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Template for assignment 1 of CSE102 - Introduction to Programming with Python
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span class=\"minerva-question\" style=\"background-color:#f15a24;color:white;padding: 5px 20px 5px 20px;line-height:30px;height:30px;border-radius:3px\">Important Note</span> For guidance on how to write in markdown, please consult [this documentation](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1. Introduction"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You should write your assignment introduction here."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1.1 Step-By-Step Algorithm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Write each step of the algorithm you are proposing to solve the assignment problem here."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1.2 Flowchart Diagram"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Include the flowchart for your diagram here. \n",
"\n",
"**NOTE:** Let \"my_image.png\" be an image which is in the same directory as your jupyter notebook. If you would like to include that image on this notebook, then you can simply write in a code cell:\n",
"\n",
"```from IPython.display import Image\n",
"Image(\"my_image.png\")```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1.3 Explanation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Provide a detailed explanation of how your algorithm works."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2. Code"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.1 Import statements"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {},
"outputs": [],
"source": [
"# include here all the modules that your code requires to run"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.2 Function definitions"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {},
"outputs": [],
"source": [
"# include here all the functions which your script will use"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.3 Script"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {},
"outputs": [],
"source": [
"# include here the code for your scripr"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.4 Test Cases"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# demonstrate the correctness of your code by showing it works as intended on a number of well-identified test cases"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.5 Additional Code Description"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Include any other details of your algorithmic approach or any other points here."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3. References"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The references you used for your work will go here."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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