用于Python中的可再现环境的工具(或工具的组合)-Tool(orcombinationoftools)forreproducibleenvironmentsinPython

18  

1. virtualenv to create a contained virtual environment (prevent different versions of Python or Python packages from stomping on each other). There is increasing buzz from people moving to this tool. The author is the same as the older working-env.py mentioned by Aaron.

   virtualenv创建一个包含的虚拟环境(防止不同版本的Python或Python包互相踩踏)。越来越多的人使用这个工具。作者与较老的工作环境相同。py提到的亚伦。

2. pip to install packages inside a virtualenv. The traditional is easy_install as answered by S. Lott, but pip works better with virtualenv. easy_install still has features not found in pip though.

   pip在virtualenv中安装包。传统的方法是按照S. Lott的回答easy_install，但是pip在virtualenv中工作得更好。easy_install仍然具有pip中没有的特性。

3. scons as a build tool, although you won't need this if you stay purely Python.

   scons是一种构建工具，但是如果您只使用Python，就不需要它。

4. Fabric paste, or paver for deployment.

   织物浆糊，或摊铺机用于部署。

5. buildbot for continuous integration.

   buildbot持续集成。

6. Bazaar, mercurial, or git for version control.

   版本控制的Bazaar、mercurial或git。

7. Nose as an extension for unit testing.

   鼻子作为单元测试的扩展。

8. PyFit for FIT testing.

   PyFit FIT测试。

3  

I also work with both java and python. For python development the maven equivalent is setuptools (http://peak.telecommunity.com/DevCenter/setuptools). For web application development I use this in combination with paster (http://pythonpaste.org/) for the deployment process

我还使用java和python。对于python开发来说，与maven等价的是setuptools (http://peak.telecommunity.com/DevCenter/setuptools)。对于web应用程序开发，我将它与paster (http://pythonpaste.org/)结合用于部署过程

2  

Other than easy_install?

除了easy_install吗?

For our Linux servers, we use easy_install and yum.

对于Linux服务器，我们使用easy_install和yum。

For our Windows development laptops, we use easy_install and a few MSI's for some projects.

对于我们的Windows开发笔记本电脑，我们在一些项目中使用easy_install和一些MSI。

Most of the Python libraries we use are source-only, so we can use the same distribution on all boxes. If we could have a network shared device, we'd put them all there. Sadly, our infrastructure is kind of scattered, so we have to either move .TAR files around or redo the installs to rebuild the environments.

我们使用的大多数Python库都是源代码库，所以我们可以在所有的盒子上使用相同的发行版。如果我们有一个网络共享设备，我们会把它们都放在那里。遗憾的是，我们的基础设施有点分散，所以我们要么移动. tar文件，要么重新安装，以重新构建环境。

In a few cases (e.g., PIL), we have to recompile and check the version numbers.

在一些情况下(例如PIL)，我们必须重新编译并检查版本号。

2  

You will want easy_setup to get the eggs (roughly what Maven calls an artifact).

您将需要easy_setup来获取鸡蛋(大致就是Maven所称的工件)。

For setting up your environment, have a look at working-env.py

要设置环境，请查看working-env.py

Python is not compiled but you can put all files for a project in an egg. This is done with setuptools

Python不是编译的，但是您可以将项目的所有文件放在一个鸡蛋中。这是使用setuptools完成的

For CI, check this answer.

对于CI，检查这个答案。

2  

We would be remiss not to also mention Paver, which was created by Kevin Dangoor of TurboGears fame. The project is still in alpha, but it appears very promising. A snippet from the project page:

我们很遗憾，更不用说帕弗了，它是由涡轮齿轮公司的Kevin Dangoor创建的。这个项目仍在alpha阶段，但看起来很有希望。项目页面中的一个片段:

Paver is a Python-based build/distribution/deployment scripting tool along the lines of Make or Rake. What makes Paver unique is its integration with commonly used Python libraries. Common tasks that were easy before remain easy. More importantly, dealing with your applications specific needs and requirements is now much easier.

Paver是一个基于python的构建/分发/部署脚本工具，与Make或Rake类似。Paver的独特之处在于它与常用Python库的集成。以前容易做的普通任务仍然容易。更重要的是，现在处理应用程序特定的需求和需求要容易得多。

0  

I do exactly this with a combination of setuptools and Hudson. I know Hudson is a java app, but it can run Python stuff just fine.

我用setuptools和Hudson来做这个。我知道Hudson是一个java应用，但是它可以很好地运行Python。

0  

You might want to check our Devenv. It allows you to standardize the build environments for development, QA and UAT. It's free as in "free beer".

你可以查一下我们的Devenv。它允许您为开发、QA和UAT标准化构建环境。它是免费的，就像“免费啤酒”一样。

HTH

HTH