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InstallationInstallations methods include:.Methods differ in ease of use, coverage, maintenance of old versions,system-wide versus local environment use, and control. With pip or Anaconda’sconda, you can control the package versions for a specific project to preventconflicts. Conda also controls non-Python packages, like MKL or HDF5. Systempackage managers, like apt-get, install across the entire computer, oftenhave older versions, and don’t have as many available versions. Sourcecompilation is much more difficult but is necessary for debugging and development.If you don’t know which installation method you need or prefer, we recommendthe Scientific Python Distribution. Scientific Python Distributions (recommended)Python distributions provide the language itself, along with the most commonlyused packages and tools.
These downloadable files require little configuration,work on almost all setups, and provide all the commonly used scientific python tools.works on Windows, Mac, andLinux, provides over 1,500 Python/R packages, and is used by over 15 millionpeople. Python - m pip install - user numpy scipy matplotlib ipython jupyter pandas sympy noseWe recommend using an user install, sending the -user flag to pip.pip installs packages for the local user and does not write to the systemdirectories.
Preferably, do not use sudo pip, as this combination can cause problems.Pip accesses the Python Package Index, whichstores almost 200,000 projects and all previous releases of said projects.Because the repository keeps previous versions, you can pin to a version andnot worry about updates causing conflicts. Pip can also install packages inlocal virtualenv, or virtual environment.
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