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%% Cell type:markdown id:becc5c8b tags:
# Exercise 1: Jupyter Notebooks
## Introduction to Jupyter Notebooks
Try out different cell types, including code and markdown cells.
%% Cell type:markdown id:4cd048de tags:
### 1: Markdown cells
%% Cell type:markdown id:f9f4a25b tags:
#### 1.1 Headers in Markdown
Create 4 header levels using Markdown. Each header should be labeled as "Level 1", "Level 2", "Level 3", and "Level 4", corresponding to the Markdown syntax for headers.<br>
%% Cell type:markdown id:72014df9 tags:
# Level 1
## Level 2
### Level 3
#### Level 4
%% Cell type:markdown id:9778cbbe tags:
#### 1.2 Text formatting in Markdown
Write the following words with the desired formatting using a line break between each word <br>
A word printed **in bold**: “Word1” <br>
One word printed in *italics*: “Word2” <br>
One ~~strikethrough~~ word: “Word3” <br>
One ___italic and bold word___: “Word4” <br>
%% Cell type:markdown id:b0a6b08a tags:
**Word 1**
*Word 2*
~~Word 3~~
***Word 4***
%% Cell type:markdown id:189de41f tags:
#### 1.3 Tables in Markdown
Create a table with three columns and three rows that contains the profiles of three individuals, including their name, age, and profession. <br>
Use the extension **"Nice Tables"** for this
1. To download the extension, open the Extensions Menu on the left side of your Markdown editor.
2. Search for "Nice Tables" and install it.
3. Once installed, use it to create the table structure and fill it with the appropriate data.
4. Open the Command Menu with CTRL + SHIFT + P.
5. Search for "Text Tables: Create Table".
6. Enter the desired table size. You can navigate between cells using the Tab key. The size of the cells should adjust automatically.
%% Cell type:markdown id:80a329a0 tags:
| Name | Age | Profession |
|-----|-----|-----|
| Jonas | Andri | Andrin |
| 24 | 30 | 24 |
| Student | Student | Student |
%% Cell type:markdown id:e3d789bd tags:
#### 1.4 Mathematical formulas in Markdown
Insert the formula for calculating the volume of a sphere from a radius <br>
> here a Cheat sheet that can help: https://www.upyesp.org/posts/makrdown-vscode-math-notation/
Example midnight formula:
x = $\frac{-b \pm \sqrt{b^2 - 4ac}}{2a}$
%% Cell type:markdown id:4845547f tags:
V = $\frac{4}{3} \times r^3 \times \pi$
%% Cell type:markdown id:303a067d tags:
#### 1.5 Links and Images
##### 1.5.1 Web Images
Add any image from the web in Markdown and add a hyperlink with the URL matching the image<br>
%% Cell type:markdown id:f7735d6f tags:
![image.png](attachment:image.png)
https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQQ4dxQwrR5MlFeYezH7ykCLFj6XjeadfJD1Q&s
%% Cell type:markdown id:be12e31e tags:
##### 1.5.2 local Images
Add an image to the project by first creating a new folder named Pictures inside the week_1 folder. Place the image file in this folder and update the Markdown file with a relative link to the image, ensuring the link works regardless of where the project is saved or moved.
> To make sure the link works universally, use a relative path like (./week_1/Pictures/image_name.jpg)" instead of an absolute path.
%% Cell type:markdown id:87c4eef8 tags:
%% Cell type:markdown id:d4878f98 tags:
#### 1.6 Lists
##### 1.6.1 numbered lists
Create an ordered list as shown in the example below
1. First item
2. Second item
3. Third item
1. Indented item
2. Indented item
4. Fourth item
<br> <br>
The list should consist of two main items fruits and vegetables, with sub-items of fruits being bananas and apples and sub-items of vegetables being carrots and potatoes
%% Cell type:markdown id:5795b9c2 tags:
%% Cell type:markdown id:68f111de tags:
##### 1.6.1 Bulletpoint lists
Create an unordered list with bullet points with Point 1 Point 2
%% Cell type:markdown id:91106711 tags:
%% Cell type:markdown id:81e4c706 tags:
1.7 Quotes
Make the sentence below a quotation <br>
Programming is the art of telling another human being what one wants the computer to do.
%% Cell type:markdown id:177f1a55 tags:
%% Cell type:markdown id:97ae5c25 tags:
#### 2: Code Cells
%% Cell type:markdown id:432de469 tags:
#### 2.1 Hello world!
Next insert a code cell which displays hello world!
%% Cell type:markdown id:77f74fb5 tags:
%% Cell type:markdown id:bc1be52c tags:
#### 3: First step in Python
%% Cell type:markdown id:d4cc568a tags:
Create a Python program that performs the following arithmetic operations using two variables ``a`` and ``b``
- Addition
- Subtraction
- Multiplication
- Division
%% Cell type:code id:4fdc25ef tags:
``` python
a = 10
b = 5
```
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# Python_exercises_William_DosSantos
## Getting started
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
## Add your files
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
```
cd existing_repo
git remote add origin https://gitlab.ost.ch/william.santos/python_exercises_william_dossantos.git
git branch -M main
git push -uf origin main
```
## Integrate with your tools
- [ ] [Set up project integrations](https://gitlab.ost.ch/william.santos/python_exercises_william_dossantos/-/settings/integrations)
## Collaborate with your team
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Test and Deploy
Use the built-in continuous integration in GitLab.
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
***
# Editing this README
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
## Name
Choose a self-explaining name for your project.
## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
## Badges
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
## Visuals
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
## Support
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
## Roadmap
If you have ideas for releases in the future, it is a good idea to list them in the README.
## Contributing
State if you are open to contributions and what your requirements are for accepting them.
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
## Authors and acknowledgment
Show your appreciation to those who have contributed to the project.
## License
For open source projects, say how it is licensed.
## Project status
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
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%% Cell type:markdown id: tags:
# Introduction to Python for Engineers
## Agenda
- [Where do we start?](#where-do-we-start)
- [An Example of a Python Program](#an-example-of-a-python-program)
- [Background and History of Python Programming Language](#background-and-history-of-python-programming-language)
- [About this Course](#about-this-course)
- [Lession 1: Introduction to Jupyter Notebook](#lesson-1)
%% Cell type:markdown id: tags:
# Where do we start?
Let's do a short Poll to see what you alredy know about Python.
1. I have never used Python before.
1. I have used Python before, but I am not very familiar with it.
1. I have used Python before and I am somewhat familiar with it.
1. I am a Python expert.
%% Cell type:markdown id: tags:
# An Example of a Python Program
Below you see an example of a python program.
If you are used to other programming languages, this looks a bit different... but you'll get used to it!
%% Cell type:code id: tags:
``` python
print('Python is fun!')
```
%% Output
Python is fun!
%% Cell type:code id: tags:
``` python
for g in range(3, 0, -1):
print(g)
```
%% Output
3
2
1
%% Cell type:markdown id: tags:
As you can see python is easy to read, almost like English. You will learn more about the Python syntax, later on.
%% Cell type:markdown id: tags:
# Background and History of Python Programming Language
%% Cell type:markdown id: tags:
## Why Python?
Python is a very popular programming language for a variety of reasons
* **Readability and Simplicity**: Python has a clean and readable syntax, which makes it easy to learn and understand.
* **Versatility**: Python is a general-purpose language, meaning it can be used for a wide range of applications, from web development to data analysis, machine learning, automation, and more. (e.g. our PLM System "CIM Database" is written in Python)
* **Large Standard Library**: Python comes with a vast standard library that provides modules and functions for many common tasks, reducing the need for external libraries.
* **Extensive Ecosystem**: There is a rich ecosystem of third-party libraries and frameworks that extend Python’s capabilities across different domains.
* **Community Support**: Python has a large and active community, which means extensive documentation, a wealth of tutorials, and community-contributed packages are readily available.
* **Cross-Platform Compatibility**: It can run on various operating systems like Windows, macOS, and Linux without modification.
* **Data Science and Machine Learning**: Python has become the go-to language for data science and machine learning, largely due to libraries like NumPy, Pandas, Scikit-learn, and TensorFlow.
%% Cell type:markdown id: tags:
## Background and History of Python Programming Language
Let's trace the roots of this programming language
* https://www.youtube.com/watch?v=Tm5u97I7OrM
* https://www.youtube.com/watch?v=ucD_1ryKKm0
* https://www.youtube.com/watch?v=J0Aq44Pze-w
%% Cell type:markdown id: tags:
## Different Ways to use Python
* **Python in "Jupiter Notebooks"**: This slide you see is a document, called Jupiter Notebook. It combines text / documentation with coding. In every code cell we can execute some python. All cells know of each other. This is a very convenient way do data analytics, since you can explain your thoughts, run your code, and visualize the results at the same place.
* **Standalone Python Applications**. You write your code in an IDE such as VS-Code and execute it. There many different types of applications, such as web-applications, command line applications, or applications with a user interface that runs on your operating system.
* **Micro-Python**: This is a subset of Python to write code, that runs on micro-controllers. This is becoming more and more popular for prototyping IoT applications. However, in terms of speed, it cannot compete with C/C++.
* **Python Scripting**: And many software systems use Python as a scripting language to enhance its functionality (like our PLM solution at OST, or AWS Lambda Functions)
%% Cell type:markdown id: tags:
# About this Course
%% Cell type:markdown id: tags:
## Some Comments Upfront
1. The goal of this course is a dedicated introduction to the programming language for engineers
* Basic usage of the language
* Crunching data and connecting from different sources
* Dealing with math and visualization
2. With 2 ECTS we can only scrath at the surface
* We will give you a lot of hints where you can do a deep dive yourself
* If you want to become a programmer: you need to programm, A LOT!
* We highly recommend to to give yourself challanges (AI is a good source to find ideas on how you can challange yourselg)
3. Language: This course is in English language
* Most of the documentaiton and examples you find are in English anyway
* We plan to offer this course to incomming exchange students
4. There are tons of material to read, learn, and get support online
* Most of the time this course refers to: https://docs.python.org/3/ and https://www.w3schools.com/
* The fist is comprehensive and accurate to the latest standard
* The second one is simple, sets focus on the basics, and it looks the same for many programming languages
%% Cell type:markdown id: tags:
## Content of this Course
1. The basics (Week 1-4)
* Working with Jupiter Notebooks and VS-Code
* Python syntax, data types, and control structures, loops
* Functions, namespaces, and libraries
2. Working with data (Week 5-7)
* Extended list types: dictionary, tuples, sets
* Crunching strings
* Reading and writing files
3. Dedicated libraries for engineers (Week 8-10)
* Pandas
* NumPy
* MathPlot
4. Advanced programming skills (Week 11-14)
* Using webservices
* Object oriented programming with Python
You will find all required links on Moodle. And all lecture notebooks can be accessed here:
https://gitlab.ost.ch/edu-public/python-for-engineers/pyeng-lectures
%% Cell type:markdown id: tags:
## About coding and AI in this course
* AI and co-pilots are great tools! I use them a lot for programming, it makes me faster
* At these days, we cannot trust into AI.
* Sometimes it does not understand the problem, your are trying to solve,
* sometimes it just makes things up that that do not exist
* AI has become a problem in cyber security
* Thus, AI is only a helpful tool, if you can understand the output of it
* When using AI, make sure you know what you are doing.
**If you are new to a langugage don't use co-pilots. You need to get familiar with the syntax and you need to figure out how to use the language yourself**
Remark, this Video explains very well, what you should consider when learning Python, and how to use/not use AI/Co-Pilots: https://www.youtube.com/watch?v=St48epdRDZw
%% Cell type:markdown id: tags:
## Our Development Environment
* In this course we use **Visual Studio Vode** as our IDE (most of you should be familiar with this)
* Most of the exercises will be done on **Jupiter Notebook**
* All templates and exercises are deliveres thoroug **gitlab**: https://gitlab.ost.ch/edu-public/python-for-engineers/pyeng-exercises
* We highly encourage you to store your code in a personal ***git repository***!
* This is the way programmers work, and you won't loose your code
* If you want support, this is the best way to share code with us (I will not accept python files via email)
* For those who don't know git, go here: https://www.youtube.com/watch?v=r8jQ9hVA2qs
* In class we are working with **Python version 3.7**
* Feel free to use your own device and upgrade to version **3.12**. However, we will not support or assist with private installations.
%% Cell type:markdown id: tags:
# Lesson 1: Introduction to Jupyter Notebook
%% Cell type:markdown id: tags:
## About Jupyter Notebook
* As mentioned before Jupyter Notebooks are a great way to program, explain, document and present results all in one place.
* Jupyter notebook is a fusion of two very fundamental technologies
* Markdown: A simple notation convention to create formated text using a plain text editor
* Python: Our programming language
* In short jupiter notebook is a simple file with the ending .ipynb
* Visual Studio Code (or in Jupyterlab, wich is another tool work with Jupyter notebooks) help you make these files interactive
* Inside these file we can create blocks
* Markdown blocks to wirte text
* Python blocks to write code
* Each python block is followed by an output block where we see the results of the python code.
%% Cell type:markdown id: tags:
## Let's Create our First Notebook
<img src="images/pynb-hello-world.png" class="float-left" />
You see, it's simple...
%% Cell type:markdown id: tags:
## Here's What a Real Document Could Look Like
[Example](http://localhost:8888/notebooks/lecture1/example.ipynb#)
Need more hints?
* This a good introduction to jupyter notebooks: https://www.dataquest.io/blog/jupyter-notebook-tutorial/
* This is a good guide to work with jupyter in VSCode: https://code.visualstudio.com/docs/datascience/jupyter-notebooks
%% Cell type:markdown id: tags:
## The most Important Markdown Rules
| Sign | Explanation | Exampe |
| --------------- | ----------------------------- | --------------------------------------- |
| `# Title` | Heading 1 | <h1>Heading 1</h1> |
| `## Title` | Heading 2 | <h2>Heading 1</h1> |
| `*some text*` | Italic | *This is italic text* |
| `**some text**` | Bold | **This is bold text** |
| `* Point` | Bullet point | <ul><li>Point 1</li></ul> |
| `1. Item` | Numberd Item (allways use 1.) | <ol><li>Item 1</li><li>Item 2</li></ol> |
| `---` | Horizontal line | |
| \`code\` | Code (mono spcae) | `code example` |
with the sign `(``` python)` you can format Markdown text into python code
``` python
print("hello World")
For further reference go here: [https://markdownguide.org/cheat-sheet/]
%% Cell type:markdown id: tags:
# We did it, that's all for today.
## *Now let's get our hands dirty!*
pyeng-lectures @ 6283ee5c
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