CS计算机代考程序代写 python Quadratic equations

Quadratic equations
Eric Martin, CSE, UNSW

COMP9021 Principles of Programming

[1]: from math import sqrt

A quadratic equation is determined by three real numbers a, b and c with a 6= 0. Depending on
whether ∆ = −b

2a
is strictly negative, equal to 0 or strictly positive, the equation has no real root,

a single real root or two distinct real roots, respectively. We want to be able to:

• create a quadratic equation with specific values for a, b and c;
• modify a given quadratic equation by changing the value of any of a, b and c, possibly two of

them, possibly all of them;
• nicely display a given quadratic equation;
• automatically compute the root or roots of a given quadratic equation, if a unique root or two

distinct roots exist, respectively, when the equation is created, and whenever the equation is
modified.

We will go through 5 successive designs via gradual modifications, the first design being satisfactory
from a functional point of view, the last one satisfactory from an object oriented point of view.
Going through this exercise will provide us with a deep understanding of object oriented design
and syntax.

To create a quadratic equation, it is sensible to define a function that provides the default values
of 1 for a and 0 for b and c (so making x2 = 1 the default quadratic equation). Some or all of those
default values can then be changed using keyword arguments, in any order:

[2]: def f(a=1, b=0, c=0):
print(a, b, c)

f()
f(a=2)
f(c=4)
f(a=2, c=4)
f(c=4, b=3)
f(b=3, a=2, c=4)

1 0 0
2 0 0
1 0 4
2 0 4
1 3 4
2 3 4

1

The user can also provide positional arguments, to overwrite the default value of the first argument,
or to overwrite the default values of the first and second arguments, or to overwrite the values of
the first, second and third arguments:

[3]: f(2)
f(2, 3)
f(2, 3, 4)

2 0 0
2 3 0
2 3 4

In particular, when the user provides three positional arguments, we expect him to know that they
are provided in the order a, b and c. Even if the function is well documented, it is reasonable not
to have such an expectation, and force the user to explictly name each value. The * symbol can be
used on its own for that purpose. With the version of f() that follows, only the values of a and b
can be overwritten with positional arguments:

[4]: def f(a=1, b=0, *, c=0):
print(a, b, c)

f(2)
f(2, 3)
f(2, 3, c=4)
f(2, c=4, b=3)
f(b=3, a=2, c=4)
f(2, 3, 4)

2 0 0
2 3 0
2 3 4
2 3 4
2 3 4


↪→—————————————————————————

TypeError Traceback (most recent call␣
↪→last)

in
7 f(2, c=4, b=3)
8 f(b=3, a=2, c=4)

—-> 9 f(2, 3, 4)

TypeError: f() takes from 0 to 2 positional arguments but 3 were given

2

With the version of f() that follows, only the value of a can be overwritten with a positional
argument:

[5]: def f(a=1, *, b=0, c=0):
print(a, b, c)

f(2)
f(2, b=3)
f(2, c=4, b=3)
f(b=3, a=2, c=4)
f(2, 3)

2 0 0
2 3 0
2 3 4
2 3 4


↪→—————————————————————————

TypeError Traceback (most recent call␣
↪→last)

in
6 f(2, c=4, b=3)
7 f(b=3, a=2, c=4)

—-> 8 f(2, 3)

TypeError: f() takes from 0 to 1 positional arguments but 2 were given

With the version of f() that follows, no value can be overwritten with a positional argument:

[6]: def f(*, a=1, b=0, c=0):
print(a, b, c)

f(b=3)
f(c=4, b=3)
f(b=3, a=2, c=4)
f(2)

1 3 0
1 3 4
2 3 4


↪→—————————————————————————

3

TypeError Traceback (most recent call␣
↪→last)

in
5 f(c=4, b=3)
6 f(b=3, a=2, c=4)

—-> 7 f(2)

TypeError: f() takes 0 positional arguments but 1 was given

The function initialise() below is meant to create a quadratic equation represented as a dic-
tionary with 5 keys, to keep track of the values of a, b and c, but also of the values of the roots,
computed by the function compute_roots() as soon as the former are known. We might think
that create() would be a better name; we will soon understand why we opted for initialise():

[7]: def initialise(*, a=1, b=0, c=0):
if a == 0:

print(‘a cannot be equal to 0.’)
return

equation = {‘a’: a, ‘b’: b, ‘c’: c, ‘root_1’: None, ‘root_2’: None}
compute_roots(equation)
return equation

def compute_roots(equation):
a, b, c = equation[‘a’], equation[‘b’], equation[‘c’]
delta = b ** 2 – 4 * a * c
if delta < 0: equation['root_1'] = equation['root_2'] = None elif delta == 0: equation['root_1'] = -b / (2 * a) equation['root_2'] = None else: sqrt_delta = sqrt(delta) equation['root_1'] = (-b - sqrt_delta) / (2 * a) equation['root_2'] = (-b + sqrt_delta) / (2 * a) [8]: initialise(a=0, b=1) a cannot be equal to 0. [9]: eq1 = initialise() eq1['a'] eq1['b'] eq1['c'] 4 eq1['root_1'] eq1['root_2'] # None [9]: 1 [9]: 0 [9]: 0 [9]: 0.0 [10]: eq2 = initialise(b=4) eq2['a'] eq2['b'] eq2['c'] eq2['root_1'] eq2['root_2'] [10]: 1 [10]: 4 [10]: 0 [10]: -4.0 [10]: 0.0 The function that follows allows one to change any number of parameters, that again have to be named even in case the change affects all of them; compute_roots() recomputes the roots as soon as the possibly new values of a, b and c are known: [11]: def update(equation, *, a=None, b=None, c=None): if a == 0: print('a cannot be equal to 0.') return if a is not None: equation['a'] = a if b is not None: equation['b'] = b if c is not None: equation['c'] = c compute_roots(equation) [12]: eq3 = initialise(a=1, b=3, c=2) eq3['a'] eq3['b'] 5 eq3['c'] eq3['root_1'] eq3['root_2'] print() update(eq3, a=0) print() update(eq3, b=-1) eq3['a'] eq3['b'] eq3['c'] eq3['root_1'] # None eq3['root_2'] # None print() update(eq3, c=0.3, a=0.5) eq3['a'] eq3['b'] eq3['c'] eq3['root_1'] eq3['root_2'] [12]: 1 [12]: 3 [12]: 2 [12]: -2.0 [12]: -1.0 a cannot be equal to 0. [12]: 1 [12]: -1 [12]: 2 [12]: 0.5 6 [12]: -1 [12]: 0.3 [12]: 0.3675444679663241 [12]: 1.632455532033676 To nicely display an equation, we have to carefully deal with the cases where where a is equal to 1 or -1, b is equal to 1 or -1 or otherwise strictly positive or strictly negative, and c is strictly positive or strictly negative: [13]: def display(equation): a, b, c = equation['a'], equation['b'], equation['c'] if a == 1: displayed_equation = 'x^2' elif a == -1: displayed_equation = '-x^2' else: displayed_equation = f'{a}x^2' if b == 1: displayed_equation += ' + x' elif b == -1: displayed_equation -= ' - x' elif b > 0:

displayed_equation += f’ + {b}x’
elif b < 0: displayed_equation += f'- {-b}x' if c > 0:

displayed_equation += f’ + {c}’
elif c < 0: displayed_equation += f' - {-c}' print(displayed_equation, 0, sep=' = ') [14]: display(initialise()) display(initialise(c=-5, a=2)) display(initialise(b=1, a=-1, c=-1)) x^2 = 0 2x^2 - 5 = 0 -x^2 + x - 1 = 0 That ends the first design. For the second design, we package the functionality associ- ated with quadratic equations; a dictionary offers a simple way to do so. The dictionary QuadraticEquationDict below captures the view that a quadratic equation is an entity that can be created (initialised), displayed, modified (updated) and has roots that can be computed. All of the dictionary’s values are functions; they have been previously defined, but two of them are given a slightly different implementation, reflecting the fact that the four functions are now part of the 7 QuadraticEquationDict “package”: [15]: def initialise_variant_1(*, a=1, b=0, c=0): if a == 0: print('a cannot be equal to 0.') return equation = {'a': a, 'b': b, 'c': c, 'root_1': None, 'root_2': None} QuadraticEquationDict['compute_roots'](equation) return equation def update_variant_1(equation, *, a=None, b=None, c=None): if a == 0: print('a cannot be equal to 0.') return if a is not None: equation['a'] = a if b is not None: equation['b'] = b if c is not None: equation['c'] = c QuadraticEquationDict['compute_roots'](equation) QuadraticEquationDict = {'initialise': initialise_variant_1, 'display': display, 'compute_roots': compute_roots, 'update': update_variant_1 } The code that tests all four functions is similarly changed and relative to the QuadraticEquationDict “package”: [16]: QuadraticEquationDict['initialise'](a=0, b=1) a cannot be equal to 0. [17]: eq1 = QuadraticEquationDict['initialise']() eq1['a'] eq1['b'] eq1['c'] eq1['root_1'] eq1['root_2'] # None [17]: 1 [17]: 0 [17]: 0 8 [17]: 0.0 [18]: eq2 = QuadraticEquationDict['initialise'](b=4) eq2['a'] eq2['b'] eq2['c'] eq2['root_1'] eq2['root_2'] [18]: 1 [18]: 4 [18]: 0 [18]: -4.0 [18]: 0.0 [19]: eq3 = QuadraticEquationDict['initialise'](a=1, b=3, c=2) eq3['a'] eq3['b'] eq3['c'] eq3['root_1'] eq3['root_2'] print() QuadraticEquationDict['update'](eq3, a=0) print() update(eq3, b=-1) eq3['a'] eq3['b'] eq3['c'] eq3['root_1'] # None eq3['root_2'] # None print() QuadraticEquationDict['update'](eq3, c=0.3, a=0.5) eq3['a'] eq3['b'] eq3['c'] eq3['root_1'] eq3['root_2'] 9 [19]: 1 [19]: 3 [19]: 2 [19]: -2.0 [19]: -1.0 a cannot be equal to 0. [19]: 1 [19]: -1 [19]: 2 [19]: 0.5 [19]: -1 [19]: 0.3 [19]: 0.3675444679663241 [19]: 1.632455532033676 [20]: QuadraticEquationDict['display'](QuadraticEquationDict['initialise']()) QuadraticEquationDict['display'](QuadraticEquationDict['initialise'](c=-5, a=2) ) QuadraticEquationDict['display'](QuadraticEquationDict['initialise'](b=1, a=-1, c=-1 ) ) x^2 = 0 2x^2 - 5 = 0 -x^2 + x - 1 = 0 With the third design, we meet the object oriented paradigm. All four functions are implemented slightly differently: [21]: def initialise_variant_2(equation, *, a=1, b=0, c=0): if a == 0: 10 print('a cannot be equal to 0.') return equation.a = a equation.b = b equation.c = c QuadraticEquationType.compute_roots(equation) def display_variant_1(equation): a, b, c = equation.a, equation.b, equation.c if a == 1: displayed_equation = 'x^2' elif a == -1: displayed_equation = '-x^2' else: displayed_equation = f'{a}x^2' if b == 1: displayed_equation += ' + x' elif b == -1: displayed_equation -= ' - x' elif b > 0:

displayed_equation += f’ + {b}x’
elif b < 0: displayed_equation += f'- {-b}x' if c > 0:

displayed_equation += f’ + {c}’
elif c < 0: displayed_equation += f' - {-c}' print(displayed_equation, 0, sep=' = ') def compute_roots_variant_2(equation): a, b, c = equation.a, equation.b, equation.c delta = b ** 2 - 4 * a * c if delta < 0: equation.root_1 = equation.root_2 = None elif delta == 0: equation.root_1 = -b / (2 * a) equation.root_2 = None else: sqrt_delta = sqrt(delta) equation.root_1 = (-b - sqrt_delta) / (2 * a) equation.root_2 = (-b + sqrt_delta) / (2 * a) def update_variant_2(equation, *, a=None, b=None, c=None): if a == 0: print('a cannot be equal to 0.') return if a is not None: 11 equation.a = a if b is not None: equation.b = b if c is not None: equation.c = c QuadraticEquationType.compute_roots(equation) QuadraticEquationType = type('QuadraticEquationType', (), {'__init__' : initialise_variant_2, 'display': display_variant_1, 'compute_roots': compute_roots_variant_2, 'update': update_variant_2 } ) QuadraticEquationType seems to embed QuadraticEquationDict, with 'initialise' changed to '__init__'; 'initialise' was an arbitrary name, whereas '__init__' is imposed. With 'initialise', we chose a name close enough to '__init__' so as to reflect the similarity of the implementations. QuadraticEquationType is a type, with the name 'QuadraticEquationType', above provided as first argument to type(); another use of type() below shows that QuadraticEquationType is indeed a type: [22]: type(QuadraticEquationType) QuadraticEquationType.__name__ [22]: type [22]: 'QuadraticEquationType' The second argument to type() is an empty tuple, making QuadraticEquationType a direct subtype of object, the mother of all types: [23]: QuadraticEquationType.__base__ [23]: object The third argument to type() is a dictionary of attributes, that are all members of __dict__, which itself is another attribute of QuadraticEquationType: [24]: QuadraticEquationType.__dict__ [24]: mappingproxy({'__init__': ,

‘display’: ,
‘compute_roots’: ,
‘update’: ,

12

‘__module__’: ‘__main__’,
‘__dict__’: ,
‘__weakref__’: ,
‘__doc__’: None})

object also has a __dict__ attribute:

[25]: object.__dict__

[25]: mappingproxy({‘__repr__’: ,
‘__hash__’: ,
‘__str__’: ,
‘__getattribute__’: ,
‘__setattr__’: ,
‘__delattr__’: ,
‘__lt__’: ,
‘__le__’: ,
‘__eq__’: ,
‘__ne__’: ,
‘__gt__’: ,
‘__ge__’: ,
‘__init__’: ,
‘__new__’: ,
‘__reduce_ex__’: ,
‘__reduce__’: ,
‘__subclasshook__’: ,
‘__init_subclass__’: ,
‘__format__’: ,
‘__sizeof__’: ,
‘__dir__’: ,
‘__class__’: ,
‘__doc__’: ‘The base class of the class hierarchy.\n\nWhen called,

it accepts no arguments and returns a new featureless\ninstance that has no
instance attributes and cannot be given any.\n’})

The dir() function returns a list of attributes of its argument; with object as argument, that list
consists of nothing but the attributes in object.__dict__:

[26]: dir(object)

set(object.__dict__) == set(dir(object))

13

[26]: [‘__class__’,
‘__delattr__’,
‘__dir__’,
‘__doc__’,
‘__eq__’,
‘__format__’,
‘__ge__’,
‘__getattribute__’,
‘__gt__’,
‘__hash__’,
‘__init__’,
‘__init_subclass__’,
‘__le__’,
‘__lt__’,
‘__ne__’,
‘__new__’,
‘__reduce__’,
‘__reduce_ex__’,
‘__repr__’,
‘__setattr__’,
‘__sizeof__’,
‘__str__’,
‘__subclasshook__’]

[26]: True

With QuadraticEquationType as argument, dir() returns a list of attributes that consists pre-
cisely of the attributes in object.__dict__ (or equivalently, the attributes in dir(object)), all
inherited by QuadraticEquationType, and the attributes in QuadraticEquationType.__dict__:

[27]: dir(QuadraticEquationType)

set(dir(QuadraticEquationType)) == set(object.__dict__)\
| set(QuadraticEquationType.__dict__)

[27]: [‘__class__’,
‘__delattr__’,
‘__dict__’,
‘__dir__’,
‘__doc__’,
‘__eq__’,
‘__format__’,
‘__ge__’,
‘__getattribute__’,
‘__gt__’,
‘__hash__’,
‘__init__’,

14

‘__init_subclass__’,
‘__le__’,
‘__lt__’,
‘__module__’,
‘__ne__’,
‘__new__’,
‘__reduce__’,
‘__reduce_ex__’,
‘__repr__’,
‘__setattr__’,
‘__sizeof__’,
‘__str__’,
‘__subclasshook__’,
‘__weakref__’,
‘compute_roots’,
‘display’,
‘update’]

[27]: True

Two attributes belong to both object.__dict__ and QuadraticEquationType.__dict__; they
are attributes of object inherited by QuadraticEquationType, but also overwritten by
QuadraticEquationType:

[28]: set(dir(object)) & set(QuadraticEquationType.__dict__)
object.__doc__
QuadraticEquationType.__doc__ # None
object.__init__
QuadraticEquationType.__init__

[28]: {‘__doc__’, ‘__init__’}

[28]: ‘The base class of the class hierarchy.\n\nWhen called, it accepts no arguments
and returns a new featureless\ninstance that has no instance attributes and
cannot be given any.\n’

[28]:

[28]:

With the syntax QuadraticEquationType.compute_roots, we are trying to access the
‘compute_roots’ attribute of QuadraticEquationType, which is equivalent to retrieving the value
of the ‘compute_roots’ key of the ‘__dict__’ attribute of QuadraticEquationType (this raises
the question of how ‘__dict__’ itself is retrieved…):

[29]: QuadraticEquationType.compute_roots
QuadraticEquationType.__dict__[‘compute_roots’]

15

[29]:

[29]:

The key difference between initialise_variant_1() and initialise_variant_2() is that the
latter has an extra argument, equation, and returns None, whereas the former returns a dictionary
that is the counterpart to equation. What value is assigned to equation; what provides it? One
of QuadraticEquationType’s attributes is ‘__new__’, which we know is inherited from and not
overwritten by object:

[30]: QuadraticEquationType.__new__
QuadraticEquationType.__new__ is object.__new__

[30]:

[30]: True

When called with QuadraticEquationType as argument, the function that
QuadraticEquationType.__new__, or equivalently, object.__new__, evaluates to, returns
an object (not to be confused with object) of type QuadraticEquationType:

[31]: QuadraticEquationType.__new__(QuadraticEquationType)
type(QuadraticEquationType.__new__(QuadraticEquationType))

[31]: <__main__.QuadraticEquationType at 0x1106627f0>

[31]: __main__.QuadraticEquationType

The object returned by QuadraticEquationType.__new__(QuadraticEquationType)
can then be passed as an argument to initialise_variant_2(), the function that
QuadraticEquationType.__init__ evaluates to:

[32]: eq = QuadraticEquationType.__new__(QuadraticEquationType)

QuadraticEquationType.__init__(eq, a=0, b=1)

a cannot be equal to 0.

The object returned by QuadraticEquationType.__new__(QuadraticEquationType) has a
__dict__ attribute, that happens to be empty; the dir() function returns the same list of at-
tributes when it is given either the object or QuadraticEquationType as argument, reflecting the
fact that the object inherits all those attributes from QuadraticEquationType:

[33]: eq1 = QuadraticEquationType.__new__(QuadraticEquationType)

eq1.__dict__
dir(eq1) == dir(QuadraticEquationType)

[33]: {}

16

[33]: True

A call to QuadraticEquationType.__init__() provides eq1 with new attributes, which are now
in eq1.__dict__ and also part of dir(eq_1). With the syntax eq1.a, eq1.b, eq1.c, eq1.root_1
and eq1.root_2, we are trying to access the ‘a’, ‘b’, ‘c’, ‘root_1’ and ‘root_2’ attributes
of eq1, which is equivalent to retrieving the values of the ‘a’, ‘b’, ‘c’, ‘root_1’ and ‘root_2’
keys of the ‘__dict__’ attribute of eq1 (this again raises the question of how ‘__dict__’ itself is
retrieved):

[34]: QuadraticEquationType.__init__(eq1)

eq1.__dict__
set(dir(eq1)) – set(dir(QuadraticEquationType))
eq1.__dict__[‘a’]
eq1.a
eq1.__dict__[‘b’]
eq1.b
eq1.__dict__[‘c’]
eq1.c
eq1.__dict__[‘root_1’]
eq1.root_1
eq1.__dict__[‘root_2’] # None
eq1.root_2 # None

[34]: {‘a’: 1, ‘b’: 0, ‘c’: 0, ‘root_1’: 0.0, ‘root_2’: None}

[34]: {‘a’, ‘b’, ‘c’, ‘root_1’, ‘root_2’}

[34]: 1

[34]: 1

[34]: 0

[34]: 0

[34]: 0

[34]: 0

[34]: 0.0

[34]: 0.0

We now understand what value initialise_variant_2()’s first argument, equation, receives, and
what provides it, but in practice, we do not explicitly call first QuadraticEquationType.__new__()
and then QuadraticEquationType.__init__(); instead, we use the following syntax, that in one
sweep move, both creates an object and initialises it:

17

[35]: eq2 = QuadraticEquationType(b=4)

eq2.a
eq2.b
eq2.c
eq2.root_1
eq2.root_2

[35]: 1

[35]: 4

[35]: 0

[35]: -4.0

[35]: 0.0

compute_roots, update and display are attributes of both QuadraticEquationType and of ob-
jects returned by QuadraticEquationType.__new__(QuadraticEquationType), but they evaluate
to different entities:

[36]: QuadraticEquationType.compute_roots
QuadraticEquationType.__new__(QuadraticEquationType).compute_roots

print()

QuadraticEquationType.update
QuadraticEquationType.__new__(QuadraticEquationType).update

print()

QuadraticEquationType.display
QuadraticEquationType.__new__(QuadraticEquationType).display
eq = QuadraticEquationType.__new__(QuadraticEquationType)

[36]:

[36]: >

[36]:

[36]: >

18

[36]:

[36]: >

These bound methods essentially allow one to call compute_roots_variant_2(),
update_variant_2() and display_variant_1() using ‘compute_roots’, ‘update’ and
‘display’ as object attributes rather than QuadraticEquationType attributes, providing the
desired value as first argument. More precisely, one can think of the bound method M of an object
o of type QuadraticEquationType as a pair:

• the first member of the pair is a QuadraticEquationType function f , meant to take an object
of type QuadraticEquationType as first (and possibly unique) argument;

• the second member of the pair is o, meant to be that first argument.

Having both f and o in hand together with any other arguments for f , if any, f
can then be called with o provided as first argument. This can done either as
QuadraticEquationType.variable_referring_to_f(variable_referring_to_o, possibly
followed by extra arguments), or as variable_referring_to_o.variable_referring_to_f(possibly,
extra arguments). This alternative syntax is more compact and the one used in practice:

[37]: eq3 = QuadraticEquationType(a=1, b=3, c=2)
eq3.a
eq3.b
eq3.c
eq3.root_1
eq3.root_2

print()
# update() called as a QuadraticEquationType function
QuadraticEquationType.update(eq3, a=0)
print()

# update() called as a QuadraticEquationType function
QuadraticEquationType.update(eq3, b=-1)
eq3.a
eq3.b
eq3.c
eq3.root_1 # None
eq3.root_2 # None

print()

# update() called as an eq3 bound method
eq3.update(c=0.3, a=0.5)
eq3.a
eq3.b
eq3.c

19

eq3.root_1
eq3.root_2

[37]: 1

[37]: 3

[37]: 2

[37]: -2.0

[37]: -1.0

a cannot be equal to 0.

[37]: 1

[37]: -1

[37]: 2

[37]: 0.5

[37]: -1

[37]: 0.3

[37]: 0.3675444679663241

[37]: 1.632455532033676

[38]: # display() called as a QuadraticEquationType function
QuadraticEquationType.display(QuadraticEquationType())
# display() called as a QuadraticEquationType function
QuadraticEquationType.display(QuadraticEquationType(c=-5, a=2))
# display() called as a bound method of the object
# returned by QuadraticEquationType()
QuadraticEquationType(c=-5, a=2).display()

x^2 = 0
2x^2 – 5 = 0
2x^2 – 5 = 0

The fourth design is essentially nothing but a syntactic variant on the third design, with class
followed by the first argument to type() (that we change to QuadraticEquationClass), and with

20

the functions that are the values of the dictionary provided as third argument to type() now in the
body of the class statement. Also, display is renamed __str__, and whereas the former returns
None and executes print() statements, the latter returns a string: when print() is given an object
as argument, it calls the object’s __str__() bound method and displays the returned string:

[39]: class QuadraticEquationClass:
def __init__(equation, *, a=1, b=0, c=0):

if a == 0:
print(‘a cannot be equal to 0.’)
return

equation.a = a
equation.b = b
equation.c = c
equation.compute_roots()

def __str__(equation):
if equation.a == 1:

displayed_equation = ‘x^2’
elif equation.a == -1:

displayed_equation = ‘-x^2′
else:

displayed_equation = f'{equation.a}x^2’
if equation.b == 1:

displayed_equation += ‘ + x’
elif equation.b == -1:

displayed_equation -= ‘ – x’
elif equation.b > 0:

displayed_equation += f’ + {equation.b}x’
elif equation.b < 0: displayed_equation += f'- {-equation.b}x' if equation.c > 0:

displayed_equation += f’ + {equation.c}’
elif equation.c < 0: displayed_equation += f' - {-equation.c}' return f'{displayed_equation} = 0' def compute_roots(equation): delta = equation.b ** 2 - 4 * equation.a * equation.c if delta < 0: equation.root_1 = equation.root_2 = None elif delta == 0: equation.root_1 = -equation.b / (2 * equation.a) equation.root_2 = None else: sqrt_delta = sqrt(delta) equation.root_1 = (-equation.b - sqrt_delta) / (2 * equation.a) equation.root_2 = (-equation.b + sqrt_delta) / (2 * equation.a) 21 def update(equation, *, a=None, b=None, c=None): if a == 0: print('a cannot be equal to 0.') return if a is not None: equation.a = a if b is not None: equation.b = b if c is not None: equation.c = c equation.compute_roots() The syntax for object creation and initialisation and for calls to compute_roots() and update() is the same as with the third design: [40]: QuadraticEquationClass(a=0, b=1) print() eq1 = QuadraticEquationClass.__new__(QuadraticEquationClass) QuadraticEquationClass.__init__(eq1) eq1.a eq1.b eq1.c eq1.root_1 eq1.root_2 print() eq2 = QuadraticEquationClass.__new__(QuadraticEquationClass) eq2.__init__(b=4) eq2.a eq2.b eq2.c eq2.root_1 eq2.root_2 print() eq3 = QuadraticEquationClass(a=1, b=3, c=2) eq3.a eq3.b eq3.c eq3.root_1 eq3.root_2 22 print() eq3.update(a=0) print() QuadraticEquationClass.update(eq3, b=-1) eq3.a eq3.b eq3.c eq3.root_1 eq3.root_2 print() eq3.update(c=0.3, a=0.5) eq3.a eq3.b eq3.c eq3.root_1 eq3.root_2 a cannot be equal to 0. [40]: <__main__.QuadraticEquationClass at 0x10e594370>

[40]: 1

[40]: 0

[40]: 0

[40]: 0.0

[40]: 1

[40]: 4

[40]: 0

[40]: -4.0

[40]: 0.0

23

[40]: 1

[40]: 3

[40]: 2

[40]: -2.0

[40]: -1.0

a cannot be equal to 0.

[40]: 1

[40]: -1

[40]: 2

[40]: 0.5

[40]: -1

[40]: 0.3

[40]: 0.3675444679663241

[40]: 1.632455532033676

As previously mentioned, we now display quadratic equations not with calls to display(), but
with calls directly to print() that behind the scene, calls __str()__:

[41]: print(QuadraticEquationClass())
print(QuadraticEquationClass(c=-5, a=2))
print(QuadraticEquationClass(b=1, a=-1, c=-1))

x^2 = 0
2x^2 – 5 = 0
-x^2 + x – 1 = 0

The fifth design “cleans” the fourth design, changing the first argument of the bound methods
to self as always done in practice. Another special bound method, __repr()__, is overwritten:
similarly to __str()__, it returns a string, and it is called when the executed statement is just the
object name. It has a default implementation, but the output is not particularly insightful:

[42]: eq3

24

[42]: <__main__.QuadraticEquationClass at 0x10e594160>

It is standard practice to let __repr()__ output the very statement that creates the object, so for
eq3, QuadraticEquationClass(a=1, b=3, c=2), as we will see below.

Finally, note that with the fourth design, QuadraticEquationClass(a=0, b=1) prints out an error
message but still returns an ill defined object of type QuadraticEquationClass. It is preferable
to raise an error instead. We define a specific exception by defining a class that derives from
Exception rather than from object:

[43]: class QuadraticEquationError(Exception):
pass

QuadraticEquationError.__base__
raise QuadraticEquationError(‘a cannot be equal to 0’)

[43]: Exception


↪→—————————————————————————

QuadraticEquationError Traceback (most recent call␣
↪→last)

in
3
4 QuadraticEquationError.__base__

—-> 5 raise QuadraticEquationError(‘a cannot be equal to 0’)

QuadraticEquationError: a cannot be equal to 0

Putting things together, here is the final implementation, that abides by the principles of object
oriented design in Python:

[44]: class QuadraticEquation:
def __init__(self, *, a=1, b=0, c=0):

if a == 0:
raise QuadraticEquationError(‘a cannot be equal to 0.’)

self.a = a
self.b = b
self.c = c
self.compute_roots()

def __repr__(self):
return f’QuadraticEquation(a={self.a}, b={self.b}, c={self.c})’

25

def __str__(self):
if self.a == 1:

displayed_equation = ‘x^2’
elif self.a == -1:

displayed_equation = ‘-x^2′
else:

displayed_equation = f'{self.a}x^2’
if self.b == 1:

displayed_equation += ‘ + x’
elif self.b == -1:

displayed_equation -= ‘ – x’
elif self.b > 0:

displayed_equation += f’ + {self.b}x’
elif self.b < 0: displayed_equation += f'- {-self.b}x' if self.c > 0:

displayed_equation += f’ + {self.c}’
elif self.c < 0: displayed_equation += f' - {-self.c}' return f'{displayed_equation} = 0' def compute_roots(self): delta = self.b ** 2 - 4 * self.a * self.c if delta < 0: self.root_1 = self.root_2 = None elif delta == 0: self.root_1 = -self.b / (2 * self.a) self.root_2 = None else: sqrt_delta = sqrt(delta) self.root_1 = (-self.b - sqrt_delta) / (2 * self.a) self.root_2 = (-self.b + sqrt_delta) / (2 * self.a) def update(self, *, a=None, b=None, c=None): if a == 0: raise QuadraticEquationError('a cannot be equal to 0.') if a is not None: self.a = a if b is not None: self.b = b if c is not None: self.c = c self.compute_roots() An error of type QuadraticEquationError is raised at object creation, or when incorrectly updat- ing an existing object: 26 [45]: QuadraticEquation(a=0, b=1) ␣ ↪→--------------------------------------------------------------------------- QuadraticEquationError Traceback (most recent call␣ ↪→last) in
—-> 1 QuadraticEquation(a=0, b=1)

in __init__(self, a, b, c)
2 def __init__(self, *, a=1, b=0, c=0):
3 if a == 0:

—-> 4 raise QuadraticEquationError(‘a cannot be equal to 0.’)
5 self.a = a
6 self.b = b

QuadraticEquationError: a cannot be equal to 0.

[46]: eq3 = QuadraticEquation(a=1, b=3, c=2)
eq3.update(a=0)


↪→—————————————————————————

QuadraticEquationError Traceback (most recent call␣
↪→last)

in
1 eq3 = QuadraticEquation(a=1, b=3, c=2)

—-> 2 eq3.update(a=0)

in update(self, a, b, c)
46 def update(self, *, a=None, b=None, c=None):
47 if a == 0:

—> 48 raise QuadraticEquationError(‘a cannot be equal to 0.’)
49 if a is not None:
50 self.a = a

27

QuadraticEquationError: a cannot be equal to 0.

Otherwise, there is no difference with the 4th design when it comes to creating objects or calling
methods:

[47]: eq1 = QuadraticEquation.__new__(QuadraticEquation)
QuadraticEquation.__init__(eq1)
eq1.a
eq1.b
eq1.c
eq1.root_1
eq1.root_2

print()

eq2 = QuadraticEquation.__new__(QuadraticEquation)
eq2.__init__(b=4)
eq2.a
eq2.b
eq2.c
eq2.root_1
eq2.root_2

print()

eq3 = QuadraticEquation(a=1, b=3, c=2)
eq3.a
eq3.b
eq3.c
eq3.root_1
eq3.root_2

QuadraticEquation.update(eq3, b=-1)
eq3.a
eq3.b
eq3.c
eq3.root_1
eq3.root_2

print()

eq3.update(c=0.3, a=0.5)
eq3.a
eq3.b
eq3.c
eq3.root_1
eq3.root_2

28

[47]: 1

[47]: 0

[47]: 0

[47]: 0.0

[47]: 1

[47]: 4

[47]: 0

[47]: -4.0

[47]: 0.0

[47]: 1

[47]: 3

[47]: 2

[47]: -2.0

[47]: -1.0

[47]: 1

[47]: -1

[47]: 2

[47]: 0.5

[47]: -1

[47]: 0.3

[47]: 0.3675444679663241

[47]: 1.632455532033676

29

Observe the difference between calling either __repr__() or __str__() behind the scene:

[48]: eq1 = QuadraticEquation()
eq1
print(eq1)

eq2 = QuadraticEquation(c=-5, a=2)
eq2
print(eq2)

eq3 = QuadraticEquation(b=1, a=-1, c=-1)
eq3
print(eq3)

[48]: QuadraticEquation(a=1, b=0, c=0)

x^2 = 0

[48]: QuadraticEquation(a=2, b=0, c=-5)

2x^2 – 5 = 0

[48]: QuadraticEquation(a=-1, b=1, c=-1)

-x^2 + x – 1 = 0

30