How To Download And Install Scipy
Carlita Giandomenico
Do NOT use brew to install a Python package, use an environment. brew is great to install system dependencies or other dev tools, but should not be used to install Python packages. Down the road this is a recipe for trouble.
I had the same issue when installing scipy into a virtualenv on my Nano. Not sure why it would be so for scipy specifically, but it relates to not being the owner (in your case) of /home/enroutenano/.cache/pip, hence the permission denied message. The fix was simple, at least it was on my Nano, try this hopefully it should solve the problem; sudo chown -R enroutenano /home/enroutenano/.cache/pip
Regards.
Building SciPy from source requires setting up system-level dependencies(compilers, BLAS/LAPACK libraries, etc.) first, and then invoking a build. Thebuild may be done in order to install SciPy for local usage, develop SciPyitself, or build redistributable binary packages. And it may be desired tocustomize aspects of how the build is done. This guide will cover all theseaspects. In addition, it provides background information on how the SciPy buildworks, and links to up-to-date guides for generic Python build & packagingdocumentation that is relevant.
If you are using Conda, you can skip the steps in this section - with theexception of installing compilers for Windows or the Apple Developer Toolsfor macOS. All other dependencies will be installed automatically by themamba env create -f environment.yml command.
First, install Microsoft Visual Studio - the 2019 Community Edition or anynewer version will work (see theVisual Studio download site).This is needed even if you use the MinGW-w64 or Intel compilers, in orderto ensure you have the Windows Universal C Runtime (the other components ofVisual Studio are not needed when using Mingw-w64, and can be deselected ifdesired, to save disk space).
The MSVC installer does not put the compilers on the system path, andthe install location may change. To query the install location, MSVCcomes with a vswhere.exe command-line utility. And to make theC/C++ compilers available inside the shell you are using, you need torun a .bat file for the correct bitness and architecture (e.g., for64-bit Intel CPUs, use vcvars64.bat).
If you are using a conda environment, pip is still the tool you use toinvoke a from-source build of SciPy. It is important to always use the--no-build-isolation flag to the pip install command, to avoidbuilding against a numpy wheel from PyPI. In order for that to work youmust first install the remaining build dependencies into the condaenvironment:
On Windows it is possible that the environment creation will not work dueto an outdated Fortran compiler. If that happens, remove the compilersentry from environment.yml and try again. The Fortran compiler shouldbe installed as described under the Windows tab of the System-leveldependencies section higher up.
This will install SciPy inside the repository (by default in abuild-install directory). You can then run tests (python dev.py test),drop into IPython (python dev.py ipython), or take other development stepslike build the html documentation or running benchmarks. The dev.pyinterface is self-documenting, so please see python dev.py --help andpython dev.py --help for detailed guidance.
This wikiHow teaches you how to install the main SciPy packages from the SciPy library, using Windows, Mac or Linux. SciPy is a free and open-source Python library with packages optimized and developed for scientific and technical computing. If you have Python installed, you can use Python's standard pip package manager, and install it from the Python Package index. On some Linux distributions, you can use your system's native package manager to perform a system-wide installation.
Today I tried installing these modules under Cygwin with pip. The whole thing took a few hours to figure out thanks to crappy bundled packages that pip fetches and lack of consistency between helps available online.
you have to get numpy running correctly for matplotlib install to happen, plus a bunch of other cygwin installs as mentioned here. Yes, you cygwin setup install a bunch of stuff, including g++, c compiler, fortran stuff, gtk stuff, etc etc etc. Here a cygcheck -c dump, sorry so long.
Thank you! I have been combing the Internet for information on how to successfully install scipy on a Windows computer and cygwin. Your info about the Cygwin packages that were dependencies did the trick! After I installed, through the cygwin installer, liblapack-devel, libopenblas, gcc-fortran, python-gtk2, tcl-tk, libpng, and pkg-config (I already had this one), I was able to install scipy:
pip install scipy
with no problem. Thanks again!
Anyway, one good workaround for this is to not use keras.preprocessing since these run in python/numpy/scipy not in tensorflow. keras.layers.experimental.preprocessing contains pure-tensorflow layers that implemnent common image transformations.
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