This versioned tutorial group will guide you through installing Python 3 on your local machine and setting up a programming environment via the command line.

Ubuntu

20.04

### Introduction

Python is a flexible and versatile programming language that can be leveraged for many use cases, with strengths in scripting, automation, data analysis, machine learning, and back-end development. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use. Quick to set up, and written in a relatively straightforward style with immediate feedback on errors, Python is a great choice for beginners and experienced developers alike. [Python 3 is the most current version](https://www.digitalocean.com/community/tutorials/python-2-vs-python-3-practical-considerations-2) of the language and is considered to be the future of Python.  

This tutorial will guide you through installing Python 3 on your **local** Linux machine and setting up a programming environment via the command line. This tutorial will explicitly cover the installation procedures for Ubuntu 20.04, but the general principles apply to any other distribution of Debian Linux. 

## Prerequisites

You will need a computer or virtual machine with Ubuntu 20.04 installed, as well as have administrative access to that machine and an internet connection. You can download this operating system via the [Ubuntu 20.04 releases page](http://releases.ubuntu.com/focal/). 

Alternatively, you can use an interactive terminal embedded on this page to experiment with the sample commands in this tutorial. Click the following **Launch an Interactive Terminal!** button to open a terminal window and begin working with an Ubuntu 20.04 environment.
  
[terminal ubuntu:focal-python3]

## Step 1 — Setting Up Python 3

We’ll be completing our installation and setup on the command line, which is a non-graphical way to interact with your computer. That is, instead of clicking on buttons, you’ll be typing in text and receiving feedback from your computer through text as well. 

The command line, also known as a shell or terminal, can help you modify and automate many of the tasks you do on a computer every day, and is an essential tool for software developers. There are many terminal commands to learn that can enable you to do more powerful things. The article “[An Introduction to the Linux Terminal] (https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal)” can get you better oriented with the terminal.

On Ubuntu 20.04, you can find the Terminal application by clicking on the Ubuntu icon in the upper-left hand corner of your screen and typing “terminal” into the search bar. Click on the Terminal application icon to open it. Alternatively, you can hit the `CTRL`, `ALT`, and `T` keys on your keyboard at the same time to open the Terminal application automatically. 

![Ubuntu Terminal](https://assets.digitalocean.com/articles/eng_python/UbuntuDebianSetUp/UbuntuSetUp.png)

Ubuntu 20.04 ships with both Python 3 and Python 2 pre-installed. To make sure that our versions are up-to-date, let’s update and upgrade the system with the `apt` command to work with Ubuntu’s **A**dvanced **P**ackaging **T**ool:

```command
sudo apt update
sudo apt -y upgrade
```

The `-y` flag will confirm that we are agreeing that all items to be installed, but depending on your version of Linux, you may need to confirm additional prompts as your system updates and upgrades. 

Once the process is complete, we can check the version of Python 3 that is installed in the system by typing: 

```command
python3 -V
```

You will receive output in the terminal window that will let you know the version number. The version number may vary, but it will be similar to this:

```
[secondary_label Output]
Python <^>3.8.10<^>
```

To manage software packages for Python, let’s install **pip**, a tool that will install and manage programming packages we may want to use in our development projects. You can learn more about modules or packages that you can install with pip by reading “[How To Import Modules in Python 3](https://www.digitalocean.com/community/tutorials/how-to-import-modules-in-python-3).”

```command
sudo apt install -y python3-pip
```

Python packages can be installed by typing:

```command
pip3 install <^>package_name<^>
```

Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3 install numpy`.

There are a few more packages and development tools to install to ensure that we have a robust set-up for our programming environment:

```command
sudo apt install build-essential libssl-dev libffi-dev python-dev
```

Press `y` if prompted to do so.

Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.

## Step 2 —  Setting Up a Virtual Environment

Virtual environments enable you to have an isolated space on your computer for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.

Setting up a programming environment provides us with greater control over our Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages. 

You can set up as many Python programming environments as you want. Each environment is basically a directory or folder in your computer that has a few scripts in it to make it act as an environment. 

While there are a few ways to achieve a programming environment in Python, we’ll be using the **venv** module here, which is part of the standard Python 3 library. Let’s install venv by typing: 

```command
sudo apt install -y python3-venv
```

With this installed, we are ready to create environments. Let’s either choose which directory we would like to put our Python programming environments in, or create a new directory with `mkdir`, as in:

```command
mkdir <^>environments<^>
cd <^>environments<^>
```

Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:

```command
python3 -m venv <^>my_env<^>
```

Essentially, this sets up a new directory that contains a few items which we can view with the `ls` command:

```command
ls my_env
```

```
[secondary_label Output]
bin include lib lib64 pyvenv.cfg share
```

Together, these files work to make sure that your projects are isolated from the broader context of your local machine, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs. Python Wheels, a built-package format for Python that can speed up your software production by reducing the number of times you need to compile, will be in the Ubuntu 18.04 `share` directory.

To use this environment, you need to activate it, which you can do by typing the following command that calls the activate script:

```command
source <^>my_env<^>/bin/activate
```

Your prompt will now be prefixed with the name of your environment, in this case it is called <^>my_env<^>. Your prefix may appear somewhat differently, but the name of your environment in parentheses should be the first thing you see on your line:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
  
```

This prefix lets us know that the environment <^>my_env<^> is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages. 

<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3`, and `pip` instead of `pip3` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3` and `pip3` commands exclusively. 
<$>

After following these steps, your virtual environment is ready to use.

## Step 3 — Creating a “Hello, World” Program

Now that we have our virtual environment set up, let’s create a traditional “Hello, World!” program. This will let us test our environment and provides us with the opportunity to become more familiar with Python if we aren’t already. 

To do this, we’ll open up a command-line text editor such as nano and create a new file:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
nano hello.py
```

When the text file opens up in the terminal window we’ll type out our program:

```python
print("Hello, World!")
```

Exit nano by typing the `CTRL` and `X` keys, and when prompted to save the file press `y`. 

Once you exit out of nano and return to your shell, we’ll run the program:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
python hello.py
```

The `hello.py` program that you created should cause your terminal to produce the following output:

```
[secondary_label Output]
Hello, World!
```

To leave the environment, type the command `deactivate` and you will return to your original directory. 

## Conclusion

Congratulations! At this point you have a Python 3 programming environment set up on your local Ubuntu machine and can begin a coding project!

If you are using a different local machine, refer to the tutorial that is relevant to your operating system in our “[How To Install and Set Up a Local Programming Environment for Python 3](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3)” series. Alternatively, if you’re using an Ubuntu server, you can follow the “[How To Install Python and Set Up a Programming Environment on an Ubuntu 20.04 Server](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-20-04-server)” tutorial.

With your local machine ready for software development, you can continue to learn more about coding in Python by reading our free [*How To Code in Python 3* eBook](https://do.co/python-book), or consulting our [Programming Project tutorials](https://www.digitalocean.com/community/tags/project). 




Python is a flexible and versatile programming language that can be leveraged for many use cases, with strengths in scripting, automation, data analysis, machine learning, and back-end development. This tutorial will guide you through installing Python 3 on your local Ubuntu 20.04 Linux machine and setting up a programming environment via the command line.

How To Install Python 3 and Set Up a Local Programming Environment on Ubuntu 20.04

How To Install Python 3 and Set Up a Local Programming Environment

18.04

### Introduction

Python is a flexible and versatile programming language that can be leveraged for many use cases, with strengths in scripting, automation, data analysis, machine learning, and back-end development. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use. Quick to set up, and written in a relatively straightforward style with immediate feedback on errors, Python is a great choice for beginners and experienced developers alike. [Python 3 is the most current version](https://www.digitalocean.com/community/tutorials/python-2-vs-python-3-practical-considerations-2) of the language and is considered to be the future of Python.  

This tutorial will guide you through installing Python 3 on your **local** Linux machine and setting up a programming environment via the command line. This tutorial will explicitly cover the installation procedures for Ubuntu 18.04, but the general principles apply to any other distribution of Debian Linux. 

Alternatively, you can use an interactive terminal embedded on this page to experiment with the sample commands in this tutorial. Click the following **Launch an Interactive Terminal!** button to open a terminal window and begin working with an Ubuntu 18.04 environment.
  
[terminal ubuntu:bionic-python3]

## Prerequisites

You will need a computer or virtual machine with Ubuntu 18.04 installed, as well as have administrative access to that machine and an internet connection. You can download this operating system via the [Ubuntu 18.04 releases page](http://releases.ubuntu.com/releases/18.04/). 

## Step 1 — Setting Up Python 3

We’ll be completing our installation and setup on the command line, which is a non-graphical way to interact with your computer. That is, instead of clicking on buttons, you’ll be typing in text and receiving feedback from your computer through text as well. 

The command line, also known as a shell or terminal, can help you modify and automate many of the tasks you do on a computer every day, and is an essential tool for software developers. There are many terminal commands to learn that can enable you to do more powerful things. The article “[An Introduction to the Linux Terminal] (https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal)” can get you better oriented with the terminal.

On Ubuntu 18.04, you can find the Terminal application by clicking on the Ubuntu icon in the upper-left hand corner of your screen and typing “terminal” into the search bar. Click on the Terminal application icon to open it. Alternatively, you can hit the `CTRL`, `ALT`, and `T` keys on your keyboard at the same time to open the Terminal application automatically. 

![Ubuntu Terminal](https://assets.digitalocean.com/articles/eng_python/UbuntuDebianSetUp/UbuntuSetUp.png)

Ubuntu 18.04 ships with both Python 3 and Python 2 pre-installed. To make sure that our versions are up-to-date, let’s update and upgrade the system with the `apt` command to work with Ubuntu’s **A**dvanced **P**ackaging **T**ool:

```command
sudo apt update
sudo apt -y upgrade
```

The `-y` flag will confirm that we are agreeing that all items to be installed, but depending on your version of Linux, you may need to confirm additional prompts as your system updates and upgrades. 


Once the process is complete, we can check the version of Python 3 that is installed in the system by typing: 

```command
python3 -V
```

You will receive output in the terminal window that will let you know the version number. The version number may vary, but it will be similar to this:

```
[secondary_label Output]
Python <^>3.6.9<^>
```

To manage software packages for Python, let’s install **pip**, a tool that will install and manage programming packages we may want to use in our development projects. You can learn more about modules or packages that you can install with pip by reading “[How To Import Modules in Python 3](https://www.digitalocean.com/community/tutorials/how-to-import-modules-in-python-3).”

```command
sudo apt install -y python3-pip
```

Python packages can be installed by typing:

```command
pip3 install <^>package_name<^>
```

Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3 install numpy`.

There are a few more packages and development tools to install to ensure that we have a robust set-up for our programming environment:

```command
sudo apt install build-essential libssl-dev libffi-dev python-dev
```

Press `y` if prompted to do so.

Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.

## Step 2 —  Setting Up a Virtual Environment

Virtual environments enable you to have an isolated space on your computer for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.

Setting up a programming environment provides us with greater control over our Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages. 

You can set up as many Python programming environments as you want. Each environment is basically a directory or folder in your computer that has a few scripts in it to make it act as an environment. 

While there are a few ways to achieve a programming environment in Python, we’ll be using the **venv** module here, which is part of the standard Python 3 library. Let’s install venv by typing: 

```command
sudo apt install -y python3-venv
```

With this installed, we are ready to create environments. Let’s either choose which directory we would like to put our Python programming environments in, or create a new directory with `mkdir`, as in:

```command
mkdir <^>environments<^>
cd <^>environments<^>
```

Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:

```command
python3 -m venv <^>my_env<^>
```

Essentially, this sets up a new directory that contains a few items which we can view with the `ls` command:

```command
ls my_env
```

```
[secondary_label Output]
bin include lib lib64 pyvenv.cfg share
```

Together, these files work to make sure that your projects are isolated from the broader context of your local machine, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs. Python Wheels, a built-package format for Python that can speed up your software production by reducing the number of times you need to compile, will be in the Ubuntu 18.04 `share` directory.

To use this environment, you need to activate it, which you can do by typing the following command that calls the activate script:

```command
source <^>my_env<^>/bin/activate
```

Your prompt will now be prefixed with the name of your environment, in this case it is called <^>my_env<^>. Your prefix may appear somewhat differently, but the name of your environment in parentheses should be the first thing you see on your line:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
  
```

This prefix lets us know that the environment <^>my_env<^> is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages. 

<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3`, and `pip` instead of `pip3` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3` and `pip3` commands exclusively. 
<$>

After following these steps, your virtual environment is ready to use.

## Step 3 — Creating a “Hello, World” Program

Now that we have our virtual environment set up, let’s create a traditional “Hello, World!” program. This will let us test our environment and provides us with the opportunity to become more familiar with Python if we aren’t already. 

To do this, we’ll open up a command-line text editor such as nano and create a new file:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
nano hello.py
```

When the text file opens up in the terminal window we’ll type out our program:

```python
print("Hello, World!")
```

Exit nano by typing the `CTRL` and `X` keys, and when prompted to save the file press `y`. 

Once you exit out of nano and return to your shell, we’ll run the program:

```custom_prefix((my_env)\ssammy@localhost:~/environments$)
python hello.py
```

The `hello.py` program that you just created should cause your terminal to produce the following output:

```
[secondary_label Output]
Hello, World!
```

To leave the environment, type the command `deactivate` and you will return to your original directory. 

## Conclusion

Congratulations! At this point you have a Python 3 programming environment set up on your local Ubuntu machine and can begin a coding project!

If you are using a different local machine, refer to the tutorial that is relevant to your operating system in our “[How To Install and Set Up a Local Programming Environment for Python 3](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3)” series. Alternatively, if you’re using an Ubuntu server, you can follow the “[How To Install Python and Set Up a Programming Environment on an Ubuntu 18.04 Server](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-18-04-server)” tutorial.

With your local machine ready for software development, you can continue to learn more about coding in Python by reading our free [*How To Code in Python 3* eBook](https://do.co/python-book), or consulting our [Programming Project tutorials](https://www.digitalocean.com/community/tags/project). 


Python is a flexible and versatile programming language that can be leveraged for many use cases, with strengths in scripting, automation, data analysis, machine learning, and back-end development. This tutorial will guide you through installing Python 3 on your local Ubuntu 18.04 Linux machine and setting up a programming environment via the command line. 

How To Install Python 3 and Set Up a Local Programming Environment on Ubuntu 18.04

Debian

### Introduction


A versatile programming language, Python can be used for many different programming projects. With a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use and first published it in 1991. Easy to set up, and written in a relatively straightforward style with immediate feedback on errors, Python is a great choice for beginners and experienced developers alike. Python 3 is the most current version of the language and is considered to be the future of Python. 


This tutorial will guide you through installing Python 3 on your local Linux machine and setting up a programming environment via the command line. This tutorial will explicitly cover the installation procedures for and Debian 8, but the general principles apply to any other distribution of Debian Linux. 


## Prerequisites


You will need a computer with Debian 8 or another version of Debian Linux installed, as well as have administrative access to that machine and an internet connection.


## Step 1 — Setting Up Python 3


We’ll be completing our installation and setup on the command line, which is a non-graphical way to interact with your computer. That is, instead of clicking on buttons, you’ll be typing in text and receiving feedback from your computer through text as well. The command line, also known as a shell, can help you modify and automate many of the tasks you do on a computer every day, and is an essential tool for software developers. There are many terminal commands to learn that can enable you to do more powerful things. The article “[An Introduction to the Linux Terminal] (https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal)” can get you better oriented with the terminal.


On Debian 8, you can open the Menu in the lower left-hand corner of your screen, and search for “terminal” in the search bar. Click on Terminal to open the program. You can also hit the `CTRL`, `ALT`, and `T` keys on your keyboard at the same time to open the Terminal application automatically. 


![Debian Terminal](https://assets.digitalocean.com/articles/eng_python/UbuntuDebianSetUp/DebianSetUp.png)


Debian 8, and other versions of Debian Linux ship with both Python 3 and Python 2 pre-installed. To make sure that our versions are up-to-date, let’s update and upgrade the system with `apt-get`:


```command
sudo apt-get update
sudo apt-get -y upgrade
```


The `-y` flag will confirm that we are agreeing for all items to be installed, but depending on your version of Linux, you may need to confirm additional prompts as your system updates and upgrades. 


Once the process is complete, we can check the version of Python 3 that is installed in the system by typing: 


```command
python3 -V
```


You will receive output in the terminal window that will let you know the version number. The version number may vary, but it will look similar to this:


```
[secondary_label Output]
Python <^>3.4.2<^>
```


To manage software packages for Python, let’s install **pip**:


```command
sudo apt-get install -y python3-pip
```


A tool for use with Python, **pip** installs and manages programming packages we may want to use in our development projects. You can install Python packages by typing:


```command
pip3 install <^>package_name<^>
```


Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3 install numpy`.


There are a few more packages and development tools to install to ensure that we have a robust set-up for our programming environment:


```command
sudo apt-get install build-essential libssl-dev libffi-dev python-dev
```


Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.


## Step 2 —  Setting Up a Virtual Environment


Virtual environments enable you to have an isolated space on your computer for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.


Setting up a programming environment provides us with greater control over our Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages. 


You can set up as many Python programming environments as you want. Each environment is basically a directory or folder in your computer that has a few scripts in it to make it act as an environment. 


We need to first install the **venv** module, part of the standard Python 3 library, so that we can create virtual environments for us. Let’s install venv by typing: 


```command
sudo apt-get install -y python3-venv
```


With this installed, we are ready to create environments. Let’s choose which directory we would like to put our Python programming environments in, or we can create a new directory with `mkdir`, as in:


```command
mkdir <^>environments<^>
cd <^>environments<^>
```


Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:


```command
python3 -m venv <^>my_env<^>
```


Essentially, this sets up a new directory that contains a few items which we can view with the `ls` command:


```command
ls my_env
```


```
[secondary_label Output]
bin  include  lib  lib64  pyvenv.cfg
```


Together, these files work to make sure that your projects are isolated from the broader context of your local machine, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs. Python Wheels is a built-package format for Python that can speed up your software production by reducing the number of times you need to compile. You’ll find this in each of the `lib` directories.


To use this environment, you need to activate it, which you can do by typing the following command that calls the activate script:


```command
source <^>my_env<^>/bin/activate
```


Your prompt will now be prefixed with the name of your environment, in this case it is called <^>my_env<^>. Depending on what version of Debian Linux you are running, your prefix may look somewhat different, but the name of your environment in parentheses should be the first thing you see on your line:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
  
```


This prefix lets us know that the environment <^>my_env<^> is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages. 


<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3`, and `pip` instead of `pip3` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3` and `pip3` commands exclusively. 
<$>


After following these steps, your virtual environment is ready to use.


## Step 3 — Creating a Simple Program


Now that we have our virtual environment set up, let’s create a simple “Hello, World!” program. This will make sure that our environment is working and gives us the opportunity to become more familiar with Python if we aren’t already. 


To do this, we’ll open up a command-line text editor such as nano and create a new file:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
nano hello.py
```


Once the text file opens up in the terminal window we’ll type out our program:


```python
print("Hello, World!")
```


Exit nano by typing the `control` and `x` keys, and when prompted to save the file press `y`. 


Once you exit out of nano and return to your shell, let’s run the program:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
python hello.py
```


The hello.py program that you just created should cause your terminal to produce the following output:


```
[secondary_label Output]
Hello, World!
```


To leave the environment, simply type the command `deactivate` and you will return to your original directory. 


## Conclusion


Congratulations! At this point you have a Python 3 programming environment set up on your local Debian Linux machine and can begin a coding project!


To set up Python 3 on another computer, follow the [local programming environment guides](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3) for [Ubuntu 16.04](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-local-programming-environment-on-ubuntu-16-04), [CentOS 7](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-centos-7), [Windows 10](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-windows-10), or [macOS](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-mac-os-x). You can also read about [installing Python and setting up a programming environment on an Ubuntu 16.04 server](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-16-04-server), which is especially useful when working on development teams.


With your local machine ready for software development, you can continue to learn more about coding in Python by following “[Understanding Data Types in Python 3](https://www.digitalocean.com/community/tutorials/understanding-data-types-in-python-3)” and “[How To Use Variables in Python 3](https://www.digitalocean.com/community/tutorials/how-to-use-variables-in-python-3)”.




This tutorial will get you up and running with a local Python 3 programming environment in Debian 8. Python is a versatile programming language that can be used for many different projects. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use. 

How To Install Python 3 and Set Up a Local Programming Environment on Debian 8

CentOS

###Introduction

Python is a versatile programming language that can be used for many different programming projects. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use. Easy to set up, and written in a relatively straightforward style with immediate feedback on errors, Python is a great choice for beginners and experienced developers alike. Python 3 is the most current version of the language and is considered to be the future of Python. 

This tutorial will guide you through installing Python 3 on your local CentOS 7 machine and setting up a programming environment via the command line. 

##Prerequisites

You will need a CentOS 7 computer with a non-root superuser account that is connected to the internet.

##Step 1 — Preparing the System

We will be completing this installation through the command line. If your CentOS 7 computer starts up with a Graphical User Interface (GUI) desktop, you can gain access to the command line interface through the Menu, by navigating to Applications, then Utilities, and then clicking on Terminal. If you need more guidance on the terminal, be sure to read through the article “[An Introduction to the Linux Terminal] (https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal).”

Before we begin with the installation, let's make sure to update the default system applications to have the latest versions available.

We will be using the open-source package manager tool **yum**, which stands for Yellowdog Updater Modified. This is a commonly used tool for working with software packages on Red Hat based Linux systems like CentOS. It will let you easily install and update, as well as remove software packages on your computer.

Let’s first make sure that yum is up to date by running this command:

```command
sudo yum -y update
```

The `-y` flag is used to alert the system that we are aware that we are making changes, preventing the terminal from prompting us to confirm.

Next, we will install **yum-utils**, a collection of utilities and plugins that extend and supplement yum:

```command
sudo yum -y install yum-utils
```

Finally, we’ll install the CentOS Development Tools, which are used to allow you to build and compile software from source code:

```command
sudo yum -y groupinstall development
```

Once everything is installed, our setup is in place and we can go on to install Python 3.

##Step 2 — Installing and Setting Up Python 3

CentOS is derived from RHEL (Red Hat Enterprise Linux), which has stability as its primary focus. Because of this, tested and stable versions of applications are what is most commonly found on the system and in downloadable packages, so on CentOS you will only find Python 2.

Since instead we would like to install the most current upstream stable release of Python 3, we will need to install **IUS**, which stands for Inline with Upstream Stable. A community project, IUS provides Red Hat Package Manager (RPM) packages for some newer versions of select software.

To install IUS, let’s install it through `yum`: 

```command
sudo yum -y install https://centos7.iuscommunity.org/ius-release.rpm
```

Once IUS is finished installing, we can install the most recent version of Python:

```command
sudo yum -y install python36u
```

When the installation process of Python is complete, we can check to make sure that the installation was successful by checking for its version number with the `python3.6` command: 

```command
python3.6 -V
```

With a version of Python 3.6 successfully installed, we will receive the following output:

```
[secondary_label Output]
Python <^>3.6.1<^>
```

We will next install **pip**, which will manage software packages for Python:

```command
sudo yum -y install python36u-pip
```

A tool for use with Python, we will use **pip** to install and manage programming packages we may want to use in our development projects. You can install Python packages by typing:

```command
sudo pip3.6 install <^>package_name<^>
```

Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3.6 install numpy`.

Finally, we will need to install the IUS package **python36u-devel**, which provides us with libraries and header files we will need for Python 3 development:

```command
sudo yum -y install python36u-devel
```

The **venv** module will be used to set up a virtual environment for our development projects in the next step.

##Step 3 —  Setting Up a Virtual Environment

Now that we have Python installed and our system set up, we can go on to create our programming environment with venv. 

Virtual environments enable you to have an isolated space on your computer for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.

Setting up a programming environment provides us with greater control over our Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages. 

You can set up as many Python programming environments as you want. Each environment is basically a directory or folder in your computer that has a few scripts in it to make it act as an environment. 

Choose which directory you would like to put your Python programming environments in, or create a new directory with `mkdir`, as in:

```command
mkdir <^>environments<^>
cd <^>environments<^>
```

Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:

```command
python3.6 -m venv <^>my_env<^>
```

Essentially, this command creates a new directory (in this case called <^>my_env<^>) that contains a few items that we can see with the `ls` command:

```
bin include lib lib64 pyvenv.cfg
```

Together, these files work to make sure that your projects are isolated from the broader context of your local machine, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs.

To use this environment, you need to activate it, which you can do by typing the following command that calls the **activate** script in the `bin` directory:

```command
source <^>my_env<^>/bin/activate
```

Your prompt will now be prefixed with the name of your environment, in this case it is called <^>my_env<^>:

```custom_prefix((my_env)\s[sammy@localhost]\senvironments]$)
  
```

This prefix lets us know that the environment <^>my_env<^> is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages. 

<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3.6`, and `pip` instead of `pip3.6` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3.6` and `pip3.6` commands exclusively. 
<$>

After following these steps, your virtual environment is ready to use.

##Step 4 — Creating a Simple Program

Now that we have our virtual environment set up, let’s create a simple “Hello, World!” program. This will make sure that our environment is working and gives us the opportunity to become more familiar with Python if we aren’t already. 

To do this, we’ll open up a command-line text editor such as **vim** and create a new file:

```custom_prefix((my_env)\s[sammy@localhost]\senvironments]$)
vi hello.py
```

Once the text file opens up in our terminal window, we will have to type `i` to enter insert mode, and then we can write our first program:

```python
print("Hello, World!")
```

Now press `ESC` to leave insert mode. Next, type `:x` then `ENTER` to save and exit the file.

We are now ready to run our program:

```custom_prefix((my_env)\s[sammy@localhost]\senvironments]$)
python hello.py
```

The hello.py program that you just created should cause the terminal to produce the following output:

```
[secondary_label Output]
Hello, World!
```

To leave the environment, simply type the command `deactivate` and you’ll return to your original directory. 

##Conclusion

Congratulations! At this point you have a Python 3 programming environment set up on your local CentOS 7 machine and can begin a coding project!

To set up Python 3 on another computer, follow the [local programming environment guides](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3) for [Ubuntu 16.04](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-in-ubuntu-16-04), [Debian 8](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-local-programming-environment-on-debian-8), [macOS](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-mac-os-x), or [Windows 10](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-windows-10). You can also read about [installing Python and setting up a programming environment on an Ubuntu 16.04 server](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-16-04-server), which is especially useful when working on development teams.

With your local machine ready for software development, you can continue to learn more about coding in Python by following “[Understanding Data Types in Python 3](https://www.digitalocean.com/community/tutorials/understanding-data-types-in-python-3)” and “[How To Use Variables in Python 3](https://www.digitalocean.com/community/tutorials/how-to-use-variables-in-python-3)”.

This tutorial will guide you through installing Python 3 on your local CentOS 7 machine and setting up a programming environment via the command line. Python is a versatile programming language that can be used for many different projects.

How To Install Python 3 and Set Up a Local Programming Environment on CentOS 7

16.04

###Introduction


This tutorial will get you up and running with a local Python 3 programming environment in Ubuntu 16.04. 


Python is a versatile programming language that can be used for many different programming projects. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use. Easy to set up, and written in a relatively straightforward style with immediate feedback on errors, Python is a great choice for beginners and experienced developers alike. Python 3 is the most current version of the language and is considered to be the future of Python. 


This tutorial will guide you through installing Python 3 on your local Linux machine and setting up a programming environment via the command line. This tutorial will explicitly cover the installation procedures for Ubuntu 16.04, but the general principles apply to any other distribution of Debian Linux. 


##Prerequisites


You will need a computer with Ubuntu 16.04 installed, as well as have administrative access to that machine and an internet connection.


##Step 1 — Setting Up Python 3


We’ll be completing our installation and setup on the command line, which is a non-graphical way to interact with your computer. That is, instead of clicking on buttons, you’ll be typing in text and receiving feedback from your computer through text as well. The command line, also known as a shell, can help you modify and automate many of the tasks you do on a computer every day, and is an essential tool for software developers. There are many terminal commands to learn that can enable you to do more powerful things. The article “[An Introduction to the Linux Terminal] (https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal)” can get you better oriented with the terminal.


On Ubuntu 16.04, you can find the Terminal application by clicking on the Ubuntu icon in the upper-left hand corner of your screen and typing “terminal” into the search bar. Click on the Terminal application icon to open it. Alternatively, you can hit the `CTRL`, `ALT`, and `T` keys on your keyboard at the same time to open the Terminal application automatically. 


![Ubuntu Terminal](https://assets.digitalocean.com/articles/eng_python/UbuntuDebianSetUp/UbuntuSetUp.png)


Ubuntu 16.04 ships with both Python 3 and Python 2 pre-installed. To make sure that our versions are up-to-date, let’s update and upgrade the system with `apt-get`:


```command
sudo apt-get update
sudo apt-get -y upgrade
```


The `-y` flag will confirm that we are agreeing for all items to be installed, but depending on your version of Linux, you may need to confirm additional prompts as your system updates and upgrades. 


Once the process is complete, we can check the version of Python 3 that is installed in the system by typing: 


```command
python3 -V
```


You will receive output in the terminal window that will let you know the version number. The version number may vary, but it will look similar to this:


```
[secondary_label Output]
Python <^>3.5.2<^>
```


To manage software packages for Python, let’s install **pip**:


```command
sudo apt-get install -y python3-pip
```


A tool for use with Python, **pip** installs and manages programming packages we may want to use in our development projects. You can install Python packages by typing:


```command
pip3 install <^>package_name<^>
```


Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3 install numpy`.


There are a few more packages and development tools to install to ensure that we have a robust set-up for our programming environment:


```command
sudo apt-get install build-essential libssl-dev libffi-dev python-dev
```


Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.


##Step 2 —  Setting Up a Virtual Environment


Virtual environments enable you to have an isolated space on your computer for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.


Setting up a programming environment provides us with greater control over our Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages. 


You can set up as many Python programming environments as you want. Each environment is basically a directory or folder in your computer that has a few scripts in it to make it act as an environment. 


We need to first install the **venv** module, part of the standard Python 3 library, so that we can create virtual environments. Let’s install venv by typing: 


```command
sudo apt-get install -y python3-venv
```


With this installed, we are ready to create environments. Let’s choose which directory we would like to put our Python programming environments in, or we can create a new directory with `mkdir`, as in:


```command
mkdir <^>environments<^>
cd <^>environments<^>
```


Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:


```command
python3 -m venv <^>my_env<^>
```


Essentially, this sets up a new directory that contains a few items which we can view with the `ls` command:


```command
ls my_env
```


```
[secondary_label Output]
bin include lib lib64 pyvenv.cfg share
```


Together, these files work to make sure that your projects are isolated from the broader context of your local machine, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs. Python Wheels, a built-package format for Python that can speed up your software production by reducing the number of times you need to compile, will be in the Ubuntu 16.04 `share` directory.


To use this environment, you need to activate it, which you can do by typing the following command that calls the activate script:


```command
source <^>my_env<^>/bin/activate
```


Your prompt will now be prefixed with the name of your environment, in this case it is called <^>my_env<^>. Your prefix may look somewhat different, but the name of your environment in parentheses should be the first thing you see on your line:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
  
```


This prefix lets us know that the environment <^>my_env<^> is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages. 


<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3`, and `pip` instead of `pip3` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3` and `pip3` commands exclusively. 
<$>


After following these steps, your virtual environment is ready to use.


##Step 3 — Creating a Simple Program


Now that we have our virtual environment set up, let’s create a simple “Hello, World!” program. This will make sure that our environment is working and gives us the opportunity to become more familiar with Python if we aren’t already. 


To do this, we’ll open up a command-line text editor such as nano and create a new file:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
nano hello.py
```


Once the text file opens up in the terminal window we’ll type out our program:


```python
print("Hello, World!")
```


Exit nano by typing the `control` and `x` keys, and when prompted to save the file press `y`. 


Once you exit out of nano and return to your shell, let’s run the program:


```custom_prefix((my_env)\ssammy@sammy:~/environments$)
python hello.py
```


The hello.py program that you just created should cause your terminal to produce the following output:


```
[secondary_label Output]
Hello, World!
```


To leave the environment, simply type the command `deactivate` and you will return to your original directory. 


##Conclusion


Congratulations! At this point you have a Python 3 programming environment set up on your local Ubuntu machine and can begin a coding project!


To set up Python 3 on another computer, follow the [local programming environment guides](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3) for [Debian 8](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-local-programming-environment-on-debian-8), [CentOS 7](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-centos-7), [Windows 10](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-windows-10), or [macOS](https://www.digitalocean.com/community/tutorials/how-to-set-up-a-local-programming-environment-for-python-3-on-mac-os-x). You can also read about [installing Python and setting up a programming environment on an Ubuntu 16.04 server](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-16-04-server), which is especially useful when working on development teams.


With your local machine ready for software development, you can continue to learn more about coding in Python by following “[Understanding Data Types in Python 3](https://www.digitalocean.com/community/tutorials/understanding-data-types-in-python-3)” and “[How To Use Variables in Python 3](https://www.digitalocean.com/community/tutorials/how-to-use-variables-in-python-3)”.






This tutorial will get you up and running with a local Python 3 programming environment in Ubuntu 16.04. It will guide you through installing Python 3 on your local Linux machine and setting up a programming environment via the command line. Though it will explicitly cover the installation procedures for Ubuntu 16.04, the general principles apply to any other Debian-based distributions.


How To Install Python 3 and Set Up a Local Programming Environment on Ubuntu 16.04

22.04

### Introduction

The Python programming language is an increasingly popular choice for both beginners and experienced developers. Flexible and versatile, Python has strengths in scripting, automation, data analysis, machine learning, and back-end development. First published in 1991 with a name inspired by the British comedy group Monty Python, the development team wanted to make Python a language that was fun to use.

This tutorial will get your Ubuntu 22.04 server set up with a Python 3 programming environment. Programming on a server has many advantages and supports collaboration across development projects. The general principles of this tutorial will apply to any distribution of Debian Linux.

## Prerequisites

In order to complete this tutorial, you should have a non-root user with `sudo` privileges on an Ubuntu 22.04 server. To learn how to achieve this setup, follow our [initial server setup guide](https://www.digitalocean.com/community/tutorials/initial-server-setup-with-ubuntu-22-04).

If you’re not already familiar with a terminal environment, you may find the article [An Introduction to the Linux Terminal](https://www.digitalocean.com/community/tutorials/an-introduction-to-the-linux-terminal) useful for becoming better oriented with the terminal.

If you would prefer to follow this tutorial using a terminal in your browser, click the **Launch an Interactive Terminal!** button to get started. You'll be able to experiment with and run all the commands directly in your browser.

[terminal ubuntu:jammy]


## Step 1 — Setting Up Python 3

Ubuntu 22.04 and other versions of Debian Linux ship with Python 3 pre-installed. To make sure that our versions are up-to-date, update your local package index:

```command
sudo apt update
```

Then upgrade the packages installed on your system to ensure you have the latest versions:

```command
sudo apt -y upgrade
```

The `-y` flag will confirm that we are agreeing for all items to be installed, but depending on your version of Linux, you may need to confirm additional prompts as your system updates and upgrades.


Once the process is complete, we can check the version of Python 3 that is installed in the system by typing:

```command
python3 -V
```

You’ll receive output in the terminal window that will let you know the version number. While this number may vary, the output will be similar to this:

```
[secondary_label Output]
Python <^>3.10.2+<^>
```

To manage software packages for Python, let’s install **pip**, a tool that will install and manage programming packages we may want to use in our development projects. You can learn more about modules or packages that you can install with pip by reading [How To Import Modules in Python 3](https://www.digitalocean.com/community/tutorials/how-to-import-modules-in-python-3).

```command
sudo apt install -y python3-pip
```

Python packages can be installed by typing:

```command
pip3 install <^>package_name<^>
```

Here, `<^>package_name<^>` can refer to any Python package or library, such as Django for web development or NumPy for scientific computing. So if you would like to install NumPy, you can do so with the command `pip3 install numpy`.

There are a few more packages and development tools to install to ensure that we have a robust setup for our programming environment:

```command
sudo apt install -y build-essential libssl-dev libffi-dev python3-dev
```

Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.

## Step 2 —  Setting Up a Virtual Environment

Virtual environments enable you to have an isolated space on your server for Python projects, ensuring that each of your projects can have its own set of dependencies that won’t disrupt any of your other projects.

Setting up a programming environment provides greater control over Python projects and over how different versions of packages are handled. This is especially important when working with third-party packages.

You can set up as many Python programming environments as you would like. Each environment is basically a directory or folder on your server that has a few scripts in it to make it act as an environment.

While there are a few ways to achieve a programming environment in Python, we’ll be using the **venv** module here, which is part of the standard Python 3 library. Let’s install venv by typing:

```command
sudo apt install -y python3-venv
```

With this installed, we are ready to create environments. Let’s either choose which directory we would like to put our Python programming environments in, or create a new directory with `mkdir`, as in:

```command
mkdir <^>environments<^>
```

Then navigate to the directory where you'll store your programming environments:

```command
cd <^>environments<^>
```

Once you are in the directory where you would like the environments to live, you can create an environment by running the following command:

```command
python3 -m venv <^>my_env<^>
```

Essentially, `pyvenv` sets up a new directory that contains a few items which we can view with the `ls` command:

```command
ls my_env
```

```
[secondary_label Output]
bin include lib lib64 pyvenv.cfg share
```

Together, these files work to make sure that your projects are isolated from the broader context of your server, so that system files and project files don’t mix. This is good practice for version control and to ensure that each of your projects has access to the particular packages that it needs. Python Wheels, a built-package format for Python that can speed up your software production by reducing the number of times you need to compile, will be in the Ubuntu 22.04 `share` directory.

To use this environment, you need to activate it, which you can achieve by typing the following command that calls the **activate** script:

```command
source <^>my_env<^>/bin/activate
```

Your command prompt will now be prefixed with the name of your environment, in this case it is called `<^>my_env<^>`. Depending on what version of Debian Linux you are running, your prefix may appear somewhat differently, but the name of your environment in parentheses should be the first thing you see on your line:

```custom_prefix((my_env)\ssammy@ubuntu:~/environments$)
 
```

This prefix lets us know that the environment `<^>my_env<^>` is currently active, meaning that when we create programs here they will use only this particular environment’s settings and packages.

<$>[note]
**Note:** Within the virtual environment, you can use the command `python` instead of `python3`, and `pip` instead of `pip3` if you would prefer. If you use Python 3 on your machine outside of an environment, you will need to use the `python3` and `pip3` commands exclusively.
<$>

After following these steps, your virtual environment is ready to use.

## Step 3 — Creating a “Hello, World” Program

Now that we have our virtual environment set up, let’s create a traditional “Hello, World!” program. This will let us test our environment and provides us with the opportunity to become more familiar with Python if we aren’t already.

To do this, we’ll open up a command line text editor such as `nano` and create a new file:

```custom_prefix((my_env)\ssammy@ubuntu:~/environments$)
nano hello.py
```

Once the text file opens up in the terminal window we’ll type out our program:

```python
[label hello.py]
print("Hello, World!")
```

Save the file and exit `nano` by pressing `CTRL + X`, `Y`, and then `ENTER`.

Once you exit out of the editor and return to your shell, you can run the program:

```custom_prefix((my_env)\ssammy@ubuntu:~/environments$)
python hello.py
```

The `hello.py` program that you created should cause your terminal to produce the following output:

```
[secondary_label Output]
Hello, World!
```

To leave the environment, type the command `deactivate` and you will return to your original directory.

## Conclusion

Congratulations! At this point you have a Python 3 programming environment set up on your Ubuntu Linux server and you can now begin a coding project!

If you are using a local machine rather than a server, refer to the tutorial that is relevant to your operating system in our [How To Install and Set Up a Local Programming Environment for Python 3](https://www.digitalocean.com/community/tutorial_series/how-to-install-and-set-up-a-local-programming-environment-for-python-3) series.

With your server ready for software development, you can continue to learn more about coding in Python by reading our free [*How To Code in Python 3* eBook](https://do.co/python-book), or consulting our [Python tutorials](https://www.digitalocean.com/community/tags/python/tutorials).

This tutorial will get your Ubuntu 22.04 server set up with a Python 3 programming environment. Programming on a server has many advantages and supports collaboration across development projects. The general principles of this tutorial will apply to any distribution of Debian Linux.

How To Install Python 3 and Set Up a Programming Environment on Ubuntu 22.04

This tutorial series will guide you through installing Python 3 on your local machine and setting up a programming environment via the command line.

Python is a versatile programming language that can be used for many different projects. 

How To Install and Set Up a Local Programming Environment for Python 3

How To Install Python 3 and Set Up a Local Programming Environment on macOS

How To Install Python 3 and Set Up a Local Programming Environment on Windows 10

Associate Developer Educator

Senior DevOps Technical Writer

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