In the Anaconda repository, there are two types of installers:
"Anaconda installers" and "Miniconda installers".
What are their differences? Besides, for an installer file, Anaconda2-4.4.0.1-Linux-ppc64le.sh, what does 2-4.4.0.1 stand for?
The difference is that miniconda is just shipping the repository management system. So when you install it there is just the management system without packages. Whereas with Anaconda, it is like a distribution with some built in packages.
Like with any Linux distribution, there are some releases which bundles lots of updates for the included packages. That is why there is a difference in version numbering. If you only decide to upgrade Anaconda, you are updating a whole system.
Per the original docs (link is now dead):
Choose Anaconda if you:
- Are new to conda or Python
- Like the convenience of having Python and over 150 scientific packages automatically installed at once
- Have the time and disk space (a few minutes and 3 GB), and/or
- Don’t want to install each of the packages you want to use individually.
Choose Miniconda if you:
- Do not mind installing each of the packages you want to use individually.
- Do not have time or disk space to install over 150 packages at once, and/or
- Just want fast access to Python and the conda commands, and wish to sort out the other programs later.
I use Miniconda myself. Anaconda is bloated. Many of the packages are never used and could still be easily installed if and when needed.
Note that Conda is the package manager (e.g. conda list displays all installed packages in the environment), whereas Anaconda and Miniconda are distributions. A software distribution is a collection of packages, pre-built and pre-configured, that can be installed and used on a system. A package manager is a tool that automates the process of installing, updating, and removing packages.
Anaconda is a full distribution of the central software in the PyData ecosystem, and includes Python itself along with the binaries for several hundred third-party open-source projects. Miniconda is essentially an installer for an empty conda environment, containing only Conda, its dependencies, and Python. Source.
Once Conda is installed, you can then install whatever package you need from scratch along with any desired version of Python.
2-4.4.0.1 is the version number for your Anaconda installation package. Strangely, it is not listed in their Old Package Lists.
In April 2016, the Anaconda versioning jumped from 2.5 to 4.0 in order to avoid confusion with Python versions 2 & 3. Version 4.0 included the Anaconda Navigator.
Release notes for subsequent versions can be found here.
Miniconda gives you the Python interpreter itself, along with a command-line tool called conda which operates as a cross-platform package manager geared toward Python packages, similar in spirit to the apt or yum tools that Linux users might be familiar with.
Anaconda includes both Python and conda, and additionally bundles a suite of other pre-installed packages geared toward scientific computing. Because of the size of this bundle, expect the installation to consume several gigabytes of disk space.
Source: Jake VanderPlas's Python Data Science Handbook
The 2 in Anaconda2 means that the main version of Python will be 2.x rather than the 3.x installed in Anaconda3. The current release has Python 2.7.13.
The 4.4.0.1 is the version number of Anaconda. The current advertised version is 4.4.0 and I assume the .1 is a minor release or for other similar use. The Windows releases, which I use, just say 4.4.0 in the file name.
Others have now explained the difference between Anaconda and Miniconda, so I'll skip that.
Both Anaconda and miniconda use the conda package manager. The chief differece between between Anaconda and miniconda,however,is that
The Anaconda distribution comes pre-loaded with all the packages while the miniconda distribution is just the management system without any pre-loaded packages. If one uses miniconda, one has to download individual packages and libraries separately.
I personally use Anaconda distribution as I dont really have to worry much about individual package installations.
A disadvantage of miniconda is that installing each individual package can take a long amount of time. Compared to that installing and using Anaconda takes a lot less time.
However, there are some packages in anaconda (QtConsole, Glueviz,Orange3) that I have never had to use. I dont even know their purpose. So a disadvantage of anaconda is that it occupies more space than needed.
Anaconda is a very large installation ~ 2 GB and is most useful for those users who are not familiar with installing modules or packages with other package managers.
Anaconda seems to be promoting itself as the official package manager of Jupyter. It's not. Anaconda bundles Jupyter, R, python, and many packages with its installation.
Anaconda is not necessary for installing Jupyter Lab or the R kernel. There is plenty of information available elsewhere for installing Jupyter Lab or Notebooks. There is also plenty of information elsewhere for installing R studio. The following shows how to install the R kernel directly from R Studio:
To install the R kernel, without Anaconda, start R Studio. In the R terminal window enter these three commands:
install.packages("devtools")
devtools::install_github("IRkernel/IRkernel")
IRkernel::installspec()
Done. The next time Jupyter is opened, the R kernel will be available and available.
来源：https://stackoverflow.com/questions/45421163/anaconda-vs-miniconda