![]() Some further investigation (only based on numpy and python 3.6.2 leads toĬ:\Anaconda3\envs\tensorflow-cpu\Lib\site-packages\numpy\core\multiarray.cp36-win_amd64.pydĬ:\Windows\System32\mkl_intel_thread.dll (v2009)Ĭ:\Windows\System32\libiomp5md.dll (v2009) This worked fine with an old install of Anaconda3-4.3.1-Windows-x86_64.exe for a couple of weeks,Ī new install after everything was broken based on update/upgrade procedures gives the same errors. Original error was: DLL load failed: The specified procedure could not be found. ImportError: DLL load failed: The specified procedure could not be found.ĭuring handling of the above exception, another exception occurred:įile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy_ init_.py", line 142, inįile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy\add_newdocs.py", line 13, inįile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy\lib_ init_.py", line 8, inįile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy\lib\type_check.py", line 11, inįile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy\core_ init.py", line 26, in Type "help", "copyright", "credits" or "license" for more information.įile "C:\Anaconda3\envs\tensorflow-cpu\lib\site-packages\numpy\core_ init_.py", line 16, in Otherwise reinstall numpy.Īnother error just for conda Numpy WIN 64-bit v1.13.1. ![]() If you're working with a numpy git repo, try git clean -xdf (removes allįiles not under version control). Likely you are trying to import a failed build of numpy. ![]() Importing the multiarray numpy extension module failed. (worked for couple of month before, really liked it). When we use pip to install a package, it will be installed in “dist-packages” folder of specific python version.Numpy WIN 64-bit v1.13.1 just worked fine in Anaconda navigator and Spyder, but since July 2017Īnd some weird updates, NUMPY under Windows and Python 3.6.1 does not work anymore. Around 113000 python packages can be accessed through PyPI. It is a python package manager which handles only python packages mainly from a third-party software repository which is called PyPI (python package Index). I will go through each of the tools in more details and will try to present a reasonable comparison among these tools and its relation withe each other. Anaconda and Miniconda are two examples of software distribution that are specially useful for beginners. Software Distribution: It is a pre-build and pre-configured collection of packages that can be easily used on a system. Pip and conda are two examples of package manager. Package Manager: It is a tool that automates the process of installing, updating and removing packages on the corresponding system. Let’s understand two main concepts before focusing on pip, conda and anaconda: Afterward I will focus on Virtual environment that will enable us to have a full control over our system (environment) which is useful specially when we do not have root access on the system beside many other advantages. In this document, first I will go through pip, conda and anaconda and will compare them in more details. Pip, Conda and Anaconda are tools that is used extensively that together with Isolated environment make the life much easier. Setup a proper environment with specific python version and required packages is one of the main challenges that people who are working in Big Data faced daily.
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