When you write and run a Python program, the Python interpreter converts your source code into bytecode — a lower-level, platform-independent representation that runs faster.

This process produces two key file types:

• .py → Python source code file
• .pyc → Compiled bytecode file

Let’s understand the difference clearly 👇

🔹 Key Difference Between .py and .pyc Files

🧩 Example

Step 1: Create a Python File

Create a file named example.py:

def greet():
    print("Hello, Dheeraj!")

greet()

def greet():
    print("Hello, Dheeraj!")

greet()

Step 2: Run the File

When you execute:

python example.py

python example.py

Python will:

1. Compile example.py → to bytecode.
2. Save the compiled version as example.cpython-311.pyc (inside __pycache__).
3. Execute the bytecode with the Python Virtual Machine (PVM).

🧩 Step 3: Generated Folder

After running, you’ll see:

project/
│
├── example.py
└── __pycache__/
    └── example.cpython-311.pyc

project/
│
├── example.py
└── __pycache__/
    └── example.cpython-311.pyc

The .pyc file contains compiled bytecode that Python reuses for faster loading next time.

🔹 What Is Bytecode?

• Bytecode is an intermediate representation of your Python code.
• It’s not machine code — it’s a low-level, platform-independent code executed by the Python Virtual Machine (PVM).

🧠 Think of it like:

.py → (compiled by Python) → .pyc → executed by Python Virtual Machine

.py → (compiled by Python) → .pyc → executed by Python Virtual Machine

🔹 When Are .pyc Files Used?

• When you import a module, Python first looks for a .pyc file inside __pycache__.
• If found and up to date, it loads the .pyc file directly — skipping recompilation.
• If not found, Python recompiles the .py file into .pyc and caches it.

🧩 Example: Import Behavior

file1.py

def hello():
    print("Hello from file1!")

def hello():
    print("Hello from file1!")

main.py

import file1
file1.hello()

import file1
file1.hello()

When you run:

python main.py

python main.py

Python will:

• Compile file1.py → __pycache__/file1.cpython-311.pyc
• Next time you import file1, it uses the cached .pyc file directly.

🔹 Deleting .pyc Files

You can safely delete .pyc files — Python will regenerate them automatically next time the module runs.

To remove all .pyc files:

find . -name "*.pyc" -delete   # Linux / macOS

find . -name "*.pyc" -delete   # Linux / macOS

or

del /s *.pyc   # Windows

del /s *.pyc   # Windows

🔹 Can You Run a .pyc File Directly?

Normally, no — .pyc files are not meant to be run manually.
However, you can run them using:

python __pycache__/example.cpython-311.pyc

python __pycache__/example.cpython-311.pyc

But usually, you run the .py file, and Python handles .pyc automatically.

🔹 Advantages of .pyc Files

✅ Faster Execution:
Python skips recompilation and directly executes bytecode.

✅ Portability:
Same .pyc file can run on any system with a compatible Python version.

✅ Efficiency in Imports:
Modules load faster when imported multiple times.

🔹 Disadvantages of .pyc Files

⚠️ Not Human Readable:
Cannot be easily edited or understood.

⚠️ Version Dependent:
A .pyc file generated in Python 3.9 may not work with Python 3.11.

⚠️ Automatically Overwritten:
Regenerated when the source .py file changes.

🧾 Summary Table

✅ In short:

• .py = Your source code (you write it).
• .pyc = Python’s compiled version (Python creates it for faster execution).
• Python stores .pyc files inside __pycache__ and uses them to speed up imports and runtime performance.