[Py3]--heap module and heap sequencing

Heapify ()

The Heapify () function is used to convert a sequence into an initialized heap

 nums=[16,7,3,20,17,8,-1  print  ( Span style= "color: #800000;" > '  

Heappush ()

Heappush () is an operation that implements inserting elements into the heap
Be sure to initialize the sequence before the Heappush () operation! Heappush is for the "heap" Operation! Otherwise, it doesn't make sense.

Nums=[16,7,3,20,17,8,-1]print(nums) show_tree (nums)       [7, 3, 8, 1]                                              7                 3       8        -1     ------------------------------------

Heapq.heapify (nums)print (' initialize heap:', nums) show_tree (nums) Initialize piles: [-1, 7, 3, 8, +, +]- 1 7 3 8------------------------------------     

 forIinchRandom.sample (Range (1,8), 2):    Print("This push:", i) Heapq.heappush (nums,i)Print(nums) show_tree (nums) This push:5    [-1, 5, 3, 7, 17, 8, 16, 20]                     -1 5 3 7 8----------- -------------------------This push:7    [-1, 5, 3, 7, 17, 8, 16, 20, 7]                     -1 5 3 7 (8) 7------- -----------------------------

Heappop ()

Heappop () is an operation that implements removing an element out of a heap
Be sure to initialize the sequence before the same operation, otherwise it doesn't make sense.

Nums=[16,7,3,20,17,8,-1]print(nums) show_tree (nums)          [7, 3, 8, 1]                                                      7                 3       8        -1         ------------------------------------heapq.heapify ( nums)print(' Initialize heap:', Nums) show_tree (nums)        initialize piles: [ -1, 7, 3, 1, 8, +                         ]-7                                 3 8                 -           ---------------------- --------------

 forIinchRange (0,2):    Print("this time pop:", Heapq.heappop (nums))Print(nums) show_tree (nums) This pop:-1        [3, 7, 8, 20, 17, 16]                         3 7 8---------------- --------------------this time pop:3        [7, 16, 8, 20, 17]                         7 8------------------------- -----------

Nlargest ()/nsmallest ()

Sorted (iterable, Key=key, reverse=true) [: n]

• Nlargest (n,iterable) to find TOPN in sequence iterable | Nsmallest (n,iterable) to find BTMN in sequence iterable

Import heapqnums=[16,7,3,20,17,8,-1]print(heapq.nlargest (3, nums))print( Heapq.nsmallest (3, nums)) [1, 3, 7]

• Nlargest (n, iterable, KEY=LAMBDA) | Nsmallest (n, iterable, KEY=LAMBDA) key accepts the keyword parameter for use in more complex data structures

defPrint_price (dirt): forIinchDirt: forX, yinchI.items ():ifx==' Price':                Print(x, y) portfolio= [    {'name':'IBM','shares': 100,' Price': 91.1},    {'name':'AAPL','shares': 50,' Price': 543.22},    {'name':'FB','shares': 200,' Price': 21.09},    {'name':'HPQ','shares': 35,' Price': 31.75},    {'name':'YHOO','shares': 45,' Price': 16.35},    {'name':'ACME','shares': 75,' Price': 115.65}]cheap=heapq.nsmallest (3,portfolio,key=Lambdax:x[' Price']) Expensive=heapq.nlargest (3,portfolio,key=Lambday:y[' Price']) print_price (cheap) print_price (expensive) price16.35 Price21.09 Price31.75 Price543.22 Price115.65 Price91.1

About the heap and heap sort

For the nums=[16,7,3,20,17,8,-1] sequence above, the diagram illustrates:

Constructing the heap operations (click to view)

Push heap operations (click to view)

Operation of the Pop heap (click to view)

Reference Articles

Details of the use of the HEAPQ module in Python (including Show_tree ())

Detailed heap Sequencing

Discussion on algorithm and data structure: five-priority queue and heap sort

[Py3]--heap module and heap sequencing