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Windows Scipy安装：未找到Lapack / Blas资源

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问题：Windows Scipy安装：未找到Lapack / Blas资源
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我的python版本是2.7.10，64位Windows 7。
My python’s version is 2.7.10, 64-bits Windows 7.
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问题：Windows Scipy安装：未找到Lapack / Blas资源

我正在尝试在64位Windows 7桌面上安装python和一系列软件包。我已经安装了Python 3.4，已经安装了Microsoft Visual Studio C ++，并且已经成功安装了numpy，pandas和其他一些软件。尝试安装scipy时出现以下错误；

numpy.distutils.system_info.NotFoundError: no lapack/blas resources found

我正在离线使用pip install，我正在使用的安装命令是；

pip install --no-index --find-links="S:\python\scipy 0.15.0" scipy

我已经阅读了有关要求编译器的信息，如果我正确理解的话，则是VS C ++编译器。我正在使用2010版本，就像在使用Python 3.4。这对于其他软件包也有效。

我必须使用窗口二进制文件还是有办法让pip安装正常工作？

非常感谢您的帮助

点击查看英文原文

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

回答 0

此处介绍了在Windows 7 64位系统上不安装SciPy的BLAS / LAPACK库的解决方案：

http://www.scipy.org/scipylib/building/windows.html

安装Anaconda会容易得多，但是如果不付费就无法获得Intel MKL或GPU的支持（它们在MKL Optimizations和Anaconda的加速附件中-我不确定他们是否同时使用PLASMA和MAGMA） 。通过MKL优化，numpy在大型矩阵计算上的性能优于IDL十倍。MATLAB内部使用Intel MKL库并支持GPU计算，因此如果他们是学生，则不妨将其作为价格使用（MATLAB为50美元，并行计算工具箱为10美元）。如果您获得了Intel Parallel Studio的免费试用版，它将附带MKL库以及C ++和FORTRAN编译器，如果您想在Windows上从MKL或ATLAS安装BLAS和LAPACK，它们将派上用场：

http://icl.cs.utk.edu/lapack-for-windows/lapack/

Parallel Studio还带有Intel MPI库，可用于群集计算应用程序及其最新的Xeon处理器。尽管使用MKL优化来构建BLAS和LAPACK的过程并非易事，但针对Python和R这样做的好处却是巨大的，如以下英特尔网络研讨会所述：

https://software.intel.com/zh-CN/articles/powered-by-mkl-accelerating-numpy-and-scipy-performance-with-intel-mkl-python

Anaconda和Enthought通过使此功能和其他一些事情更易于部署而建立了业务。但是，愿意做一点工作（一点学习）的人可以免费使用它。

对于那些谁使用R，你现在可以得到优化MKL BLAS和LAPACK免费使用R打开从革命Analytics（分析）。

编辑：Anaconda Python现在附带MKL优化，以及通过Intel Python发行版对许多其他Intel库优化的支持。但是，Accelerate库（以前称为NumbaPro）中对Anaconda的GPU支持仍然超过1万美元！最好的替代方法可能是PyCUDA和scikit-cuda，因为铜头鱼（基本上是Anaconda Accelerate的免费版本）不幸在五年前停止开发。如果有人想在他们离开的地方接机，可以在这里找到。

点击查看英文原文

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.

回答 1

以下链接应解决Windows和SciPy的所有问题；只需选择适当的下载即可。我能够毫无问题地安装该软件包。我尝试过的所有其他解决方案都让我头疼。

来源：http : //www.lfd.uci.edu/~gohlke/pythonlibs/#scipy

命令： 

 pip install [Local File Location]\[Your specific file such as scipy-0.16.0-cp27-none-win_amd64.whl]

假定您已经安装了以下软件：

  1. 使用Python工具安装Visual Studio 2015/2013
    （在2015年安装时已集成到安装选项中）

  2. 安装用于Python的Visual Studio C ++编译器
    来源：http : //www.microsoft.com/zh-cn/download/details.aspx?id=44266
    文件名：VCForPython27.msi

  3. 选择安装的Python版本
    来源：python.org
    文件名（例如）：python-2.7.10.amd64.msi

点击查看英文原文

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:

  1. Install Visual Studio 2015/2013 with Python Tools
    (Is integrated into the setup options on install of 2015)

  2. Install Visual Studio C++ Compiler for Python
    Source: http://www.microsoft.com/en-us/download/details.aspx?id=44266
    File Name: VCForPython27.msi

  3. Install Python Version of choice
    Source: python.org
    File Name (e.g.): python-2.7.10.amd64.msi

回答 2

我的python版本是2.7.10，64位Windows 7。

  1. scipy-0.18.0-cp27-cp27m-win_amd64.whl从下载http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy
  2. 打开 cmd
  3. 确保scipy-0.18.0-cp27-cp27m-win_amd64.whl位于cmd当前目录中，然后键入pip install scipy-0.18.0-cp27-cp27m-win_amd64.whl。

将成功安装。

点击查看英文原文

My python’s version is 2.7.10, 64-bits Windows 7.

  1. Download scipy-0.18.0-cp27-cp27m-win_amd64.whl from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy
  2. Open cmd
  3. 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.

回答 3

抱歉necro，但这是第一个Google搜索结果。这是为我工作的解决方案：

  1. 从http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy下载numpy + mkl滚轮 。使用与python版本相同的版本（使用python -V检查）。例如。如果您的python是3.5.2，请下载显示cp35的转盘

  2. 打开命令提示符，然后导航到下载滚轮的文件夹。运行命令：pip install [wheel文件名]

  3. 从以下网址下载SciPy滚轮：http：//www.lfd.uci.edu/~gohlke/pythonlibs/#scipy （类似于上述步骤）。

  4. 如上所述，pip install [wheel的文件名]

点击查看英文原文

Sorry to necro, but this is the first google search result. This is the solution that worked for me:

  1. 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

  2. Open command prompt and navigate to the folder where you downloaded the wheel. Run the command: pip install [file name of wheel]

  3. Download the SciPy wheel from: http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy (similar to the step above).

  4. As above, pip install [file name of wheel]

回答 4

这是我一切正常的顺序。第二点是最重要的。科学需要Numpy+MKL，而不仅仅是香草Numpy。

  1. 安装python 3.5
  2. pip install "file path"（从此处http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy下载Numpy + MKL轮子）
  3. pip install scipy
点击查看英文原文

This was the order I got everything working. The second point is the most important one. Scipy needs Numpy+MKL, not just vanilla Numpy.

  1. Install python 3.5
  2. pip install "file path" (download Numpy+MKL wheel from here http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy)
  3. pip install scipy

回答 5

如果您使用的是Windows和Visual Studio 2015

输入以下命令

  • “康达安装numpy的”
  • “康达安装熊猫”
  • “ conda安装scipy”
点击查看英文原文

If you are working with Windows and Visual Studio 2015

Enter the following commands

  • “conda install numpy”
  • “conda install pandas”
  • “conda install scipy”

回答 6

我的5美分；您可以从https://github.com/scipy/scipy/releases安装整个（预编译的）SciPy

祝好运！

点击查看英文原文

My 5 cents; You can just install the entire (pre-compiled) SciPy from https://github.com/scipy/scipy/releases

Good Luck!

回答 7

在Windows中简单快速地安装Scipy

  1. 从http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy下载适用于您的Python版本的正确Scipy软件包（例如，适用于python 3.5和Windows x64的正确软件包scipy-0.19.1-cp35-cp35m-win_amd64.whl）。
  2. cmd在包含下载的Scipy软件包的目录中打开。
  3. 键入pip install <<your-scipy-package-name>>（例如pip install scipy-0.19.1-cp35-cp35m-win_amd64.whl）。
点击查看英文原文

Simple and Fast Installation of Scipy in Windows

  1. 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).
  2. Open cmd inside the directory containing the downloaded Scipy package.
  3. Type pip install <<your-scipy-package-name>> (e.g. pip install scipy-0.19.1-cp35-cp35m-win_amd64.whl).

回答 8

对于 python27 1，安装numpy + mkl（下载链接：http : //www.lfd.uci.edu/~gohlke/pythonlibs/）2，安装scipy（在同一站点）OK！

点击查看英文原文

For python27 1、Install numpy + mkl（download link:http://www.lfd.uci.edu/~gohlke/pythonlibs/） 2、install scipy (the same site) OK!

回答 9

英特尔现在免费提供用于Linux / Windows / OS X的Python发行版，称为“ 英特尔Python发行版 ”。

它是一个完整的Python发行版（例如，软件包中包含python.exe），其中包括一些根据Intel的MKL（数学内核库）编译的预安装模块，因此针对更快的性能进行了优化。

发行版包括模块NumPy，SciPy，scikit-learn，pandas，matplotlib，Numba，tbb，pyDAAL，Jupyter等。缺点是升级到最新版本的Python有点晚。例如，从今天（2017年5月1日）开始，发行版提供CPython 3.5，而3.6版本已经发布。但是，如果您不需要这些新功能，则应该很好。

点击查看英文原文

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.

回答 10

安装scikit-fuzzy时我也遇到了同样的错误。我解决了如下错误：

  1. 安装Whl文件Numpy
  2. 安装Scipy，再次是whl文件

根据python版本选择文件，例如python3的amd64和python27的其他win32文件

  1. 然后 pip install --user skfuzzy

我希望，它将为您工作

点击查看英文原文

I was also getting same error while installing scikit-fuzzy. I resolved error as follows:

  1. Install Numpy, a whl file
  2. Install Scipy, again a whl file

choose file according to python version like amd64 for python3 and other win32 file for the python27

  1. then pip install --user skfuzzy

I hope, It will work for you

回答 11

解决方案：

  1. 如许多答案中所指定，请从http://www.lfd.uci.edu/~gohlke/pythonlibs/下载NumPy和SciPy whl 并安装

    pip install <whl_location>

  2. 从源代码构建BLAS / LAPACK

  3. 使用Miniconda。

参考：

  1. ScikitLearn安装
  2. 为scipy安装BLAS和LAPACK的最简单方法？
点击查看英文原文

Solutions:

  1. 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>

  2. Building BLAS/LAPACK from source

  3. Using Miniconda.

Refer:

  1. ScikitLearn Installation
  2. Easiest way to install BLAS and LAPACK for scipy?

回答 12

使用http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy上的资源 可以解决此问题。但是，您应该注意版本兼容性。经过几次尝试，最终我决定卸载python，然后与numpy一起安装了新版本的python，然后安装了scipy，这解决了我的问题。

点击查看英文原文

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.

回答 13

安装python的intel发行版https://software.intel.com/zh-cn/intel-distribution-for-python

更好的python发行版应首先包含它们

点击查看英文原文

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

回答 14

这样做，它为我解决了 pip install -U scikit-learn

点击查看英文原文

do this, it solved for me pip install -U scikit-learn