Introduction to Programming in Python (1)

Transcription

1 to Programming in Python (1) Steve Renals ICL 26 September 2005 Steve to Programming in Python (1)

2 Announcements Lab sessions: Groups listed on the web: Steve to Programming in Python (1)

3 Overview Running programs Modules Numbers and variables Strings Lists Dictionaries Conditionals Loops Steve to Programming in Python (1)

4 Overview Running programs Modules Python books Mark Lutz and David Ascher (2004). Learning Python, 2nd Edition, O Reilly. Allen Downey, Jeff Elkner and Chris Meyers (2001), How to Think Like a Computer Scientist: Learning with Python, Green Tea Press. David Beazley (2001), Python Essential Reference, 2nd edition, New Riders. Mark Lutz (2002). Python Pocket Reference, 2nd Edition, O Reilly. Mark Lutz (2001). Programming Python, 2nd Edition, O Reilly. (O Reilly books available via on the web Safari Books Online: Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

5 Overview Running programs Modules Python features Free, portable, powerful Steve to Programming in Python (1)

6 Overview Running programs Modules Python features Free, portable, powerful Easy to mix in components from other languages Steve to Programming in Python (1)

7 Overview Running programs Modules Python features Free, portable, powerful Easy to mix in components from other languages Object-oriented (including operator overloading, polymorphism, multiple inheritance) Steve to Programming in Python (1)

8 Overview Running programs Modules Python features Free, portable, powerful Easy to mix in components from other languages Object-oriented (including operator overloading, polymorphism, multiple inheritance) Easy to use, easy to learn, easy to understand Steve to Programming in Python (1)

9 Overview Running programs Modules Python features Free, portable, powerful Easy to mix in components from other languages Object-oriented (including operator overloading, polymorphism, multiple inheritance) Easy to use, easy to learn, easy to understand NLTK and NLTK-Lite are Python packages that we will use in ICL (Learning Python, chapter 1) Steve to Programming in Python (1)

10 Overview Running programs Modules Using Python interactively The easiest way to use Python initially is interactively: % python2.4 >>> print ICL ICL >>> print 3*4 12 >>> print 2** >>> myname = Steve >>> myname Steve (Learning Python, chapter 3) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

11 Overview Running programs Modules Using Python interactively The easiest way to use Python initially is interactively: % python2.4 >>> print ICL ICL >>> print 3*4 12 >>> print 2** >>> myname = Steve >>> myname Steve (Learning Python, chapter 3) Can also use the IDLE environment: idle2.4 (X)Emacs users have python-mode. Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

12 Overview Running programs Modules Modules To save code you need to write it in files Module: a text file containing Python code Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

13 Overview Running programs Modules Modules To save code you need to write it in files Module: a text file containing Python code Example: write the following to file foo.py: print 25*3 # multiply by 3 print ICL + lecture 2 # concatenate strings using + myname = Steve (No leading spaces!) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

14 Overview Running programs Modules Modules To save code you need to write it in files Module: a text file containing Python code Example: write the following to file foo.py: print 25*3 # multiply by 3 print ICL + lecture 2 # concatenate strings using + myname = Steve (No leading spaces!) Then run it as follows: % python foo.py 75 ICL lecture 2 % Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

15 Overview Running programs Modules Importing modules Every file ending in.py is a Python module. Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

16 Overview Running programs Modules Importing modules Every file ending in.py is a Python module. Modules can contain attributes such as functions, Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

17 Overview Running programs Modules Importing modules Every file ending in.py is a Python module. Modules can contain attributes such as functions, We can import this module into Python: % python >>> import foo 75 ICL lecture 2 >>> foo.myname Steve Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

18 Overview Running programs Modules Executable scripts On unix/linux can make normal Python text files executable: The first line is special beginning with #! File has executable privileges (chmod +x file.py) Steve to Programming in Python (1)

19 Overview Running programs Modules Executable scripts On unix/linux can make normal Python text files executable: The first line is special beginning with #! File has executable privileges (chmod +x file.py) Example: write the following to file foo.py: #!/usr/bin/python2.4 print 25*3 # multiply by 3 print ICL + lecture 2 # concatenate strings using + myname = Steve Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

20 Overview Running programs Modules Executable scripts On unix/linux can make normal Python text files executable: The first line is special beginning with #! File has executable privileges (chmod +x file.py) Example: write the following to file foo.py: #!/usr/bin/python2.4 print 25*3 # multiply by 3 print ICL + lecture 2 # concatenate strings using + myname = Steve % chmod +x foo.py % foo.py 75 ICLlecture 2 % Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

21 Overview Running programs Modules Module reloads Importing is expensive after the first import of a module, repeated imports of a module have no effect (even if you have edited it) Use reload for force Python to rerun the file again: Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

22 Overview Running programs Modules Module reloads Importing is expensive after the first import of a module, repeated imports of a module have no effect (even if you have edited it) Use reload for force Python to rerun the file again: >>> import foo 75 ICL lecture 2 Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

23 Overview Running programs Modules Module reloads Importing is expensive after the first import of a module, repeated imports of a module have no effect (even if you have edited it) Use reload for force Python to rerun the file again: >>> import foo 75 ICL lecture 2 Redit foo.py to print 25*4 and reload >>> reload(foo) 100 ICL lecture 2 <module foo from foo.py > Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

24 Overview Running programs Modules Module attributes Consider bar.py: university = Edinburgh school = Informatics Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

25 Overview Running programs Modules Module attributes Consider bar.py: university = Edinburgh school = Informatics >>> import bar >>> print bar.school Informatics Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

26 Overview Running programs Modules Module attributes Consider bar.py: university = Edinburgh school = Informatics >>> import bar >>> print bar.school Informatics >>> from bar import school >>> print school Informatics Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

27 Overview Running programs Modules Module attributes Consider bar.py: university = Edinburgh school = Informatics >>> import bar >>> print bar.school Informatics >>> from bar import school >>> print school Informatics >>> from bar import * >>> print university Edinburgh Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

28 Overview Running programs Modules Module attributes Consider bar.py: university = Edinburgh school = Informatics >>> import bar >>> print bar.school Informatics >>> from bar import school >>> print school Informatics >>> from bar import * >>> print university Edinburgh from copies named attributes from a module, so they are variables in the recipient. Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

29 Overview Running programs Modules Python program structure Programs are composed of modules Steve to Programming in Python (1)

30 Overview Running programs Modules Python program structure Programs are composed of modules Modules contain statements Steve to Programming in Python (1)

31 Overview Running programs Modules Python program structure Programs are composed of modules Modules contain statements Statements contain expressions Steve to Programming in Python (1)

32 Overview Running programs Modules Python program structure Programs are composed of modules Modules contain statements Statements contain expressions Expressions create and process objects Steve to Programming in Python (1)

33 Overview Running programs Modules Python program structure Programs are composed of modules Modules contain statements Statements contain expressions Expressions create and process objects (Statements include: variable assignment, function calls, control flow, module access, building functions, building objects, print) (Learning Python, chapter 4) Steve to Programming in Python (1)

34 Numbers and variables Strings Lists Dictionaries Python s built-in objects 1. Numbers: integer, floating point, complex 2. Strings 3. Lists 4. Dictionaries 5. Tuples 6. Files Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

35 Numbers and variables Strings Lists Dictionaries Numbers (and variables) Usual number operators, eg: +, *, /, **, and, & Usual operator precedence: A * B + C * D = (A * B) + (C * D) (use parens for clarity and to reduce bugs) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

36 Numbers and variables Strings Lists Dictionaries Numbers (and variables) Usual number operators, eg: +, *, /, **, and, & Usual operator precedence: A * B + C * D = (A * B) + (C * D) (use parens for clarity and to reduce bugs) Useful packages: math, random Serious users: numeric, numarray Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

37 Numbers and variables Strings Lists Dictionaries Numbers (and variables) Usual number operators, eg: +, *, /, **, and, & Usual operator precedence: A * B + C * D = (A * B) + (C * D) (use parens for clarity and to reduce bugs) Useful packages: math, random Serious users: numeric, numarray Variables created when first assigned a value replaced with their values when used in expressions must be assigned before use no need to declare ahead of time Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

38 Numbers and variables Strings Lists Dictionaries Strings String handling in Python is easy and powerful (unlike C, C++, Java) (Learning Python, chapter 5) Steve to Programming in Python (1)

39 Numbers and variables Strings Lists Dictionaries Strings String handling in Python is easy and powerful (unlike C, C++, Java) Strings may be written using single quotes: This is a Python string or double quotes "and so is this" (Learning Python, chapter 5) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

40 Numbers and variables Strings Lists Dictionaries Strings String handling in Python is easy and powerful (unlike C, C++, Java) Strings may be written using single quotes: This is a Python string or double quotes "and so is this" They are the same, it just makes it easy to include single (double) quotes: He said "what?", "He s here" (Learning Python, chapter 5) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

41 Numbers and variables Strings Lists Dictionaries Backslash in strings Backslash \ can be used to escape (protect) certain non-printing or special characters \n is newline, \t is tab Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

42 Numbers and variables Strings Lists Dictionaries Backslash in strings Backslash \ can be used to escape (protect) certain non-printing or special characters \n is newline, \t is tab >>> s = Name\tAge\nJohn\t21\nBob\t44 >>> print s Name Age John 21 Bob 44 >>> t = "Mary\ s" >>> print t "Mary s" Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

43 Numbers and variables Strings Lists Dictionaries Triple quote Use a triple quote (""" or ) for a string over several lines: >>> s = """this is... a string... over 3 lines""" >>> t = so... is... this >>> print s this is a string over 3 lines >>> print t so is this Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

44 Numbers and variables Strings Lists Dictionaries String operations Concatenation (+) Length (len) Repetition (*) Indexing and slicing ([]) Steve to Programming in Python (1)

45 Numbers and variables Strings Lists Dictionaries String operations Concatenation (+) Length (len) Repetition (*) Indexing and slicing ([]) s = computational t = linguistics cl = s + + t # computational linguistics l = len(cl) # 25 u = - * 6 # c = s[3] # p x = cl[11:16] # al li y = cl[20:] # stics z = cl[:-1] # computational linguistic Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

46 Numbers and variables Strings Lists Dictionaries String methods Methods are functions applied associated with objects String methods allow strings to be processed in a more sophisticated way Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

47 Numbers and variables Strings Lists Dictionaries String methods Methods are functions applied associated with objects String methods allow strings to be processed in a more sophisticated way s = example s = s.capitalize() # Example t = s.lower() # example flag = s.isalpha() # True s = s.replace( amp, M ) # exmle i = t.find( xa ) # 1 n = t.count( e ) # 2 Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

48 Numbers and variables Strings Lists Dictionaries Lists in Python Ordered collections of arbitrary objects Accessed by indexing based on offset Variable length, heterogenous (can contain any type of object), nestable Mutable (can change the elements, unlike strings) Steve to Programming in Python (1)

49 Numbers and variables Strings Lists Dictionaries Lists in Python Ordered collections of arbitrary objects Accessed by indexing based on offset Variable length, heterogenous (can contain any type of object), nestable Mutable (can change the elements, unlike strings) >>> s = [ a, b, c ] >>> t = [1, 2, 3] >>> u = s + t # [ a, b, c, 1, 2, 3] >>> n = len(u) # 6 >>> for x in s:... print x... a b c Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

50 Numbers and variables Strings Lists Dictionaries Indexing and slicing lists Indexing and slicing work like strings Indexing returns the object element Slicing returns a list Can use indexing and slicing to change contents Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

51 Numbers and variables Strings Lists Dictionaries Indexing and slicing lists Indexing and slicing work like strings Indexing returns the object element Slicing returns a list Can use indexing and slicing to change contents l = [ a, b, c, d ] x = l[2] # c m = l[1:] # [ b, c, d ] l[2] = z # [ a, b, z, d ] l[0:2] = [ x, y ] # [ x, y, z, d ] (Learning Python, chapter 6) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

52 Numbers and variables Strings Lists Dictionaries List methods Lists also have some useful methods append adds an item to the list extend adds multiple items sort orders a list in place Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

53 Numbers and variables Strings Lists Dictionaries List methods Lists also have some useful methods append adds an item to the list extend adds multiple items sort orders a list in place l = [ x, y, z, d ] l.sort() # [ d, x, y, z ] l.append( q ) # [ d, x, y, z, q ] l.extend([ r, s ]) # [ d, x, y, z, q, r, s ] l.append([ v, w ]) # [ d, x, y, z, q, r, s, [ v, w ]] Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

54 Numbers and variables Strings Lists Dictionaries Dictionaries Dictionaries are Addressed by key, not by offset Unordered collections of arbitrary objects Variable length, heterogenous (can contain any type of object), nestable Mutable (can change the elements, unlike strings) Steve to Programming in Python (1)

55 Numbers and variables Strings Lists Dictionaries Dictionaries Dictionaries are Addressed by key, not by offset Unordered collections of arbitrary objects Variable length, heterogenous (can contain any type of object), nestable Mutable (can change the elements, unlike strings) Think of dictionaries as a set of key:value pairs Use a key to access its value (Learning Python, chapter 7) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

56 Numbers and variables Strings Lists Dictionaries Dictionary example level = { icl : 9, nlssd : 11, inf2b : 8} x = level[ nlssd ] # 11 n = len(level) # 3 flag = level.has key( inf2b ) # True l = level.keys() # [ nlssd, inf2b, icl ] level[ dil ] = 11 # { dil : 11, nlssd : 11, inf2b : 8, icl : 9} level[ icl ] = 10 # { dil : 11, nlssd : 11, inf2b : 8, icl : 10} l = level.items() # [( dil, 11), ( nlssd, 11), ( inf2b, 8), ( icl, 10)] l = level.values() # [11, 11, 8, 10] Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

57 Numbers and variables Strings Lists Dictionaries Notes on dictionaries Sequence operations don t work: dictionaries are mappings, not sequences Dictionaries have a set of keys: only one value per key Assigning to a new key adds an entry Keys can be any immutable object, not just strings Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

58 Numbers and variables Strings Lists Dictionaries Notes on dictionaries Sequence operations don t work: dictionaries are mappings, not sequences Dictionaries have a set of keys: only one value per key Assigning to a new key adds an entry Keys can be any immutable object, not just strings Dictionaries can be used as records Dictionaries can be used for sparse matrices Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

59 Numbers and variables Strings Lists Dictionaries Other objects Tuples: like lists, but immutable (cannot be changed) Steve to Programming in Python (1)

60 Numbers and variables Strings Lists Dictionaries Other objects Tuples: like lists, but immutable (cannot be changed) emptyt = () T1 = (1, 2, 3) x = T1[1] n = len(t1) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

61 Numbers and variables Strings Lists Dictionaries Other objects Tuples: like lists, but immutable (cannot be changed) emptyt = () T1 = (1, 2, 3) x = T1[1] n = len(t1) Files: objects with methods for reading and writing to files Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

62 Numbers and variables Strings Lists Dictionaries Other objects Tuples: like lists, but immutable (cannot be changed) emptyt = () T1 = (1, 2, 3) x = T1[1] n = len(t1) Files: objects with methods for reading and writing to files fil = open( myfile, w ) fil.write( hello file\n ) fil.close() Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

63 Numbers and variables Strings Lists Dictionaries Other objects Tuples: like lists, but immutable (cannot be changed) emptyt = () T1 = (1, 2, 3) x = T1[1] n = len(t1) Files: objects with methods for reading and writing to files fil = open( myfile, w ) fil.write( hello file\n ) fil.close() f2 = open( myfile, r ) s = f2.readline() # hello file\n t = f2.readline() # (Learning Python, chapter 7) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

64 Conditionals Loops if tests course = icl if course == icl : print Ewan / Steve elif course == dil : print Phillip else: print Someone else Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

65 Conditionals Loops if tests course = icl if course == icl : print Ewan / Steve elif course == dil : print Phillip else: print Someone else Indentation determines the block structure Indentation to the left is the only place where whitespace matters in Python Indentation enforces readability Tests after if and elif can be anything that returns True/False (Learning Python, chapter 9) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

66 Conditionals Loops while loops A while loop keeps iterating while the test at the top remains True. a = 0 b = 10 while a < b: print a a = a + 1 Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

67 Conditionals Loops while loops A while loop keeps iterating while the test at the top remains True. a = 0 b = 10 while a < b: print a a = a + 1 s = icl while len(s) > 0: print s s = s[1:] (Learning Python, chapter 10) Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

68 Conditionals Loops for loops for is used to step through any sequence object l = [ a, b, c ] for i in l: print i Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

69 Conditionals Loops for loops for is used to step through any sequence object l = [ a, b, c ] for i in l: print i sum = 0 for x in [1, 2, 3, 4, 5, 6]: sum = sum + x print sum Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

70 Conditionals Loops for loops for is used to step through any sequence object l = [ a, b, c ] for i in l: print i sum = 0 for x in [1, 2, 3, 4, 5, 6]: sum = sum + x print sum range() is a useful function: range(5) = [0, 1, 2, 3, 4] range(2, 5) = [2, 3, 4] range(0, 6, 2) = [0, 2, 4] Steve Renalss.renals@ed.ac.uk to Programming in Python (1)

71 to Python Python programs and modules Basic objects: numbers, strings, lists, dictionaries Control flow: if, while, for Steve to Programming in Python (1)