See the Solution and Explanation.

See the Solution and Explanation.

Visualize your Python data structure with just one click: Linked List

🧠 Understand what your Python code is really doing by memory_graph visualization, despite the difficulties of the Python Data Model:

• references

• mutable vs immutable data types

• function calls and variable scope

• sharing data between variables

• shallow vs deep copy

🧩 For example, what is the output of this program?

import copy

def fun(c1, c2, c3, c4):
    c1[0].append(1)
    c2[0].append(2)
    c3[0].append(3)
    c4[0].append(4)

mylist = [[0]]
c1 = mylist
c2 = mylist.copy()
c3 = copy.copy(mylist)
c4 = copy.deepcopy(mylist)
fun(c1, c2, c3, c4)

print(mylist) # What do you expect?

💥 See the live demo in Memory Graph Web Debugger.

Understanding and debugging Data Structures is easier when you can see the structure of your data using memory_graph. Here we show values being inserted in a Binary Tree.

🎥 See the Quick Intro video for the VS Code integration.

See the Solution and Explanation.

• Changing a value of immutable type results in an automatic copy

• Changing a value of mutable type causes it to mutate in place

🧠 Understand the Python data model better using memory_graph.

🎥 Watch the explainer on Python Mutability.

• c1: assignment, nothing is copied, everything is shared

• c2: shallow copy, only the first value is copied, all the underlying values are shared

• c3: custom copy, you decide what is copied and shared

• c4: deep copy, everything is copied, nothing is shared

🧠 Learn the right mental model to think about Python data using memory_graph.

🎥 See the Quick Intro video for the VS Code debugger setup.