In this article we are going to discuss about best Python Machine Learning IDEs and will find out which one suits you according to your needs. Also we will be deciding what should be the system requirements and hardware configuration of our machine to run these IDEs smoothly without any lag. So without wasting a moment let us get straight to the point.

在本文中，我们将讨论最佳的Python机器学习IDE，并根据您的需求找出最适合的一种。 此外，我们将决定机器的系统要求和硬件配置应该是什么，以便顺利运行这些IDE而不会出现任何延迟。 因此，不要浪费时间，让我们直接说清楚。

IDE (Integrated Development Environment)

IDE(集成开发环境)

As it is very much clear from the name itself what an IDE is and for most of the people here who are into programming this is not a new term. So here we are talking about different IDEs that are available for us as a data-engineer/enthusiast and to decide which one will be an ideal choice according to our needs.

从名称本身就可以很清楚地知道IDE是什么，对于这里的大多数编程人员来说，这并不是一个新名词。 因此，在这里，我们讨论作为数据工程师/爱好者提供给我们的各种IDE，并根据我们的需求决定哪种IDE是理想的选择。

So, here we are going to mention five IDEs that are being helpful for the data scientists and engineers and are productive too. Based on their respective features you will be very easily to choose an IDE of your choice. Come let’s explore.

因此，在这里我们将提到五个IDE，它们对数据科学家和工程师都非常有帮助，并且也很有生产力。 根据它们各自的功能，您将很容易选择所需的IDE。 快来探索吧。

5个最佳Python机器学习IDE (5 Best Python Machine Learning IDEs)

1. Spyder (1. Spyder)

Coming to our very first focus i.e. Spyder. This IDE got this short name from it’s name itself: “Scientific Python Development Environment”. Pierre Raybaut is the author of Spyder and it got officially released on October 18, 2009 and is written solely in Python.

来到我们的第一个焦点，即Spyder。 该IDE的名称本身就是“科学Python开发环境”。 Pierre Raybaut是Spyder的作者，它于2009年10月18日正式发布，仅使用Python编写。

Features at a glance:

功能一览：

• Very simple and light-weight IDE with detailed documentation and quite easy to install.
  非常简单，轻巧的IDE，带有详细的文档，并且易于安装。
• This is an open source editor and supports code completion, introspection, goto definition as well as horizontal and vertical splitting.
  这是一个开源编辑器，支持代码完成，自省，goto定义以及水平和垂直拆分。

• This editor comes with a Documentation Viewer where you can see the documentation related to classes or functions you gotta use.

  该编辑器随附有一个文档查看器 ，您可以在其中查看与要使用的类或函数相关的文档。

• Like most of the IDEs, this also supports Variable Explorer which is a helpful tool to explore and edit the variables that we have created during file execution.

  与大多数IDE一样，它也支持Variable Explorer ，它是一个有用的工具，可用于浏览和编辑在文件执行过程中创建的变量。

• It supports runtime debugging i.e. the errors will be seen on the screen as soon as you type them.
  它支持运行时调试，即键入错误后，错误就会立即显示在屏幕上。

This IDE integrates with some of the crucial like NumPy, Matplotlib, SciPy etc.

该IDE与一些关键集成在一起，例如NumPy，Matplotlib，SciPy等。

Spyder is considered best in the cases where it is been used as an interactive console for testing and development of scientific applications and scripts which make use of libraries such as SciPy, NumPy and Matplotlib.

在将Spyder用作测试和开发使用诸如SciPy，NumPy和Matplotlib之类的库的科学应用程序和脚本的交互式控制台的情况下，Spyder被认为是最好的。

Tip: Want to download? No need to bother we’ve got you covered. to download your version of Spyder.

提示 ：要下载吗？ 无需打扰，我们已为您覆盖。 下载您的Spyder版本。

2. Geany (2. Geany)

Geany is primarily a Python machine learning IDE authored by Enrico Troger and got officially released on October 19, 2005. It has been written in C & C++ and is a light-weight IDE. Despite of being a small IDE it is as capable as any other IDE present out there.

Geany主要是由Enrico Troger编写的Python机器学习IDE，并于2005年10月19日正式发布。它是用C＆C ++编写的，是一种轻量级的IDE。 尽管它是一个小型IDE，但它与现有的其他IDE一样强大。

Features at a glance

功能一览

• Geany’s editor supports highlighting of the Syntax and line numebering.
  Geany的编辑器支持突出显示语法和行号。
• It comes equipped with the features like code completion, auto closing of braces, auto HTML and XML tags closing.
  它具有代码完成，括号自动关闭，HTML和XML标签自动关闭等功能。
• It also comes with code folding.
  它还带有代码折叠功能。
• This IDE supports code navigation.
  此IDE支持代码导航。

Tip: Download your instance of Geany

提示： 下载您的Geany实例

3.牛仔竞技表演 (3. Rodeo)

This is special we got here. This is a Python IDE that primarily focuses and built for the purpose of machine learning and data science. This particular IDE use IPython kernel (you will know this later) and was authored by Yhat.

这是我们来到这里的特别之处。 这是一个Python IDE，主要针对机器学习和数据科学进行开发。 这个特定的IDE使用IPython内核(稍后会知道)，由Yhat编写。

Features at a glance

功能一览

• It is mainly famous due to its ability to let users explore, compare and interact with the data frames & plots.
  它之所以出名，主要是因为它能够让用户探索，比较数据框和图并与之交互。
• Like Geany’s editor this also comes with a editor that has capability of auto-completion, syntax highlighting.
  像Geany的编辑器一样，该编辑器还具有自动完成功能，语法突出显示功能。
• This also provides a support for IPython making the code writing fast.
  这也提供了对IPython的支持，使代码编写更快。
• Also Rodeo comes with Python tutorials integrated within which makes it quite favourable for the users.
  Rodeo还集成了Python教程，这对用户非常有利。

This IDE is well known for the fact that for the data scientists and engineers who work on RStudio IDE can very easily adapt to it.

该IDE众所周知，因为使用RStudio IDE的数据科学家和工程师可以很容易地适应它。

Perfection doesn’t exist and so is the case for Rodeo, it doesn’t consist of code analysis, PEP 8, etc.

完美不存在，而Rodeo就是如此，它不包括代码分析，PEP 8等。

Tip: Download your Rodeo workspace .

提示： 下载Rodeo工作区。

4. PyCharm (4. PyCharm)

PyCharm is the IDE which is most famous in the professional world whether it is for data science or for conventional Python programming. This IDE is built by one of the big company out there that we all might have heard about: Jetbrains, company released the official version of PyCharm in October 2010.

PyCharm是IDE，无论是数据科学还是常规Python编程，在专业领域中都是最著名的。 这个IDE是由我们可能都听说过的大公司之一构建的：Jetbrains ，该公司于2010年10月发布了正式版的PyCharm。

PyCharm comes in two different editions: Community Edition which we all can have access to essentially for free and second one is the Professional Edition for which you will need to pay some bucks.

PyCharm有两种不同的版本：社区版，我们所有人都可以免费使用，而第二版是专业版，您需要为此支付一些费用。

Features at a glance

功能一览

• It includes code completion, auto-indentation and code formatting.
  它包括代码完成，自动缩进和代码格式化。
• This also comes with runtime debugger i.e. will display the errors as soon as you type them.
  这也随运行时调试器一起提供，即在键入错误后立即显示错误。
• It contains PEP-8 that enables writing neat codes.
  它包含允许编写整洁代码的PEP-8。
• It consist of debugger for Javascript and Python with a GUI.
  它由Java调试器和带有GUI的Python组成。
• It has one of the most advanced documentation viewer along with video tutorials.
  它具有最高级的文档查看器之一以及视频教程。

PyCharm being accepted widely among big companies for the purpose of Machine Learning is due to its ability to provide support for important libraries like Matplotlib, NumPy and Pandas.

PyCharm以机器学习为目的而在大公司中被广泛接受，这是因为它能够为Matplotlib，NumPy和Pandas等重要库提供支持。

Also PyCharm is capable of distinguishing between different environments (Python 2.7, Python 3.5) according to different project’s needs.

此外，PyCharm能够根据不同项目的需求区分不同的环境(Python 2.7，Python 3.5)。

Tip: Download your version of Pycharm .

提示： 下载您的Pycharm版本。

5. JuPyter笔记本或IPython笔记本 (5. JuPyter Notebook or IPython Notebook)

Due to its simplicity this one became a sensational IDE among the data enthusiasts as it is the descendant of IPython. Best thing about JuPyter is that there you can very easily switch between the different versions of python (or any other language) according to your preference.

由于它的简单性，它是IPython的后代，因此在数据爱好者中引起了轰动。 JuPyter的最好之处在于，您可以根据自己的喜好在python的不同版本(或任何其他语言)之间轻松切换。

Features at a glance

功能一览

• It’s an open source platform
  这是一个开源平台
• It can support up to 40 different languages to work on including languages beneficial for data sciences like R, Python, Julia, etc.
  它可以支持多达40种不同的语言进行工作，包括对数据科学有益的语言，例如R，Python，Julia等。
• It supports sharing live codes, and even documents with equations and visualizations.
  它支持共享实时代码，甚至支持带有公式和可视化效果的文档。
• In JuPyter you can produce outputs in the form of images, videos and even LaTex with the help of several useful widgets.
  在JuPyter中，您可以借助一些有用的小部件以图像，视频甚至LaTex的形式生成输出。
• You can even avail the advantage of Big Data tools due to the fact that JuPyter has got Big Data integration within to help the data scientists.
  您甚至可以利用大数据工具的优势，因为JuPyter已集成了大数据来帮助数据科学家。

Tip: Download the JuPyter IDE .

提示：在下载JuPyter IDE。

Conclusion

结论

Since we have gone through all the IDEs that are famous in the field of , now you must be able to make your choices based on the points we’ve discussed above.

由于我们已经遍历了领域中所有著名的IDE，因此您现在必须能够根据以上讨论的观点做出选择。

Pro Tip: We would recommend our readers to use JuPyter Notebook if you are giving a start to ML. It has got that simplicity and features that most of the IDEs have combined. Apart from the features discussed above it also supports for data cleaning, transformation, etc. to help its users. Talking in terms of ML JuPyter has a good support for the libraries like Pandas, NumPy and Matplotlib. You can get complete guide on how to install and configure JuPyter .

专家提示：如果您开始学习ML，我们建议读者使用JuPyter Notebook。 它具有大多数IDE结合的简单性和功能。 除上述功能外，它还支持数据清理，转换等，以帮助用户。 就ML JuPyter而言，它对Pandas，NumPy和Matplotlib等库提供了良好的支持。 您可以在获得有关如何安装和配置JuPyter的完整指南。

Comment down below if you know about any other good machine learning ide for python.

如果您了解python的其他优秀机器学习理念，请在下面注释掉。

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