 1 / 0 except ArithmeticError: print 'ArithmeticError caught' ArithmeticException caught

93 Propagation of Exceptions
Uncaught exceptions propagate up to the calling function def func1(): try: a = 1 / 0 except ValueError: print 'caught by func1' def func2(): func1()‏ except: print 'caught by func2' >>> func2()‏ caught by func2

94 [ expression for var in list ]
List Comprehensions [ expression for var in list ] Apply an expression to every element of a list Can simultaneously map and filter >>> import math >>> [math.pow(2,x) for x in range(1,7)] [2.0, 4.0, 8.0, 16.0, 32.0, 64.0]

95 List Comprehension with filter
result = [ expr for var in list if expr2 ] apply to elements of list where expr2 is true Example: Remove smallest element from list >>> lst1 = [5, 10, 3, 9] >>> [x for x in lst1 if x != min(lst1)] [5, 10, 9] Example: Sum all lists of size greater than 2 >>> lst1 = [[1, 2, 4], [3, 1], [5, 9, 10, 11]] >>> [reduce(operator.add, x) for x in lst1 if len(x) > 2] [7, 35]

96 [expr for x in list1 for y in list2]
List Comprehension with nested for [expr for x in list1 for y in list2] The loops will be nested >>> vowels = ['a','e','i','o','u'] >>> const = ['b','s'] >>> [c+v for c in const for v in vowels] ['ba', 'be', 'bi', 'bo', 'bu', 'sa', 'se', 'si', 'so', 'su']

97 List Comprehension for files
Find all files in directory larger than 1MB Return the real path to file import os, glob [os.path.realpath(f) for f in glob.glob('*.*') if os.stat(f).st_size >= ]

98 dict = {expr for var in list if expr2}
Dictionary Comprehensions dict = {expr for var in list if expr2} Like list comprehension but generates a dictionary. expr must be key:value pair (of course) # Create dictionary of .exe filenames and sizes. import os, glob os.chdir('/windows/system32') files = {fname:os.stat(fname).st_size for fname in glob.glob('*.exe') } # print them for (key,val) in files.items(): print("%-20s %8d" % (key,val))

99 OO Programming

100 Defining a Class Syntax: Create a class with default superclass
class name[(base_class)]: body # old style class name: body # new style class name(object): body class MyClass(object): myvar = 30 >>> MyClass.myvar 30

101 Defining Constructor and Methods
All instance methods must must have explicit object reference (self) as the first parameter self is the conventional name (like Java "this") class Rectangle(object): def __init__(self, width, height): self.width = width self.height = height def area(self): return self.width * self.height constructor >>> r = Rectangle(10, 20)‏ >>> Rectangle.area(r)‏ 200 >>> r.area()‏ No "new".

102 Weak Encapsulation Everything is public.
Instance methods can be used in static way. class Person: def __init__(self, name): self.name = name def greet(self): print("Hello "+self.name) >>> p = Person("Me") >>> p.name # attributes are public >>> p.greet() # O-O style method call >>> Person.greet(p) # imperative style

103 Hiding by name mangling
Any attribute name that begins with "_ _" is mangled to "_Class_ _name". class Person: def __init__(self, name): self.__name = name # Mangled to _Person__name @property def name(self): return self.__name #auto demangle >>> p = Person("Lone Ranger") >>> p.name # returns the name Lone Ranger >>> p.name = "Zoro" builtins.AttributeError: can't set attribute

104 Only One Constructor Python classes can only have one __init__.
You can overload it using params with default values. class Point: '''Point with x,y coordinates''' def __init__(self, x=0, y=0): self.x = x self.y = y >>> p = Point(3,4) >>> q = Point( ) # same as Point(0,0)

105 Static Methods To define a static method, prefix and no self parameter. class Point: '''create a point using polar coordinates.''' @staticmethod def makePoint(r,a): return Point(r*math.cos(a), r*math.sin(a)) >>> p = Point.makePoint( 10, math.pi/4 ) Static factory methods can help overcome limitation of only one constructor.

106 Properties Properties are like synthetic attributes. Used like "get" properties in C#. Only parameter is self. class Point: def __init__(self,x=0,y=0): self.x = x self.y = y @property def length(self): return math.hypot(self.x, self.y) >>> p = Point(3,4) >>> p.length 5

107 "Set" properties Can to protect attributes. class Person: def __init__(self,name): self.__name = name # hide the name @property def name(self): # name accessor return self.__name @name.setter def name(self,value): # set the name if not isinstnace(value, str): raise TypeError("Name must be str") self.__name = value

108 Restricting Keys in the Object dict
You can restrict the allowed attribute names. Use a tuple named __slots__ class Point: __slots__ = ('x','y','name') f.name = "weak, weak" def __init__(x=0,y=0): self.x, self.y = x, y >>> p = Point(2,3) >>> p.junk = "ha ha" builtins.AttributeError: 'Point' object has no attribute 'junk'

109 Inheritance Subclass must invoke parent's constructor explicitly
class Square(Rectangle): def __init__(self, width): Rectangle.__init__(self, width, width)‏ >>> s = Square(100)‏ >>> s.area()‏ 10000

110 accessing superclass Python 3 has a super() method to access superclass. class Square(Rectangle): def __init__(self, width): super().__init__( width, width)‏ >>> s = Square(100)‏ >>> s.area()‏ 10000

111 Polymorphism All methods are virtual import math class Circle(object):
def __init__(self, radius): self.radius = radius def area(self): return math.pi*self.radius*self.radius >>> shapes = [Square(5), Rect(2,8), Circle(3)] >>> for x in shapes: print x.area()‏ 25 16

112 Operator Overloading Objects can implement infix operators by defining specialy named methods, such as __add__ operators: +, -, *, /, **, &, ^, ~, != class Point: def __init__(self, x, y): this.x, this.y = x, y def __add__(self, other): return Point(self.x+other.x, self.y+other.y); >>> a = Point(1,2) >>> b = Point(3,7) >>> print(a + b) # invokes Point.__add__(a,b) (4, 9) # assuming we also define Point.__str__

113 Python Object Hooks Objects can support built-in operators by implementing special methods operators: +, -, *, /, **, &, ^, ~, != Indexing (like sequences): obj[idx] Calling (like functions): obj(args,...)‏ Iteration and containment tests for item in obj: ... if item in obj: ...

114 Object Data is Stored as a Dictionary
Attributes are stored in a dictionary (__dict__). You can add attributes to existing object! f.name = value invokes f.__setattr__("name",value) del f.name invokes f.__delattr__("name") f = Fraction(2,3) f.name = "weak, weak" f.__dict__ {'num': 2, 'denom':3, 'name':'weak, weak'}

115 Testing object type Get the type of a variable:
Test the type using isinstance: >>> p = Point( 1, 3) >>> type(p) <class '__main__.Point'> >>> p = Point( 1, 3) >>> isinstance(p, Point) True >>> isinstance(p, float) False

116 Functional Programming

117 Functional Approaches
In Function Programming, functions can be used in the same way as other data types. Python borrows from functional languages: Lisp/Scheme Haskell Python built-in functions for functional style: map()‏ filter()‏ reduce()‏ zip()‏

118 map: "Apply to all" operation
result = map(func, list) func is applied to each element of the list result is a new list, same length as original list the original list is not altered >>> list = [2, 3, 4, 5] >>> roots = map( math.sqrt, list )‏ >>> for x in roots: print(x) 2.0 Function as argument.

119 map in Action y1 y2 y3 y4 y5 y6 y7 y8 func ŷ1

120 map in Action y1 y2 y3 y4 y5 y6 y7 y8 func ŷ1 ŷ2

121 map in Action y1 y2 y3 y4 y5 y6 y7 y8 func ŷ1 ŷ2 ŷ3

122 map in Action y1 y2 y3 y4 y5 y6 y7 y8 func ŷ1 ŷ2 ŷ3 ŷ4

123 map in Action y1 y2 y3 y4 y5 y6 y7 y8 func ŷ1 ŷ2 ŷ3 ŷ4 ŷ5 ŷ6 ŷ7 ŷ8

124 map with multiple lists
What if the function requires more than one argument? result = map(func, list1, ..., listn)‏ All lists must be of same length (not really) Number of lists (n) must match #args needed by func # powers of 2 pows = map( math.pow, [2]*5, [1,2,3,4,5] ) # same thing, using a range pows = map( math.pow, [2]*5, range(1,6) )

125 Use map to reduce coding
lst1 = [0, 1, 2, 3] lst2 = [4, 5, 6, 7] lst3 = [] for k in range(len(lst1)): lst3.append( add2(lst1[k],lst2[k]) )‏ lst1 = [0, 1, 2, 3] lst2 = [4, 5, 6, 7] lst3 = map(add2, lst1, lst2)‏

126 Benefits The map function can be used like an expression
Can be used as a parameter to a function >>> lst1 = [1, 2, 3, 4] >>> string.join(lst1) # Error: lst1 contains ints … TypeError: sequence item 0: expected string, int found >>> string.join( map(str, lst1) ) # Correct ' '

127 sublist = filter(func, list)‏
filter elements of a list sublist = filter(func, list)‏ return a sublist from list containing only elements that "pass" func (func returns True or non-zero for element) the result has length less than or equal to the list list is not altered def isEven(x): return x%2 == 0 lst = [2, 7, 9, 8, -12, 11] even = filter(isEven, lst) # even = [2, 8, -12]

128 result = reduce(func, list)‏
reduce accumulate a result result = reduce(func, list)‏ Apply func cumulatively to a sequence func must take 2 parameters For each element in list, previous func result is used as 1st arg. def multiply(x, y): return x*y lst = [1,2,3,4,5] result = reduce(multiply, lst) # result = 1*2*3*4*5

129 reduce(func, initial_value, list)‏
reduce with initial value reduce(func, initial_value, list)‏ Use initial_value as parameter in first call to func lst = [2,3,4,5] result = reduce(multiply, 10, lst) # result = 10 * 2 * 3 * 4 * 5

130 Code Comparison lst1 = [ [2, 4], [5, 9], [1, 7] ]
result = operator.add([100], lst1[0])‏ for element in lst1[1:]: result = operator.add(sum, element)‏ lst1 = [ [2, 4], [5, 9], [1, 7] ] result = reduce(operator.add, lst1, [100])‏

131 Join lists element-by-element
zip(list1, …, listn)‏ Example: Combine two lists >>> lst1 = [1, 2, 3, 4] >>> lst2 = ['a', 'b', 'c', 'd', 'e'] >>> result = zip(lst1, lst2)‏ >>> result [(1, 'a'), (2, 'b'), (3, 'c'), (4, 'd')] The ‘e’ element was truncated since lst1 only has 4 elements The result is a list of tuples

132 Uses for zip Create a dictionary using zip() and dict()‏
>>> produce = ['apples', 'oranges', 'pears'] >>> prices = [0.50, 0.45, 0.55] >>> priceDict = dict(zip(produce, prices))‏ >>> print priceDict {'pears': 0.55, 'apples': 0.5, 'oranges': 0.45}

133 Lambda Functions Anonymous functions. Can be used assigned to variable. Syntax : lambda p1[,…,pn]: expression expression should not use return Example: create a square function >>> sqr = lambda x: x*x >>> print sqr(5)‏ 25 Example: average of 2 values >>> avg = lambda x,y: (x+y)/2‏ >>> avg(2,7)‏ 4.5

134 Function can return a Lambda
Lambda's can be return values or function arguments. # define a power function: only x is "bound" to the lambda define power(n): return lambda x: math.pow(x, n) cube = power(3) cube(10) 1000.0 list( map( cube, range(1,10) ) ) [1.0, 8.0, 27.0, ..., 729.0]

135 Generator and Iterators
Any function that uses yield is a generator. The return value is a generator type. def fibonacci(max): '''compute all fibonacci numbers < max''' a, b = 0, 1 while b < max: yield b # the next() result a, b = b, a+b >>> f = fibonacci(100) >>> f <generator object fibonacci at 0x00E52210>

136 Using Generator as Iterator
Each call to f.__next__( ) gets next return value. >>> f = fibonacci(100) >>> f.__next__( ) 1 2 3

137 Using Generator in context
Generators can be used in loops and as list generators for x in fibonacci(40): print( x ) 1 2 3 5 8 13 21 34 lst = list(fibonacci(40)) [1,1,2,3,5,8,13,21,34]

138 Infinite Series Lazily generate values in a series. import Fraction
def harmonic(): '''return elements of harmonic series''' n = 1 while True: yield Fraction(1,n) # the next() result n = n + 1 # Print harmonic series until the sum > 5 sum = Fraction(0) for f in harmonic():

139 Iterators Iterators implement the Iterator pattern.
In Python, no "hasNext" method. obj.__iter__() returns an iterator (usually self) obj.__next__() returns next item. Raise a StopIteration exception if no next Note: in Python 2.x, __next__() was named next()

140 References Python Documentation http://docs.python.org Videos
Python for Programmers by Alex Martelli Advanced Python (Understanding Python) by Thomas Wouters

141 References Books Practical Programming: an Introduction ... by Jennifer Campbell, et al. (Pragmatic Programmers, 2009) Good book for novice programmer. Python Essential Reference, 4E. (Addison Wesley) Recommended by CPE/SKE students. Has tutorial and language description. More than just a reference.

142 Exercise Write a Python program freq.py to:
Fetch a text file from the web Report the most frequently used words in file $ python freq.py 345: the 221: of 192: to 184: a 151: or 128: you 102: license 98: and 97: work 91: that $

143 Exercise Hints Accessing command-line arguments
Read a webpage - don't do this, use an iterator Extracting all English words from text import sys url = sys.argv[1] import urllib contents = urllib.openurl(url).readlines()‏ import re words = re.findall('[A-Za-z]+', text)‏