Anaconda vs miniconda

Question

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

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Anaconda or Miniconda  Choose Anaconda if you   Are new to conda or Python   Like the convenience of having Python and over 1 500 scientific packages automatically installed at once   Have the time and disk space---a few minutes and 3 GB   Do not want to individually install each of the packages you want to use    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 1 500 packages at once   Want fast access to Python and the conda commands and you wish to sort out the other programs later    Source

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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

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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

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Per the original docs  Choose Anaconda if you   Are new to conda or Python Like the convenience of having Python and over 1500 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 1500 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  amp  3  Version 4 0 included the Anaconda Navigator  Release notes for subsequent versions can be found here

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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

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Brief  conda is both a command line tool  and a python package   Miniconda installer   Python   conda  Anaconda installer   Python   conda   meta package anaconda  meta Python pkg anaconda   about 160 Python pkgs for daily use in data science  Anaconda installer   Miniconda installer   conda install anaconda  Detail   conda is a python manager and an environment manager  which makes it possible to   install package with conda install flake8 create an environment with any version of Python with conda create -n myenv python 3 6  Miniconda installer   Python   conda  conda  the package manager and environment manager  is a Python package  So Python is installed  Cause conda distribute Python interpreter with its own libraries dependencies but not the existing ones on your operating system  other minimal dependencies like openssl  ncurses  sqlite  etc are installed as well   Basically  Miniconda is just conda and its minimal dependencies  And the environment where conda is installed is the  base  environment  which is previously called  root  environment  Anaconda installer   Python   conda   meta package anaconda meta Python package anaconda   about 160 Python pkgs for daily use in data science     Meta packages  are packages that do NOT contain actual softwares and simply depend on other packages to be installed    Download an anaconda meta package from Anaconda Cloud and extract the content from it  The actual 160  packages to be installed are listed in info recipe meta yaml   package      name  anaconda     version   2019 07  build      ignore run exports          -         number   0      pin depends  strict     string  py36 0 requirements      build          - python 3 6 8 haf84260 0     is meta pkg          - true     run          - alabaster 0 7 12 py36 0         - anaconda-client 1 7 2 py36 0         - anaconda-project 0 8 3 py 0                       - beautifulsoup4 4 7 1 py36 1                       - curl 7 65 2 ha441bb4 0                       - hdf5 1 10 4 hfa1e0ec 0                       - ipykernel 5 1 1 py36h39e3cac 0         - ipython 7 6 1 py36h39e3cac 0         - ipython genutils 0 2 0 py36h241746c 0         - ipywidgets 7 5 0 py 0                       - jupyter 1 0 0 py36 7         - jupyter client 5 3 1 py 0         - jupyter console 6 0 0 py36 0         - jupyter core 4 5 0 py 0         - jupyterlab 1 0 2 py36hf63ae98 0         - jupyterlab server 1 0 0 py 0                       - matplotlib 3 1 0 py36h54f8f79 0                       - mkl 2019 4 233         - mkl-service 2 0 2 py36h1de35cc 0         - mkl fft 1 0 12 py36h5e564d8 0         - mkl random 1 0 2 py36h27c97d8 0                       - nltk 3 4 4 py36 0                       - numpy 1 16 4 py36hacdab7b 0         - numpy-base 1 16 4 py36h6575580 0         - numpydoc 0 9 1 py 0                       - pandas 0 24 2 py36h0a44026 0         - pandoc 2 2 3 2 0                       - pillow 6 1 0 py36hb68e598 0                       - pyqt 5 9 2 py36h655552a 2                       - qt 5 9 7 h468cd18 1         - qtawesome 0 5 7 py36 1         - qtconsole 4 5 1 py 0         - qtpy 1 8 0 py 0                       - requests 2 22 0 py36 0                       - sphinx 2 1 2 py 0         - sphinxcontrib 1 0 py36 1         - sphinxcontrib-applehelp 1 0 1 py 0         - sphinxcontrib-devhelp 1 0 1 py 0         - sphinxcontrib-htmlhelp 1 0 2 py 0         - sphinxcontrib-jsmath 1 0 1 py 0         - sphinxcontrib-qthelp 1 0 2 py 0         - sphinxcontrib-serializinghtml 1 1 3 py 0         - sphinxcontrib-websupport 1 1 2 py 0         - spyder 3 3 6 py36 0         - spyder-kernels 0 5 1 py36 0                 The pre-installed packages from meta pkg anaconda are mainly for web scraping and data science  Like requests  beautifulsoup  numpy  nltk  etc   If you have a Miniconda installed  conda install anaconda will make it same as an Anaconda installation  except that the installation folder names are different  Miniconda2 v s  Miniconda  Anaconda2 v s  Anaconda    2 means the bundled Python interpreter for conda in the  base  environment is Python 2  but not Python 3

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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  quot devtools quot   devtools  install github  quot IRkernel IRkernel quot   IRkernel  installspec    Done  Next time Jupyter is opened  the R kernel will be available

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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

[python] Anaconda vs. miniconda

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