All good software developers must use the right tools. Devs typically write their code using an IDE. A developer will likely undertake several projects simultaneously, so it’s helpful to have an efficient way of organizing these projects. Currently, Python is widely used worldwide. Depending upon the purpose and system requirement, your project will have various tools available.
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Where is Python used?
Python is one of the most universal programming languages, and it can be used in data science, scientific computing, machine learning, web development, for creating complex codes to execute multiple operations on servers, or just for simple scripts.
What Python development tools do you recommend?
Python is an open-source programming language that runs on all major operating systems (Linux, Mac, Windows), and its easy syntax makes it a popular choice among beginners. Python programmers should use an integrated development environment (IDE) to speed up their workflow. We have reviewed the 10 most popular GUIs together with their pros and cons in this article:
Or if you want to start right away, just download PyScripter, our favorite integrated development environment and start coding.
What features should an IDE offer?
With so many options available, it might be confusing how to choose an IDE that fits all your needs. Must-have features of a good IDE include
- Syntax highlighting
- Code completion
- A project explorer
- A Python interpreter
- A debugger
Modern features include
- Integration with Python development tools such as PyLint, TabNanny and Profile
- Easy switch between different Python versions
- Unit testing
- Remote work
You can find all the above features in PyScripter.
Some GUIs are able to handle not just Python but also other powerful programming languages such as C or Java, for example, Visual Studio code. However, we recommend using a tool that is specific to the programming language you intend to use.
What Python packages should I install and how?
There are some universal Python packages that are used in many Python projects, while others are only written with a limited application in mind. Mathematical functions are found in the numpy library, data scientists often employ pandas as the frontend to read in data and analyse it. More specific math routines for data analysis are found in the package scipy. Popular machine learning packages are TensorFlow and PyTorch.
The traditional way to install packages is via a smart tool called pip which is invoked from the command line. However, advanced IDEs such as PyScripter offer a built-in call to pip, so that you never need to leave the IDE window when you are missing a package. You simply need to head over to Tools -> Tools -> Install Packages with pip.
A Miniconda or an Anaconda installation comes bundled with all kinds of packages. That makes it easier to just start writing code, but most likely all the Python packages that come along are something you will never need. You can decide for yourself whether you would like to install by hand or get all at once.
How to evaluate the performance of my code?
There are various ways to evaluate how efficient code is. The simplest way is to just print the time via the datetime package, however, this is a very outdated approach. Nowadays, there are specialized profiling tools that perform a deep analysis of the code. They report CPU and memory usage, and identify bottlenecks.
How to debug code?
Debugging is a critical part of coding. Everybody makes mistakes, but sometimes they are not so obvious. The script crashes and it leaves the programmer confused. Coding should not be like that. That is why there are useful debugging tools that you need to know if you want to learn Python coding properly.
The Python programming language is interpreted, which is in contrast to other traditional languages such as C and Fortran which need to be compiled. The compiler does some checks while building an executable, whereas, the Python interpreter tends to recognise only syntax errors. It cannot take any flags specifying the computer architecture or code optimisation level.
What are some useful Python projects that I can try?
If you have have familiarized yourself with the basics, you can try creating some simple and efficient tool for Python automation. You will be surprised at how useful these can be since Python is one of the most versatile multi-purpose programming languages. You can extract data, for example, by parsing html documents, or edit an Excel sheet without even opening it in MS Excel. Python code can send emails, for example.
If you want to jump straight into the deep, you can try performing machine learning algorithms. There are open-source data sets online that data science researchers have shared with the world for free. Just make a quick Google search and you will find many examples and tutorials. Maybe you will create a cool artificial intelligence tool using Python data science libraries?
Can I make a graphical interface in Python?
Absolutely. There are many useful Python tools for creating a graphical user interface (GUI). You can check out the list of Python packages that we have reviewed recently. Also, we have a practical example for building a Python GUI currency converter. You can start by watching the videos in the following article and write test scripts to see which tool offers what you need.
Frequently asked questions
Which tool is best for Python development?
If you want to be a better Python developer, you should learn how to code efficiently. There is no need to reinvent the wheel. Just download Python and an IDE such as PyScripter and start coding.
Is Python a software development tool?
Not quite. Python is a programming language. There are various software developer tools that may come with a code editor, a debugger and an interpreter.
What tools do I need to learn Python?
You should start by installing an integrated development environment. There are various options. Most IDEs offer the basic tools python developers need on a daily basis. Some come with advanced features. For more information,
Is Jupyter an IDE?
Jupyter is an alternative to traditional IDEs that runs in various and multiple browsers. It is a Python code editor and runs a Python kernel, so that you can execute your scripts, but there are no debugging tools. Also, you cannot build GUI programs via the browser notebook. However, it allows you to learn Python online.
Can Notepad++ run Python?
No. Notepad++ is a text editor. It supports code syntax highlighting, but it cannot run a Python program.
To conclude
Python is a language that suits not only software engineers but any enthusiast who wants to know more about programming. There are countless Python modules, so that you do not need to write everything from scratch. The nice thing about a Python script or program is that it can be run on multiple platforms. And remember that practice makes perfect. The most useful Python tools are those that make your coding life easier, so you should test out various options and see what feels best.
Start learning Python today in PyScripter. Click here to download it.
