Introduction to Python Programming

Python Introduction

• Python is a versatile programming language suitable for various tasks like web development, machine learning, and data science.
• It's known for its readability, using English keywords and fewer syntactical constructions.

History of Python

• Developed by Guido van Rossum in the late 1980s and early 1990s.
• Influenced by languages like ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell scripting.
• Python source code is available under the GNU General Public License (GPL).

Python Features

• Easy to learn: Simple syntax with few keywords.
• Easy to read: Clear and visible code.
• Easy to maintain: Well-structured code simplifies maintenance.
• Extensive Standard Library: Offers a wide range of portable and cross-platform modules.
• Interactive Mode: Supports interactive testing and debugging of code snippets.
• Portable: Runs on various hardware platforms with consistent interface.
• Extendable: Allows adding low-level modules to customize tools.
• Database Support: Interfaces with major commercial databases.
• GUI Programming: Supports GUI application development across different systems.
• Scalable: Provides better structure and support for large programs compared to shell scripting.

Python Environment Setup

• Download the latest Python version from python.org and install it.
• Verify installation by checking the Python version in the command line/terminal.

PyCharm IDE Installation

• Download the latest PyCharm Community Edition from https://www.jetbrains.com/pycharm/download.
• Run the installer, following the steps for your operating system.

Python Basic Syntax

• First Python program: Use the print() function to display messages. Strings are enclosed in single, double, or triple quotes.

  print("Hello World!") 
  

Identifiers

• Names used to identify variables, functions, classes, modules, and other objects.
• Start with a letter (A-Z or a-z), underscore (_), followed by letters, underscores, and digits (0-9).
• Punctuation characters (@, $, %) are not allowed within identifiers.
• Python is case-sensitive, distinguishing between "Manpower" and "manpower."

Naming Conventions

• Class names begin with an uppercase letter.
• Other identifiers start with a lowercase letter.
• A single leading underscore indicates a private identifier.
• Two leading underscores indicate a strongly private identifier.

Standard Data Types

• Python Lists:

  • Versatile compound data type holding items separated by commas within square brackets ([]).
  • Similar to arrays in C but allowing diverse data types within a list.
  • Accessed using slice operator ([ ] and [:]) with indexes starting at 0.
  • Concatenated with (+) and repeated with (*).

• Python Tuples:

  • Similar to lists but enclosed in parentheses (()).
  • Immutable, meaning their elements and size cannot be changed.
  • Considered read-only lists.

• Python Dictionaries:

  • Hash table type, similar to associative arrays or hashes.
  • Consist of key-value pairs where keys can be any Python type (usually numbers or strings) and values can be any Python object.
  • Enclosed in curly braces ({}) and values are accessed using square brackets ([]).

Data Types Conversion

• Built-in functions convert values between data types. These functions return new objects.
  • int(): Converts to integer
  • float(): Converts to floating-point number
  • str(): Converts to string
  • complex(): Converts to complex number

Python Operators

• Arithmetic Operators:

  • + (addition)
  • - (subtraction)
  • * (multiplication)
  • / (division)
  • % (modulo)
  • ** (exponentiation)
  • // (floor division)

• Comparison Operators:

  • == (equal to)
  • != (not equal to)
  • > (greater than)
  • < (less than)
  • >= (greater than or equal to)
  • <= (less than or equal to)

• Assignment Operators:

  • = (assignment)
  • += (add and assign)
  • -= (subtract and assign)
  • *= (multiply and assign)
  • /= (divide and assign)
  • %= (modulo and assign)
  • **= (exponentiation and assign)
  • //= (floor division and assign)

• Bitwise Operators:

  • & (bitwise AND)
  • | (bitwise OR)
  • ^ (bitwise XOR)
  • ~ (bitwise NOT)
  • << (left shift)
  • >> (right shift)

• Logical Operators:

  • and (logical AND)
  • or (logical OR)
  • not (logical NOT)

• Membership Operators:

  • in (membership)
  • not in (non-membership)

• Identity Operators:

  • is (identity)
  • is not (non-identity)

Python Operators Precedence

• Operators have specific order of execution based on their precedence.
• Parentheses () are used to force a specific order of operations.

Python Functions

• Block of statements performing a specific task.

• Reusability: Avoid repetitive code by calling functions with different inputs.

• Function Syntax:

  def function_name(parameters):
      """Docstring: Explains what the function does."""
      statement(s)
  

• Docstring: The first string after the function header, used for documentation.

• Return Statement:

  • Exits the function and returns a value to the caller.
  • Syntax: return [expression_list]

• Function Arguments:

  • Required arguments: Passed in the correct order during function call.
  • Keyword arguments: Identified by parameter name during function call.
  • Default arguments: Assume default value if not provided.
  • Variable-length arguments: Handle more arguments than initially specified.

Python Sets

• Unordered collection of unique objects.

• Useful for creating lists with distinct values in large datasets.

• Mutable, allowing elements to be added or removed.

• Defining a Set:

  • Using set() function.
  • By listing elements within curly braces {}.
  • If set() has a list, string, or tuple as input, it returns a set of its elements.

• Creating a Set:

  my_set = {1, 2, 3}
  my_set = set([1, 2, 3]) 
  my_set = set("hello")
  

• Set Size and Membership:

  • len(): Returns the number of elements.
  • in and not in: Test for membership.

• Set Methods:

  • add(s): Adds an element.
  • discard(s): Removes an element (if present).
  • union(s): Returns the union of two sets.
  • intersection(s): Returns the intersection of two sets.
  • clear(s): Removes all elements.

• Accessing Values in a Set:

  • Individual values cannot be accessed directly.
  • Loop through the set to access elements.

• Compare Sets:

  • issubset(): Checks if one set is a subset of another.
  • issuperset(): Checks if one set is a superset of another.

Python Files

• Files are crucial for storage and retrieval of information.

• Basic file operations include:

  • open(): Opens a file with a specified mode: 'w' (writing), 'r' (reading), or 'a' (appending).
  • read(): Reads the entire file.
  • readline(): Reads one line at a time.
  • write(): Writes a string to a file.
  • close(): Closes the file.

• The open() Function:

  • Takes the filename and mode as arguments.
  • Example:

  file = open("myfile.txt", "r") 
  

Explore the fundamentals of Python, a versatile programming language popular for web development, machine learning, and data science. This quiz covers Python's history, features, and advantages, highlighting its readability and extensive standard library.