This is a great way to get things configured out of the box. On installation, Komodo informs you about the programming languages, package managers, and other development tools it discovers on your system. Python is one of many languages supported in Komodo, and one of many languages for which ActiveState provides custom runtime builds. OpenKomodo works as both a standalone multi-language IDE and as a point of integration with ActiveState’s language platform. Unfortunately, that means many aspects of OpenKomodo now feel dated. ActiveState ceased development on Komodo and now maintains it as an open source project. OpenKomodoIDE is the open source version of what was ActiveState's commercial Komodo IDE product. ![]() IDLE is free with Python, but its minimal feature set make it best suited for beginners. Even beginners will need to graduate to a more robust option before long. The second is for beginners who are just getting started with Python. In sum, IDLE is best for two scenarios: The first is when you want to hack together a quick Python script, and you need a preconfigured environment to work in. Using any other tooling, like test suites, can only be done manually. The only discernible way to do this is to create a venv and invoke IDLE from its parent installation of Python. IDLE also has no concept of a project, and thus no provisions for working with a Python virtual environment. And the collection of third-party add-ons available for IDLE (such as IdleX) is nowhere near as rich as you’ll find with other IDEs. But the implementations for most of these features are primitive compared to other IDEs, and hidebound by Tkinter’s limited selection of UI components. IDLE also includes a few tools found in other IDEs, such as providing suggestions for keywords or variables when you hit Ctrl-Space, and an integrated debugger. In fact, this interactive shell is the first item presented to the user when IDLE is launched, rather than an empty editor. It sports a built-in read-eval-print loop (REPL), or interactive console, for Python. Bear this in mind if you experience performance issues with a Python program in IDLE. Printing large amounts of text from a script into the console, for instance, is many orders of magnitude slower than running the script directly from the command line. As a downside, the interface can be terribly slow. One advantage of building IDLE this way is that it runs cross-platform with a consistent set of behaviors. Aside from the CPython interpreter itself, this includes the Tkinter interface toolkit. IDLE is built entirely with components that ship with a default installation of Python. (See this case study in application modernization for an interesting discussion of the efforts to improve IDLE.) Still, IDLE remains one of the default options for Python developers to get a leg up with the language, and it has improved incrementally with each Python release. ![]() However, IDLE is by no means a substitute for full-blown development it’s more like a fancy file editor. IDLE, the integrated development and learning environment included with almost every installation of Python, could be considered the default Python IDE. Let's take a look at the leading IDEs for Python development today. Because of that, your choice of IDE may be determined by whether or not you have experience with another IDE from the same family. Many strive for universal appeal.Ī good number of IDEs now are frameworks outfitted with plugins for specific languages and tasks, rather than applications written to support development in a given language. Each one has particular strengths and will likely be useful for a specific type of Python development or level of experience with Python. ![]() Some are built exclusively for Python, while others are multilanguage IDEs that support Python through an add-on or have been retrofitted with Python-specific extensions. These seven IDEs with Python support cover the gamut of use cases. Python’s rise in popularity has brought with it a strong wave of IDE support, with tools aimed at both the general programmer and those who use Python for tasks like scientific work and analytical programming. Of all the metrics you could use to gauge the popularity and success of a language, one surefire indicator is the number of development environments available for it.
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