#Miniconda vs anaconda install#
#Miniconda vs anaconda upgrade#
#Miniconda vs anaconda software#

It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.' A conda install provides a whole suite of command line tools for installing and managing packages and environments.

#Miniconda vs anaconda software#

conda: 'Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them.

I have also switched from using virtualenvs to using conda environments, and I am loving it.īefore explaining my workflow, here's a quick glossary of the similarly-named products that Continuum offers. In 2015, I have almost exclusively used Python installations provided through Continuum Analytics's Conda/Anaconda platform. You have to install each version yourself and then tell virtualenv to use it. virtualenv also provides no helping in actually managing Python versions. In my experience, getting started with virtualenv is cumbersome and confusing to this day, I have to look up the command to create a Python 3 virtualenv. If you use virtualenv, each project you work on can have its own version of Python with its own 3rd party packages (hopefully specified in an requirements.txt file).

#Miniconda vs anaconda upgrade#

While this may sound convenient, it causes problems if you (1) install different packages with the same name (2) need to use different versions of the same package (3) upgrade your operating system (OS X will delete all the packages you have installed).įor many years, best practice for Python developers was to use virtualenv to create a sandbox-ed environment for each project. Secondly, if you install 3rd party packages with pip, every package is installed into the same globally accessible directory. First, it's probably an old version of Python. There are several good reasons to stop using the system Python. Some of the packages will cause trouble while installing using pip in windows.Many new Python programmers rely on their system install of Python to run their scripts. I would recommend miniconda for using as the development environment in windows for basic level python developers as it will be easy to handle the dependencies. Official Python - This is the standard version of Python. So it is very easy to find and install dependent packages using conda. Using conda, we can install the required package from several thousands of cloud repositories. It is a small, bootstrap version of Anaconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib and a few others.īoth Anaconda and Miniconda comes with conda package manager. Miniconda - This is a minimal version of anaconda. This is like a complete ecosystem of libraries and packages for a data scientist or an advanced python programmer. This is the best option for someone who is interested to learn datascience & machine learning. Here I will be explaining these from an individual user's perspective.Īnaconda - This is one of the world's popular opensource python distribution with lot of machine learning and datascience packages. If you are a python developer or someone who is interested to learn python, you should definitely know this. Have you heard about Anaconda or Miniconda ?