Makindo Medical Notes

Overview of Python Programming

Python is a high-level, interpreted programming language known for its simplicity and readability. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Python is widely used in web development, data science, automation, and many other fields.

Basic Syntax and Structure

• Comments:
  • Single-line comments start with a hash (#).

  # This is a single-line comment

  • Multi-line comments are enclosed in triple quotes (''' or """).

  """
  This is a multi-line comment
  spanning multiple lines
  """

• Variables and Data Types:
  • Variables are dynamically typed and do not require explicit declaration.

  x = 10 # Integer
  y = 3.14 # Float
  name = "Alice" # String
  is_active = True # Boolean

• Control Structures:
  • Conditional statements (if, elif, else) for decision making.

  if x > 5:
   print("x is greater than 5")
  elif x == 5:
   print("x is equal to 5")
  else:
   print("x is less than 5")

  • Loops (for, while) for iteration.

  for i in range(5):
   print(i) # Prints 0 to 4
  j = 0
  while j < 5:
   print(j)
   j += 1 # Prints 0 to 4

Functions

• Defining Functions:
  • Functions are defined using the def keyword.

  def greet(name):
   return f"Hello, {name}!"
  print(greet("Alice")) # Output: Hello, Alice!

• Lambda Functions:
  • Anonymous functions defined using the lambda keyword.

  square = lambda x: x * x
  print(square(5)) # Output: 25

Data Structures

• Lists:
  • Ordered, mutable collections of elements.

  fruits = ["apple", "banana", "cherry"]
  print(fruits[0]) # Output: apple
  fruits.append("date") # Adds "date" to the list

• Tuples:
  • Ordered, immutable collections of elements.

  coordinates = (10, 20)
  print(coordinates[1]) # Output: 20

• Dictionaries:
  • Unordered collections of key-value pairs.

  person = {"name": "Alice", "age": 30}
  print(person["name"]) # Output: Alice
  person["age"] = 31 # Updates the value of "age"

• Sets:
  • Unordered collections of unique elements.

  unique_numbers = {1, 2, 3, 2, 1}
  print(unique_numbers) # Output: {1, 2, 3}

Object-Oriented Programming

• Classes and Objects:
  • Classes define the blueprint for objects.
  • Objects are instances of classes.

  class Dog:
   def __init__(self, name, age):
   self.name = name
   self.age = age
   def bark(self):
   return f"{self.name} says woof!"
  my_dog = Dog("Buddy", 3)
  print(my_dog.bark()) # Output: Buddy says woof!

• Inheritance:
  • Allows a class to inherit attributes and methods from another class.

  class Animal:
   def __init__(self, name):
   self.name = name
   def speak(self):
   pass
  class Dog(Animal):
   def speak(self):
   return f"{self.name} says woof!"
  my_dog = Dog("Buddy")
  print(my_dog.speak()) # Output: Buddy says woof!

Modules and Packages

• Importing Modules:
  • Modules are files containing Python code that can be imported into other Python files.

  import math
  print(math.sqrt(16)) # Output: 4.0

• Creating Packages:
  • Packages are directories containing multiple modules, allowing for organized project structure.

  # Directory structure:
  # mypackage/
  # __init__.py
  # module1.py
  # module2.py
  # In a Python file:
  from mypackage import module1
  module1.some_function()

File I/O

• Reading from a File:

  with open("example.txt", "r") as file:
   content = file.read()
   print(content)

• Writing to a File:

  with open("example.txt", "w") as file:
   file.write("Hello, world!")

Exception Handling

• Try-Except Blocks:

  try:
   result = 10 / 0
  except ZeroDivisionError:
   print("Cannot divide by zero!")

• Finally Block:
  • Code in the finally block always executes, regardless of whether an exception occurred.

  try:
   result = 10 / 0
  except ZeroDivisionError:
   print("Cannot divide by zero!")
  finally:
   print("This will always be printed")

Standard Libraries and Tools

• NumPy:
  • Library for numerical computing and array operations.

  import numpy as np
  arr = np.array([1, 2, 3, 4])
  print(arr * 2) # Output: [2 4 6 8]

• Pandas:
  • Library for data manipulation and analysis.

  import pandas as pd
  data = {"name": ["Alice", "Bob"], "age": [30, 25]}
  df = pd.DataFrame(data)
  print(df)

• Matplotlib:
  • Library for creating static, animated, and interactive visualizations.

  import matplotlib.pyplot as plt
  plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
  plt.xlabel("X-axis")
  plt.ylabel("Y-axis")
  plt.show()

• Requests:
  • Library for making HTTP requests.

  import requests
  response = requests.get("https://api.github.com")
  print(response.status_code)

Summary

Python is a versatile programming language with simple syntax and powerful features. It supports various programming paradigms and is widely used in different fields. Understanding the basic syntax, control structures, functions, data structures, object-oriented programming, and libraries is essential for effective Python programming. With its extensive standard libraries and community support, Python is an excellent choice for beginners and experienced developers alike.