1 / 105

Introduction to Python

Introduction to Python. Materials based on contents from the course Programming with Python by Chad Haynes. Outline. Overview Built-in objects Functions and scopes Object-oriented programming Functional programming Exercise. Import a library module. Function definition.

popem
Download Presentation

Introduction to Python

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Introduction to Python Materials based on contents from the course Programming with Python by Chad Haynes

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

  3. Import a library module Function definition Class definition Comment Object instantiation Calling a function Python At First Glance import math def showArea(shape): print "Area = %d" % 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)

  4. Why use Python? • Simple, clean syntax • Portable • Flexible • Large standard library • Short development time • Lots of 3rd-party tools/add-ons • Many good implementations • CPython, PyPy, IronPython, Jython • Strong support from open-source community

  5. Similarities to Java • Everything inherits from "object" • Also numbers, functions, classes, … • Everything is first-class • Vast, powerful standard library • Garbage collection • Introspection, serialization, threads, net,…

  6. Similarities to C++ • Multi-paradigm • OOP, procedural, generic, functional (a little) • Multiple inheritance • Operator overloading

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

  8. Getting Started • Python already included in most Linux distributions • Windows users can download from: • http://python.org/download • Add python to PATH to run scripts from command line

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

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

  11. Variables • Reference Model • Variables refer to an object • More than one variable can refer to the same object Var1 Var1_copy Var2

  12. Numeric Types • Integers • Generally 32 signed bits • Long Integers • Unlimited size • Format: <number>L • Example: 4294967296L • Float • Platform dependant “double” precision • Complex • Format: <real>+<imag>j • Example: 6+3j

  13. Strings • A sequence of characters enclosed with quotes • 3 quoting styles • 'Single Quotes' • "Double Quotes" • """Triple Quotes""" • Examples >>> print 'This may contain a "' This may contain a " >>> print "A ' is allowed" A ' is allowed >>> print """Either " or ' are OK""" Either " or ' are OK

  14. Built-in Function: raw_input • Syntax: raw_input([prompt]) • Use prompt to ask user to input a string • Example >>> info = raw_input('-> ') -> Here is info >>> print info Here is info

  15. Basic Operations • Arithmetic • + - * // / ** % abs • Example >>> 5 + 3 # Addition • 8 • >>> 2 ** 8 # Exponentiation • 256 • >>> 13 / 4 # Integer (Truncating) Division* • 3 • >>> float(13) / 4 # Float Division • 3.25 • >>> 13 % 4 # Remainder • 1 • >>> abs(-3.5) # Absolute Value • 3.5 * Becomes float division in version 3.x

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

  17. i1 not i1 1 0 0 1 Basic Operations • Boolean • and or not • Based on Boolean Algebra i1 i2 i1and i2 i1or i2 1 1 1 1 1 0 0 1 0 1 0 1 0 0 0 0

  18. Basic Operations • Boolean • Example >>> 1 == 1 and 2 >= 3 0 • >>> 1 == 1 or 2 >= 3 • 1 • >>> not 5.3 != 2.2 # same as: not (5.3 != 2.2) • 0 • >>> 2 and '23' > '11' or 0 • 1

  19. Strings - Operations • Concatenation (+) • Syntax: string1 + string2 • Example: • >>> 'Rockefeller' + 'University' • 'RockefellerUniversity' • Repetition (*) • Syntax: string * number • Example: • >>> 'dog' * 5 • 'dogdogdogdogdog'

  20. Strings - Formatting • C-Style formatting (extended printf) • Examples: • >>> "%i %s in the basket" % (2, "eggs") • '2 eggs in the basket' • >>> "%f to 2 decimal places: %.2f" %(2.0/9.0, 2.0/9.0) • '0.222222 to 2 decimal places: 0.22' • >>> length = 5 • >>> obj = "fence" • >>> "Length of the %(obj)s is %(length)i" % vars() • 'Length of the fence is 5'

  21. Built-in Function: type • Syntax: type(object) • Used to determine the type of an object • Example • >>> type(2.45) • <type 'float'> • >>> type('x') • <type 'str'> • >>> type(2**34) • <type 'long'> • >>> type(3+2j) • <type 'complex'>

  22. Type Conversions • Use built-in functions to convert between types • str() int() float() long() complex() bool() • Example • >>> str(42.3) • '42.3' • >>> float('-1.32e-3') • -0.00132 • >>> int('0243') • 243 • >>> int(2**34) • Traceback (most recent call last): • File "<pyshell#12>", line 1, in ? • int(2**34) • OverflowError: long int too large to convert to int • >>> long(2**34) • 17179869184L

  23. Data Structures • Lists • Tuples • Dicts

  24. Lists • Construction • Syntax: [elem1, elem2, …] • Heterogeneous, ordered sequence • Mutable • Example: • >>> list1 = [1, 'hello', 4+2j, 123.12] • >>> list1 • [1, 'hello', (4+2j), 123.12] • >>> list1[0] = 'a' • >>> list1 • ['a', 'hello', (4+2j), 123.12]

  25. Lists - Operations • Concatenation (+) • Syntax: list1 + list2 • Example: • >>> [1, 'a', 'b'] + [3, 4, 5] • [1, 'a', 'b', 3, 4, 5] • Repetition (*) • Syntax: list * number • Example: • >>> [23, 'x'] * 4 • [23, 'x', 23, 'x', 23, 'x', 23, 'x']

  26. Indexing • Indexing operator: [ ] • Positive indices count from the left • Negative indices count from the right 0 1 2 3 4 5 6 a b c d e f g -7 -6 -5 -4 -3 -2 -1 sequence[0] == a sequence[-7] == a sequence[6] == g sequence[-1] == g sequence[2] == c sequence[-5] == c

  27. List Slicing • Two indices separated by a colon • Available for both strings and lists • Example • >>> sequence = [0, 1, 2, 3, 4, 5, 6, 7] • >>> sequence[1:4] • [1, 2, 3] • >>> sequence[2:-1] • [2, 3, 4, 5, 6] • Missing Index implies end point • >>> sequence[:2] • [0, 1] • >>> sequence[3:] • [3, 4, 5, 6, 7]

  28. Tuples • Immutable version of list • Syntax: (elem1, elem2, …) • Items in tuple can not be altered • 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

  29. Built-in Function: len • Syntax: len(object) • Return the length of object • Example • >>> list1 = [1, 2, 3, 4, 5] • >>> len(list1) • 5 • >>> string1 = "length of a string" • >>> len(string1) • 18

  30. 'z' 'ab' 2.1 3 Dictionaries • Mapping • Associate a key with a value • Each key must be unique keys 10 [2] (3,8) 'hello' values

  31. Dictionaries • Construction • Syntax: {key1: value1, key2: value2 …} • Unordered map • Example: • >>> dict1 = {'a': 1, 'b': 2} • >>> dict1 • {'a': 1, 'b': 2} • >>> dict1['a'] • 1 • >>> dict1['b'] • 2

  32. Control Flow Examples ifcondition: body elifcondition: body else: body if x%2 == 0: y = y + x else: y = y - x whilecondition: body while i < 0: count = count + 1 fornameiniterable: body for x in [1,2,3]: sum = sum + x

  33. Built-in Function: range • Syntax: 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]

  34. Controlling Flow • Using range with for • Generate list used by for with range • Example • >>> for i in range(4): • print i • 0 • 1 • 2 • 3

  35. Using Data Structures • Data structures also have methods • Use built-in function dir to list all available methods • Example • >>> lst = [1, 3, 2] • >>> dir(lst) • ['__add__', '__class__', '__contains__', '__delattr__', '__delitem__', '__delslice__', '__doc__', '__eq__', '__ge__', '__getattribute__', '__getitem__', '__getslice__', '__gt__', '__hash__', '__iadd__', '__imul__', '__init__', '__le__', '__len__', '__lt__', '__mul__', '__ne__', '__new__', '__reduce__', '__repr__', '__rmul__', '__setattr__', '__setitem__', '__setslice__', '__str__', 'append', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort']

  36. Lists - Methods • append • Syntax: list.append(element) • Add element to end of list • Example: • >>> list1 = [3, '10', 2] • >>> list1.append('new') • >>> list1 • [3, '10', 2, 'new']

  37. Lists - Methods • insert • Syntax: list.insert(index, element) • Insert element into list at position index • Example: • >>> list2 = [0, 1, 2, 3, 4, 5] • >>> list2.insert(3, 'new') • >>> list2 • [0, 1, 2, 'new', 3, 4, 5]

  38. Lists - Methods • sort • Syntax: list.sort([cmpfunc]) • Sort list in place • Example: • >>> list3 = [4, 12, 3, 9] • >>> list3.sort() • >>> list3 • [3, 4, 9, 12]

  39. Getting Help • For interactive use, calling help function will invoke the built-in help system • Call help() without argument for interactive mode >>> help(str) Help on class str in module __builtin__: class str(basestring) | str(object) -> string | | Return a nice string representation of the object. | If the argument is a string, the return value is the same object. | | Method resolution order: | str | basestring | object | | Methods defined here: | | __add__(...) | x.__add__(y) <==> x+y | | __contains__(...) | x.__contains__(y) <==> y in x :

  40. Functions and Scopes

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

  42. Functions • Parameters • Parameters can be any type • A function can take any number of parameters (or none at all) • Example: • >>> 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

  43. Functions • Default Parameters • One or more parameters can be given a default value • The function can be called with fewer arguments than there are parameters • All non-default (required) parameters must precede default parameters • Example: • >>> def printName(last, first, mi=""): • print "%s, %s %s" % (last, first, mi) • >>> printName("Smith", "John") • Smith, John • >>> printName("Smith", "John", "Q") • Smith, John Q

  44. Functions • Calling functions • Syntax: func(arg1, arg2, … argn) • Order of arguments must match order of declared parameters • No type checking is done • Example • >>> def display(arg1, arg2, arg3): • print arg1 • print arg2 • print arg3 • >>> display(1, 'x', 4.3) • 1 • x • 4.3

  45. Functions • Keyword arguments • Functions can be called using the keyword of the argument • Syntax: func(keyword=value, …) • The order of the values passed by keyword does not matter • Example • def keywords(key1="X", key2="X", key3="X",key4="X"): • print key1, key2, key3, key4 • >>> keywords(key3="O", key2="O") • X O O X • >>> keywords() • X X X X

  46. Functions • Functions as variables • Functions can be assigned • Example • def sub(a, b): • return a-b • >>> op = sub • >>> print op(3, 5) • -2 • >>> type(op) • <type 'function'>

  47. Functions • Functions as parameters • Functions can be passed to other functions • Example • 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', '5', '10', '53'], float) • [1.0, 5.0, 10.0, 53.0] • >>> convert(['1', '5', '10', '53'], complex) • [(1+0j), (5+0j), (10+0j), (53+0j)]

  48. Functions • Returning multiple values • Return a tuple containing the values to return • Example • def separate(text, size=3): • start = text[:size] • end = text[-size:] • return (start, end) • >>> separate('sample text') • ('sam', 'ext') • >>> start, end = separate('sample text') • >>> print start • sam • >>> print end • ext

  49. Generators • Generators are functions that generate sequence of items • Generated sequence can be infinite def fibonacci(): i = j = 1 while True: r, i, j = i, j, i+j yield r for rabbits in fibbonacci(): print rabbits if rabbits > 100: break 1 1 2 3 5 8 13 21 34 55 89 144

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

More Related