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Semester 1: Python Programming
Introduction - computer science basics, strings, assignment, comments, data types, loops, selection statements
Introduction to Computer Science Basics
Computer Science Fundamentals
Computer science is the study of computers and computational systems. It encompasses both the theoretical and practical aspects of computer technology, including algorithms, data structures, and software engineering.
Understanding Strings
Strings are sequences of characters used to represent text. In programming, strings can be manipulated through various operations such as concatenation, slicing, and searching.
Assignment in Programming
Assignment statements are used to assign values to variables. In Python, the '=' operator is used to store data in variables, allowing for dynamic manipulation of data throughout the program.
Comments in Code
Comments are annotations in the code that explain what the code does. They are ignored by the interpreter and are essential for documenting the code to improve readability and maintainability.
Data Types in Python
Python supports several data types including integers, floats, strings, and booleans. Each data type serves a specific purpose and has unique properties that affect how operations are performed.
Loops in Programming
Loops are used to execute a block of code repeatedly until a certain condition is met. Common types of loops include for loops and while loops, which help in efficiently processing collections of data.
Selection Statements
Selection statements allow the program to choose different paths of execution based on certain conditions. In Python, 'if', 'elif', and 'else' statements are used to control the flow of the program based on boolean expressions.
Strings and text files - accessing characters, encryption, string methods
Strings and Text Files
Accessing Characters
In Python, strings are sequences of characters. Each character in a string can be accessed using indexing. Indexing starts at zero, meaning the first character is at index 0. Negative indexing can also be used, with -1 referring to the last character of the string. Slicing allows for accessing a range of characters in a string using a start and stop index.
String Methods
Python provides several built-in methods for string manipulation. Some common methods include .lower(), .upper(), .strip(), .find(), .replace(), and .split(). These methods enable transformation of character cases, removal of whitespace, searching for characters, replacing substrings, and splitting strings into lists.
Text Files Handling
Python provides functionalities to work with text files through the open() function. Files can be opened in various modes, including read (r), write (w), and append (a). The read() method reads the entire content of the file, while readlines() reads line by line. Closing a file using close() is important to free up resources.
Encryption of Strings
String encryption can be performed using various algorithms. Python libraries such as cryptography or hashlib can be utilized for encrypting and decrypting strings. Symmetric encryption requires a shared key, while asymmetric encryption uses a pair of keys (private and public). The choice of encryption method depends on the security requirements.
Design with functions - top-down design, recursion, namespaces, higher-order functions
Design with functions
Top-down design
Top-down design is a methodology that divides a system into smaller parts, making it easier to manage complexity. It starts with the main function and breaks it down into subtasks or sub-functions, allowing for clear hierarchy and better organization. This approach helps in identifying the necessary functions prototype early, encouraging a structured program development process.
Recursion
Recursion is a powerful programming technique where a function calls itself to solve a problem. It is often used to break down complex problems into simpler subproblems. Each recursive call should bring the solution closer to a base case, which is necessary to terminate the recursive calls and avoid infinite loops. Understanding recursion is crucial for solving problems like factorial calculation, Fibonacci series, and tree traversals.
Namespaces
Namespaces are a way of organizing code in Python, preventing naming conflicts by encapsulating variables and functions. They allow for the definition of identically named items in different contexts. Python uses built-in namespaces, global namespaces, and local namespaces to manage scope. Understanding namespaces is essential for writing clear and maintainable Python code.
Higher-order functions
Higher-order functions are functions that take other functions as arguments or return them as results. They provide a powerful way to abstract and encapsulate behavior. Common examples of higher-order functions in Python include map, filter, and reduce. Using higher-order functions can lead to more concise and readable code by allowing for functional programming styles.
Classes and OOP - objects, inheritance, polymorphism, GUI basics, terminals and events
Classes and OOP
Objects
Objects are instances of classes that encapsulate data and methods. They represent real-world entities and have attributes (data) and behaviors (methods). In Python, objects are created from classes and can be manipulated through their methods.
Inheritance
Inheritance is a mechanism where a new class, known as a child class, derives properties and behavior from an existing class, known as a parent class. This allows for code reusability and the establishment of a hierarchical relationship between classes.
Polymorphism
Polymorphism allows objects of different classes to be treated as objects of a common superclass. It enables a single interface to represent different underlying data types. In Python, polymorphism is often implemented through method overriding and operator overloading.
GUI Basics
Graphical User Interface (GUI) is an interface that allows users to interact with software through graphical elements rather than text-based commands. In Python, libraries such as Tkinter and PyQt are commonly used to create rich GUI applications.
Terminals and Events
Terminals enable users to interact with applications through command-line interfaces. Events are actions or occurrences that can be detected by the program, such as mouse clicks or key presses. In GUI applications, event-driven programming is used to manage user interactions and respond to events.
Python packages - NumPy ndarray, pandas series and dataframe, matplotlib visualization
Python packages - NumPy ndarray, pandas series and dataframe, matplotlib visualization
NumPy ndarray
NumPy is a foundational package for numerical computing in Python. The main feature of NumPy is the ndarray (n-dimensional array), which is a powerful N-dimensional array object. Key points include: 1. Multidimensional array: Supports arrays of arbitrary dimensions. 2. Element-wise operations: Allows for fast operations on arrays. 3. Broadcasting: Enables arithmetic operations between arrays of different shapes. 4. Integration with other libraries: Compatible with libraries like SciPy and Matplotlib.
Pandas Series
Pandas is a powerful data manipulation library. A Series is a one-dimensional labeled array capable of holding any data type. Key features include: 1. Flexible: Allows different data types in one series. 2. Indexing: Each value has an associated label or index. 3. Operations: Supports vectorized operations for data manipulation.
Pandas DataFrame
A DataFrame is a two-dimensional labeled data structure similar to a table in a database or a spreadsheet. Key attributes include: 1. Labeled axes: Both rows and columns have labels. 2. Data alignment: Automatic alignment for arithmetic operations. 3. Data manipulation: Provides functions for merging, reshaping, and aggregating data.
Matplotlib Visualization
Matplotlib is a plotting library for Python, providing a variety of plotting options. Key components include: 1. Figure and Axes: Fundamental objects for creating plots. 2. Plot types: Supports line plots, scatter plots, bar charts, and more. 3. Customization: Allows extensive customization for axes, titles, and labels. 4. Integration: Works well with NumPy and Pandas for visualizing data.
Django - installation, project creation, schema design, admin site, QuerySets, views
Django
Installation
To install Django, use the command pip install django. Ensure that Python and pip are already installed on your system.
Project Creation
To create a new Django project, use the command django-admin startproject projectname. This will create a new directory with necessary files.
Schema Design
Schema design in Django involves defining models. A model is a Python class that defines the structure of your data.
Admin Site
Django includes an auto-generated admin interface. To create an admin interface, register your models in admin.py. Access it by visiting /admin in the browser.
QuerySets
QuerySets are used to retrieve data from the database. They use methods like filter, exclude, and all to interact with the data.
Views
Views handle the logic of your application. They can return HTML content, redirect to another page, or return a 404 error.
