This repository contains the files, libraries and applications for a Python development environment.

You'll set up this environment and use it to create a simple project of your choice. Here are a few suggestions:

• Mad Libs
• Calculator
• Hangman
• Tic Tac Toe
• Blackjack

The goal of this project is to learn basic programming and get more comfortable working in an environment that's not visual. Building a website lets a developer see the results in a web browser and the kinds of applications we use every day have things like buttons to interact with, but often these are powered by programs that can only be interacted with by text. Pressing that button might send a text command to a different program running on a server, and an important part of thinking like a developer is being able to understand a program's code without actually seeing the results or have a visual way to interact with it.

After completing this project, you'll have an understanding of writing code in Python but also ideas that apply to other programming languages. We'll use that and combine it with what you've learned so far to create a web app using HTML, CSS, and Javascript.

First, though, you'll start by learning the basics of Python by decoding an example program that is a simple guess the secret number game. Think of it like a puzzle or a toy to take apart, trying to figure out how it works on the inside. Other examples will help to guide the process as a sort of partial answer key, showing how the smaller parts work, but you'll be trying to understand how it all works together to make the game function. Along the way, try to keep track of questions or parts you are stuck in. Getting stuck is totally normal when understanding how some code works, and actually an important part of learning how to write code. Most of all, try to have fun being curious about taking apart a puzzle to put it back together again.

With this project, you'll be creating a new virtual environment in Docker. This will be the workspace that you'll run your Python programs, since not every computer has Python installed. This virtual environment will have Python preinstalled and everything set up to run Python programs, but can only be interacted with using the terminal.

You'll need 3 things first: a code editor, Docker Desktop, and the Github application. Review the readme for the https://github.com/passthefist/dev_container repository for some of these steps.

Right now, this project isn't owned by you, so you'll need to create a copy of it that you own. The steps to clone this project are the same as the ones for the dev_container. Click the "Fork" button to create a copy of this project for your Github account, which will create another repository for this project separate from the dev_container one. It will take you to a prompt, where you can choose your user in the "Owner" dropdown and just keep the defaults for the rest. Clicking the "Create Fork" button will create your own version of this project owned by your account.

Right now, the code for the project only exists on the GitHub website, but you'll need it to be on your computer to work on. Again, this is similar to the steps for the dev_container project. First, open the GitHub Desktop app on your computer, then click the "Clone a Repository From the Internet" button.

In the upper left corner of the Github Desktop app, you can search for your repositories. Choose this one (it should be called "python_workspace") to create a copy of the repository to work with on your computer. You will now have this repository as well as the one for the dev container from before.

The easiest way to do this is using the command line in Visual Studio Code, which can be opened from the terminal menu. Make sure Docker Desktop is running and use the docker-compose command to build the workspace container with docker-compose build, then start it with docker-compose up.

If you see an error message like this, make sure that the Docker Desktop app is running.

error during connect: this error may indicate that the docker daemon is not running: Get "http://%2F%2F.%2Fpipe%2Fdocker_engine/_ping": open //./pipe/docker_engine: The system cannot find the file specified.

Once built, the container can be ran and managed from the Docker Desktop app like the dev_container. You can also use the docker-compose up and docker-compose down commands in a terminal to start and stop it respectively.

Connect to your Python workspace by typing the command docker attach python_workspace into a terminal. This tells the docker program to run the attach command to attach your terminal to a specified docker container. Here, the command will find the container named python_workspace (the one you just created) and connect your terminal there. Importantly, this is a different terminal than the one you initially opened which was running on your computer. Now, this terminal is actually running on your virtual Python workspace, which has Python preinstalled. Having a container already set up like this avoids any issues that might make installing Python difficult or difference between computers. This way, the workspace is always consistent and ready to use once built.

Any time you want to run a Python program, you'll need to do it after attaching to the python workspace container.

With a terminal attached to you workspace container, you can run the ls command to get a list of all the files and folders in this project. Refer to this cheatsheet for common commands to navigate a terminal environment and an explanation of them.

Next, you can use the cd command to open the examples folder. Whenever you attach to your python workspace to run the examples, you'll need to cd into the directory.

Try using ls to see what's in this folder. You'll see a bunch of files that end in .py, which means they are Python program files. Open hello_world.py in your editor and run it in your workspace with python 1_hello_world.py. This command tells Python to run the 1_hello_world.py program. Read through the code in the file and try to match it to the output.

Then, run the guess_the_number.py program. This is a guess the number game, where you have to guess a secret number. Opening it in an editor and looking through the code might be intimidating to start, but by the end you'll be able to understand how it works by using the other examples to help.

You've now set up everything you need to write and run Python programs. Before starting on your project, work through some of the other programs in the examples folder to get a feel for Python.

Refer to this cheatsheet for common commands to navigate a terminal environment and an explanation of them.

Start with opening the tunning the python guess_the_number.py in your Python workspace container. This program is a simple game where the player tries to guess a secret number. There is a consistent strategy that will always allow you to find the number, see if you can find that strategy as you play the game. This will be the program you'll be trying to understand. Open the guess_the_number.py program in your editor and take a look. It might be intimidating but by going through the examples you'll be able to read the code and know how the game works.

The other examples are made to build on each other, starting with 1_hello_world.py. Open the file in your editor and run it in the terminal that you've attached to your Python workspace with python 1_hello_world.py. This example shows one of the most basic programs. Each of the other examples are meant to build on each other, so after each one try going back to the game program and see what new parts you can start to understand. You'll be going back and forth between the examples and the game program as you go, using the examples as clues to solving the puzzle. Don't expect to be able to understand the whole program all at once, just little parts at a time. Eventually, start trying understand how the parts work together and how the program works as a whole.

Remember that getting stuck is part of the process. It's a lot to learn, so focus on one bit at a time and keep track of questions, where you're getting stuck, and any notes in general.

An interactive Python session allows you to try out bits of Python at a time. You can write lines of code one at a time and see what they do interactively instead of running a whole file.

You can start an interactive Python session with just the python command and no file after it. It will open a special console that lets you try out some Python code line by line. Initially, it should look like this:

Python 3.8.3 (default, Jun  9 2020, 17:39:39) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> 

If you type a bit of code such as adding some numbers together and hit enter, it will run that code and print the result on the next line.

Python 3.8.3 (default, Jun  9 2020, 17:39:39) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> 1 + 2
3  

The interactive session is a real Python environment, so you can define functions and variables, and they will be kept even for other lines of code (see the 3_intro_variables.py and 6_function.py files for more on variables and functions).

Python 3.8.3 (default, Jun  9 2020, 17:39:39) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> a = 4
>>> b = 5
>>> a + b
9   
>>> def add_3(num):
...     return num + 3
...
>>> add_3(7)
10