Using easy_install" - which is a highly debatable (and frequently ![]() Was "having to use a separate installer is more complex than just ![]() My (unfounded) suspicion is that the argument Suggested this was inappropriately complex" you mention above were I'd be curious to know whether the "people who Setuptools, unfortunately, has divided the Python distributionĬommunity quite badly. ![]() "inappropriately complex" - but that is a setuptools problem, NOT anģ. Where setuptools is involved, things do start to become (yes, I know, they give you eggs, and easy_install, yadda yadda.) So This increases the burden onĭistributors, which as a result means that you are less likely to findīdist_wininst installers for setuptools-using pure python packages It changes the default bdist_wininst behaviour somehow, so that the Understand, but which annoy me intensely. Setuptools messes this clean picture up, for reasons I cannot Installers even when all it saves is a bit of my time.Ģ. Precisely because it's pure Python) but I feel that it's considerateĪnd helpful of distributors to offer bdist_wininst (or bdist_msi) Pure-python modules which do not come with an installer (easy enough, I can (and do) build my own installers for Procedure (and more importantly, uniform *un*install procedure) is a Packages is, in my view, *entirely* appropriate. Using distutils to build Windows installers for pure-python I've lost the context for this discussion completely, but can I offerĪ couple of points from a Windows user's point of view:ġ. > In so far as "end users" won't wish to install individual Python modules > this argument may have had some merit, but I personally thought the > criticism unjustified since Mike's technique gave a uniform install > procedure for everything. He then had to suffer criticism > from people who suggested this was inappropriately complex for pure > Python modules. Anaconda is a good choice for those focused on creating non-commercial data science applications since you can take advantage of Anaconda’s proven Python ecosystem for free.> As far as memory serves, Mike built the installers precisely by using > distutils to build Windows installers.Since ActiveState provides commercial support, ActivePython is the best choice for those focused on building commercial applications.These kinds of “batteries included” Python environments provide everything you need to get started coding right away. New to Python? We’d recommend starting with a pre-built version of Python such as those offered by ActivePython or Anaconda in order to simplify and speed setup. ![]() For the time being, dependency resolution will still need to be managed manually. Additionally, these vendors enhance Python with their own ecosystem, which can often make Python easier to deploy, build and manage.Įxperienced Pythonistas will likely prefer to use ’s Python core, and then manually install all the packages they require from PyPI using pip. Foremost among these vendors are Anaconda and ActiveState. To simplify and speed project startup, a number of commercial vendors package together a version of the Python core with hundreds of the most popular packages from PyPI. Typically, developers download the Python core for the most recent release of the language from, and then source any third party packages, libraries and components they may require for their project from the Python Package Index (PyPI). The first choice for many is, the home of the Python Software Foundation, which is the body responsible for creating and releasing new versions of Python. When it comes to installing Python, developers have a number of choices, all of which are suitable for developing a wide range of applications. Not sure whether you should download Anaconda, ActivePython or community Python for your next Python project? While they’re all good, depending on how you work, one may be more appropriate than the others.
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