Black Jack
Black Jack

Black Jack

Learning Exercise



Python supports the following basic comparison operators:

Operator Operation Description
> "greater than" a > b is True if a is strictly greater in value than b
< "less than" a < b is True if a is strictly less in value than b
== "equal to" a == b is True if a is strictly equal to b in value
>= "greater than or equal to" a >= b is True if a > b OR a == b in value
<= "less than or equal to" a <= b is True if a < b or a == b in value
!= "not equal to" a != b is True if a == b is False
is "identity" a is b is True if and only if a and b are the same object
is not "negated identity" a is not b is True if a and b are not the same object
in "containment test" a in b is True if a is member, subset, or element of b
not in "negated containment test" a not in b is True if a is not a member, subset, or element of b

They all have the same priority (which is higher than that of Boolean operations, but lower than that of arithmetic or bitwise operations).

Comparison between different data types

Objects that are different types (except numeric types) never compare equal by default. Non-identical instances of a class will also not compare as equal unless the class defines special rich comparison methods that customize the default object comparison behavior. Customizing via rich comparisons will be covered in a follow-on exercise. For (much) more detail on this topic, see Value comparisons in the Python documentation.

Numeric types are (mostly) an exception to this type matching rule. An integer can be considered equal to a float (or an octal equal to a hexadecimal), as long as the types can be implicitly converted for comparison.

For the other numeric types in the Python standard library (complex, decimal, fractions), comparison operators are defined where they "make sense" (where implicit conversion does not change the outcome), but throw a TypeError if the underlying objects cannot be accurately converted for comparison. For more information on the rules that python uses for numeric conversion, see arithmetic conversions in the Python documentation.

>>> import fractions

# A string cannot be converted to an int.
>>> 17 == '17'

# An int can be converted to float for comparison.
>>> 17 == 17.0

# The fraction 6/3 can be converted to the int 2
# The int 2 can be converted to 0b10 in binary.
>>> 6/3 == 0b10

# An int can be converted to a complex number with a 0 imaginary part.
>>> 17 == complex(17)

# The fraction 2/5 can be converted to the float 0.4
>>> 0.4 == 2/5

>>> complex(2/5, 1/2) == complex(0.4, 0.5)

Any ordered comparison of a number to a NaN (not a number) type is False. A confusing side effect of Python's NaN definition is that NaN never compares equal to NaN.

>>> x = float('NaN')

>>> 3 < x

>>> x < 3

# NaN never compares equal to NaN
>>> x == x

Comparing Strings

Unlike numbers, strings (str) are compared lexicographically, using their individual Unicode code points (the result of passing each code point in the str to the built-in function ord(), which returns an int). If all code points in both strings match and are in the same order, the two strings are considered equal. This comparison is done in a 'pair-wise' fashion - first-to-first, second-to-second, etc. In Python 3.x, str and bytes cannot be directly coerced/compared.

>>> 'Python' > 'Rust'

>>> 'Python' > 'JavaScript'

# Examples with Mandarin.
# hello < goodbye
>>> 'δ½ ε₯½' < '再见'

# ord() of first characters
>>> ord('δ½ '), ord('再')
(20320, 20877)

# ord() of second characters
>>> ord('ε₯½'), ord('见')
(22909, 35265)

# And with Korean words.
# Pretty < beautiful.
>>> '예쁜' < 'μ•„λ¦„λ‹€μš΄'

>>> ord('예'), ord('μ•„')
(50696, 50500)

Comparison Chaining

Comparison operators can be chained arbitrarily -- meaning that they can be used in any combination of any length. Note that the evaluation of an expression takes place from left to right.

As an example, x < y <= z is equivalent to x < y and y <= z, except that y is evaluated only once. In both cases, z is not evaluated at all when x < y is found to be False. This is often called short-circuit evaluation - the evaluation stops if the truth value of the expression has already been determined.

Short circuiting is supported by various boolean operators, functions, and also by comparison chaining in Python. Unlike many other programming languages, including C, C++, C#, and Java, chained expressions like a < b < c in Python have a conventional mathematical interpretation and precedence.

>>> x = 2
>>> y = 5
>>> z = 10

>>> x < y < z

>>> x < y > z

>>> x > y < z

Comparing object identity

The operators is and is not test for object identity, as opposed to object value. An object's identity never changes after creation and can be found by using the id() function.

<apple> is <orange> evaluates to True if and only if id(<apple>) == id(<orange>). <apple> is not <orange> yields the inverse.

Due to their singleton status, None and NotImplemented should always be compared to items using is and is not. See the Python reference docs on value comparisons and PEP8 for more details on this convention.

>>> my_fav_numbers = [1, 2, 3]

>>> your_fav_numbers = my_fav_numbers

>>> my_fav_numbers is your_fav_numbers

# The returned id will differ by system and python version.
>>> id(my_fav_numbers)

# your_fav_numbers is only an alias pointing to the original my_fav_numbers object.
# Assigning a new name does not create a new object.
>>> id(your_fav_numbers)

>>> my_fav_numbers is not your_fav_numbers

>>> my_fav_numbers is not None

>>> my_fav_numbers is NotImplemented

Membership comparisons

The operators in and not in test for membership. <fish> in <soup> evaluates to True if <fish> is a member of <soup> (if <fish> is a subset of or is contained within <soup>), and evaluates False otherwise. <fish> not in <soup> returns the negation, or opposite of <fish> in <soup>.

For string and bytes types, <name> in <fullname> is True if and only if <name> is a substring of <fullname>.

# A set of lucky numbers.
>>> lucky_numbers = {11, 22, 33}
>>> 22 in lucky_numbers

>>> 44 in lucky_numbers

# A dictionary of employee information.
>>> employee = {'name': 'John Doe', 
                'id': 67826, 'age': 33, 
                'title': 'ceo'}

# Checking for the membership of certain keys.
>>> 'age' in employee

>>> 33 in employee

>>> 'lastname' not in employee

# Checking for substring membership
>>> name = 'Super Batman'
>>> 'Bat' in name

>>> 'Batwoman' in name


In this exercise you are going to implement some rules of Blackjack, such as the way the game is played and scored.

Note : In this exercise, A means ace, J means jack, Q means queen, and K means king. Jokers are discarded. A standard French-suited 52-card deck is assumed, but in most versions, several decks are shuffled together for play.

1. Calculate the value of a card

In Blackjack, it is up to each individual player if an ace is worth 1 or 11 points (more on that later). Face cards (J, Q, K) are scored at 10 points and any other card is worth its "pip" (numerical) value.

Define the value_of_card(<card>) function with parameter card. The function should return the numerical value of the passed-in card string. Since an ace can take on multiple values (1 or 11), this function should fix the value of an ace card at 1 for the time being. Later on, you will implement a function to determine the value of an ace card, given an existing hand.

>>> value_of_card('K')

>>> value_of_card('4')

>>> value_of_card('A')

2. Determine which card has a higher value

Define the higher_card(<card_one>, <card_two>) function having parameters card_one and card_two. For scoring purposes, the value of J, Q or K is 10. The function should return which card has the higher value for scoring. If both cards have an equal value, return both. Returning both cards can be done by using a comma in the return statement:

# Using a comma in a return creates a Tuple.  Tuples will be covered in a later exercise.
>>> def returning_two_values(value_one, value_two):
        return value_one, value_two

>>> returning_two_values('K', '3')
('K', '3')

An ace can take on multiple values, so we will fix A cards to a value of 1 for this task.

>>> higher_card('K', '10')
('K', '10')

>>> higher_card('4', '6')

>>> higher_card('K', 'A')

3. Calculate the value of an ace

As mentioned before, an ace can be worth either 1 or 11 points. Players try to get as close as possible to a score of 21, without going over 21 (going "bust").

Define the value_of_ace(<card_one>, <card_two>) function with parameters card_one and card_two, which are a pair of cards already in the hand before getting an ace card. Your function will have to decide if the upcoming ace will get a value of 1 or a value of 11, and return that value. Remember: the value of the hand with the ace needs to be as high as possible without going over 21.

Hint: if we already have an ace in hand, then the value for the upcoming ace would be 1.

>>> value_of_ace('6', 'K')

>>> value_of_ace('7', '3')

4. Determine a "Natural" or "Blackjack" Hand

If the first two cards a player is dealt are an ace (A) and a ten-card (10, K , Q or J), then the player has a score of 21. This is known as a blackjack hand.

Define the is_blackjack(<card_one>, <card_two>) function with parameters card_one and card_two, which are a pair of cards. Determine if the two-card hand is a blackjack, and return the boolean True if it is, False otherwise.

Note : The score calculation can be done in many ways. But if possible, we'd like you to check if there is an ace and a ten-card in the hand (or at a certain position), as opposed to summing the hand values.

>>> is_blackjack('A', 'K')

>>> is_blackjack('10', '9')

5. Splitting pairs

If the players first two cards are of the same value, such as two sixes, or a Q and K a player may choose to treat them as two separate hands. This is known as "splitting pairs".

Define the can_split_pairs(<card_one>, <card_two>) function with parameters card_one and card_two, which are a pair of cards. Determine if this two-card hand can be split into two pairs. If the hand can be split, return the boolean True otherwise, return False

>>> can_split_pairs('Q', 'K')

>>> can_split_pairs('10', 'A')

6. Doubling down

When the original two cards dealt total 9, 10, or 11 points, a player can place an additional bet equal to their original bet. This is known as "doubling down".

Define the can_double_down(<card_one>, <card_two>) function with parameters card_one and card_two, which are a pair of cards. Determine if the two-card hand can be "doubled down", and return the boolean True if it can, False otherwise.

>>> can_double_down('A', '9')

>>> can_double_down('10', '2')
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