Restructure folders & notebooks
- drop 'chapter_' prefix for chapter folders - drop numbers for ToC sub-chapters - split exercises into one problem set per notebook - adjust titles in notebooks => show sub-chapter titles on the same line as the actual chapter titles
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25 changed files with 497 additions and 547 deletions
3064
02_functions/00_content.ipynb
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3064
02_functions/00_content.ipynb
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241
02_functions/01_exercises.ipynb
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241
02_functions/01_exercises.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Note**: Click on \"*Kernel*\" > \"*Restart Kernel and Run All*\" in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) *after* finishing the exercises to ensure that your solution runs top to bottom *without* any errors. If you cannot run this file on your machine, you may want to open it [in the cloud <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_mb.png\">](https://mybinder.org/v2/gh/webartifex/intro-to-python/develop?urlpath=lab/tree/02_functions/01_exercises.ipynb)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Chapter 2: Functions & Modularization (Coding Exercises)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The exercises below assume that you have read the [first part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) of Chapter 2.\n",
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"\n",
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"The `...`'s in the code cells indicate where you need to fill in code snippets. The number of `...`'s within a code cell give you a rough idea of how many lines of code are needed to solve the task. You should not need to create any additional code cells for your final solution. However, you may want to use temporary code cells to try out some ideas."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Volume of a Sphere"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q1**: The [volume of a sphere <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_wiki.png\">](https://en.wikipedia.org/wiki/Sphere) is defined as $\\frac{4}{3} * \\pi * r^3$. Calculate this value for $r=10.0$ and round it to 10 digits after the comma.\n",
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"\n",
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"Hints:\n",
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"- use an appropriate approximation for $\\pi$\n",
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"- you may use the [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) to do so if you have already looked at the [second part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb) of Chapter 2."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import ... # you may drop this cell and use your own approximation for Pi"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"..."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q2**: Encapsulate the logic into a function `sphere_volume()` that takes one *positional* argument `radius` and one *keyword-only* argument `digits` defaulting to `5`. The volume should be returned as a `float` object under *all* circumstances."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def sphere_volume(...):\n",
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" \"\"\"Calculate the volume of a sphere.\n",
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"\n",
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" Args:\n",
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" radius (float): radius of the sphere\n",
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" digits (optional, int): number of digits\n",
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" for rounding the resulting volume\n",
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"\n",
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" Returns:\n",
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" volume (float)\n",
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" \"\"\"\n",
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" return ..."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q3**: Evaluate the function with `radius = 100.0` and 1, 5, 10, 15, and 20 digits respectively."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"radius = ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sphere_volume(...)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sphere_volume(...)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sphere_volume(...)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sphere_volume(...)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sphere_volume(...)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q4**: What observation do you make?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q5**: Using the [range() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-range) built-in, write a `for`-loop and calculate the volume of a sphere with `radius = 42.0` for all `digits` from `1` through `20`. Print out each volume on a separate line.\n",
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"\n",
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"Note: This is the first task where you need to use the built-in [print() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#print) function."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"radius = ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"for ... in ...:\n",
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" ..."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q6**: What lesson do you learn about the `float` type?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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},
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"toc": {
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"base_numbering": 1,
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"nav_menu": {},
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"number_sections": false,
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"sideBar": true,
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"skip_h1_title": true,
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"title_cell": "Table of Contents",
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"title_sidebar": "Contents",
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"toc_cell": false,
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"toc_position": {},
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"toc_section_display": false,
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"toc_window_display": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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1625
02_functions/02_content.ipynb
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02_functions/02_content.ipynb
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90
02_functions/03_summary.ipynb
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02_functions/03_summary.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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}
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},
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"source": [
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"# Chapter 2: Functions & Modularization (TL;DR)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"A user-defined **function** is a **named sequence** of statements that perform a computation.\n",
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"\n",
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"Functions provide benefits as they\n",
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"\n",
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"- make programs easier to comprehend and debug for humans as they give names to the smaller parts of a larger program (i.e., they **modularize** a code base), and\n",
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"- eliminate redundancies by allowing **reuse of code**.\n",
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"\n",
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"Functions are **defined** once with the `def` statement. Then, they may be **called** many times with the call operator `()`.\n",
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"\n",
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"They may process **parameterized** inputs, **passed** in as **arguments**, and output a **return value**.\n",
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"\n",
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"Arguments may be passed in by **position** or **keyword**. Some functions may even require **keyword-only** arguments.\n",
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"\n",
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"**Lambda expressions** create anonymous functions.\n",
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"\n",
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"Functions are a special kind of **callables**. Any object that may be **called** with the call operator `()` is a callable. Built-in functions and **constructors** are other kinds of callables.\n",
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"\n",
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"Core Python can be extended with code from either the **standard library** or **third-party** libraries.\n",
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"\n",
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"Outside Jupyter notebooks, Python code is put into **modules** that are grouped in **packages**."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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},
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"livereveal": {
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"auto_select": "code",
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"auto_select_fragment": true,
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"scroll": true,
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"theme": "serif"
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},
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"toc": {
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"base_numbering": 1,
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"nav_menu": {},
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"number_sections": false,
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"sideBar": true,
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"skip_h1_title": true,
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"title_cell": "Table of Contents",
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"title_sidebar": "Contents",
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"toc_cell": false,
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"toc_position": {
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"height": "calc(100% - 180px)",
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"left": "10px",
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"top": "150px",
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"width": "384px"
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},
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"toc_section_display": false,
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"toc_window_display": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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229
02_functions/04_review.ipynb
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02_functions/04_review.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Chapter 2: Functions & Modularization (Review Questions)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The questions below assume that you have read the [first <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/00_content.ipynb) and the [second <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/02_functions/02_content.ipynb) part of Chapter 2.\n",
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"\n",
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"Be concise in your answers! Most questions can be answered in *one* sentence."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Essay Questions "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q1**: What behavior of the `def` statement makes it a **statement**? Is there a way to use an **expression** to create a function?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q2**: One of the first confusions of experienced programmers coming from other languages to Python regards the observation that **\"everything in Python is an object\"** (cf., this [discussion](https://www.reddit.com/r/learnpython/comments/8rypx9/everything_in_python_is_an_object/)). How does this relate to **functions**?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q3**: What does it mean for a variable to go out of **scope**?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q4**: How can a **global** variable be **shadowed**? Is this good or bad?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q5**: Explain the concept of **forwarding** a **function call**."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q6**: What are **keyword-only arguments** and when is it appropriate to use them?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q7**: What are **callables**? How do they relate to `function` objects?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" < your answer >"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## True / False Questions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Motivate your answer with *one short* sentence!"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Q8**: A mere function **call** is just an **expression**."
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]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
" < your answer >"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q9**: When using the `import` statement, we need to ensure that the imported attributes do *not* overwrite any already defined variables and functions."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
" < your answer >"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q10:** Functions always have a name by which we can call them."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
" < your answer >"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Q11**: The [standard library <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/index.html) is a collection of numerical tools often used in scientific computing, for example, advanced mathematical functions or utilities for simulation."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
" < your answer >"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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": "3.8.6"
|
||||
},
|
||||
"toc": {
|
||||
"base_numbering": 1,
|
||||
"nav_menu": {},
|
||||
"number_sections": false,
|
||||
"sideBar": true,
|
||||
"skip_h1_title": true,
|
||||
"title_cell": "Table of Contents",
|
||||
"title_sidebar": "Contents",
|
||||
"toc_cell": false,
|
||||
"toc_position": {},
|
||||
"toc_section_display": false,
|
||||
"toc_window_display": false
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 4
|
||||
}
|
||||
76
02_functions/sample_module.py
Normal file
76
02_functions/sample_module.py
Normal file
|
|
@ -0,0 +1,76 @@
|
|||
"""This is a sample module.
|
||||
|
||||
It defines three functions average(), average_evens(), and average_odds().
|
||||
The point is to show how we can put Python code in a .py file to be re-used
|
||||
in some other place.
|
||||
|
||||
We should never forget to document the code as well, both on the module
|
||||
level (i.e., this docstring) but also in every function it defines.
|
||||
|
||||
When imported, Python modules are executed top to bottom before the flow of
|
||||
execution returns to wherever they were imported into.
|
||||
|
||||
An important convention is to prefix variables and functions that are not to
|
||||
be used outside the module with a single underscore "_". This way, we can
|
||||
design the code within a module in a modular fashion and only "export" what we
|
||||
want.
|
||||
|
||||
Here, all three functions internally forward parts of their computations
|
||||
to the utility functions _round_all() and _scaled_average() that contain all
|
||||
the logic common to the three functions.
|
||||
|
||||
While this example is stylized, it shows how Python modules are often
|
||||
designed.
|
||||
"""
|
||||
|
||||
def _round_all(numbers):
|
||||
"""Internal utility function to round all numbers in a list."""
|
||||
return [round(n) for n in numbers]
|
||||
|
||||
|
||||
def _scaled_average(numbers, scalar):
|
||||
"""Internal utility function to calculate scaled averages."""
|
||||
average = sum(numbers) / len(numbers)
|
||||
return scalar * average
|
||||
|
||||
|
||||
def average(numbers, *, scalar=1):
|
||||
"""Calculate the average of all numbers in a list.
|
||||
|
||||
Args:
|
||||
numbers (list of int's/float's): numbers to be averaged;
|
||||
if non-whole numbers are provided, they are rounded
|
||||
scalar (float, optional): multiplies the average; defaults to 1
|
||||
|
||||
Returns:
|
||||
scaled_average (float)
|
||||
"""
|
||||
return _scaled_average(_round_all(numbers), scalar)
|
||||
|
||||
|
||||
def average_evens(numbers, *, scalar=1):
|
||||
"""Calculate the average of all even numbers in a list.
|
||||
|
||||
Args:
|
||||
numbers (list of int's/float's): numbers to be averaged;
|
||||
if non-whole numbers are provided, they are rounded
|
||||
scalar (float, optional): multiplies the average; defaults to 1
|
||||
|
||||
Returns:
|
||||
scaled_average (float)
|
||||
"""
|
||||
return _scaled_average([n for n in _round_all(numbers) if n % 2 == 0], scalar)
|
||||
|
||||
|
||||
def average_odds(numbers, *, scalar=1):
|
||||
"""Calculate the average of all odd numbers in a list.
|
||||
|
||||
Args:
|
||||
numbers (list of int's/float's): numbers to be averaged;
|
||||
if non-whole numbers are provided, they are rounded
|
||||
scalar (float, optional): multiplies the average; defaults to 1
|
||||
|
||||
Returns:
|
||||
scaled_average (float)
|
||||
"""
|
||||
return _scaled_average([n for n in _round_all(numbers) if n % 2 != 0], scalar)
|
||||
Loading…
Add table
Add a link
Reference in a new issue