Coding with Python is so much more than just knowing what code to write. It also requires knowing how to setup and maintain your Python programming environment. You should know how use the terminal, how to install and work with code other people wrote, how to setup and activate your virtual environment, and of course so much more.
This may sound intimidating at first, but it really isn't all that bad. It's actually a very fun part of programming because it helps you understand how the code you write comes to life when you run it. To me it's part of the "engineering" side of software engineering.
In this chapter, you will setup your Python environment on your computer. You will use the terminal, install software, and learn two ways to run your Python code. Early in this chapter, you will already be writing Python code! You will write code directly into the terminal. At the end of this chapter, you will have your basic Python environment setup on your computer and will begin writing code inside Python files. You will write a Python script in a .py file that prints a message to your terminal.
Before you can start writing Python code, you need to make sure you have Python installed on your computer. Some computers have Python pre-installed and others don't. Even if a computer has Python pre-installed, because Python has versions 2 and 3 available for use, you want to make sure you know which version you have.
Check whether you have Python installed and which versions by using the terminal. You should check for both Python 2 and Python 3. Open up a terminal session on your computer and enter python --version to check for Python 2 and python3 --version to check for Python3.
python --versionpython3 --versionIf you have that Python version installed, the terminal will respond with the version number.
Python 2.7.16Python 3.7.7You don't need both versions installed. You will probably work with one or the other. As for which one you should use, it depends. If you're starting out learning Python or don't have any Python 2 projects, you should probably work with Python 3. If, however, you have a specific need to use Python 2, then make sure you have it installed.
If you don't have the Python version that you want to work with installed on your computer, you should install it. To download Python, visit the Python downloads page. Check to make sure you're on the page for your operating system (for instance, Mac, Windows, etc.). Choose the version you want to download and follow the installation instructions.
When installation is complete, check again whether Python is installed. Depending upon which version you installed, enter in the terminal python --version to check for Python 2 or python3 --version to check for Python3.
python --versionpython3 --versionIf installation succeeded, the terminal will respond with the version number that you installed.
Test it out! Write Python code directly in your terminal.
You can open a Python session in the terminal by typing python3 and hitting Enter. The python3 command starts a session using Python 3 (use python to start a session using Python 2). The terminal should respond with the Python version, some additional information, and then >>>. Next to the >>>, you can write Python code.
Python 3.7.7 (default, Mar 10 2020, 15:43:03)
[Clang 11.0.0 (clang-1100.0.33.17)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> Start by getting Python to print something to the terminal. You'll learn later about data types, but for now know that if you want Python to print text to the terminal, you need to tell Python that the text is a string. To do that, wrap in single ' ' or double " " quotes what you type into the terminal, and Python will know that what you typed is a string. The terminal should print what you typed.
In your terminal session, next to the >>>, type 'Coding with Python' (be sure to include the quotes) and hit Enter.
>>> 'Coding with Python'
'Coding with Python'Try something else. Below the print, you should see another >>>. Next to it, type Coding with Python (but this time don't wrap it in quotes) and hit Enter. The terminal should print an error message.
>>> Coding with Python
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'Coding with Python' is not definedWhat?! You receive this error because you need to wrap text in single ' ' or double " " quotes. Without the quotes, Python doesn't know what it is that you entered because Python thinks the text is a variable, looks for it in the memory, doesn't find it, and then tells you that the text is undefined.
Strings are one of several Python built-in data types. Numbers are another data type. Try printing a number in the termianl. You should see another >>> at the bottom of your Python session in the terminal. Next to it, type a number, like 8 (don't wrap it in quotes) and hit Enter. The terminal doesn't return an error! It prints the number. Python recognizes the number you entered as number data type. Numbers are not wrapped in quotes.
>>> 8
8You will learn more about data types in later chapters.
To exit the Python session in your terminal, type exit() and hit Enter. The terminal should show the path to your present working directory (the folder on your computer to which the terminal is pointing).
Writing Python code in your terminal is an okay way to practice writing Python code. Using and integrated development environment (IDE) is a better option. An IDE is software for building applications. They make it easy to write and test code. Plus, IDEs usually combine common developer tools into one interface.
You have several IDEs available. One of the most popular is Microsoft's Visual Studio Code. It is a free code editor that can be used with Windows, Linux and macOS. VS Code has built-in tools to help you write code. For instance, it has tools that help with debugging, highlight syntax, provide intelligent code auto-completion, suggest code snippets, format your code, and embed Git. You can also install extensions that add additional functionality.
Install VS Code by visiting the Microsoft installation page. Follow the instructions for downloading the correct version to your operating system.
Next, create an empty folder somewhere on your computer. Name it python_practice. Then, in VS Code, choose File --> Open and open the python_practice folder. On the lefthand side of your VS Code, you shoul see a pane that lists the python_practice folder.
In VS Code, right click on the python_practice and choose New File. Name the new file app.py. At the top of your app.py file, type print("Python practice").
Next, in VS Code, choose File --> Terminal. This should open up a terminal session inside your VS Code. If you read the line that appears in the terminal when you open it, you should see that it is located within your python_practice project folder. If not, in the terminal, type cd, then spacebar, and then drag your python_practice folder to the terminal (which should result in a path to your python_practice folder). Then hit enter.
Once your terminal is in your python_practice project folder, you can run your Python file. In the terminal, type python3 app.py. It should print to the terminal the message you put in the print statement in your app.py file --> "Python practice".
If that worked, then your project setup is correct!
After confirming that your project setup is correct, create and activate your virtual environment. By creating a virtual environment, you keep the project dependencies for this project separate from the project dependencies of your other projects on the same computer. For instance, using virtual environments allows you to have one Flask project that uses Flask version 1.1.2 and Python 3.7 and another Flask project that uses Flask version 1.0 and Python 3.6.4. You can run them from the same computer without having to uninstall and reinstall the packages when switching between projects.
Because of its role as a partition between projects, setting up a virtual environment should be part of the initial setup of every Flask application. The first step is to install, or confirm that you already have installed, the tool for creating and managing a virtual environment.The next step is to actually create the virtual environment.
Confirm the terminal is in the root level of your project folder. Look at your project folder and notice that it does not have an env folder.
As shown below, enter the command in your terminal that creates the virtual environment. The last item in the command is the name of the virtual environment folder that will appear in your project folder. You can name it whatever your want, but the convention is to name it env or venv. In this example, I name it env. After you run the command, look in your project folder. You should see a folder named env.
For MacOS users, create a virtual environment by entering the following in your terminal:
python3 -m venv envFor Windows users, create a virtual environment by entering the following in your terminal:
py -m venv envActivate the virtual environment. Now that you have a virtual environment, you need to activate it. Each time you open your project folder, you will need to activate your virtual environment.
For MacOS users, activate the virtual environment by entering the following in your terminal:
source env/bin/activateFor Windows users, activate the virtual environment by entering the following in your terminal:
.\env\Scripts\activateConfirm you are in the virtual environment. In your terminal, if you see on the far left of the command line the name of your virtual environment inside parenthesis, then you have successfully activated your virtual environment. You can also confirm whether you are in your virtual environment using a terminal command.
For macOS users, confirm that you are in your virtual environment by entering the following in your terminal:
which pythonFor Windows users, confirm that you are in your virtual environment by entering the following in your terminal:
where pythonIf your virtual environment is activated, your terminal will point you to the directory in which your virtual environment exists (i.e., the env folder). For instance:
. . . /env/bin/pythonIf your virtual environment is not activated, your terminal will point you to the directory in which your Python installation lives globally on your computer. For instance:
/usr/bin/pythonWhile still in your project folder, create a requirements.txt file. Instructions below. It will list the packages installed in your env.
Before you run the command below, look in your project folder and notice that it is missing a requirements.txt file. After running the command, look again. Your project folder should have a requirements.txt file.
pip3 freeze > requirements.txtIf you look inside the requirements.txt file, it should be empty.
Also create a .gitignore file (starts with a . and ends with no extension). Inside the .gitignore file, type env. By having a requirements.txt file that lists the dependencies and a .gitignore file that lists the env file containing the dependencies, you can save your code to GitHub without pushing all the dependency packages. Without including the dependencies, your code will download and upload more quickly and will take less storage space on GitHub. Then, when you or someone pulls the code from GitHub, you can install the dependencies listed in the requirements.txt file.
Now you can install packages. Install Flask so that you can set up your server.
pip3 install FlaskNext, in your terminal, again run
pip3 freeze > requirements.txt This updates the requirements.txt file with the installed packages. After freezing your requirements.txt file, if you look at your requirements.txt file, you should see an updated list of the packages installed for your project’s virtual environment. Yours should include Flask and any other packages you installed. When you push to GitHub, notice that the env folder is missing (if you remembered to create your .gitignore file).
Sidenote: You can freeze as many times as you want. It is best to do so before deployment and also good practice to do so after installing one or more new packages.
To deactivate your virtual environment, type in your terminal
deactivateFor now, do not deactivate your virtual environment. You should continue working in it for the remainder of the tutorial.