The tutorial is from Dan Klein and Pieter Abbeel

A good tutorial: https://docs.python.org/2/tutorial/

Table of Contents

• Invoking the Interpreter
• Operators
• Strings
• Dir and Help
• Built-in Data Structures
• Lists
• Tuples
• Sets
• Dictionaries
• Writing Scripts
• Indentation
• Tabs vs Spaces
• Writing Functions
• Object Basics
• Defining Classes
• Using Objects
• Tips and Tricks
• Troubleshooting
• More References

  ?

  Python, an interpreted, object-oriented language that shares some features with both Java and Scheme. This tutorial will walk through the primary syntactic constructions in Python, using short examples

  ?

  Invoking the Interpreter

  Python can be run in one of two modes. It can either be used?interactively, via an interpreter, or it can be called from the command line to execute a?script. We will first use the Python interpreter interactively.

  Operators

  The Python interpreter can be used to evaluate expressions, for example simple arithmetic expressions. If you enter such expressions at the prompt (>>>) they will be evaluated and the result will be returned on the next line.

  >>> 1 + 1?
  2?
  >>> 2 * 3?
  6

  Boolean operators also exist in Python to manipulate the primitive?True?and?False?values.

  >>> 1==0?
  False?
  >>> not (1==0)?
  True?

  ?

  Strings

  Like Java, Python has a built in string type. The?+?operator is overloaded to do string concatenation on string values.

  >>> ‘artificial‘ + "intelligence"?
  ‘artificialintelligence‘

  There are many built-in methods which allow you to manipulate strings.

  >>> ‘artificial‘.upper()
  ‘ARTIFICIAL‘

  ?

  Notice that we can use either single quotes?‘ ‘?or double quotes?" "?to surround string. This allows for easy nesting of strings.

  We can also store expressions into variables.

  >>> s = ‘hello world‘?
  >>> print s?
  hello world?
  >>> s.upper()
  ‘HELLO WORLD‘

  ?

  In Python, you do not have declare variables before you assign to them.

  Exercise: Dir and Help

  Learn about the methods Python provides for strings. To see what methods Python provides for a datatype, use the?dir?and?help?commands:

  >>> s = ‘abc‘?
  
  >>> dir(s)

  [‘__add__‘, ‘__class__‘, ‘__contains__‘, ‘__delattr__‘, ‘__doc__‘, ‘__eq__‘, ‘__ge__‘, ‘__getattribute__‘, ‘__getitem__‘, ‘__getnewargs__‘, ‘__getslice__‘, ‘__gt__‘, ‘__hash__‘, ‘__init__‘,‘__le__‘, ‘__len__‘, ‘__lt__‘, ‘__mod__‘, ‘__mul__‘, ‘__ne__‘, ‘__new__‘, ‘__reduce__‘, ‘__reduce_ex__‘,‘__repr__‘, ‘__rmod__‘, ‘__rmul__‘, ‘__setattr__‘, ‘__str__‘, ‘capitalize‘, ‘center‘, ‘count‘, ‘decode‘, ‘encode‘, ‘endswith‘, ‘expandtabs‘, ‘find‘, ‘index‘, ‘isalnum‘, ‘isalpha‘, ‘isdigit‘, ‘islower‘, ‘isspace‘, ‘istitle‘, ‘isupper‘, ‘join‘, ‘ljust‘, ‘lower‘, ‘lstrip‘, ‘replace‘, ‘rfind‘,‘rindex‘, ‘rjust‘, ‘rsplit‘, ‘rstrip‘, ‘split‘, ‘splitlines‘, ‘startswith‘, ‘strip‘, ‘swapcase‘, ‘title‘, ‘translate‘, ‘upper‘, ‘zfill‘]

  >>> help(s.find)

  Help on built-in function find:
  

  find(...)

  S.find(sub [,start [,end]]) -> int

  ?

  Return the lowest index in S where substring sub is found,

  such that sub is contained within s[start,end]. Optional

  arguments start and end are interpreted as in slice notation.

  ?

  Return -1 on failure.

  ?

  >> s.find(‘b‘)
  1

  Try out some of the string functions listed in?dir?(ignore those with underscores ‘_‘ around the method name).

  ?

  Built-in Data Structures

  Python comes equipped with some useful built-in data structures, broadly similar to Java‘s collections package.

  Lists

  Lists?store a sequence of mutable items:

  >>> fruits = [‘apple‘,‘orange‘,‘pear‘,‘banana‘]
  >>> fruits[0]?
  ‘apple‘

  We can use the?+?operator to do list concatenation:

  >>> otherFruits = [‘kiwi‘,‘strawberry‘]
  >>> fruits + otherFruits
  >>> [‘apple‘, ‘orange‘, ‘pear‘, ‘banana‘, ‘kiwi‘, ‘strawberry‘]

  Python also allows negative-indexing from the back of the list. For instance,?fruits[-1]?will access the last element?‘banana‘:

  >>> fruits[-2]
  ‘pear‘
  >>> fruits.pop()
  ‘banana‘
  >>> fruits
  [‘apple‘, ‘orange‘, ‘pear‘]
  >>> fruits.append(‘grapefruit‘)?
  >>> fruits?
  [‘apple‘, ‘orange‘, ‘pear‘, ‘grapefruit‘]?
  >>> fruits[-1] = ‘pineapple‘?
  >>> fruits?
  [‘apple‘, ‘orange‘, ‘pear‘, ‘pineapple‘]

  We can also index multiple adjacent elements using the slice operator. For instance,?fruits[1:3], returns a list containing the elements at position 1 and 2. In general?fruits[start:stop]?will get the elements in?start, start+1, ..., stop-1. We can also do?fruits[start:]?which returns all elements starting from the?start?index. Also?fruits[:end]?will return all elements before the element at position?end:

  >>> fruits[0:2]?
  [‘apple‘, ‘orange‘]?
  >>> fruits[:3]
  [‘apple‘, ‘orange‘, ‘pear‘]?
  >>> fruits[2:]
  [‘pear‘, ‘pineapple‘]?
  >>> len(fruits)?
  4

  ?

  The items stored in lists can be any Python data type. So for instance we can have lists of lists:

  >>> lstOfLsts = [[‘a‘,‘b‘,‘c‘],[1,2,3],[‘one‘,‘two‘,‘three‘]]?
  >>> lstOfLsts[1][2]?
  3
  >>> lstOfLsts[0].pop()
  ‘c‘
  >>> lstOfLsts
  [[‘a‘, ‘b‘],[1, 2, 3],[‘one‘, ‘two‘, ‘three‘]]

  ?

  Exercise: Lists

  Play with some of the list functions. You can find the methods you can call on an object via thedir?and get information about them via the?help?command:

  >>> dir(list)

  ?

  >>> help(list.reverse)

  >>> lst = [‘a‘,‘b‘,‘c‘]
  >>> lst.reverse()
  >>> [‘c‘,‘b‘,‘a‘]

  ?

  Note: Ignore functions with underscores "_" around the names; these are private helper methods. Press ‘q‘ to back out of a help screen.

  Tuples

  A data structure similar to the list is the?tuple, which is like a list except that it is immutable once it is created (i.e. you cannot change its content once created). Note that tuples are surrounded with parentheses while lists have square brackets.

  >>> pair = (3,5)
  >>> pair[0]
  3
  >>> x,y = pair
  >>> x
  3
  >>> y
  5?
  >>> pair[1] = 6
  TypeError: object does not support item assignment

  The attempt to modify an immutable structure raised an exception. Exceptions indicate errors: index out of bounds errors, type errors, and so on will all report exceptions in this way.

  Sets

  A?set?is another data structure that serves as an unordered list with no duplicate items. Below, we show how to create a set, add things to the set, test if an item is in the set, and perform common set operations (difference, intersection, union):

  >>> shapes = [‘circle‘,‘square‘,‘triangle‘,‘circle‘]
  >>> setOfShapes = set(shapes)
  >>> setOfShapes?
  set([‘circle‘,‘square‘,‘triangle‘])?
  >>> setOfShapes.add(‘polygon‘)?
  >>> setOfShapes?
  set([‘circle‘,‘square‘,‘triangle‘,‘polygon‘])?
  >>> ‘circle‘ in setOfShapes?
  True?
  >>> ‘rhombus‘ in setOfShapes?
  False?
  >>> favoriteShapes = [‘circle‘,‘triangle‘,‘hexagon‘]
  >>> setOfFavoriteShapes = set(favoriteShapes)
  >>> setOfShapes - setOfFavoriteShapes?
  set([‘square‘,‘polyon‘])?
  >>> setOfShapes & setOfFavoriteShapes?
  set([‘circle‘,‘triangle‘])
  >>> setOfShapes | setOfFavoriteShapes?
  set([‘circle‘,‘square‘,‘triangle‘,‘polygon‘,‘hexagon‘])

  Note that the objects in the set are unordered; you cannot assume that their traversal or print order will be the same across machines!

  Dictionaries

  The last built-in data structure is the?dictionary?which stores a map from one type of object (the key) to another (the value). The key must be an immutable type (string, number, or tuple). The value can be any Python data type.

  Note: In the example below, the printed order of the keys returned by Python could be different than shown below. The reason is that unlike lists which have a fixed ordering, a dictionary is simply a hash table for which there is no fixed ordering of the keys (like HashMaps in Java). The order of the keys depends on how exactly the hashing algorithm maps keys to buckets, and will usually seem arbitrary. Your code should not rely on key ordering, and you should not be surprised if even a small modification to how your code uses a dictionary results in a new key ordering.

  >>> studentIds = {‘knuth‘: 42.0, ‘turing‘: 56.0, ‘nash‘: 92.0 }
  >>> studentIds[‘turing‘]
  56.0
  >>> studentIds[‘nash‘] = ‘ninety-two‘
  >>> studentIds
  {‘knuth‘: 42.0, ‘turing‘: 56.0, ‘nash‘: ‘ninety-two‘}
  >>> del studentIds[‘knuth‘]
  >>> studentIds
  {‘turing‘: 56.0, ‘nash‘: ‘ninety-two‘}
  >>> studentIds[‘knuth‘] = [42.0,‘forty-two‘]
  >>> studentIds
  {‘knuth‘: [42.0, ‘forty-two‘], ‘turing‘: 56.0, ‘nash‘: ‘ninety-two‘}
  >>> studentIds.keys()
  [‘knuth‘, ‘turing‘, ‘nash‘]
  >>> studentIds.values()
  [[42.0, ‘forty-two‘], 56.0, ‘ninety-two‘]
  >>> studentIds.items()
  [(‘knuth‘,[42.0, ‘forty-two‘]), (‘turing‘,56.0), (‘nash‘,‘ninety-two‘)]
  >>> len(studentIds)?
  3

  As with nested lists, you can also create dictionaries of dictionaries.

  Exercise: Dictionaries

  Use?dir?and?help?to learn about the functions you can call on dictionaries.

  Writing Scripts

  Now that you‘ve got a handle on using Python interactively, let‘s write a simple Python script that demonstrates Python‘s?for?loop. Open the file called?foreach.py?and update it with the following code:

  control structures (e.g.,?if?and?else) in Python

  ?

  If you like functional programming you might also like?map?and?filter:

  >>> map(lambda x: x * x, [1,2,3])
  [1, 4, 9]
  >>> filter(lambda x: x > 3, [1,2,3,4,5,4,3,2,1])
  [4, 5, 4]

  ?

  The next snippet of code demonstrates Python‘s?list comprehension?construction:

  nums = [1,2,3,4,5,6]

  plusOneNums = [x+1 for x in nums]

  oddNums = [x for x in nums if x % 2 == 1]

  print oddNums

  Exercise: List Comprehensions

  Write a list comprehension which, from a list, generates a lowercased version of each string that has length greater than five. You can find the solution in?listcomp2.py.

  strings = [‘Some string‘,‘Art‘,‘Music‘,‘Artificial Intelligence‘]

  print [x.lower() for x in strings if len(x) > 5]

  Beware of Indendation!

  Unlike many other languages, Python uses the indentation in the source code for interpretation. So for instance, for the following script:

  if 0 == 1: 

      print ‘We are in a world of arithmetic pain‘ 

  print ‘Thank you for playing‘ 

  will output

  Thank you for playing

  But if we had written the script as

  if 0 == 1: 

      print ‘We are in a world of arithmetic pain‘

      print ‘Thank you for playing‘

  there would be no output. The moral of the story: be careful how you indent! It‘s best to use four spaces for indentation -- that‘s what the course code uses.

  ?

  Tabs vs Spaces

  Because Python uses indentation for code evaluation, it needs to keep track of the level of indentation across code blocks. This means that if your Python file switches from using tabs as indentation to spaces as indentation, the Python interpreter will not be able to resolve the ambiguity of the indentation level and throw an exception. Even though the code can be lined up visually in your text editor, Python "sees" a change in indentation and most likely will throw an exception (or rarely, produce unexpected behavior).

  This most commonly happens when opening up a Python file that uses an indentation scheme that is opposite from what your text editor uses (aka, your text editor uses spaces and the file uses tabs). When you write new lines in a code block, there will be a mix of tabs and spaces, even though the whitespace is aligned. For a longer discussion on tabs vs spaces, see?this?discussion on StackOverflow.

  Writing Functions

  As in Java, in Python you can define your own functions:

  fruitPrices = {‘apples‘:2.00, ‘oranges‘: 1.50, ‘pears‘: 1.75}

  ?

  def buyFruit(fruit, numPounds):						

      if fruit not in fruitPrices:

          print "Sorry we don‘t have %s" % (fruit)

      else:

          cost = fruitPrices[fruit] * numPounds

          print "That‘ll be %f please" % (cost)

  ?

  # Main Function

  if __name__ == ‘__main__‘:						

      buyFruit(‘apples‘,2.4)

      buyFruit(‘coconuts‘,2)        

  Rather than having a?main?function as in Java, the?__name__ == ‘__main__‘?check is used to delimit expressions which are executed when the file is called as a script from the command line. The code after the main check is thus the same sort of code you would put in a?main?function in Java.

  attention：two_

  Object Basics

  Although this isn‘t a class in object-oriented programming, you‘ll have to use some objects in the programming projects, and so it‘s worth covering the basics of objects in Python. An object encapsulates data and provides functions for interacting with that data.

  Defining Classes

  Here‘s an example of defining a class named?FruitShop:

  class FruitShop:

  ?

  							def							__init__(self, name, fruitPrices):

          """

              name: Name of the fruit shop

  ?

              fruitPrices: Dictionary with keys as fruit 

              strings and prices for values e.g. 

              {‘apples‘:2.00, ‘oranges‘: 1.50, ‘pears‘: 1.75} 

          """

          self.fruitPrices = fruitPrices

          self.name = name

          print ‘Welcome to the %s fruit shop‘ % (name)

  ?

      def getCostPerPound(self, fruit):

  							"""						

              fruit: Fruit string

          Returns cost of ‘fruit‘, assuming ‘fruit‘

          is in our inventory or None otherwise

  							"""						

          if fruit not in self.fruitPrices:

              print "Sorry we don‘t have %s" % (fruit)

              return None

          return self.fruitPrices[fruit]

  ?

      def getPriceOfOrder(self, orderList):

          """

              orderList: List of (fruit, numPounds) tuples

  ?

          Returns cost of orderList. If any of the fruit are  

          """ 

          totalCost = 0.0             

          for fruit, numPounds in orderList:

              costPerPound = self.getCostPerPound(fruit)

              if costPerPound != None:

                  totalCost += numPounds * costPerPound

          return totalCost

  ?

      def getName(self):

          return self.name

  The?FruitShop?class has some data, the name of the shop and the prices per pound of some fruit, and it provides functions, or methods, on this data. What advantage is there to wrapping this data in a class?

• Encapsulating the data prevents it from being altered or used inappropriately,
• The abstraction that objects provide make it easier to write general-purpose code.

  ?

  Using Objects

  So how do we make an object and use it? Make sure you have the?FruitShop?implementation inshop.py. We then import the code from this file (making it accessible to other scripts) using?import shop, since?shop.py?is the name of the file. Then, we can create?FruitShop?objects as follows:

  import shop

  ?

  shopName = ‘the Berkeley Bowl‘

  fruitPrices = {‘apples‘: 1.00, ‘oranges‘: 1.50, ‘pears‘: 1.75}

  berkeleyShop = shop.FruitShop(shopName, fruitPrices)

  applePrice = berkeleyShop.getCostPerPound(‘apples‘)

  print applePrice

  print(‘Apples cost $%.2f at %s.‘ % (applePrice, shopName))

  ?

  otherName = ‘the Stanford Mall‘

  otherFruitPrices = {‘kiwis‘:6.00, ‘apples‘: 4.50, ‘peaches‘: 8.75}

  otherFruitShop = shop.FruitShop(otherName, otherFruitPrices)

  otherPrice = otherFruitShop.getCostPerPound(‘apples‘)

  print otherPrice

  print(‘Apples cost $%.2f at %s.‘ % (otherPrice, otherName))

  print("My, that‘s expensive!")

  This code is in?shopTest.py; you can run it like this:

  [cs188-ta@nova ~]$ python shopTest.py

  Welcome to the Berkeley Bowl fruit shop

  1.0

  Apples cost $1.00 at the Berkeley Bowl.

  Welcome to the Stanford Mall fruit shop

  4.5

  Apples cost $4.50 at the Stanford Mall.

  My, that‘s expensive!

  So what just happended? The?import shop?statement told Python to load all of the functions and classes in?shop.py. The line?berkeleyShop = shop.FruitShop(shopName, fruitPrices)?constructs aninstance?of the?FruitShop?class defined in?shop.py, by calling the?__init__?function in that class. Note that we only passed two arguments in, while?__init__?seems to take three arguments:?(self, name, fruitPrices). The reason for this is that all methods in a class have?self?as the first argument. The?self?variable‘s value is automatically set to the object itself; when calling a method, you only supply the remaining arguments. The?self?variable contains all the data (nameand?fruitPrices) for the current specific instance (similar to?this?in Java). The print statements use the substitution operator (described in the?Python docs?if you‘re curious).

  Static vs Instance Variables

  The following example illustrates how to use static and instance variables in Python.

  Create the?person_class.py?containing the following code:

  class Person:

  							population = 0

      def __init__(self, myAge):

  							self.age = myAge

          Person.population += 1

      def get_population(self):

          return Person.population

      def get_age(self):

          return self.age

  We first compile the script:

  [cs188-ta@nova ~]$ python person_class.py

  Now use the class as follows:

  >>> import person_class
  >>> p1 = person_class.Person(12)
  >>> p1.get_population()
  1?
  >>> p2 = person_class.Person(63)
  >>> p1.get_population()
  2?
  >>> p2.get_population()
  2?
  >>> p1.get_age()
  12?
  >>> p2.get_age()
  63

  In the code above,?age?is an instance variable and?population?is a static variable.?population?is shared by all instances of the?Person?class whereas each instance has its own?age?variable.

  Troubleshooting

  These are some problems (and their solutions) that new Python learners commonly encounter.

• Problem:
  ImportError: No module named py

  Solution:
  When using?import, do not include the ".py" from the filename.?
  For example, you should say:?import shop?
  NOT:?import shop.py

• Problem:
  NameError: name ‘MY VARIABLE‘ is not defined
  Even after importing you may see this.

  Solution:
  To access a member of a module, you have to type?MODULE NAME.MEMBER NAME, where?MODULE NAME?is the name of the?.py?file, and?MEMBER NAME?is the name of the variable (or function) you are trying to access.

• Problem:
  TypeError: ‘dict‘ object is not callable

  Solution:
  Dictionary looks up are done using square brackets: [ and ]. NOT parenthesis: ( and ).

• Problem:
  ValueError: too many values to unpack

  Solution:
  Make sure the number of variables you are assigning in a?for?loop matches the number of elements in each item of the list. Similarly for working with tuples.

  For example, if?pair?is a tuple of two elements (e.g.?pair =(‘apple‘, 2.0)) then the following code would cause the "too many values to unpack error":

  (a,b,c) = pair

  Here is a problematic scenario involving a?for?loop:

  pairList = [(‘apples‘, 2.00), (‘oranges‘, 1.50), (‘pears‘, 1.75)]

  for fruit, price, color in pairList:

      print ‘%s fruit costs %f and is the color %s‘ % (fruit, price, color)

• Problem:
  AttributeError: ‘list‘ object has no attribute ‘length‘ (or something similar)

  Solution:
  Finding length of lists is done using?len(NAME OF LIST).

• Problem:
  Changes to a file are not taking effect.

  Solution:

• Make sure you are saving all your files after any changes.
• If you are editing a file in a window different from the one you are using to execute python, make sure you?reload(YOUR_MODULE)?to guarantee your changes are being reflected.?reload?works similarly to?import.

  More References

• The place to go for more Python information:?www.python.org
• A good reference book:?Learning Python?(From the UCB campus, you can read the whole book online)