Algorithms in Python can be easier understood with step-by-step visualization using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵. Here we show a Breadth First algorithm that finds the shortest path in a graph from node 'a' to node 'b'.
Algorithms can be easier understood with step-by-step visualization using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵. Here we show a Breadth First algorithm that finds the shortest path in a graph from node 'a' to node 'b'.
An exercise to help build the right mental model for Python data. What is the output of this program?
float1 = 0.0 ; float2 = float1
str1 = "0" ; str2 = str1
list1 = [0] ; list2 = list1
tuple1 = (0,) ; tuple2 = tuple1
set1 = {0} ; set2 = set1
float2 += 0.1
str2 += "1"
list2 += [1]
tuple2 += (1,)
set2 |= {1}
print(float1, str1, list1, tuple1, set1)
# --- possible answers ---
# A) 0.0 0 [0] (0,) {0}
# B) 0.0 0 [0, 1] (0,) {0, 1}
# C) 0.0 0 [0, 1] (0, 1) {0, 1}
# D) 0.0 01 [0, 1] (0, 1) {0, 1}
# E) 0.1 01 [0, 1] (0, 1) {0, 1}
The “Solution” link uses 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵 to visualize execution and reveals what’s actually happening.