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‎Decorators.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "57d57c9e",
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"metadata": {},
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"source": [
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"#### 🧩 Python Decorators & First-Class Functions\n",
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"\n",
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"---\n",
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"\n",
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"#### 1. What are Decorators?\n",
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"\n",
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"Decorators in Python are **functions that modify the behavior of other functions** without changing their code. They allow us to extend or enhance functions in a clean and reusable way.\n",
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"\n",
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"##### 🔑 Key Features:\n",
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"- Allow code reusability.\n",
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"- Improve code readability.\n",
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"- Commonly used for:\n",
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" - Logging\n",
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" - Authentication\n",
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" - Measuring execution time\n",
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" - Access control\n",
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"\n",
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"---\n",
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"\n",
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"#### 2. Why Do We Use Decorators?\n",
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"\n",
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"Decorators help us **avoid code duplication** by adding extra functionality **without modifying the core function logic**.\n",
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"\n",
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"#### 💡 Common Use Cases:\n",
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"- Logging function execution\n",
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"- Measuring execution time\n",
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"- Checking user authentication before executing a function\n",
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"\n",
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"---\n",
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"\n",
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"#### 3. Functions as First-Class Citizens\n",
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"\n",
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"In Python, functions are treated like **first-class citizens**, meaning they can:\n",
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"- Be **assigned** to a variable\n",
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"- Be **passed** as an argument to another function\n",
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"- Be **returned** from another function\n",
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"\n",
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"#### 🧪 Example: Passing a Function as an Argument"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "1eb196a4",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hello\n"
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]
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}
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],
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"source": [
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"def greet():\n",
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" return \"Hello\"\n",
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"\n",
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"def call_function(func):\n",
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" return func() # Provide the required argument\n",
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"# Pass the greet function as an argument\n",
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"result = call_function(greet)\n",
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"print(result) # Output: Hello, Alice!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "708a9a5e",
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"metadata": {},
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"source": [
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"#### 4. 🧱 Basic Structure of a Decorator\n",
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"\n",
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"A **decorator** is a function that wraps another function to modify or extend its behavior without permanently changing it.\n",
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"\n",
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"### 📝 Syntax:\n",
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"\n",
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"```python\n",
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"def decorator_function(original_function):\n",
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" def wrapper_function():\n",
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" # Add extra functionality\n",
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" return original_function()\n",
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" return wrapper_function\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "8debd928",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Calling function: say_hello\n",
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"Hello!\n"
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]
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}
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],
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"source": [
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"## 💡 Example: A Simple Decorator That Logs Function Calls\n",
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"# This example demonstrates how to create a simple decorator that logs function calls.\n",
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"\n",
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"\n",
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"# Define a decorator function that takes another function as an argument\n",
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"def log_decorator(func):\n",
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" # Define a wrapper function that will modify the behavior of the original function\n",
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" def wrapper():\n",
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" print(f'Calling function: {func.__name__}') # Print the name of the function being called\n",
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" return func() # Call the original function\n",
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" return wrapper # Return the modified function\n",
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"\n",
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"# Apply the decorator to the 'say_hello' function using @log_decorator\n",
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"@log_decorator\n",
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"def say_hello():\n",
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" print(\"Hello!\") # This function simply prints \"Hello!\"\n",
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"\n",
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"# Call the decorated function\n",
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"say_hello()\n",
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"# Decorator to measure consultation time\n",
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"def timer_decorator(func):\n",
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" def wrapper(patient_name):\n",
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" start = time.time() # Record start time\n",
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" result = func(patient_name) # Call the original function\n",
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" end = time.time() # Record end time\n",
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" print(f\"Consultation time: {end - start:.4f} seconds\")\n",
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" return result\n",
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" return wrapper"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6cd4d24d",
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"metadata": {},
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"source": [
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"##### 5. Using Multiple Decorators\n",
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"\n",
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"Multiple decorators can be applied by **stacking them on top of a function**.\n",
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"\n",
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"##### 💡 Example Use Case: Checking Consultation Time \n",
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"*(Timing how long it takes)*\n",
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"\n",
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"Instead of making every doctor manually do these extra steps, a hospital can create a system that **automatically ensures every doctor follows these steps** — this is what a **decorator** does in programming!\n",
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"\n",
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"Decorators help wrap extra functionality around functions in a clean and reusable way.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "ac742f91",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Patient details logged for Alice\n",
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"Doctor is consulting Alice\n",
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"Prescription given to Alice\n",
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"Consultation time: 1.0117 seconds\n"
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]
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}
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],
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"source": [
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"import time\n",
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"\n",
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"# Decorator to log patient details\n",
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"def log_decorator(func):\n",
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" def wrapper(patient_name):\n",
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" print(f\"Patient details logged for {patient_name}\")\n",
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" return func(patient_name)\n",
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" return wrapper\n",
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"\n",
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"# Decorator to measure consultation time\n",
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"def timer_decorator(func):\n",
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" def wrapper(patient_name):\n",
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" start = time.time() # Record start time\n",
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" result = func(patient_name) # Call the original function\n",
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" end = time.time() # Record end time\n",
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" print(f\"Consultation time: {end - start:.4f} seconds\")\n",
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" return result\n",
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" return wrapper\n",
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"\n",
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"# Applying decorators to the doctor's consultation function\n",
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"@log_decorator # Log patient details\n",
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"@timer_decorator # Measure consultation time\n",
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"def doctor_consultation(patient_name):\n",
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" print(f\"Doctor is consulting {patient_name}\")\n",
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" time.sleep(1) # Simulate consultation time\n",
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" print(f\"Prescription given to {patient_name}\")\n",
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"\n",
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"# Simulating a patient visiting the doctor\n",
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"doctor_consultation(\"Alice\")\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "61771d2f",
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"metadata": {},
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"source": [
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"#### 6. Passing Arguments to Decorators:\n",
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"\n",
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"Extra Function for Argument Passing:\n",
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"\n",
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"A decorator can take arguments, for example, to repeat a function multiple times:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "753e6eba",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hello!\n",
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"Hello!\n",
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"Hello!\n"
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]
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}
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],
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"source": [
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"\n",
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"\n",
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"### 🎯 Goal: Repeat a function multiple times using a decorator\n",
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"\n",
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"\n",
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"# Outer function that takes a parameter 'times' (how many times to repeat)\n",
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"def repeat(times):\n",
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" # Inner function that acts as the actual decorator\n",
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" def decorator(func):\n",
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" # Wrapper function that modifies the behavior of 'func'\n",
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" def wrapper(*args, **kwargs):\n",
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" for _ in range(times): # Loop 'times' number of times\n",
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" func(*args, **kwargs) # Call the original function\n",
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" return wrapper # Return the modified function\n",
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" return decorator # Return the decorator function\n",
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"\n",
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"# Applying the 'repeat' decorator with 'times = 3'\n",
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"@repeat(3)\n",
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"def greet():\n",
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" print(\"Hello!\")\n",
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"\n",
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"# Calling 'greet()' will now run 3 times due to the decorator\n",
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"greet()\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b237b8a6",
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"metadata": {},
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"source": [
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"## ✅ Best Practices for Decorators\n",
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"\n",
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"- Use decorators to **extend functionality** without modifying the original code.\n",
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"- Preserve function metadata using `functools.wraps()`.\n",
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"- Avoid unnecessary nesting of decorators to keep the code **readable and maintainable**.\n",
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"\n",
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"---\n",
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"\n",
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"## 🧠 Conclusion\n",
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"\n",
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"Decorators provide a **clean, reusable** way to add additional functionality to functions, such as **logging** or **timing**, without changing the core function.\n",
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"\n",
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"They are an essential concept for writing **cleaner**, more **modular** code in Python — especially when the same functionality needs to be applied to **multiple functions**.\n"
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]
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}
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],
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