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Draw a car using Turtle in Python

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Prerequisite: Turtle module , Drawing Shapes

There are many modules in python which depict graphical illustrations, one of them is a turtle , it is an in-built module in Python, which lets the user control a pen( turtle ) to draw on the screen(drawing board). It is mostly used to illustrate figures, shapes, designs, etc.  In this article, we will learn how to draw a Car using the turtle module. 

To draw a car in Python using the Turtle module:

• We are going to create different shapes using the turtle module in order to illustrate a car.
• Tyres can be drawn using the circle() function.
• The upper body can be thought of as a rectangle.
• The roof and windows are similar to a trapezoid.
• Overlapping all the above shapes in particular positions will illustrate a car.

  Let’s try to understand it better with the help of the below program:

Output:  

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Markov decision processes (MDPs) can be used to model situations with uncertainty (which is most of the time in the real world). In this assignment, you will implement algorithms to find the optimal policy, even you know the transitions and rewards (value iteration) and when you don't (reinforcement learning). You will use these algorithms on Mountain Car, a classic control environment where the goal is to control a car to go up a mountain.

Problem 1: Value Iteration

Problem 2: transforming mdps.

In computer science, the idea of a reduction is very powerful: say you can solve problems of type A, and you want to solve problems of type B. If you can convert (reduce) any problem of type B to type A, then you automatically have a way of solving problems of type B potentially without doing much work! We saw an example of this for search problems when we reduce A* to UCS. Now let's do it for solving MDPs.

Let us define a new MDP with states $\text{States}' = \text{States} \cup \{ o \}$, where $o$ is a new state. Let's use the same actions ($\text{Actions}'(s) = \text{Actions}(s)$), but we need to keep the discount $\gamma' = 1$. Your job is to define transition probabilities $T'(s' | s, a)$ and rewards $\text{Reward}'(s, a, s')$ for the new MDP in terms of the original MDP such that the optimal values $V_\text{opt}(s)$ for all $s \in \text{States}$ are equal under the original MDP and the new MDP.

Problem 3: Value Iteration on Mountain Car

Now that we have gotten a bit of practice with general-purpose MDP algorithms, let's use them for some control problems. Mountain Car is a classic example in robot control [7] where you try to get a car to the goal located on the top of a steep hill by accelerating left or right. We will use the implementation provided by The Farama Foundation's Gymnasium, formerly OpenAI Gym.

The state of the environment is provided as a pair (position, velocity). The starting position is randomized within a small range at the bottom of the hill. At each step, the actions are either to accelerate to the left, to the right, or do nothing, and the transitions are determined directly from the physics of a frictionless car on a hill. Every step produces a small negative reward, and reaching the goal provides a large positive reward.

First, install all the dependencies needed to get Mountain Car running in your environment. Note that we are using Python 3.7 for this assignment.

pip3 install -r requirements.txt

Then to get the feel for the environment, test with an untrained agent which takes random action at each step and see how it performs.

python3 mountaincar.py --agent naive

You will see the agent struggling, not able to complete the task within the time limit. In this assignment, you will train this agent with different reinforcement learning algorithms so that it can learn to climb the hill. As the first step, we have designed two MDPs for this task. The first uses the car's continuous (position, velocity) state as is, and the second discretizes the position and velocity into bins and uses indicator vectors. Carefully examine ContinuousGymMDP and DiscreteGymMDP classes in util.py and make sure you understand.

If we want to apply value iteration to the DiscreteGymMDP (think about why we can't apply it to ContinuousGymMDP ), we require the transition probabilities $T(s, a, s')$ and rewards $R(s, a, s')$ to be known. But oftentimes in the real world, $T$ and $R$ are unknown, and the gym environments are set up in this way as well, only interfacing through the .step() function. One method to still determine the optimal policy is model-based value iteration, which runs Monte Carlo simulations to estimate $\hat{T}$ and $\hat{R}$, and then runs value iteration. This is an example of model-based RL. Examine RLAlgorithm in util.py to understand the getAction and incorporateFeedback interface and peek into the simulate function to see how they are called repeatedly when training over episodes.

• As a warm up, we will start with implementing value iteration as you learned in lectures, and run it on the number line MDP from Problem 1. Complete valueIteration function in submission.py .
• Now in submission.py , implement ModelBasedMonteCarlo which runs valueIteration every calcValIterEvery steps that the RL agent operates. The getAction method controls how we use the latest policy as determined by value iteration, and the incorporateFeedback method updates the transition and reward estimates, calling value iteration when needed. Implement the getAction and incorporateFeedback methods for ModelBasedMonteCarlo .
• Run train.py --agent value-iteration to train the agent using model based value iteration you implemented above and see the plot of reward per episode. Comment on the plot, and discuss when might model based value iteration perform poorly. You can also run mountaincar.py --agent value-iteration to visually observe how the trained agent performs the task now. 2-3 sentences describing the plot and discussion of when model based value iteration may fail.

Problem 4: Q-Learning Mountain Car

In the previous question, we've seen how value iteration can take an MDP which describes the full dynamics of the game and return an optimal policy, and we've also seen how model-based value iteration with Monte Carlo simulation can estimate MDP dynamics if unknown at first and then learn the respective optimal policy. But suppose you are trying to control a complex system in the real world where trying to explicitly model all possible transitions and rewards is intractable. We will see how model-free reinforcement learning can nevertheless find the optimal policy.

• For a discretized MDP, we have a finite set of (state, action) pairs. We learn the Q-value for each of these pairs using the Q-learning update learned in class. In the TabularQLearning class, implement the getAction method which selects action based on explorationProb , and the incorporateFeedback method which updates the Q-value given a (state, action) pair.
• For Q-learning in continuous states, we need to use function approximation. The first step of function approximation is extracting features given state. Feature extractors of different complexities work well with different problems: linear and polynomial feature extractors that work well with simpler problems may not be suitable for other problems. For the mountain car task, we are going to use a Fourier feature extractor. As background, any continuous periodic function can be approximated as a Fourier Series $$f(x) = \frac{a_0}{2} + \sum_{j=1}^n\left[a_j\cos(2\pi j x/T) + b_j\sin(2\pi j x/ T)\right]$$ with $a_j$ and $b_j$ sequences of coefficients determined by integrating $f$. To apply this to Q-learning with function approximation, we want the learned weights $w$ to emulate $a_j$ and $b_j$ and the output of $\phi$ to provide the basis of varying sinusoid periods as seen in $\cos(2\pi j x/T)$ for $j = 1, 2, \ldots, n$ [1] . Thus, for state $s = [s_1, s_2, \ldots, s_k]$, action $a$, and maximum coefficient $c$, the feature extractor $\phi$ is: $$\phi(s, a, c) = [\cos(0), \cos(s_1), \ldots, \cos(s_k), \cos(2s_1), \cos(s_1+s_2), \ldots, \cos(cs_1 + cs_2 + \ldots + cs_k)]$$ $$= \left\{\cos\left(\sum_{i=1}^k c_i s_i\right): \forall c_1\in\mathscr{C}, \ldots, c_k\in\mathscr{C}\right\}$$ where $\mathscr{C} = \{0, 1, \ldots, c\}$ is the set of non-negative integers from 0 to $c$. Note that $\phi(s, a, c) \in \mathbb{R}^{(c+1)^k}$. Implement fourierFeatureExtractor in submission.py . Looking at util.polynomialFeatureExtractor may be useful for familiarizing oneself with numpy.
• Now we can find the Q-value of each (state, action) by multiplying the extracted features from this pair with weights. Unlike the tabular Q-learning in which Q-values are updated directly, with function approximation, we are updating weights associated with each feature. Using fourierFeatureExtractor from the previous part, complete the implementation of FunctionApproxQLearning .
• Run train.py --agent tabular and train.py --agent function-approximation to see the plots for how the TabularQLearning and FunctionApproxQLearning work respectively, and comment on the plots. You should expect to see that tabular Q-learning performs better than function approximation Q-learning on this task. What might be some of the reasons? You can also run python3 mountaincar.py --agent tabular and python3 mountaincar.py --agent function-approximation to visualize the agent trained with continuous and discrete MDP respectively.
• What are some possible benefits of function approximation Q-learning for mountain car or other environments? Consider the situations where the exploration period is limited, where the state space is very high dimensional and difficult to explore, and/or you have space constraints.

Problem 5: Safe Exploration

We learned about different state exploration policies for RL in order to get information about $(s, a)$. The method implemented in our MDP code is epsilon-greedy exploration, which balances both exploitation (choosing the action $a$ that maximizes $\hat{Q}_{\text{opt}}(s, a))$ and exploration (choosing the action $a$ randomly). $$\pi_{\text{act}}(s) = \begin{cases} \arg\max_{a \in \text{Actions}}\hat{Q}_{\text{opt}}(s,a) & \text{probability } 1 - \epsilon \\ \text{random from Actions}(s) & \text{probability } \epsilon \end{cases}$$

In real-life scenarios when safety is a concern, there might be constraints that need to be set in the state exploration phase. For example, robotic systems that interact with humans should not cause harm to humans during state exploration. Safe exploration in RL is thus a critical research question in the field of AI safety and human-AI interaction [2] .

Safe exploration can be achieved via constrained RL. Constrained RL is a subfield of RL that focuses on optimizing agents' policies while adhering to predefined constraints - in order to ensure that certain unsafe behaviors are avoided during training and execution.

Assume there are harmful consequences for the driver of the Mountain Car if the car exceeds a certain velocity. One very simple approach of constrained RL is to restrict the set of potential actions that the agent can take at each step. We want to apply this approach to restrict the states that the agent can explore in order to prevent reaching unsafe speeds.

• The implementation of the Mountain Car MDP you built in the previous questions actually already has velocity constraints in the form of a self.max_speed parameter. Read through OpenAI Gym's Mountain Car implementation and explain how self.max_speed is used. One sentence on how self.max_speed parameter is used in mountain_car.py
• Run Function Approximation Q-Learning without the max_speed constraint by running python3 train.py --agent function-approximation --max_speed=100000 . We are changing max_speed from its original value of 0.07 to a very large float to approximate removing the constraint entirely. Notice that running the MDP unconstrained doesn't really change the output behavior. Explain in 1-2 sentences why this might be the case. One sentence explaining why the Q-Learning result doesn't necessarily change.
• Consider a different way of setting the constraint where you limit the set of actions the agent can take in the action space. In ConstrainedQLearning , implement constraints on the set of actions the agent can take each step such that velocity_(t+1) . Remember to handle the case where the set of valid actions is empty. Below is the equation that Mountain Car uses to calculate velocity at time step $t+1$ (the equation is also provided here ). $$\text{velocity}_{t+1} = \text{velocity}_t + (\text{action} - 1) * \text{force} - \cos(3 * \text{position}_t) * \text{gravity}$$ We've determined that in the mountain car environment, a velocity of 0.065 is considered unsafe. After implementing the velocity constraint, run grader test 5c-helper to examine the optimal policy for two continuous MDPs running Q-Learning (one with max_speed of 0.065 and the other with a very large max_speed constraint). Provide 1-2 sentences explaining why the output policies are now different. Complete the implementation of ConstrainedQLearning in submission.py , then run python3 grader.py 5c-helper . Include 1-2 sentences explaining the difference in the two scenarios.
• Respect for persons : Participation as a research subject is voluntary, and follows from informed consent; Treat individuals as autonomous agents and respect their right to determine their own best interests; Respect individuals who are not targets of research yet are impacted; Individuals with diminished autonomy, who are incapable of deciding for themselves, are entitled to protection.
• Beneficence : Do not harm; Maximize probably benefits and minimize probable harms; Systematically assess both risk of harm and benefit.
• Justice : Each person deserves equal consideration in how to be treated, and the benefits of research should be fairly distributed according to individual need, effort, societal consideration, and merit; Selection of subjects should be fair, and burdens should be allocated equitably across impacted subjects.
• Respect for Law and Public Interest : Engage in legal due diligence; Be transparent in methods and results; Be accountable for actions.

[1] Konidaris et al. Value Function Approximation in Reinforcement Learning using the Fourier Basis. AAAI. 2011.

[2] OpenAI. Benchmarking Safe Exploration in Deep Reinforcement Learning

[3] The Centers for Disease Control and Prevention. The Untreated Syphilis Study at Tuskegee Timeline.

[4] The US Department of Health and Human Services. The Belmont Report. 1978.

[5] The World Medical Association. The Declaration of Helsinki. 1964.

[6] The US Department of Homeland Security. The Menlo Report. 2012.

[7] Moore. Efficient Memory-based Learning for Robot Control. 1990.

50+ Python Projects with Source Code: Beginner to Advanced

By Faraz - February 17, 2024

Popular 50+ Python projects with source code, suitable for all skill levels. From basic to advanced, start coding today! #PythonProjects

Table of Contents

Introduction to python projects.

Python is a versatile programming language known for its simplicity and readability. It's widely used in various domains such as web development, data analysis, machine learning, automation, and more. One of the best ways to master Python is by working on projects. In this blog post, we present a comprehensive collection of over 50 Python projects complete with source code. Whether you're a beginner looking to practice your skills or an experienced programmer seeking new challenges, these projects offer something for everyone.

1. Alarm Clock

Are you looking to build your Python skills while creating something useful? Start with a simple yet practical project like an Alarm Clock. With Python, you can code an alarm clock that wakes you up with your favorite tune or a custom message.

2. Calculator

Mastering Python isn't just about complex algorithms; it's also about solving everyday problems. Build a calculator using Python to perform basic arithmetic operations. It's a great way to understand functions, user input, and mathematical operations in Python.

3. QR Code Generator

QR codes are everywhere these days, and understanding how to generate them using Python can be a valuable skill. Create a QR code generator application that allows users to input text or a URL and generates a QR code image that they can save or share.

4. Password Generator

Security is crucial, especially in the digital age. Develop a password generator application in Python that creates strong and random passwords based on user-defined criteria such as length and character types. It's a practical project that enhances your skills while promoting cybersecurity.

5. Guess the Number

Embark on a classic programming challenge by creating a "Guess the Number" game in Python. Challenge the user to guess a randomly generated number within a certain range. This project will reinforce your understanding of loops, conditionals, and user interaction in Python.

6. Age Calculator

Explore date and time manipulation in Python by building an Age Calculator. Allow users to input their birthdate, and then calculate and display their age in years, months, and days. It's a practical application that demonstrates Python's datetime module functionalities.

7. Weather Forecast App

Combine your Python skills with web scraping to develop a Weather Forecast App. Utilize APIs or web scraping techniques to fetch real-time weather data from online sources and present it in a user-friendly interface. This project will enhance your knowledge of data retrieval and visualization in Python.

8. Photo Compressor

Optimize images with a Python-based Photo Compressor. Create an application that reduces the file size of images while preserving their quality. You can explore image processing libraries like Pillow to implement various compression techniques and improve your understanding of image manipulation in Python.

9. Vending Machine

Simulate the functionality of a vending machine using Python. Design a program that allows users to select items, input payment, and receive their chosen product. This project will help you grasp concepts such as conditionals, loops, and data structures while simulating real-world scenarios.

10. Youtube Downloader

Build a Youtube Downloader application in Python to download videos from YouTube. Utilize third-party libraries like pytube to fetch video URLs, download videos, and save them to the local filesystem. This project will introduce you to working with APIs and handling multimedia data in Python.

11. Typing Speed Test

Sharpen your typing skills while practicing Python programming with a Typing Speed Test project. Develop an application that prompts users to type a passage within a specified time limit and calculates their words per minute (WPM) and accuracy. This project will enhance your understanding of string manipulation and timing functions in Python.

12. Currency Converter

Dive into the world of financial applications by creating a Currency Converter in Python. Utilize exchange rate APIs or manually input conversion rates to allow users to convert between different currencies. This project will deepen your understanding of data manipulation and user input handling in Python.

13. Quiz Application

Create an interactive Quiz Application using Python to challenge users with a variety of questions. Implement features such as multiple-choice, true/false, and fill-in-the-blank questions, along with scoring and feedback mechanisms. This project will reinforce your knowledge of data structures and user interfaces in Python.

14. Word Counter

Enhance your text processing skills by building a Word Counter application in Python. Develop a program that analyzes text input and calculates the frequency of each word, along with other statistics such as total words and unique words. This project will strengthen your understanding of dictionaries, strings, and file handling in Python.

15. Bitcoin Price Tracker

Stay up-to-date with cryptocurrency trends by creating a Bitcoin Price Tracker in Python. Fetch real-time Bitcoin prices from cryptocurrency APIs and display them in a graphical or text-based interface. This project will introduce you to working with APIs and handling JSON data in Python.

16. MP3 Player

Immerse yourself in the world of multimedia applications by developing an MP3 Player in Python. Utilize libraries like pygame or tkinter to create a graphical user interface (GUI) that allows users to play, pause, stop, and navigate through their music library. This project will enhance your understanding of audio playback and GUI programming in Python.

17. Generate Random Jokes

Inject some humor into your Python projects by building a Random Jokes Generator. Fetch jokes from online APIs or create a collection of jokes and randomly select and display them to the user. This project will reinforce your skills in working with APIs, strings, and randomization in Python.

18. Text Editor/Notepad

Create a simple Text Editor or Notepad application in Python to manage and edit text files. Implement features such as opening, editing, saving, and formatting text, along with functionalities like search and replace. This project will deepen your understanding of file handling and GUI programming in Python.

19. Digital Clock

Explore graphical user interfaces (GUIs) in Python by building a Digital Clock application. Design a clock interface that displays the current time and updates in real-time. You can use libraries like tkinter or pygame to create the GUI elements and handle time-related functionalities. This project will enhance your knowledge of GUI programming and event handling in Python.

20. Flappy Bird

Challenge yourself with game development by creating a Flappy Bird clone in Python. Utilize libraries like pygame to design the game mechanics, graphics, and user interface. Implement features such as bird movement, pipe generation, collision detection, and scoring. This project will deepen your understanding of game development concepts and object-oriented programming (OOP) in Python.

21. Brick Breaker Game

Experience the thrill of classic arcade gaming by developing a Brick Breaker game in Python. Use libraries like pygame to create the game environment, paddle, ball, and bricks. Implement features such as ball movement, collision detection, power-ups, and scoring. This project will reinforce your understanding of game physics and event handling in Python.

22. Captcha Generator

Protect websites from spam and bots by creating a Captcha Generator in Python. Design an application that generates random Captcha images with distorted text, which users must correctly identify to proceed. This project will deepen your understanding of image manipulation and randomization in Python.

23. Scientific Calculator

Delve into advanced mathematical concepts with a Scientific Calculator project in Python. Develop a calculator application that supports functions like trigonometry, logarithms, exponents, and more. This project will challenge you to implement complex mathematical algorithms and enhance your problem-solving skills in Python.

24. PDF 2 Image Converter

Unlock the potential of document processing by creating a PDF to Image Converter in Python. Utilize libraries like PyPDF2 and Pillow to extract pages from PDF files and convert them into image formats like JPEG or PNG. This project will introduce you to working with different file formats and image processing techniques in Python.

25. Hash Cracker

Explore the world of cryptography by developing a Hash Cracker application in Python. Design a program that can crack hashed passwords using techniques like dictionary attacks or brute force. This project will deepen your understanding of encryption algorithms, string manipulation, and cybersecurity concepts in Python.

26. Python Bounce Game

Immerse yourself in game development by creating a Python Bounce Game. Utilize libraries like pygame to design the game environment, ball, and paddles. Implement features such as ball movement, collision detection, and scoring. This project will deepen your understanding of game physics and event handling in Python.

27. Dino Game

Explore the world of web browser games by recreating the classic Dino Game from Google Chrome's offline mode. Use libraries like pygame to design the game environment and implement features such as jumping, ducking, and avoiding obstacles. This project will challenge you to create a game with simple mechanics while honing your skills in Python.

28. PNG to JPG

Expand your image processing skills by developing a PNG to JPG Converter in Python. Utilize libraries like Pillow to load PNG images, convert them to JPG format, and save them to the local filesystem. This project will deepen your understanding of image file formats and manipulation techniques in Python.

29. Connect Four Game

Challenge yourself with board game development by creating a Connect Four game in Python. Design the game board, pieces, and rules, and implement features such as dropping pieces, checking for win conditions, and handling player turns. This project will reinforce your understanding of game logic and algorithms in Python.

30. Car Race Game

Experience the thrill of racing games by developing a Car Race Game in Python. Utilize libraries like pygame to design the game environment, cars, and tracks. Implement features such as car movement, collision detection, and scoring. This project will deepen your understanding of game physics and simulation in Python.

31. Digital Certificate Creation

Enter the realm of cybersecurity by developing a Digital Certificate Creation tool in Python. Design a program that generates digital certificates using cryptographic techniques such as public-key encryption. This project will deepen your understanding of cryptography and secure communication protocols in Python.

32. Chatbot

Explore the exciting field of natural language processing (NLP) by creating a Chatbot in Python. Design an interactive conversational agent that can respond to user inputs and engage in meaningful conversations. This project will introduce you to NLP libraries like NLTK or spaCy and enhance your skills in text processing and machine learning in Python.

33. Rock Paper Scissors Game

Relive the timeless fun of the Rock Paper Scissors game by creating your own version in Python. Design the game mechanics, user interface, and implement features such as player input, computer AI, and scoring. This project will reinforce your understanding of conditional statements and randomization in Python.

34. Music Player

Immerse yourself in multimedia applications by developing a Music Player in Python. Utilize libraries like pygame or tkinter to create a graphical user interface (GUI) that allows users to play, pause, stop, and navigate through their music library. This project will enhance your understanding of audio playback and GUI programming in Python.

35. Restaurant Management System

Explore the world of software solutions for businesses by developing a Restaurant Management System in Python. Design a program that allows restaurant staff to manage orders, inventory, and customer information efficiently. This project will deepen your understanding of data management and user interface design in Python.

36. Python Dictionary

Dive into data structures by creating a Python Dictionary application. Design a program that allows users to add, remove, and search for entries in a dictionary. Implement features such as key-value pair management and dictionary manipulation. This project will reinforce your understanding of dictionaries and data organization in Python.

37. Test Internet Speed

Monitor your internet connection with a Test Internet Speed tool in Python. Design a program that measures the download and upload speeds of your internet connection and displays the results. This project will introduce you to network programming concepts and enhance your skills in working with external APIs in Python.

38. Task Management System

Stay organized and productive with a Task Management System in Python. Design an application that allows users to create, update, and track tasks and deadlines. Implement features such as task categorization, priority levels, and reminder notifications. This project will deepen your understanding of data management and user interaction in Python.

39. To-do List

Simplify your daily tasks with a To-do List application in Python. Design a program that allows users to create, edit, and delete tasks, along with setting deadlines and reminders. Implement features such as task categorization, sorting, and search functionalities. This project will enhance your skills in working with lists and user interfaces in Python.

40. WebScraper

Explore web scraping techniques by developing a WebScraper in Python. Design a program that extracts data from websites and saves it for further analysis or processing. Implement features such as data extraction, parsing, and storage. This project will deepen your understanding of web technologies and data manipulation in Python.

41. Paint Application

Unleash your creativity with a Paint Application in Python. Design a program that allows users to draw, paint, and manipulate images using various tools and brushes. Implement features such as color selection, brush sizes, and saving and exporting artwork. This project will enhance your understanding of graphical user interfaces (GUIs) and image processing in Python.

42. School Management System

Streamline educational processes with a School Management System in Python. Design an application that manages student records, class schedules, grades, and attendance. Implement features such as user authentication, data encryption, and reporting functionalities. This project will deepen your understanding of data management and security in Python.

43. Translator / Language Converter

Bridge language barriers with a Translator or Language Converter application in Python. Design a program that translates text or phrases between different languages using translation APIs or libraries. Implement features such as language detection, input validation, and user-friendly interfaces. This project will introduce you to working with external APIs and text processing in Python.

44. Hangman Game

Challenge your vocabulary and logic skills with a Hangman Game in Python. Design a program that randomly selects a word for the player to guess, with limited attempts. Implement features such as displaying the hangman figure and tracking incorrect guesses. This project will reinforce your understanding of strings, loops, and user interaction in Python.

45. Chess Game

Enter the world of strategy and tactics with a Chess Game in Python. Design a program that simulates a chessboard, pieces, and rules, allowing players to compete against each other or against a computer AI. Implement features such as legal move validation, check detection, and checkmate conditions. This project will challenge you to implement complex game logic and algorithms in Python.

46. Minesweeper Game

Test your puzzle-solving skills with a Minesweeper Game in Python. Design a program that generates a grid of cells containing hidden mines, and allows the player to uncover cells without detonating any mines. Implement features such as mine placement, cell revealing, and game logic. This project will reinforce your understanding of nested loops, conditionals, and algorithms in Python.

47. Ping Pong Game

Experience the excitement of classic arcade gaming with a Ping Pong Game in Python. Design a program that simulates a virtual ping pong table, allowing two players to compete against each other. Implement features such as paddle movement, ball physics, and scoring. This project will enhance your understanding of game mechanics and event handling in Python.

48. Snake Game

Relive the nostalgia of old-school gaming with a Snake Game in Python. Design a program that simulates a snake moving around a grid, eating food to grow longer while avoiding collisions with itself and the walls. Implement features such as snake movement, food generation, and scoring. This project will deepen your understanding of game logic and data structures in Python.

49. Memory Tile Game

Challenge your memory and concentration with a Memory Tile Game in Python. Design a program that generates a grid of tiles, each containing a hidden image or symbol. Implement features such as tile flipping, matching pairs, and scoring. This project will reinforce your understanding of graphical user interfaces (GUIs) and event handling in Python.

50. Sudoku Solver

Master the art of puzzle-solving with a Sudoku Solver in Python. Design a program that can solve Sudoku puzzles of varying difficulties using algorithms such as backtracking or constraint propagation. Implement features such as puzzle input, solution validation, and step-by-step solving. This project will challenge you to implement advanced algorithms and enhance your problem-solving skills in Python.

51. Tic Tac Toe Game

Enjoy a timeless classic with a Tic Tac Toe Game in Python. Design a program that simulates a Tic Tac Toe board, allowing two players to take turns marking spaces until one player wins or the board is full (resulting in a draw). Implement features such as player input, win detection, and replayability. This project will reinforce your understanding of game logic and conditional statements in Python.

52. 2048 Game

Experience the addictive gameplay of 2048 with a Python implementation of the game. Design a program that generates a grid of numbered tiles, allowing players to combine matching tiles by sliding them across the board. Implement features such as tile movement, merging, and scoring. This project will deepen your understanding of game mechanics and algorithms in Python.

Python projects with source code offer an excellent opportunity to enhance your programming skills and explore various domains. Whether you're interested in web development, data analysis, machine learning, or just looking for fun projects to try, there's something for everyone in this diverse collection. Start coding, learning, and building with Python today!

Q1. How can I get started with Python projects?

Begin by learning the basics of Python programming and then gradually progress to more complex projects. You can find project ideas online or create your own based on your interests.

Q2. Are there any prerequisites for working on Python projects?

Having a basic understanding of Python syntax and programming concepts is helpful. Additionally, familiarity with relevant libraries and frameworks for your chosen project domain can be beneficial.

Q3. Where can I find Python project ideas?

You can find project ideas on websites, forums, and GitHub repositories dedicated to Python projects. Additionally, brainstorming based on your interests and goals can help generate project ideas.

Q4. How do Python projects contribute to skill development?

Python projects provide hands-on experience, allowing developers to apply theoretical knowledge to practical scenarios. They also encourage problem-solving and foster creativity, leading to skill development.

Q5. Why is community involvement important in Python projects?

Community involvement allows developers to learn from others, collaborate on projects, and receive feedback on their work. It also fosters a sense of belonging and contributes to the growth of the Python community.

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• Homework answers

Answer to Question #296146 in HTML/JavaScript Web Application for chethan

the goal of this code is to get output using with Classes.

first line of input contains a string playerName

second line of input contains a number nitro

third line of input contains a number speed

the output contains multiple lines with the appropriate texts

Race has started

Speed 50; Nitro 50

speed 70; Nitro 60

Alyssa is the winner

Speed 0; Nitro 60

function readLine() {

 return inputString[currentLine++];

 // Create your Super Class Race and Sub Class Car here

function main() {

 const playerName = readLine();

 const nitro = JSON.parse(readLine());

 const speed = JSON.parse(readLine());

 const car1 = new Car(playerName, nitro, speed);

 console.log(car1.startRace());

 car1.nitroBoost();

 console.log(`Speed ${car1.speed}; Nitro ${car1.nitro}`);

 car1.accelerate();

 console.log(car1.endRace());

 car1.applyBreak();

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BryanHJH/Python-Car-Rental-Program-Assignment

Folders and files, repository files navigation, 1. introduction, 2.1 python files, 2.2 text files, 2.3 pdf files, 3.1 youtube, 4.1.1 role selection screen, 4.1.2 register screen, 4.1.3 login screen, 4.2.1 option screen, 4.2.2 add cars to be rented out, 4.2.3 modifying car details, 4.2.4 displaying all records, 4.2.5 displaying specific records, 4.2.6 return a rented car, 4.3.1 displaying all records, 4.4.1 modifying personal details, 4.4.2 view personal purchase history, 4.4.3 view detail of cars to be rented out, 4.4.4 renting a car for a duration, 4.4.5 making payment, 5.1 navigation between options, choose an option, please type the name of the car that you wish to modify[press y to return to main menu]: (input).

The program that is written is for APU UCDF2005(DI) Python Assignment.

The assignment requires us to write out a car rental system with people logging in with different roles. Each role will have a text file containing their login credentials, named after their roles. (e.g. role: admin, text file: admin_login_credentials.txt)

Every role will have different priveleges. All priveleges are listed in the Assignment File .

2. Expected files

This section contains all the expected files for this assignment.

• main.py: The python file where all the code goes
• customer2.txt: Text file contaning all credentials of users, including the usernames, passwords, names, age, address, contact no. and so on
• car2.txt: Text file containing the details of cars, including car names, brand, model, status (available or rented), duration being rented, price
• admin2.txt: Text file containing the details of Admins
• Documentation: Converted from a Word file about the program written.
• Instruction/Assignment Question: Assignment File

3. Links to Reference

• Python Tutorial: Create a Simple Login System Using a Text File
• python login system tutorial (For beginners) Python Tutorial
• [Searching and Replacing specific text in a file](C:\Users\Asus\Downloads\Python\APU Python lecture and tutorial\Lab 5\Q4.py)
• [Searching and replacing specific text in a file](C:\Users\Asus\Downloads\Python\APU Python lecture and tutorial\replacing string in file\test.py)

4. Flow of Program

4.1 for both roles (customer and admin).

• It would show the 2 options (Admin & Customer) or 3 options (Admin, Member, Other). For other, it is the unregistered customer. If use 3 options, the "Skip" in register screen will useless
• If it is customer , there would be an extra option which is "Skip" for the user to not register or login as they might just want to browse through the catalog
• When registering, we need to include details other than username and password. Other details (listed below) must also be included.
• All details will be appended into the text file
• IC/Passport number (4)
• Admin ID (For Admins Only)
• Phone Number
• Payment/Amount Paid (For Customers Only)
• Amount Due (For Customers Only)
• Bookings (For Customers Only)
• No. of Cars Rented/Purchase History (For Customers Only)
• Rental Duration (For Customers Only)
• Admin and Customers will have their information appended to different files, which will be accepted as an argument in register() function.
• Before registering, the system must check whether the user is already registered (It can be in another function or be in the same function)
• User will need to input their username/email and password
• Validation of the input will be done in another function named validate_user()
• One function for accessing the user's priveleges. Differentiated by their role
• Just use quit() or break.

4.2 For Admin

• List out all their privileges/options that are listed in the Assignment File .
• A text file called Car_Records.txt is available with the Car Name, Car Brand, Car Model, Seats, Fuel Type, How many doors, How many luggage can it carry, Short description, Status(rented, pending, available), duration left being rented(if status is rented) Reference from Avis
• To add these details, open the file using open(filename, 'a') and then write to the file.
• Plate Number*
• Owner's name
• Duration left being rented
• Short Description*
• Car Details should be saved as a list
• Able to modify all car details as well as removing the details.
• To modify the details, first check for the car name and owner's name (using if...else statement) and then use filename.replace('word_to_be_changed', 'new_word'). Reference
• Can be made into a function that accepts 2 arguments ('word_to_be_changed', 'new_word').
• To display only cars that are rented out , can use if...else statement to filter out the Status of the cars then print them out. (Refer to the Cars_Records.txt)
• To display only cars that are available , can use if...else statement to filter out the Status of the cars then print them out. (Refer to the Cars_Records.txt)
• To display only customers' bookings (Refer to the Customer_Records.txt)
• To display only customers' payment (Refer to the Customer_Records.txt)
• When user select options 1 and 2, it is automatically printed out because no input is needed.
• When user select options 3 and 4, the system requires an input ( probably by month is best) so that the system can check for data in that month. (Probably need to 'import datetime' )
• To display only customers' bookings , we can use if...else statement to filter out base on the customer name then print them out. (Refer to the Customer_Records.txt)
• To display only customers' payment , we can use if...else statement to filter out base on the customer name then print them out. (Refer to the Customer_Records.txt)
• User needs to input the customer name to make the search. So use if customer_name in line_of_file then print the information
• I think this is just Modifying Car Details part but only specific to the status and duration of the car. (Update details of car and customer)

4.3 For Customers (Unregistered)

• Show all car details except status, owner's name and duration. Only cars that are available are shown.

4.4 For Customers (Registered)

• IC/Passport Number
• Include all Car Details
• Accepts input (sentinel loop, meaning keep asking until the user say quit) where the user select which detail to modify.
• To modify, use the same method as the admin
• Whenever the customer rents a car, append it into a list.
• When the customer wants to view its purchase history, search for the customers name, by filtering based on his/her username then do print(*[list_of_cars], sep='\n')
• Search through the car2.txt for the customer's Full Name and print out all the cars that have the same match
• The cars that are printed out must have the status 'available', if rented, show 'rented'.
• Display all cars that are available that does not belong to the user
• Make it menu-driven like how they would choose the options on what to do next.
• When they select the car, the user needs to make another input on how many days they are renting the car. After the input, use datetime to calculate the end of the rental and tell the user. Save the end date of rental to a variable so that the system can update the Car_Records.txt after the user make the payment
• Once all the details are keyed in by the user, set the selected car's status to pending
• This is not in the main option menu. This will only appear after the Renting section where the input will be asked to "Continue to Payments" or "Continue Browsing" or "Cancel Booking".
• If "Continue to Payments", the system will check for the duration of days and multiply with the renting rate of the selected car.
• After calculation, the system will display the price then ask for payment method (Credit/Debit Card, Direct Debit, PayPal)
• Card Number
• Card Owner Name
• Expiry date
• Account Number
• Account Name
• Account Currency
• Account Type
• Request PayPal email
• Request PayPal password
• Should we include PayPal?
• After payment is completed, using the variables set in the previous section, update the Car_Records.txt

5. Extra details

So when the admin/customer selects one of the options after logging in, they need to have a button/option to go back to the main option menu screen. Since the main options are numbers, I think we can make going back to the main menu a letter like "Y" so that the user can choose other stuff to do without logging in several times. So the menu might look like:

Example of Main Option Menu (for Admin): [1] Adding Cars to be Rented Out [2] Modifying Car Details [3] Display records [4] Search records [5] Return Rented Car [6] Log Out

Example of Modifying Car Details:

Example of Display records: Display Records of: [1] Rented cars [2] Available cars [3] Customer Bookings [4] Customer Payments [Y] Return to Main Menu

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Create a Vehicle Parking Management Project in Python

Introduction

Hello friends, welcome to copyassignment.com . In this tutorial, we are going to Create a Vehicle Parking Management in Python. This project helps maintain the details of the vehicle owner, number, type, date, and the amount of time the vehicle is parked in the area. Accordingly, the bill generates for the particular vehicle parked in the area. This information is useful for all those who want to maintain a database of the individual who has parked their vehicles in the surroundings.

We are providing the complete code and detailed information about this project in this article.

Let us understand this project

1. Import Function and Initializing the variables

In this code block, we are importing the time module to implement its methods and function in the project. We have initialized the variables vehicle number, vehicle type, vehicle name, owner name date, and time to some default value. As well as bikes, cars, and bicycles with some initial value.

2. Create a while loop block to display the options in Vehicle Parking Management Project

In this code block, we have initialized the bikes, cars, and bicycles as global variables. They are accessible through the entire main block. Here we are providing the options to choose the service options from the list, for the vehicle parking management system.

Now we will understand each service option in detail.

Code for vehicle number entry

Ch is for choice, Once we select the ch option as 1 which is for vehicle entry number, then we provide the while loop. while the number(no is True). We will store the vehicle number in Vno. If the vno is empty i.e vno==“”.The user asks to enter the vehicle number, else If the vno entered is already present in the vehicle number then it prints the vehicle number already exists. Else if len(vno)==12, It will ask to append the info to the vehicle number variable.

Code to enter the vehicle type

Here we have to initialize the typee variable to true. While the condition is True, the system asks to enter the vehicle type i.e a,b, or c which will accept the input in the lower case. Here A is for bicycle, B is for Bike and C is for Car. Any vehicle type you enter is stored in the variable Vtype. If the Vtype==””(empty). It will ask to enter the vehicle type.  According to the type of variable you enter the vehicle type will be stored in the variable and typee variable is set to not True.

Code to enter the vehicle name

Here we have set the name== True. While the name == True i.e until we enter the name.vname store the value i.e. vehicle name.  if the vname is empty system asks to enter the vehicle name, else it will store the name using the append function to the vehicle name variable The name variable is initialized to not True.

Code to enter the owners name

O is initialized to True. While the condition satisfies the Owner’s name is stored in the OName variable. If the OName is empty it system asks to enter the owner name else it will store the Owner name in the owner name variable. O is now initialized to Not True.

Code enter the date and time

Similarly, we have to create a while loop to enter the date and time initializing d and t to 0. Date variable stores the date and the time-variable stores time. The date and time variable checks the condition and accordingly execute further.

Code to remove the entry from the register

In this code block, we are writing the code to remove the particular entry of a vehicle from the database. Users have entered a valid vehicle number to Create a Vehicle Parking Management in Python. If the vehicle number is present in our database and if the length of the vehicle number is 12 then it uses a pop function to remove the particular entry.  Else if the vehicle number is not present in the database it will print “No such Entry” and asks to enter a valid vehicle number.

Code to display the vehicles present in the parking area

Here ch==3  is for displaying the parked vehicles in the parking area. For this, we have to use the for loop function. It counts the length of the vehicle number. This will display the whole information of the vehicles.

Code for spaces left in the parking area

This block of code displays the spaces left for parking in the parking area.

Code for displaying the parking rate

It displays the parking rate of different types of vehicles.

Code to generate bills for different types of vehicles parked

The billing section generates the bill for the vehicle parked. We have to enter the correct vehicle number and check the length of the vehicle number and the vehicle number present in the database. After this check the time and the type of vehicle. Depending upon the vehicle type the system calculates the charges. The last choice ch==7 is to come out of the service options and quit the program.

Complete Code to Create a Vehicle Parking Management Project in Python

Here we have successfully created the vehicle Parking Management system. For more articles on python, keep visiting the website.

Thank you for reading this article.

Vehicle Parking Management System Python

In this post, we talked about the vehicle parking management system python with complete source code and output, some people were also demanding the report for this project as they want this project to submit in their college project but to be honest if you will copy this you will be caught and your professor will fail you for plagiarism. So if you want a unique code with a report then WhatApp me at +919760648231

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Mastering Python’s List Assignment: Resolving Index Out of Range Errors

Resolve "index out of range" errors

As a Python developer, working with lists is an essential part of your daily coding routine. However, even experienced programmers can stumble upon the dreaded “index out of range” error when dealing with list assignments. This error occurs when you attempt to access or modify an index that doesn’t exist within the list’s bounds. Fear not, as this comprehensive tutorial will equip you with the knowledge and techniques to conquer this challenge and unlock the full potential of Python’s list assignment.

Understanding the “Index Out of Range” Error

Before diving into the solutions, let’s first understand the root cause of the “index out of range” error. In Python, lists are zero-indexed, meaning the first element has an index of 0, the second element has an index of 1, and so on. When you try to access or modify an index that falls outside the list’s valid range, Python raises an IndexError with the “index out of range” message.

Here’s an example that illustrates the error:

In this case, we’re attempting to access the fourth element ( my_list[3] ) of a list that only contains three elements (indices 0, 1, and 2).

Solution 1: Validating Indices Before Assignment

One effective solution to prevent “index out of range” errors is to validate the index before attempting to assign a value to it. You can achieve this by checking if the index falls within the list’s valid range using the len() function and conditional statements.

In this solution, we first declare a list my_list with three elements. We then define two variables: index and new_value .

Next, we use an if statement to check if the index is less than the length of my_list . The len(my_list) function returns the number of elements in the list, which is 3 in this case.

If the condition index < len(my_list) is True, it means that the index is a valid index within the list’s bounds. In this case, we assign the new_value (4) to the element at the specified index (2) using the list assignment my_list[index] = new_value . Finally, we print the updated list, which now has the value 4 at index 2.

However, if the condition index < len(my_list) is False, it means that the index is out of range for the given list. In this case, we execute the else block and print the message “Index out of range!” to inform the user that the provided index is invalid.

This solution is effective when you need to ensure that the index you’re trying to access or modify is within the valid range of the list. By checking the index against the list’s length , you can prevent “index out of range” errors and handle invalid indices appropriately.

It’s important to note that this solution assumes that the index variable is provided or calculated elsewhere in the code. In a real-world scenario, you may need to handle user input or perform additional validation on the index variable to ensure it’s an integer and within the expected range.

Solution 2: Using Python’s List Slicing

Python’s list slicing feature allows you to access and modify a subset of elements within a list. This is a powerful technique that can help you avoid “index out of range” errors when working with list assignments .

In the first example, my_list[:2] = [10, 20] , we’re using list slicing to access and modify the elements from the start of the list up to (but not including) index 2. The slice [:2] represents the range from the beginning of the list to index 2 (0 and 1). We then assign the new values [10, 20] to this slice, effectively replacing the original values at indices 0 and 1 with 10 and 20, respectively.

In the second example, my_list[2:] = [30, 40] , we’re using list slicing to access and modify the elements from index 2 to the end of the list. The slice [2:] represents the range from index 2 to the end of the list. We then assign the new values [30, 40] to this slice. Since the original list only had three elements, Python automatically extends the list by adding a new element at index 3 to accommodate the second value (40).

List slicing is a powerful technique because it allows you to modify multiple elements within a list without worrying about “index out of range” errors. Python automatically handles the indices for you, ensuring that the assignment operation is performed within the valid range of the list.

Here are a few key points about list slicing:

• Inclusive start, exclusive end : The slice [start:end] includes the elements from start up to, but not including, end .
• Omitting start or end : If you omit the start index, Python assumes the beginning of the list. If you omit the end index, Python assumes the end of the list.
• Negative indices : You can use negative indices to start or end the slice from the end of the list. For example, my_list[-1] accesses the last element of the list.
• Step size : You can optionally specify a step size in the slice notation, e.g., my_list[::2] to access every other element of the list.

List slicing is a powerful and Pythonic way to work with lists, and it can help you avoid “index out of range” errors when assigning values to multiple elements within a list.

Solution 3: Using Python’s List Append Method

The append() method in Python is a built-in list method that allows you to add a new element to the end of an existing list. This method is particularly useful when you want to avoid “index out of range” errors that can occur when trying to assign a value to an index that doesn’t exist in the list.

In this example, we start with a list my_list containing three elements: [1, 2, 3] . We then use the append() method to add a new element 4 to the end of the list: my_list.append(4) . Finally, we print the updated list, which now contains four elements: [1, 2, 3, 4] .

Here’s how the append() method works:

• Python finds the current length of the list using len(my_list) .
• It assigns the new value ( 4 in this case) to the index len(my_list) , which is the next available index after the last element in the list.
• Since the new index is always valid (it’s one greater than the last index), there’s no risk of an “index out of range” error.

The append() method is a safe and convenient way to add new elements to the end of a list because it automatically handles the index assignment for you. You don’t need to worry about calculating the correct index or checking if the index is within the list’s bounds.

It’s important to note that the append() method modifies the original list in-place. If you want to create a new list instead of modifying the existing one, you can use the + operator or the list.copy() method to create a copy of the list first, and then append the new element to the copy.

Another advantage of using append() is that it allows you to add multiple elements to the list in a loop or by iterating over another sequence. For example:

In this example, we use a for loop to iterate over the new_elements list, and for each element, we call my_list.append(element) to add it to the end of my_list .

Overall, the append() method is a simple and effective way to add new elements to the end of a list, ensuring that you avoid “index out of range” errors while maintaining the integrity and order of your list.

Solution 4: Handling Exceptions with Try/Except Blocks

Python provides a robust exception handling mechanism using try/except blocks, which can be used to gracefully handle “index out of range” errors and other exceptions that may occur during program execution.

In this example, we first define a list my_list with three elements and an index variable with the value 4 .

The try block contains the code that might raise an exception. In this case, we attempt to access the element at my_list[index] , which is my_list[4] . Since the list only has indices from 0 to 2, this operation will raise an IndexError with the message “list index out of range” .

The except block specifies the type of exception to catch, which is IndexError in this case. If an IndexError is raised within the try block, the code inside the except block will be executed. Here, we print the message “Index out of range! Please provide a valid index.” to inform the user that the provided index is invalid.

If no exception is raised within the try block, the except block is skipped, and the program continues executing the code after the try/except block.

By using try/except blocks, you can handle exceptions gracefully and provide appropriate error messages or take alternative actions, rather than allowing the program to crash with an unhandled exception.

Here are a few key points about using try/except blocks for handling exceptions:

• Multiple except blocks : You can have multiple except blocks to handle different types of exceptions. This allows you to provide specific error handling for each exception type.
• Exception objects : The except block can optionally include a variable to hold the exception object, which can provide additional information about the exception.
• else clause : You can include an else clause after the except blocks. The else block executes if no exceptions are raised in the try block.
• finally clause : The finally clause is executed regardless of whether an exception was raised or not. It’s typically used for cleanup operations, such as closing files or releasing resources.
• Exception hierarchy : Python has a built-in exception hierarchy, where some exceptions are derived from others. You can catch a base exception to handle multiple related exceptions or catch specific exceptions for more granular control.

By using try/except blocks and handling exceptions properly, you can write more robust and resilient code that gracefully handles errors, making it easier to debug and maintain your Python programs.

Best Practices and Coding Standards

To ensure your code is not only functional but also maintainable and scalable, it’s essential to follow best practices and coding standards. Here are some recommendations:

• Validate user input : When working with user-provided indices, always validate the input to ensure it falls within the list’s valid range.
• Use descriptive variable and function names : Choose meaningful names that clearly convey the purpose and functionality of your code elements.
• Write clear and concise comments : Document your code with comments that explain the purpose, logic, and any non-obvious implementation details.
• Follow PEP 8 style guide : Adhere to Python’s official style guide , PEP 8, to ensure consistency and readability across your codebase.
• Test your code thoroughly : Implement unit tests and integrate testing into your development workflow to catch bugs and regressions early.

By following these best practices and coding standards, you’ll not only avoid “index out of range” errors but also produce high-quality, maintainable, and scalable Python code.

Mastering Python’s list assignment is crucial for efficient data manipulation and programming success. By understanding the root cause of “index out of range” errors and implementing the solutions outlined in this tutorial, you’ll be well-equipped to handle these challenges confidently. Whether you validate indices, leverage list slicing, use the append() method, or handle exceptions, you now have a comprehensive toolkit to tackle list assignment challenges head-on. Embrace these techniques, follow best practices, and continue honing your Python skills to unlock new levels of coding excellence.

• Index Out of Range
• List Assignment

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