How to Use Python Modules in Robotics


Robotics is one of the most rapidly growing fields in manufacturing, with new applications and technologies being developed every day. As a result, there is a growing demand for engineers and technicians with the skills to develop and operate robots.

One of the most popular programming languages for robotics is Python. Python is a versatile language that is easy to learn and can be used for a wide range of applications. In this mini-guide, we will introduce you to some of the most popular Python modules for robotics.

These modules will allow you to control and operate robots from your Python code. Keep reading to learn more!

What Are Modules in Python?

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Modules are a way to structure your Python code. They are self-contained pieces of code that can be used in other Python programs. Modules can define functions, classes, and variables, and they can also be used to store data.

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Modules are a handy way to keep your code organized. They also make it easy to reuse code in other programs. If you have a piece of code that you want to use in multiple programs, you can put it in a module and then import that module into the programs that need it.

If you’re just getting started with Python, you don’t need to worry about modules. But as you become more experienced with the language, you’ll find that modules can be a useful tool.

This page is a part of the larger guide on How to use Python for Robotics as a Beginner!

Why Are Python Modules Important in Robotics?

Due to its flexibility and ease of use, Python has become the standard language for many robotic applications. Modules are an important part of Python, as they allow developers to create code that can be reused in other projects. This is especially important in robotics, where developers often need to create code that can be used across a variety of platforms.

Python modules are typically stored in a central repository, such as the Python Package Index (PyPI). This allows developers to easily share their code with others and makes it easy to install new modules. PyPI is the standard repository for Python modules, but there are also many other repositories that host modules for specific applications.

Developers can also create their own modules, which can be stored in a private repository or even embedded in a robotic application. This allows for a high degree of flexibility when it comes to creating robotic applications.

Types of Python Modules in Robotics

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There are many types of Python modules that can be used in robotics. Some of the most popular include the following:

  • RoboticsPy: This module is designed to simplify the process of controlling robot motors and sensors.
  • Rospy: This module provides access to the ROS (Robot Operating System) framework.
  • Pycreate2: This module allows you to interface with the Create 2 robot from iRobot.
  • Pysabertooth: This module lets you connect to the Dimension Engineering SaberTooth motor controller.

Each of these modules has its own unique set of features and capabilities. Be sure to research each one thoroughly before deciding which is right for your robot project.

Repositories for Python Modules

There are a number of repositories that house Python modules. The most popular repository is the Python Package Index (PyPI), which is home to over 200,000 modules. However, there are a number of other repositories that are worth checking out, such as Anaconda Cloud, which has over 1,500 modules, or the Python Module Index, which has over 5,000 modules.

When choosing a repository, it’s important to consider the size and scope of the repository, as well as the quality of the modules it contains. For example, PyPI is the largest repository, but it doesn’t contain as many high-quality modules as some of the smaller repositories. On the other hand, the smaller repositories may not have the same breadth of modules as the larger ones.

No matter which repository you choose, always make sure to check the module’s documentation and reviews before downloading and installing it. This will help you ensure that the module is well-supported and of high quality.

Creating a Custom Python Module

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Python modules are files that contain a set of variables, functions, and classes that can be used by other Python programs. Modules are typically named after the thing they define, such as the math module or the turtle module.

Creating a custom module is a great way to organize your code and make it reusable. In this article, we’ll show you how to create a custom Python module and use it in your programs.

Creating a Module

To create a custom Python module, you first need to create a file with a.py extension. This file will contain all the code for your module. For example, let’s say you want to create a module that contains a function for generating prime numbers. The code for this module would go in a file called prime.py.

Next, you need to import your module into your Python program. To do this, you use the import keyword. For example, if your module is called prime, you would import it like this:

import prime

You can now access the functions in your module by qualifying them with the name of the module. For example, to call the generate_prime() function from our prime module, we would do this:

prime.generate_prime(10)

Creating a Python Package

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A package is a collection of Python modules. Packages are a great way to organize your code and make it more reusable.

To create a package, you first need to create a directory with a name that corresponds to your package. Inside this directory, you need to create an _init__.py file. This file can be empty, but it needs to be there in order for Python to treat the directory as a package.

For example, let’s say we want to create a package called mypackage. We would first create a directory called “my package”

__init__.py

Once we have our directory set up, we can add modules to it. For example,

mypackage/

__init__.py

module1.py

module2.py

With this structure, we can access our modules like this:

import mypackage.module1

mypackage.module1.some_function()

Importing a Module from a Package

In your import statement, you put the name of the package and the name of the module, separated by a dot, like this:

import mypackage.module1

Installing and Using Packages

When working with packages, you need to find or create them on your system first before using them in your scripts. In Python 2.x versions, there are two main ways to install third-party packages: distribute (also known as Distribute/Setuptools), and pip (which is built on top of distribute). The two systems are largely incompatible—they use different formats for their configuration files And they’re made by different people who don’t see eye-to-eye”</p>Distribute is bundled with Python 2.6; pip comes standard in Python 3.3+. If you’re using an earlier version of Python, then the only option you have is to use Distribute.

The use of “distribute” and “distribute” is sometimes confusing for newcomers. When people say “Distutils”, they usually mean the combined Distribute and Setuptools project. When they speak about using Distutils to create a package, this actually involves many other tools like 2to3 or pyinstaller from Distribute that are required to convert Python 2 code to Python 3 (or bundle your Python code into an executable). The term “distutils” by itself only refers to the core features of Distribute that make it easy to share your code in a simple format. It does not include any other features.

Using a Python Module in a Robotics Project

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As part of the Robotics team at XYZ Corporation, you are working on a project to create a robot that can autonomously navigate a room and avoid obstacles. After doing some research, you have decided to use the Python programming language for this project.

One of the great things about Python is that there are a lot of different modules you can use to add functionality to your project. For this project, you will need to use a module that allows you to control the robot’s motors. There are a few different options available, but you have decided to use the “RobotPy” module. The first thing you need to do is install the RobotPy module. You can do this using the “pip” utility. To install the RobotPy module, type the following command into a terminal window:

install robotpy with pip

Next, you need to import the module into your Python script. To do this, add the following line of code to the top of your script:

import robotpy

Then, you can use the methods and attributes in the RobotPy module to control the robot’s motors. For example, to set the speed of the left motor, you would use the following code:

left_motor.setSpeed(100)

Finally, you need to tell the robot to start moving. To do this, you need to call the “run” method:

robot.run()

Conclusion

In conclusion, Python is a powerful programming language that is well-suited for use in robotics. Python modules can provide functionality for a wide range of applications, from basic motion control to more advanced artificial intelligence. If you’re interested in learning more about Python and robotics, be sure to check out the next section on Python Files here: Reading and Writing Python Files for Robotics



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