【MCD4710】Introduction to Algorithms and Programming

You are likely already familiar with a plethora of prehistoric paint programs. These all have a simple premise: you draw a colour on the canvas, and this overwrites, or sits on-top of, the existing canvas colours.
Some applications support transparency, allowing you to blend colours. Some allow you to draw
shapes, and others allow you to click and drag certain elements. None of them have the liveliness that
the FoA Admin team is looking for however. We want to be able to paint sparkles, or a rainbow, on
top of our images. Rather than painting with colours, we want to paint with Eff ects !
Throughout this assignment, you'll be working on a paint application, with the following features:
Multiple diff erent ways to combine eff ects, and paint with such eff ects
Undo/Redo
A painting replay
A special action
In doing this, you'll need to demonstrate knowledge on the following topics:
Stacks, Queues, Lists
Applications of the Data Structures above
Before you get working on the application, please read these tips & tricks to ensure you don't get lost,
or lose any silly marks!
Common Mistakes
You are marked on correctness in Ed . It doesn't matter if your code passes locally, it needs to
pass in Ed. Contact a TA if you are having trouble achieving parity. Be careful of the specifi c
Python version used, and don't import any other third party modules excluding those already
in requirements.txt .
Follow the rules regarding ban on lists, other collections and use the given data_structures
almost always. Check the task speciff c page to see what collections are banned for that feature.
Write clear and concise docstrings for methods you introduce, and type-hint all methods /
variables. If introducing new classes, consider using dataclasses to simplify this deff nition.
Separate your code into small methods of at most 20 lines, and try to abstract logic if you ff nd
lots of duplicated work. Almost all methods in the sample solution are 10 lines or less. (Please
ignore the mess that is main.py :} )
Initial Setup + Running Tests
To get up and running you want to do a few things:
Import the template repository into your own - Follow the instructions in the Getting Started
with Git page.

Optional\] Make a virtual environment for the project: python3 -m pip install virtualenv \&\& python3 -m venv venv (And then activate the virtual environment) (You may need to change python3 to python or py depending on your Operating System and Python version) Install the required packages: python3 -m pip install -r requirements.txt (Same deal here with python3 ) Test it is working by running python3 main.py or python3 -m visuals.basic (These will probably raise NotImplemented errors if you haven't implemented anything, but if your setup didn't work you'll get errors complaining packages aren't installed.) To run tests, call python run_tests.py . Note that you can restrict which tests are run using a second argument. You can always assume there at most 20 Layers in the application, but design the time complexity of your solution around an unbounded amount. dataclasses are used in some of the scaff old code. In short, they do a lot of the initialisation boilerplate for you by inspecting the type hinting for class variables. You can read more about it here . This project also uses abstraction with the abc module. You can read more about it here . Since this is a paint app, here's some recommend listening while you knock these tasks out of the park!

相关推荐
Trouvaille ~19 分钟前
零基础入门 LangChain 与 LangGraph(五):核心组件上篇——消息、提示词模板、少样本与输出解析
人工智能·算法·langchain·prompt·输入输出·ai应用·langgraph
MOON404☾37 分钟前
Chapter 002. 线性回归
算法·回归·线性回归
故事和你911 小时前
洛谷-数据结构-1-3-集合3
数据结构·c++·算法·leetcode·贪心算法·动态规划·图论
春栀怡铃声1 小时前
【C++修仙录02】筑基篇:类和对象(上)
开发语言·c++·算法
ulias2121 小时前
leetcode热题 - 3
c++·算法·leetcode·职场和发展
实心儿儿1 小时前
Linux —— 进程概念 - 程序地址空间
linux·运维·算法
菜鸟丁小真2 小时前
LeetCode hot100-287.寻找重复数和994.腐烂的橘子
数据结构·算法·leetcode·知识点总结
发发就是发2 小时前
USB系统架构概述:从一次诡异的枚举失败说起
驱动开发·单片机·嵌入式硬件·算法·fpga开发
少许极端2 小时前
算法奇妙屋(四十七)-ST表
算法·st表·rmq
kishu_iOS&AI2 小时前
Pytorch —— 自动微分模块
人工智能·pytorch·python·深度学习·算法·线性回归