This Selection Sort lesson is for a beginner. Read the short notes, run each example, then change one name or number and run it again.
Selection sort finds the smallest remaining item and swaps it into the next open position.
It makes fewer swaps than bubble sort and still compares every pair of positions.
Example 1: Start here
After i steps, the first i items are in their final places.
def selection(items): # define the function; it runs when you call it
items = items[:] # a separate copy
for i in range(len(items)): # repeat once per number; range stops before the last
small = i # another name for the same value
for j in range(i + 1, len(items)): # repeat once per number; range stops before the last
if items[j] < items[small]: # run the indented lines only when this is true
small = j # another name for the same value
items[i], items[small] = items[small], items[i] # swap the two values
return items # send this value back to the caller
print(selection([4, 1, 3]))
Example 2: Walk the values
Selection Sort 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? Selection Sort 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
After i steps, the first i items are in their final places.
