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Integrated Development Environments (IDEs) are an important part of any developer’s toolkit. It provides the tools and facilities that a developer needs to build software. All development can be carried out in an IDE, making it a convenient application. As a result, that means you won’t have to constantly change between various software and put them together at the end. This makes it much quicker to produce software.
IDEs are made up of three main components:
- Debugger: This is a program that displays exactly where a bug is in the code. Having a debugger is very necessary, as finding bugs without one would be difficult and time-consuming.
- Automation tool: Specific tasks are done automatically by IDEs, such as packaging binary texts and running automated tests.
- Source code editor: A text editor that allows you to write code while giving advice on improvements. It can highlight specific bugs or mistakes in syntax, as well as provide auto-completion for certain languages.
Choosing the Right IDE:
IDEs have features for specific programming languages that aren’t available in other languages. Some IDEs are more suited and specialised for programming in Python. If you’re building your web application with Django, then any IDE that works well with Python will also work well with Django. Choosing the right IDE can make a big difference.
Certain features that you’ll want to look out for include code-folding and bracket highlighting. Integration with online repositories is another feature that you might want to look out for. Additionally, having a class hierarchy diagram for usage in object-oriented programming can be extremely useful. This is because Python is an object-oriented programming language, giving the ability to create classes and objects. Moreover, some IDEs have used advancements in AI to improve certain features.
We will look at 7 of the best IDEs that are currently available, and suited for programming in Python.
1: Jupyter
Jupyter is one of the most popular IDEs for Python for usage in data science in particular. Libraries such as Matplotlib, which is used for data visualisation, are easy to access in Jupyter. If you’re integrating machine learning into your Python application, then Jupyter is a suitable choice. Text, code and images are all combined in Jupyter. The main feature that makes Jupyter a great choice for data analysis is that you can run each line of code at a time in the same file. Other IDEs can only run all the lines of code, rather than just one.
2: Visual Studio Code
Visual Studio Code is one of the most popular IDEs available, even in other programming languages. It’s also well suited to Python due to its flexibility and a wide variety of features. Visual Studio Code contains features that other IDEs only provide in their paid version. Each line of code has its own debugger, making it easier to detect bugs. Furthermore, the extensions marketplace provides extensions for various programming languages, including Python. Visual Studio Code is a reliable and versatile choice.
3: Spyder
Spyder is a commonly used IDE that is geared toward Python specifically. It comes with Anaconda distribution, which has made it a common choice for data science and machine learning projects in Python. Similar to Jupyter, libraries such as pandas and Matplotlib are integrated into Spyder. This makes Spyder another great choice for data science and machine learning projects, as it supports data manipulation and chart plotting.
4: PyCharm
PyCharm is another IDE that is very popular for programming in Python specifically. If you’re building Python projects on a large scale, PyCharm is well suited to this task. It provides automatic code completion and highlights any errors that come up, allowing you to complete projects efficiently. In addition, it allows you to access databases directly from the IDE. Specifically, PyCharm provides various features that make it a great choice for scientific development as well.
5: PyDev
PyDev is a third-party distributed plugin for the IDE eclipse, and contains a number of plugins that provide additional features. PyDev is highly suited to web development, which means it can be a suitable choice if you’re building a web application with Django. There is an option to integrate Django into your project, making it a particularly convenient choice for Python web application projects.
Additional features include auto code completion and code coverage, along with coding templates. It also provides a browser to test code, allowing you to see how well your project is coming along.
6: IDLE
Integrated Development and Learning Environment (IDLE) is a minimal IDE for Python. However, it still comes with a range of features that make it a good choice. The powerful debugger is especially useful for over-stepping through each high-level function, as well as showing the state of local and variable functions. It also provides an interactive interpreter that highlights syntax and any error messages. Although, IDLE doesn’t have project management files, meaning it’s more suited for projects with fewer files.
7: Atom
Atom is one of the most feature-rich IDEs currently available, due to the fact that it’s created by Github. Atom has its own package manager, that is continued to be supported by its large community. A unique feature of Atom is that it allows for real-time collaboration using the Teletype package.
It has an advanced autocompletion feature, as well as support for cross-platform development. The huge number of plugins and the dedicated pluggable Python compiler makes Atom a reliable choice for Python development.
Conclusion:
Having the right IDE can save you a lot of time down the line by being able to code efficiently. It’s important to choose an IDE depending on your business goals and the specific project that you’re currently working on. For example, if you’re working on a data science and machine learning project, then Jupyter and Spyder are highly suitable choices. If you’re working on a large Python project. Then PyCharm would be a good choice.
There are various other IDEs that are also available, but this list should give you a good indication of some of the most reliable and popular choices for Python programming.
Stuck on your Python or Django project? Reach out to the Raw Jam team for advice!
Written and researched by Saleem Maroof.