What is the difference between pip and conda

Question

I know pip is a package manager for python packages  However  I saw the installation on IPython s website use conda to install IPython   Can I use pip to install IPython  Why should I use conda as another python package manager when I already have pip   What is the difference between pip and conda

User · Answer

To answer the original question  For installing packages  PIP and Conda are different ways to accomplish the same thing  Both are standard applications to install packages  The main difference is the source of the package files   PIP PyPI will have more  quot experimental quot  packages  or newer  less common  versions of packages Conda will typically have more well established packages or versions  An important cautionary side note  If you use both sources  pip and conda  to install packages in the same environment  this may cause issues later   Recreate the environment will be more difficult Fix package incompatibilities becomes more complicated  Best practice is to select one application  PIP or Conda  to install packages  and use that application to install any packages you need  However  there are many exceptions or reasons to still use pip from within a conda environment  and vice versa  For example   When there are packages you need that only exist on one  and the other doesn t have them  You need a certain version that is only available in one environment

User · Answer

The other answers give a fair description of the details  but I want to highlight some high-level points   pip is a package manager that facilitates installation  upgrade  and uninstallation of python packages   It also works with virtual python environments   conda is a package manager for any software  installation  upgrade and uninstallation    It also works with virtual system environments   One of the goals with the design of conda is to facilitate package management for the entire software stack required by users  of which one or more python versions may only be a small part   This includes low-level libraries  such as linear algebra  compilers  such as mingw on Windows  editors  version control tools like Hg and Git  or whatever else requires distribution and management   For version management  pip allows you to switch between and manage multiple python environments   Conda allows you to switch between and manage multiple general purpose environments across which multiple other things can vary in version number  like C-libraries  or compilers  or test-suites  or database engines and so on   Conda is not Windows-centric  but on Windows it is by far the superior solution currently available when complex scientific packages requiring compilation are required to be installed and managed     I want to weep when I think of how much time I have lost trying to compile many of these packages via pip on Windows  or debug failed pip install sessions when compilation was required   As a final point  Continuum Analytics also hosts  free  binstar org  now called anaconda org  to allow regular package developers to create their own custom  built   software stacks that their package-users will be able to conda install from

User · Answer

Quote from Conda for Data Science article onto Continuum s website      Conda vs pip      Python programmers are probably familiar with pip to download packages from PyPI and manage their requirements  Although  both conda and pip are package managers  they are very different          Pip is specific for Python packages and conda is language-agnostic  which means we can use conda to manage packages from any language   Pip compiles from source and conda installs binaries  removing the burden of compilation   Conda creates language-agnostic environments natively whereas pip relies on virtualenv to manage only Python environments   Though it is recommended to always use conda packages  conda also includes pip  so you don   t have to choose between the two  For example  to install a python package that does not have a conda package  but is available through pip  just run  for example       conda install pip pip install gensim

User · Answer

I may have found one further difference of a minor nature  I have my python environments under  usr rather than  home or whatever  In order to install to it  I would have to use sudo install pip  For me  the undesired side effect of sudo install pip was slightly different than what are widely reported elsewhere  after doing so  I had to run python with sudo in order to import any of the sudo-installed packages  I gave up on that and eventually found I could use sudo conda to install packages to an environment under  usr which then imported normally without needing sudo permission for python  I even used sudo conda to fix a broken pip rather than using sudo pip uninstall pip or sudo pip --upgrade install pip

User · Answer

Here is a short rundown   pip   Python packages only  Compiles everything from source  EDIT  pip now installs binary wheels  if they are available  Blessed by the core Python community  i e   Python 3 4  includes code that automatically bootstraps pip     conda   Python agnostic  The main focus of existing packages are for Python  and indeed Conda itself is written in Python  but you can also have Conda packages for C libraries  or R packages  or really anything  Installs binaries  There is a tool called conda build that builds packages from source  but conda install itself installs things from already built Conda packages   External  Conda is the package manager of Anaconda  the Python distribution provided by Continuum Analytics  but it can be used outside of Anaconda too  You can use it with an existing Python installation by pip installing it  though this is not recommended unless you have a good reason to use an existing installation     In both cases    Written in Python Open source  Conda is BSD and pip is MIT    The first two bullet points of Conda are really what make it advantageous over pip for many packages  Since pip installs from source  it can be painful to install things with it if you are unable to compile the source code  this is especially true on Windows  but it can even be true on Linux if the packages have some difficult C or FORTRAN library dependencies   Conda installs from binary  meaning that someone  e g   Continuum  has already done the hard work of compiling the package  and so the installation is easy    There are also some differences if you are interested in building your own packages  For instance  pip is built on top of setuptools  whereas Conda uses its own format  which has some advantages  like being static  and again  Python agnostic

User · Answer

Quoting from the Conda blog      Having been involved in the python world for so long  we are all aware of pip  easy install  and virtualenv  but these tools did not meet all of our specific requirements  The main problem is that they are focused around Python  neglecting non-Python library dependencies  such as HDF5  MKL  LLVM  etc   which do not have a setup py in their source code and also do not install files into Python   s site-packages directory    So Conda is a packaging tool and installer that aims to do more than what pip does  handle library dependencies outside of the Python packages as well as the Python packages themselves  Conda also creates a virtual environment  like virtualenv does   As such  Conda should be compared to Buildout perhaps  another tool that lets you handle both Python and non-Python installation tasks   Because Conda introduces a new packaging format  you cannot use pip and Conda interchangeably   pip cannot install the Conda package format  You can use the two tools side by side  by installing pip with conda install pip  but they do not interoperate either   Since writing this answer  Anaconda has published a new page on Understanding Conda and Pip  which echoes this as well      This highlights a key difference between conda and pip  Pip installs Python packages whereas conda installs packages which may contain software written in any language  For example  before using pip  a Python interpreter must be installed via a system package manager or by downloading and running an installer  Conda on the other hand can install Python packages as well as the Python interpreter directly    and further on     Occasionally a package is needed which is not available as a conda package but is available on PyPI and can be installed with pip  In these cases  it makes sense to try to use both conda and pip

User · Answer

Quoting from Conda  Myths and Misconceptions  a comprehensive description         Myth  3  Conda and pip are direct competitors  Reality  Conda and pip serve different purposes  and only directly compete in a small subset of tasks  namely installing Python packages in isolated environments   Pip  which stands for Pip Installs Packages  is Python s officially-sanctioned package manager  and is most commonly used to install packages published on the Python Package Index  PyPI   Both pip and PyPI are governed and supported by the Python Packaging Authority  PyPA    In short  pip is a general-purpose manager for Python packages  conda is a language-agnostic cross-platform environment manager  For the user  the most salient distinction is probably this  pip installs python packages within any environment  conda installs any package within conda environments  If all you are doing is installing Python packages within an isolated environment  conda and pip virtualenv are mostly interchangeable  modulo some difference in dependency handling and package availability  By isolated environment I mean a conda-env or virtualenv  in which you can install packages without modifying your system Python installation   Even setting aside Myth  2  if we focus on just installation of Python packages  conda and pip serve different audiences and different purposes  If you want to  say  manage Python packages within an existing system Python installation  conda can t help you  by design  it can only install packages within conda environments  If you want to  say  work with the many Python packages which rely on external dependencies  NumPy  SciPy  and Matplotlib are common examples   while tracking those dependencies in a meaningful way  pip can t help you  by design  it manages Python packages and only Python packages   Conda and pip are not competitors  but rather tools focused on different groups of users and patterns of use

User · Answer

For WINDOWS users   standard  packaging tools situation is improving recently    on pypi itself  there are now 48  of wheel packages as of sept  11th 2015  up from 38   in may 2015   24  in sept  2014   the wheel format is now supported out-of-the-box per latest python 2 7 9     standard   tweaks  packaging tools situation is improving also    you can find nearly all scientific packages on wheel format at http   www lfd uci edu  gohlke pythonlibs  the mingwpy project may bring one day a  compilation  package to windows users  allowing to install everything from source when needed     Conda  packaging remains better for the market it serves  and highlights areas where the  standard  should improve    also  the dependency specification multiple-effort  in standard wheel system and in conda system  or buildout  is not very pythonic  it would be nice if all these packaging  core  techniques could converge  via a sort of PEP

User · Answer

pip is for Python only  conda is only for Anaconda   other scientific packages like R dependencies etc  NOT everyone needs Anaconda that already comes with Python  Anaconda is mostly for those who do Machine learning deep learning etc  Casual Python dev won t run Anaconda on his laptop

User · Answer

Not to confuse you further   but you can also use pip within your conda environment  which validates the general vs  python specific managers comments above    conda install -n testenv pip source activate testenv pip  lt pip command gt    you can also add pip to default packages of any environment so it is present each time so you don t have to follow the above snippet

User · Answer

pip is a package manager    conda is both a package manager and an environment manager   Detail     References   Understanding Conda and Pip

User · Answer

Can I use pip to install iPython        Sure  both  first approach on page   pip install ipython   and  third approach  second is conda      You can manually download IPython from GitHub or PyPI  To install one   of these versions  unpack it and run the following from the top-level   source directory using the Terminal   pip install      are officially recommended ways to install           Why should I use conda as another python package manager when I already have pip       As said here      If you need a specific package  maybe only for one project  or if you need to share the project with someone else  conda seems more appropriate    Conda surpasses pip in  YMMV    projects that use non-python tools sharing with colleagues switching between versions switching between projects with different library versions           What is the difference between pip and conda       That is extensively answered by everyone else

[python] What is the difference between pip and conda?

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