This Linked Lists lesson is for a beginner. Read the short notes, run each example, then change one name or number and run it again.
A linked list stores each value in a node that points at the next node. Inserting at the front does not move the other nodes.
Finding the tenth item means walking nine links. A Python list is usually the better everyday choice.
Example 1: Start here
Keep a reference to the first node. Without it you cannot find the rest.
class Node: # a template for objects
def __init__(self, value, nxt=None): # runs when you create the object
self.value = value # store this on the object
self.nxt = nxt # store this on the object
head = Node("Python", Node("SQL")) # one object
print(head.nxt.value)
Example 2: Walk the values
Linked Lists starts by visiting one value at a time. Read the printed lines from top to bottom.
values = [11, 3, 11, 7] # a list; the values stay in this order
for value in values: # repeat the indented lines once per value
print(value)
Example 3: Keep the largest
Many data-structure lessons reduce a list to one answer. This one remembers the largest number seen so far.
values = [11, 3, 11, 7] # a list; the values stay in this order
best = values[0] # the first value
for value in values: # repeat the indented lines once per value
if value > best: # run the indented lines only when this is true
best = value # another name for the same value
print(best)
Example 4: Search for a target
A search asks one yes-or-no question: is the target in the collection? Linked Lists builds on that question.
values = [3, 11, 11] # a list; the values stay in this order
target = 11 # a whole number
print(target in values) # in is True when the value is found
Keep a reference to the first node. Without it you cannot find the rest.
