Here is the exact step-by-step logic that runs behind the scenes when Python executes this dictionary comprehension:

✅ What Happens Internally When You Run

dict1 = {key: value for key, value in student.items()}

Conceptually, Python expands this dictionary comprehension into something like:

dict1 = {}
for key, value in student.items():
    dict1[key] = value

That is the behind-the-scenes expanded version.
Internally, Python does NOT literally rewrite your code; instead, it executes bytecode that is equivalent to this logic.

🔍 Detailed Behind-the-Scenes Execution Flow

1. Create an empty dictionarydict1 = {}
2. Iterate through each (key, value) pair from:student.items()
3. For each iteration:
   • Bind key to the key
   • Bind value to the value
   • Assign into the new dictionary:
   dict1[key] = value
4. Return the final dictionary

🧠 Internal Bytecode View (Actual Behind-the-Scenes)

If you disassemble using dis:

import dis

student = {"a":1, "b":2}
dis.dis("{k:v for k,v in student.items()}")

You will see bytecode similar to:

BUILD_MAP
LOAD_NAME      student
LOAD_METHOD    items
CALL_METHOD
GET_ITER
FOR_ITER
UNPACK_SEQUENCE 2
STORE_FAST     k
STORE_FAST     v
LOAD_FAST      k
LOAD_FAST      v
MAP_ADD
JUMP_BACK
RETURN_VALUE

This bytecode corresponds to:

• Build an empty map
• Iterate keys/values
• Add each key/value with MAP_ADD

🎯 Final Idea (Simple Understanding)

Dictionary comprehension is just a shorter, faster, optimized syntax for:

dict1 = {}
for key, value in student.items():
    dict1[key] = value

Python internally compiles it to optimized bytecode but the logical flow is exactly the same.

If you want, I can also show:

✅ how list, set, generator comprehensions are expanded
✅ internal CPython C implementation (ceval.c → MAP_ADD opcode)
✅ performance comparison

Just tell me!