made it easy: python quick reference for beginners

Introduction to
Programming
with Python
Python Review. Modified slides from Marty Stepp and Moshe
Goldstein

 code or source code: The sequence of instructions in a program.
 syntax: The set of legal structures and commands that can
be used in a particular programming language.
 output: The messages printed to the user by a program.
 console: The text box onto which output is printed.
 Some source code editors pop up the console as an external
window,
and others contain their own console window.
Programming basics
2

Compiling and interpreting
 Many languages require you to compile (translate) your program
into a form that the machine understands.
compile
execute
 Python is instead directly interpreted into machine
instructions.
interpret
outpu
t
source code
Hello.java
byte code
Hello.class
outpu
t
source code
Hello.py
3

The Python Interpreter
•
Python is an interpreted
language
•
The interpreter provides
an interactive environment
to play with the language
•
Results of expressions are
printed on the screen
>>> 3 + 7
10
>>> 3 < 15
True
>>> 'print me'
'print me'
>>> print 'print me'
print me
>>>

Expressions
5
 expression: A data value or set of operations to compute a value.
Examples: 1 + 4 * 3
42
 Arithmetic operators we will use:
+ - * /
%
**
addition, subtraction/negation, multiplication, division
modulus, a.k.a. remainder
exponentiation
 precedence: Order in which operations are computed.
 * / % ** have a higher precedence than + -
1 + 3 * 4 is 13
 Parentheses can be used to force a certain order of evaluation.
(1 + 3) * 4 is 16

Integer division
6
 When we divide integers with / , the quotient is also an
integer.
3 52
4 ) 14 27 ) 1425
12 135
2 75
54
21
 More examples:

35 / 5 is 7

84 / 10 is 8

156 / 100 is 1
 The % operator computes the remainder from a division of
integers.
3 4 )
14
12
2
43 5 )
218
2
0
1
8
1
5

Real numbers
7
 Python can also manipulate real numbers.
 Examples: 6.022 -15.9997 42.0
2.143e17
 The operators + - * / % ** ( ) all work for real numbers.
 The / produces an exact answer: 15.0 / 2.0 is 7.5
 The same rules of precedence also apply to real numbers:
Evaluate ( ) before * / % before + -
 When integers and reals are mixed, the result is a real
number.
 Example: 1 / 2.0 is 0.5
 The conversion occurs on a per-operator basis.
7 / 3 * 1.2 + 3 / 2
2 * 1.2 + 3 / 2
2.4 + 3 / 2
2.4 + 1
3.4

8
Math commands
 Python has useful commands (or called functions) for
performing calculations.
 To use many of these commands, you must write the following at
the top of your Python program:
from math import *
Command name Description
abs(value) absolute value
ceil(value) rounds up
cos(value) cosine, in radians
floor(value) rounds down
log(value) logarithm, base e
log10(value) logarithm, base 10
max(value1, value2) larger of two values
min(value1, value2) smaller of two values
round(value) nearest whole number
sin(value) sine, in radians
sqrt(value) square root
Constant Description
e 2.7182818...
pi 3.1415926...

Numbers: Floating Point
 int(x) converts x to
an integer
 float(x) converts x
to a floating point
 The interpreter
shows
a lot of digits
>>> 1.23232
1.2323200000000001
>>> print 1.23232
1.23232
>>> 1.3E7
13000000.0
>>> int(2.0)
2
>>> float(2)
2.0

 A variable that has been given a value can be used in expressions.
x + 4 is 9
 Exercise: Evaluate the quadratic equation for a given a, b, and c.
10
Variables
 variable: A named piece of memory that can store a value.
 Usage:

Compute an expression's result,

store that result into a variable,

and use that variable later in the program.
 assignment statement: Stores a value into a variable.
 Syntax:
name = value
 Examples: x = 5
gpa = 3.14
x 5 gpa 3.14

Example
>>> x = 7
>>> x
7
>>>
x+7
14
>>> x
=
'hello'
>>> x
'hello'
>>>

 print : Produces text output on the console.
 Syntax:
print "Message"
print
Expression
 Prints the given
text message or
expression value
on the console,
and
moves the cursor
down to the next
line.
print Item1,
Item2, ...,
ItemN
 Prints several
messages and/or 12
print

Example: print Statement
>>> print 'hello'
hello
>>> print
'hello', 'there'
hello there
•
Elements separated by
commas print with a space
between them
•
A comma at the end of the
statement (print ‘hello’,)
will not print a newline
character

 input : Reads a number from user input.
 You can assign (store) the result of input into a variable.
 Example:
age = input("How old are you? ")
print "Your age is", age
print "You have", 65 - age, "years until retirement"
Output:
How old are you? 53
Your age is 53
You have 12 years until retirement
14
 Exercise: Write a Python program that prompts the user for
his/her amount of money, then reports how many Nintendo Wiis
the person can afford, and how much more money he/she will
need to afford an additional Wii.
input

Input: Example
print "What's your name?"
name = raw_input("> ")
print "What year were you born?"
birthyear = int(raw_input("> "))
print "Hi “, name, “!”, “You are “,
2016 – birthyear
% python input.py
What's your
name?
> Michael
What year were
you born?
>1980

Repetition (loops)
and Selection
(if/else)

The for loop
17
 for loop: Repeats a set of statements over a group of values.

Syntax:
for variableName in groupOfValues:
statements

We indent the statements to be repeated with tabs or spaces.

variableName gives a name to each value, so you can refer to it in the statements.

groupOfValues can be a range of integers, specified with the range function.

Example:
for x in range(1, 6):
print x, "squared is", x * x
Output:
1 squared is 1
2 squared is 4
3 squared is 9
4 squared is 16
5 squared is 25

range
18
 The range function specifies a range of
integers:

range(start, stop) - the integers between start (inclusive)
and stop (exclusive)
 It can also accept a third value specifying the change between values.

range(start, stop, step) - the integers between start (inclusive)
and stop (exclusive) by step
 Example:
for x in range(5, 0, -1):
print x
print "Blastoff!"
Output:
5
4
3
2
1
Blastoff!
 Exercise: How would we
print the "99 Bottles of Beer"
song?

Cumulative loops
19
 Some loops incrementally compute a value that is initialized outside
the loop. This is sometimes called a cumulative sum.
sum = 0
for i in range(1, 11):
sum = sum + (i * i)
print "sum of first 10 squares is", sum
Output:
sum of first 10 squares is 385
 Exercise: Write a Python program that computes the factorial of an
integer.

if
 if statement: Executes a group of statements only if a
certain condition is true. Otherwise, the statements are
skipped.
 Syntax:
if condition:
statements
 Example:
gpa = 3.4
if gpa > 2.0:
print "Your application is accepted."
20

2
if/else
 if/else statement: Executes one block of statements if a
certain condition is True, and a second block of statements if it is
False.

Syntax:
if condition:
statements
else:
statements
 Example:
gpa = 1.4
if gpa > 2.0:
print
"Welcome to
Mars
University!
"
else:
print "Your
application
is denied."
 Multiple conditions 1

Example of If Statements
import math
x = 30
if x <= 15 :
y = x + 15
elif x <= 30
:
y = x + 30
else :
y = x
print ‘y = ‘,
print
math.sin(y
)
In file ifstatement.py
>>> import ifstatement
y = 0.999911860107
>>>
In interpreter

23
while
 while loop: Executes a group of statements as long as a condition is True.
 good for indefinite loops (repeat an unknown number of times)
 Syntax:
while condition:
statements
 Example:
number = 1
while number < 200:
print number,
number = number * 2
 Output:
1 2 4 8 16 32 64 128

While Loops
x = 1
while x < 10 :
print x
x = x + 1
>>> import whileloop
1
2
3
4
5
6
7
8
9
>>>

In whileloop.py

In interpreter

 Exercise: Write code to display and count the factors of a number.
25
Logic
 Many logical expressions use relational operators:
 Logical expressions can be combined with logical operators:
Operator Example Result
and 9 != 6 and 2 < 3 True
or 2 == 3 or -1 < 5 True
not not 7 > 0 False
Operator Meaning Example Result
== equals 1 + 1 == 2 True
!= does not equal 3.2 != 2.5 True
< less than 10 < 5 False
> greater than 10 > 5 True
<= less than or equal to 126 <= 100 False
>= greater than or equal to 5.0 >= 5.0 True

Loop Control Statements
break Jumps out of the closest
enclosing loop
continue Jumps to the top of the closest
enclosing loop
pass Does nothing, empty statement
placeholder

More Examples For Loops
 Similar to perl for loops, iterating through a
list of values
for x in [1,7,13,2]:
print x forloop2.py
for x in range(5) :
print x
forloop1.py
%python forloop1.py
1
7
13
2
% python forloop2.py
0
1
2
3
4
range(N) generates a list of numbers [0,1, …, n-1]

Everything is an object
 Everything means
everything,
including functions
and classes
(more on this
later!)
 Data type is a
property of the
object and not of
the variable
>>> x = 7
>>> x
7
>>> x
=
'hello'
>>> x
'hello'
>>>

Numbers: Integers
 Integer – the
equivalent of a C long
 Long Integer – an
unbounded integer
value.
>>> 132224
132224
>>> 132323 **
2
17509376329L
>>>

Numbers: Complex
 Built into Python
 Same operations are
supported as
integer and float
>>> x = 3 + 2j
>>> y = -1j
>>> x + y
(3+1j)
>>> x * y
(2-3j)

String Literals
 + is overloaded to
do concatenation >>> x = 'hello'
>>> x = x + ' there'
>>> x
'hello there'

String Literals
 Can use single or double quotes, and
three double quotes for a multi-line
string
>>> 'I am a string'
'I am a string'
>>> "So am I!"
'So am I!'

Substrings and Methods
>>> s = '012345'
>>> s[3]
'3'
>>> s[1:4]
'123'
>>> s[2:]
'2345'
>>> s[:4]
'0123'
>>> s[-2]
'4'
•len(String) – returns the
number of characters in
the String
•str(Object) – returns a
String representation of
the Object
>>> len(x)
6
>>>
str(10.3)
'10.3'

String Formatting
 Similar to C’s printf
 <formatted string> % <elements to
insert>
 Can usually just use %s for everything,
it will convert the object to its String
representation.
>>> "One, %d, three" %
2 'One, 2, three'
>>> "%d, two, %s" %
(1,3)
'1, two, 3'
>>> "%s two %s" % (1,
'three') '1 two three'
>>>

Types for Data Collection
List, Set, and
Dictionary

List

Unordered list

Ordered Pairs of values

Lists
 Ordered collection of
data
 Data can be of
different
types
 Lists are
mutable
 Issues with shared
references and
mutability
 Same subset
>>> x = [1,'hello', (3 + 2j)]
>>> x
[1, 'hello', (3+2j)]
>>> x[2]
(3+2j)
>>>
x[0:2]
[1,
'hello']

List Functions
 list.append(x)
 Add item at the end of the list.
 list.insert(i,x)
 Insert item at a given position.
 Similar to a[i:i]=[x]
 list.remove(x)
 Removes first item from the list with value x
 list.pop(i)
 Remove item at position I and return it. If no index I is given then
remove the first item in the list.
 list.index(x)
 Return the index in the list of the first item with value x.
 list.count(x)
 Return the number of time x appears in the list
 list.sort()
 Sorts items in the list in ascending order
 list.reverse()
 Reverses items in the list

Lists: Modifying Content
 x[i] = a reassigns
the ith element to
the value a
 Since x and y point to
the same list object,
both are changed
 The method append
also modifies the list
>>> x = [1,2,3]
>>> y = x
>>> x[1] = 15
>>> x
[1, 15, 3]
>>> y
[1, 15, 3]
>>>
x.append
(12)
>>> y
[1, 15, 3,
12]

Lists: Modifying Contents
 The method
append
modifies the list
and returns
None
 List addition
(+) returns a
new list
>>> x = [1,2,3]
>>> y = x
>>> z = x.append(12)
>>> z == None
True
>>> y
[1, 2, 3, 12]
>>> x = x +
[9,10]
>>> x
[1, 2, 3, 12, 9,
10]
>>> y
[1, 2, 3, 12]

Using Lists as Stacks
 You can use a list as a stack
>>> a = ["a", "b", "c“,”d”]
>>> a
['a', 'b', 'c', 'd']
>>> a.append("e")
>>> a
['a', 'b', 'c', 'd', 'e']
>>> a.pop()
'e'
>>> a.pop()
'd'
>>> a =
["a", "b",
"c"]
>>>

Tuples
 Tuples are immutable
versions of lists
 One strange point is
the format to make a
tuple with one
element:
‘,’ is needed to
differentiate from the
mathematical
expression (2)
>>> x = (1,2,3)
>>> x[1:]
(2, 3)
>>> y = (2,)
>>> y
(2,)
>>>

Sets
 A set is another python data structure that is an
unordered collection with no duplicates.
>>> setA=set(["a","b","c","d"])
>>> setB=set(["c","d","e","f"])
>>> "a" in setA
True
>>> "a" in setB
False

Sets
>>> setA - setB
{'a', 'b'}
>>> setA | setB
{'a', 'c', 'b', 'e', 'd', 'f'}
>>> setA & setB
{'c', 'd'}
>>> setA ^ setB
{'a', 'b', 'e', 'f'}
>>>

Dictionaries
 A set of key-value pairs
 Dictionaries are mutable
>>> d= {‘one’ : 1, 'two' : 2, ‘three’ : 3}
>>> d[‘three’]
3

Dictionaries: Add/Modify
>>> d
{1: 'hello', 'two': 42, 'blah': [1, 2, 3]}
>>> d['two'] = 99
>>> d
{1: 'hello', 'two': 99, 'blah': [1, 2, 3]}
>>> d[7] = 'new entry'
>>> d
{1: 'hello', 7: 'new entry', 'two': 99, 'blah': [1, 2, 3]}
 Entries can be changed by assigning to
that entry
•
Assigning to a key that does not exist
adds an entry

Dictionaries: Deleting Elements
 The del method deletes an element from a
dictionary
>>> d
{1: 'hello', 2: 'there', 10: 'world'}
>>> del(d[2])
>>> d
{1: 'hello', 10: 'world'}

Iterating over a dictionary
>>>address={'Wayne': 'Young 678', 'John': 'Oakwood 345',
'Mary': 'Kingston 564'}
>>>for k in address.keys():
print(k,":", address[k])
Wayne : Young 678
John : Oakwood 345
Mary : Kingston
564
>>>
>>> for k in sorted(address.keys()):
print(k,":", address[k])
John : Oakwood 345
Mary : Kingston
564 Wayne : Young

Copying Dictionaries and Lists
 The built-in
list function
will copy a list
 The dictionary
has a
method
called copy
>>> l1 = [1] >>> d = {1 : 10}
>>> l2 = list(l1) >>> d2 = d.copy()
>>> l1[0] = 22 >>> d[1] = 22
>>> l1 >>> d
[22] {1: 22}
>>> l2 >>> d2
[1] {1: 10}

Data Type Summary
Integers: 2323, 3234L
Floating Point: 32.3, 3.1E2
Complex: 3 + 2j, 1j
Lists: l = [ 1,2,3]
Tuples: t = (1,2,3)
Dictionaries: d = {‘hello’ :
‘there’, 2 : 15}
 Lists, Tuples, and Dictionaries can store
any type (including other lists, tuples,
and dictionaries!)
 Only lists and dictionaries are mutable
 All variables are references

Function Basics
def max(x,y) :
if x < y :
return x
else :
retur
n y
>>> import functionbasics
>>> max(3,5)
5
>>>
max('hello',
'there')
'there'
>>> max(3, 'hello')
'hello'
functionbasics.py

Functions are objects
 Can be assigned to a variable
 Can be passed as a parameter
 Can be returned from a function
• Functions are treated like any other
variable in Python, the def statement
simply assigns a function to a variable

Function names are like any
variable
 Functions are
objects
 The same
reference rules
hold for them as
for other
objects
>>> x = 10
>>> x
10
>>>
def x
() :
...
print
'hello'
>>> x
<funct
ion x
at
0x619
f0>

Functions as Parameters
def foo(f, a) :
return f(a)
def bar(x) :
return x * x
>>> from funcasparam import *
>>> foo(bar, 3)
9

Note that the function foo takes two
parameters and applies the first as
a function with the second as its
parameter
funcasparam.py

Higher-Order Functions

map(func,seq) – for all i, applies func(seq[i]) and returns the
corresponding sequence of the calculated results.
def double(x):
return 2*x
>>> from highorder import *
>>> lst = range(10)
>>> lst
[0,1,2,3,4,5,6,7,8,9]
>>> map(double,lst)
[0,2,4,6,8,10,12,14,16,18]
highorder.p
y


filter(boolfunc,seq) – returns a sequence containing all those
items in seq for which boolfunc is True.
def even(x):
return ((x%2 ==
0)
>>> lst = range(10)
>>> lst
[0,1,2,3,4,5,6,7,8,9]
>>> filter(even,lst)
[0,2,4,6,8]
highorder.p
y


reduce(func,seq) – applies func to the items of seq, from left
to right, two-at-time, to reduce the seq to a single value.
def plus(x,y):
return (x + y)


>>> lst = [‘h’,’e’,’l’,’l’,’o’]

>>> reduce(plus,lst)

‘hello’
highorder.p
y

Functions Inside Functions
 Since they are like any other object, you
can have functions inside functions
def foo (x,y) :
def bar (z) :
return z * 2
return bar(x) + y
>>> from funcinfunc import *
>>> foo(2,3)
7
funcinfunc.py

Functions Returning Functions
def foo (x) :
def bar(y) :
return x + y
return bar
# main
f =
foo(3)
print f
print f(2)
% python funcreturnfunc.py
<function bar at 0x612b0>
5
funcreturnfunc.py

Parameters: Defaults
 Parameters can be
assigned default
values
 They are
overridden if a
parameter is given
for them
 The type of the
default doesn’t
limit the type of a
parameter

>>> def foo(x = 3) :

... print x

...

>>> foo()
3

>>> foo(10)

10

>>> foo('hello')

hello

Parameters: Named
 Call by name
 Any positional
arguments
must come
before named
ones in a call
>>> def foo (a,b,c) :
... print a, b, c
...
>>> foo(c = 10, a = 2, b =
14) 2 14 10
>>> foo(3, c = 2, b =
19) 3 19 2

Anonymous Functions
 A lambda
expression
returns a
function object
 The body can
only be a simple
expression, not
complex
statements
>>> f = lambda x,y : x + y
>>> f(2,3)
5
>>> lst =
['one',
lambda x :
x * x, 3]
>>> lst[1](4)
16

Modules
 The highest level structure of Python
 Each file with the py suffix is a module
 Each module has its own namespace

Modules: Imports
import mymodule Brings all elements
of mymodule in, but
must refer to as
mymodule.<elem>
from mymodule import x Imports x from
mymodule right into
this namespace
from mymodule import * Imports all elements
of mymodule into
this namespace

 string: A sequence of text characters in a program.

Strings start and end with quotation mark " or apostrophe '
characters.

Examples:
"hello"
"This is a string"
"This, too, is a string. It can be very long!"
 A string may not span across multiple lines or contain a " character.
"This is not
a legal String."
"This is not a "legal" String either."
 A string can represent characters by preceding them with a backslash.
68

t

n

"


tab character
new line character
quotation mark character
backslash character

Example: "HellottherenHow are
you?"
Strings

Indexes
69
 Characters in a string are numbered with indexes starting at
0:
 Example:
name = "P. Diddy"
 Accessing an individual character of a string:
variableName [ index ]
 Example:
print name, "starts with", name[0]
Output:
P. Diddy starts with P
index 0 1 2 3 4 5 6 7
character P . D i d d y

String properties
70
 len(string) - number of characters in a
string (including spaces)
- lowercase version of a string
- uppercase version of a string
 str.lower(string)
 str.upper(string)
 Example:
name = "Martin Douglas Stepp"
length = len(name)
big_name = str.upper(name)
print big_name, "has",
length, "characters"
Output:
MARTIN DOUGLAS STEPP has 20
characters

 raw_input : Reads a string of text from user input.
 Example:
name = raw_input("Howdy, pardner. What's yer name? ")
print name, "... what a silly name!"
Output:
Howdy, pardner. What's yer name? Paris Hilton
Paris Hilton ... what a silly name!
71
raw_input

Text processing
72
 text processing: Examining, editing, formatting text.
 often uses loops that examine the characters of a string one by one
 A for loop can examine each character in a string in sequence.
 Example:
for c in "booyah":
print c
Output:
b
o
o
y
a
h

Strings and numbers
73
 ord(text) - converts a string into a number.
 Example: ord("a") is 97, ord("b") is 98, ...
 Characters map to numbers using standardized mappings such as
ASCII and Unicode.
 chr(number) - converts a number into a string.
 Example: chr(99) is "c"
 Exercise: Write a program that performs a rotation cypher.
 e.g. "Attack" when rotated by 1 becomes "buubdl"

File processing
74
 Many programs handle data, which often comes from files.
 Reading the entire contents of a file:
variableName = open("filename").read()
Example:
file_text = open("bankaccount.txt").read()

Line-by-line processing
75
 Reading a file line-by-line:
for line in open("filename").readlines():
statements
Example:
count = 0
for line in open("bankaccount.txt").readlines():
count = count + 1
print "The file contains", count, "lines."
 Exercise: Write a program to process a file of DNA text, such as:
ATGCAATTGCTCGATTAG
 Count the percent of C+G present in the DNA.

Defining a Class
 Python program may own many objects
 An object is an item with fields supported by a set of method functions.

An object can have several fields (or called attribute variables) describing
such an object

These fields can be accessed or modified by object methods
 A class defines what objects look like and what functions can operate
on these object.
 Declaring a class:
class name:
statements
 Example:
class UCSBstudent:
age = 21
schoolname=‘UCSB’

Fields
name = value
 Example:
class Point:
x = 0
y = 0
# main
p1 = Point()
p1.x = 2
p1.y = -5
 can be declared directly inside class (as shown here)
or in constructors (more common)
 Python does not really have encapsulation or private
fields

relies on caller to "be nice" and not mess with
objects' contents
point.py
1
2
3
class Point:
x = 0
y = 0

Using a Class
import class
 client programs must import the classes they use
point_main.py
1 from Point import *
2
3 # main
4 p1 = Point()
5 p1.x = 7
6 p1.y = -3
7
8 p2 = Point()
9 p2.x = 7
10 p2.y = 1
# Python objects are dynamic (can add fields any time!)
p1.name = "Tyler Durden"

Object Methods
def name(self, parameter, ..., parameter):
statements
 self must be the first parameter to any object
method

represents the "implicit parameter" (this in Java)
 must access the object's fields through the self
reference
class Point:
def move(self, dx, dy):
self.x += dx
self.y += dy

Exercise Answer
point.py
1 from math import *
class Point:
x = 0
y = 0
def set_location(self, x, y):
self.x = x
self.y = y
def distance_from_origin(self):
return sqrt(self.x * self.x +
self.y * self.y)
def distance(self, other):
dx = self.x - other.x
dy = self.y - other.y
return sqrt(dx * dx + dy *
dy)
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

Calling Methods
 A client can call the methods of an object in two ways:
 (the value of self can be an implicit or explicit
parameter)
1) object.method(parameters)
or
2)
Class.method(object, parameters)
 Example:
p = Point(3, -4)
p.move(1, 5)
Point.move(p, 1, 5)

Constructors
def init (self, parameter, ..., parameter):
statements
 a constructor is a special method with the name
init
 Example:
class Point:
def __init (self, x, y):
self.x = x
self.y = y
...

How would we make it possible to
construct a
Point() with no parameters to get (0,
0)?

toString and str
def str (self):
return string
 equivalent to Java's
toString
(converts object to
a string)
 invoked
automatically when
str or print is
called
Exercise: Write a str method for Point objects that returns
strings like "(3, -14)"
def str (self):
return "(" + str(self.x) + ", " + str(self.y) + ")"

Complete Point Class
point.py
1 from math import *
2
3 class Point:
4 def init (self, x, y):
5 self.x = x
6 self.y = y
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
def distance_from_origin(self):
return sqrt(self.x * self.x + self.y * self.y)
def distance(self, other):
dx = self.x - other.x
dy = self.y - other.y
return sqrt(dx * dx + dy *
dy)
def move(self, dx, dy):
self.x += dx
self.y += dy
def str (self):
return "(" +
str(self.x) + ", "

Operator Overloading
 operator overloading: You can define functions so that
Python's built-in operators can be used with your class.

See also: http://docs.python.org/ref/customization.html
Operator Class Method
- neg (self, other)
+ pos (self, other)
* mul (self, other)
/ truediv (self, other)

Unary Operators
- neg (self)
+ pos (self)
Operator Class Method
== eq (self, other)
!= ne (self, other)
< lt (self, other)
> gt (self, other)
<= le (self, other)
>= ge (self, other)

Generating Exceptions
raise ExceptionType("message")
 useful when the client uses your object improperly

types: ArithmeticError, AssertionError, IndexError,
NameError, SyntaxError, TypeError, ValueError
 Example:
class BankAccount:
...
def deposit(self, amount):
if amount < 0:
raise ValueError("negative amount")
...

Inheritance
class name(superclass):
statements
 Example:
class Point3D(Point):
z = 0
...
# Point3D extends Point
 Python also supports multiple inheritance
class name(superclass, ..., superclass):
statements
(if > 1 superclass has the same field/method, conflicts are resolved
in left-to-right order)

Calling Superclass Methods
 methods:
 constructors:
class.method(object, parameters)
class. init (parameters)
class Point3D(Point):
z = 0
def __init (self, x, y, z):
Point. init (self, x, y)
self.z = z
def move(self, dx, dy, dz):
Point.move(self, dx, dy)
self.z += dz

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