01 | COLLECTIONS HAVE DIFFERENT PROMISES

A list is useful when order and change matter. A tuple suits a fixed ordered grouping such as a coordinate pair. A set suits unique membership, such as the distinct activities selected by a club.

Do not choose from bracket shape alone. Ask whether duplicates matter, whether positions carry meaning and whether the collection itself must change.

Each structure can hold references to objects. Its rules determine what operations are valid, and those rules are part of the data design.

02 | TUPLES KEEP AN ORDERED GROUP

A tuple stores values in order and supports indexing, negative indexing and slicing. A pair (4, 7) can represent x and y coordinates, where position has an agreed meaning.

The tuple itself is immutable: you cannot replace its item at index zero or append another item. You can bind the variable to a new tuple, just as a name can be rebound to a new string.

position = (4, 7)
print(position[0])
print(position[-1])

4
7

03 | THE COMMA MAKES A ONE-ITEM TUPLE

For one item, write (4,), including the comma. (4) is just an integer expression grouped in parentheses. The empty tuple is ().

Commas create tuple packing; parentheses make its boundary readable. result = 4, 7 also creates a tuple. Prefer clear grouping when a tuple is passed to another operation.

single = (4,)
not_a_tuple = (4)
print(type(single))
print(type(not_a_tuple))

<class 'tuple'>
<class 'int'>

04 | UNPACK MEANINGFUL POSITIONS

Unpacking assigns successive items to successive names. x, y = position makes x four and y seven. The number of destination names must match the number of supplied items for this basic form, or ValueError is raised.

Good names document what the positions mean. A two-item tuple can be practical; a long tuple whose meanings are hard to remember may be better expressed with a dictionary of named fields.

position = (4, 7)
x, y = position
print("x:", x, "y:", y)

x: 4 y: 7

05 | IMMUTABLE DOES NOT MEAN EVERYTHING INSIDE IS FROZEN

A tuple’s references cannot be replaced in place, but it can contain a mutable object such as a list. That inner list can still change.

For record = ("Maya", [8, 9]), appending to record[1] changes the list stored there, not the tuple’s slot. Assigning record[1] = another_list would instead try to replace a tuple item and fail.

Explain the level at which immutability applies rather than calling the entire nested structure permanently frozen.

record = ("Maya", [8, 9])
record[1].append(10)
print(record)

('Maya', [8, 9, 10])

06 | A SET STORES DISTINCT MEMBERS

A set contains unique items and supports membership tests with in. Repeated equal items collapse into one member. A set does not provide a positional index or promise a display order.

Use set() for an empty set. {} creates an empty dictionary, which is introduced next. A non-empty set literal uses braces, such as {"robotics", "coding"}.

Converting a list to a set removes duplicates but loses its positional sequence information. A set is not a sorted list.

activities = {"coding", "robotics", "coding"}
print(len(activities))
print("coding" in activities)

2
True

07 | ADD, DISCARD AND REMOVE

add(value) inserts a set member; adding an existing member leaves membership unchanged. discard(value) removes it if present and does not raise an error if absent.

remove(value) also removes a member, but raises KeyError when it is absent. Choose according to whether absence is expected or should expose a fault.

These methods mutate the set and return None. Do not assign the method result back as though it were the changed collection.

activities = set()
activities.add("coding")
activities.add("coding")
activities.discard("music")
print(len(activities))

1

08 | COMPARE MEMBERSHIP BETWEEN GROUPS

Union gives members appearing in either set. Intersection gives shared members. Difference gives members in the first set but not the second.

Use | for union, & for intersection and - for difference. Difference is directional: A - B is not generally the same as B - A. These expressions create resulting sets rather than altering their operands.

When you need predictable readable display for simple comparable strings, sorted(result) produces a sorted list. That is a display choice, not a change to the set’s ordering rule.

first = {"coding", "robotics"}
second = {"robotics", "music"}
print(sorted(first | second))
print(sorted(first & second))
print(sorted(first - second))

['coding', 'music', 'robotics']
['robotics']
['coding']

09 | MEMBERS MUST BE HASHABLE

A set uses hashing to organise membership. A hashable object has a stable hash and equality behaviour suitable for that role. Strings and integers are suitable common examples; lists and dictionaries are not.

A tuple is hashable only if all its items are hashable. A coordinate tuple of numbers can be a set member, but a tuple containing a list cannot.

The beginner rule “all immutable things work” is too broad without checking their contents. Start with simple text, numbers and suitable tuples.

10 | EXPLORE UNIQUE MEMBERS AND SHARED ACTIVITIES

Enter comma-separated simple activity names for two groups. The demo trims surrounding spaces, ignores empty pieces and treats names as case-sensitive. It shows sorted display lists so the output is predictable.

Try repeated values, no shared values and an empty group. Explain why this tool does not assign numbered positions to set members.

11 | YOUR COLLECTION-CHOICE CHALLENGE

Store a coordinate pair in a tuple and unpack its two meanings. Separately, collect club activity names and use sets to report shared and distinct choices.

Test duplicate activity names and an absent member removal. Explain why discard is suitable if the removal request is optional, while remove can reveal an unexpected absence.

Extension: compare a tuple containing a list with a tuple containing only numbers. Explain which can be a set member and why.

PUT YOUR SKILLS TO WORK

Use the Section 3 challenges to practise these ideas independently. Work in your Python editor, predict results and keep a short test record.