I used following process to install:
Download & install 64-bit Python: https://www.python.org/downloads/release/python-342/
Download the 64-bit version of numpy:
pip install "numpy-1.9.2rc1-cp34-none-win_amd64.whl"
pip install pandas==0.14.0
Error message is attached.
Thank you for help.
enter image description here
When you intstall pandas it will automatically install numpy so need to install numpy seperately, also you need to have microsfit visual basic C++ 10.0.
I had the same case and when I installed it everythig went fine.
I'm trying to install tensorflow on windows. I have python3 (3.5.2) and pip3 (9.0.1):
pip3 install --upgrade tensorflow
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
Found this issue here as well: tensorflow not found in pip
but none of the solutions worked for me. Any ideas?
Try the following at a Python command prompt:
import platform
platform.architecture()[0]
It should display '64bit'
Just having an x86 version of Python isn't enough.
I had the same problem. Thought I had a 64 bit installation but it turned out to be 32 bit.
BTW. it will also work fine with the Conda Python 3.6 distribution. And indeed use the distro from the Gohlke page as indicated by Guillaume Jacquenot.
You can download binary wheel from Christoph Gohlke's webpage
Once downloaded, you can run pip install tensorflow‑1.0.1‑cp35‑cp35m‑win_amd64.whl for Python 3.5 64 bit
This is what worked for me.
Currently, Tensorflow only works with 64-bit windows, not 32-bit.
So, you could create a new 64-bit environment and install tensorflow in it:
set CONDA_FORCE_32BIT=
conda create --name name_of_your_created_environment python=3.5
activate name_of_your_created_environment
conda install -c conda-forge tensorflow
CONDA_FORCE_32BIT=1 sets to a 32-bit environment whilst CONDA_FORCE_32BIT= sets to a 64-bit environment.
I have written a blog over this topic, you might find it interesting and helpful:
Mainly issue that people face is they install 32 bit python:
Solution as follows
Install Python 3.6 (Note down installation path, or simply custom install to C:\Python36) in your system - Make sure that Python is of "x64" architecture.
To check your python architecture
Import platform
platform.architecture()[0]
Link to download Python36 with 64 bit architecture : https://www.python.org/ftp/python/3.6.2/python-3.6.2-amd64.exe
For more info you can follow the this link
https://tensorflowwindows.quora.com/
pip3 install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.0.0-py3-none-any.whl
try this one under your python environment
Just follow 3 steps:
Install python 3.5.x version (64bit MUST)
Install pip
pip install tensorflow==2.0.0-alpha0
And you are good to go.
Found this after struggling for days
You need to install Python 3.7 to download end version of Tensorflow ->2.3 and some packages:
visual studio tools C++
cuda_10.1.105_418.96_win10
After spending hours I am able to fix TensorFlow installation issue on Windows. here is the summary https://stackoverflow.com/a/50475864/1996802
I am having a strange issue installing numpy or nltk python-modules in my windows-7 machine. I have successfully installed Python 2.7.12 but I get this error when I type pip install numpy as in this screenshot. I have also included the directory of pip.exe in the PATH. Any help would be appreciated.Thank you :)
Installing such these things in windows are sometime difficult, specially for someone new to python packages(also for some experts!)
Try to use Anaconda for windows: https://www.continuum.io/downloads#_windows
This install a python for you and many requirement packages(e.g Numpy, Scipy, Scikit and many more)
You can use older version of Anaconda, for python2.x if you want strictly python2.x
An alternative way is to download Numpy from github and then install it as a python package, that contain setup.py file
python setup.py install
Or you can download Numpy wheel package, then install it localy with pip
I am pretty new to python and programming , all self taught. I started a new position late last year requiring me to create and maintain large scientific data sets. A big hurdle was learning to install the pyhdf and netcdf4 modules for 64 bit python 2.7 on windows. Here is how to do that.
NEW CONDENSED VERSION ----- JUNE 2016
I have learned more since I wrote this question. Anaconda makes everything except pyhdf (to my knowledge) easier.
1. Anaconda
Download Anaconda 2.7 windows 64 bit from here! and install at C:\Anaconda
2. Numpy
conda update numpy
3. PIP
conda update pip
4. Pyhdf
Download pyhdf python 2.7 64 bit from here!
pip install C:\Users\username\Downloads\pyhdf_file
5. Netcdf
conda update netcdf4
=========================================================================
=========================================================================
OLD METHOD ----- OCTOBER 2014
1. Anaconda
Download Anaconda 2.7 windows 64 bit from here! and install at C:\Anaconda
2. Numpy
In command prompt. You could also use the below method to pip install numpy.
conda install numpy
3. PIP
I used the directions found here!. They are also found below.
Download ez_setup.py and then run:
python ez_setup.py
Then download get-pip.py and run:
python get-pip.py
upgrade installed setuptools by pip:
pip install setuptools --upgrade
4. Pyhdf
Download pyhdf python 2.7 64 bit from here!
pip install C:\Users\username\Downloads\pyhdf_file
5. Netcdf
Download netcdf4 python 2.7 64 bit from here!
pip install C:\Users\username\Downloads\netcdf4_file
I am trying to install python and a series of packages onto a 64bit windows 7 desktop. I have installed Python 3.4, have Microsoft Visual Studio C++ installed, and have successfully installed numpy, pandas and a few others. I am getting the following error when trying to install scipy;
numpy.distutils.system_info.NotFoundError: no lapack/blas resources found
I am using pip install offline, the install command I am using is;
pip install --no-index --find-links="S:\python\scipy 0.15.0" scipy
I have read the posts on here about requiring a compiler which if I understand correctly is the VS C++ compiler. I am using the 2010 version as I am using Python 3.4. This has worked for other packages.
Do I have to use the window binary or is there a way I can get pip install to work?
Many thanks for the help
The following link should solve all problems with Windows and SciPy; just choose the appropriate download. I was able to pip install the package with no problems. Every other solution I have tried gave me big headaches.
Source: http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy
Command:
pip install [Local File Location]\[Your specific file such as scipy-0.16.0-cp27-none-win_amd64.whl]
This assumes you have installed the following already:
Install Visual Studio 2015/2013 with Python Tools
(Is integrated into the setup options on install of 2015)
Install Visual Studio C++ Compiler for Python
Source: http://www.microsoft.com/en-us/download/details.aspx?id=44266
File Name: VCForPython27.msi
Install Python Version of choice
Source: python.org
File Name (e.g.): python-2.7.10.amd64.msi
My python's version is 2.7.10, 64-bits Windows 7.
Download scipy-0.18.0-cp27-cp27m-win_amd64.whl from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy
Open cmd
Make sure scipy-0.18.0-cp27-cp27m-win_amd64.whl is in cmd's current directory, then type pip install scipy-0.18.0-cp27-cp27m-win_amd64.whl.
It will be successful installed.
The solution to the absence of BLAS/LAPACK libraries for SciPy installations on Windows 7 64-bit is described here:
http://www.scipy.org/scipylib/building/windows.html
Installing Anaconda is much easier, but you still don't get Intel MKL or GPU support without paying for it (they are in the MKL Optimizations and Accelerate add-ons for Anaconda - I'm not sure if they use PLASMA and MAGMA either). With MKL optimization, numpy has outperformed IDL on large matrix computations by 10-fold. MATLAB uses the Intel MKL library internally and supports GPU computing, so one might as well use that for the price if they're a student ($50 for MATLAB + $10 for the Parallel Computing Toolbox). If you get the free trial of Intel Parallel Studio, it comes with the MKL library, as well as C++ and FORTRAN compilers that will come in handy if you want to install BLAS and LAPACK from MKL or ATLAS on Windows:
http://icl.cs.utk.edu/lapack-for-windows/lapack/
Parallel Studio also comes with the Intel MPI library, useful for cluster computing applications and their latest Xeon processsors. While the process of building BLAS and LAPACK with MKL optimization is not trivial, the benefits of doing so for Python and R are quite large, as described in this Intel webinar:
https://software.intel.com/en-us/articles/powered-by-mkl-accelerating-numpy-and-scipy-performance-with-intel-mkl-python
Anaconda and Enthought have built businesses out of making this functionality and a few other things easier to deploy. However, it is freely available to those willing to do a little work (and a little learning).
For those who use R, you can now get MKL optimized BLAS and LAPACK for free with R Open from Revolution Analytics.
EDIT: Anaconda Python now ships with MKL optimization, as well as support for a number of other Intel library optimizations through the Intel Python distribution. However, GPU support for Anaconda in the Accelerate library (formerly known as NumbaPro) is still over $10k USD! The best alternatives for that are probably PyCUDA and scikit-cuda, as copperhead (essentially a free version of Anaconda Accelerate) unfortunately ceased development five years ago. It can be found here if anybody wants to pick up where they left off.
Sorry to necro, but this is the first google search result. This is the solution that worked for me:
Download numpy+mkl wheel from
http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy.
Use the version that is the same as your python version (check using python -V). Eg. if your python is 3.5.2, download the wheel which shows cp35
Open command prompt and navigate to the folder where you downloaded the wheel. Run the command: pip install [file name of wheel]
Download the SciPy wheel from: http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy (similar to the step above).
As above, pip install [file name of wheel]
This was the order I got everything working. The second point is the most important one. Scipy needs Numpy+MKL, not just vanilla Numpy.
Install python 3.5
pip install "file path" (download Numpy+MKL wheel from here http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy)
pip install scipy
You probably just have too new (unsupported) Python 3.x installed.
This page has overcomplicated solutions to the problem. Most of numpy / scipy users should not need to compile their numpy installations or need to rely on 3rd party "numpy+mkl" wheels.
Downloading a compiler is an anti-pattern, you do not want to build
numpy, only use it. [github.com/numpy]
Solution
Once you have installed supported python version, remove your non-working numpy installation with
pip uninstall numpy
and install scipy with
pip install scipy --only-binary numpy
The --only-binary numpy will force installing binary wheel (.whl) version of numpy. If it fails, you have too new (not yet supported) version of python.
If you have multiple python versions installed, you can ensure that pip is installing the python version you want by
<path_to_python_executable> -m pip install <X>
instead of pip install <X>.
Why this is happening?
Scipy relies on numpy, as can be seen from the setup.py or just by reading the pip install logs.
If you have too new (non-supported) python installation, there are no built wheel (.whl) in the pip repository, but tarballs (.tar.gz), which in this case require the user machine to compile some C++-code during installation. See also: Python packaging: wheels vs tarball (tar.gz)
Appendix
Check the https://pypi.org/project/numpy/ for list of supported Python versions. Currently (2020-11-04) the newest supported python version is Python 3.9. when using numpy 1.19.3 or above, and Python 3.8 for numpy 1.19.2. (For compatibility of older numpy versions, see numpy release notes)
If you are on Windows and see pip trying to install numpy-<x>.tag.gz, you know it probably will not work. Try older version of Python, instead. You want to see pip to installing a binary wheel for numpy for Windows (numpy-<x>.whl). You can check the wheels in pip available for numpy here.
If you are working with Windows and Visual Studio 2015
Install miniconda http://conda.pydata.org/miniconda.html
Change your python environment to python 3.4 (32bit)
click on python environment 3.4 and open cmd
Enter the following commands
"conda install numpy"
"conda install pandas"
"conda install scipy"
Simple and Fast Installation of Scipy in Windows
From http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy download the
correct Scipy package for your Python version (e.g. the correct
package for python 3.5 and Windows x64 is scipy-0.19.1-cp35-cp35m-win_amd64.whl).
Open cmd inside the directory containing the downloaded Scipy
package.
Type pip install <<your-scipy-package-name>> (e.g. pip install
scipy-0.19.1-cp35-cp35m-win_amd64.whl).
My 5 cents; You can just install the entire (pre-compiled) SciPy from
https://github.com/scipy/scipy/releases
Good Luck!
For python27
1、Install numpy + mkl（download link:http://www.lfd.uci.edu/~gohlke/pythonlibs/）
2、install scipy (the same site)
OK!
Intel now provides a Python distribution for Linux / Windows / OS X for free called "Intel distribution for Python".
Its a complete Python distribution (e.g. python.exe is included in the package) which includes some pre-installed modules compiled against Intel's MKL (Math Kernel Library) and thus optimized for faster performance.
The distribution includes the modules NumPy, SciPy, scikit-learn, pandas, matplotlib, Numba, tbb, pyDAAL, Jupyter, and others. The drawback is a bit of lateness in upgrading to more recent versions of Python. For example as of today (1 May 2017) the distribution provides CPython 3.5 while the 3.6 version is already out. But if you don't need the new features they should be perfectly fine.
I was also getting same error while installing scikit-fuzzy. I resolved error as follows:
Install Numpy, a whl file
Install Scipy, again a whl file
choose file according to python version like amd64 for python3 and other win32 file for the python27
then pip install --user skfuzzy
I hope, It will work for you
Solutions:
As specified in many answers, download NumPy and SciPy whl from http://www.lfd.uci.edu/~gohlke/pythonlibs/ and install with
pip install <whl_location>
Building BLAS/LAPACK from source
Using Miniconda.
Refer:
ScikitLearn Installation
Easiest way to install BLAS and LAPACK for scipy?
do this, it solved for me
pip install -U scikit-learn
I got the same error trying to install scipy, having also installed Visual Studio C++, numpy, etc. My problem was that I'd just installed Python 3.9.
I removed version 3.9.0 and downgraded to version 3.8.6 and scipy installed without problems.
Using resources at http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy will solve the problem. However, you should be careful about versions compatibility. After trying for several times, finally I decided to uninstall python and then installed a fresh version of python along with numpy and then installed scipy and this resolved my problem.
install intel's distribution of python https://software.intel.com/en-us/intel-distribution-for-python
better of for distribution of python should contain them initially