Anaconda vs. EPD Enthought vs. Python 的手动安装
问题描述
各种 Python 包(EPD/Anaconda)与手动安装相比有哪些优缺点?
What are the relative merits / downsides of various Python bundles (EPD / Anaconda) vs. a manual install?
我已经安装了 EPD Academic，我对此没有任何问题.它提供了更多我认为我将需要的软件包，并且使用 enpkg enstaller 很容易更新.EPD 学术许可证需要每年更新一次，但免费版本的更新并不容易.
I have installed EPD academic, and I have no issues with it. It provides more packages that I think I will ever need, and it is very easy to update using enpkg enstaller. The EPD academic licence requires yearly renewal however and the free version does not do updates as easily.
目前我真的只使用少数几个包，例如 Pandas、NumPy, SciPy, matplotlib, IPython,Statsmodels 及其各自的依赖项.
At the moment I really only use a handful of packages such as Pandas, NumPy, SciPy, matplotlib, IPython, Statsmodels and their respective dependencies.
对于这种有限的使用，我最好手动安装和 pip install --upgrade 'package' 还是捆绑包提供除此之外的任何东西?
For such limited use am I better off with manual install and pip install --upgrade 'package' or do the bundles offer anything over and above this?
解决方案
2015 年更新:现在我总是推荐 Anaconda.它包含许多用于科学计算、数据科学、Web 开发等的 Python 包.它还提供了一个出色的环境工具 conda，它允许在环境之间轻松切换，甚至在 Python 2 和 Python 3 之间切换.包的新版本一发布它也会很快更新，你可以通过 conda update packagename 来更新它.
Update 2015: Nowadays I always recommend Anaconda. It includes lots of Python packages for scientific computing, data science, web development, etc. It also provides a superior environment tool, conda, which allows to easily switch between environments, even between Python 2 and 3. It is also updated very quickly as soon as a new version of a package is released, and you can just do conda update packagename to update it.
原答案如下:
在 Windows 上，编译数学包很复杂，所以我认为只有当您只对 Python 感兴趣而没有其他包时，手动安装才是一个可行的选择.
On Windows, what is complicated is to compile the math packages, so I think a manual install is a viable option only if you are interested only in Python, without other packages.
因此最好选择 EPD(现在的 Canopy)或 Anaconda.
Therefore better chose either EPD (now Canopy) or Anaconda.
Anaconda 有大约 270 个包，包括对大多数科学应用和数据分析最重要的包，即 NumPy, SciPy, 熊猫, IPython, matplotlib, Scikit-learn.所以如果这对你来说足够了，我会选择 Anaconda.
Anaconda has around 270 packages, including the most important for most scientific applications and data analysis, that is, NumPy, SciPy, Pandas, IPython, matplotlib, Scikit-learn. So if this is enough for you, I would choose Anaconda.
相反，如果您对其他软件包感兴趣，甚至如果您使用任何 Enthought 软件包(Chaco 例如对于实时数据可视化非常有用)，那么 EPD/Canopy 可能是更好的选择.学术版在基础安装中有更多的软件包，在存储库中还有更多.Anaconda 还包括 Chaco.
Instead, if you are interested in other packages, and even more if you use any of the Enthought packages (Chaco for example is very useful for realtime data visualization), then EPD/Canopy is probably a better choice. The Academic version has a larger number of packages in the base install, and many more in the repository. Anaconda also includes Chaco.
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