创建python环境时出现UnsatisfiableError

时间：2019-03-30 07:20:31

标签： python windows dependencies conda

我正在关注python教程。当我尝试创建python env时，出现此错误。

  

UnsatisfiableError：发现以下规格   冲突：     -mkl == 2019.0 = 118     -scipy == 1.1.0 = py36h4f6bf74_1-> numpy [version ='> = 1.15.1，<2.0a0']-> mkl [version ='> = 2019.1，<2020.0a0']使用“ conda搜索--info ”   查看每个程序包的依赖性。

这是我的yml文件

name: python-cvcourse
channels:
  - michael_wild
  - defaults
dependencies:
  - absl-py=0.4.1=py36_0
  - appdirs=1.4.3=py36h28b3542_0
  - asn1crypto=0.24.0=py36_0
  - astor=0.7.1=py36_0
  - attrs=18.2.0=py36h28b3542_0
  - automat=0.7.0=py36_0
  - backcall=0.1.0=py36_0
  - blas=1.0=mkl
  - bleach=2.1.4=py36_0
  - ca-certificates=2018.03.07=0
  - certifi=2018.10.15=py36_0
  - cffi=1.11.5=py36h74b6da3_1
  - colorama=0.3.9=py36h029ae33_0
  - constantly=15.1.0=py36h28b3542_0
  - cryptography=2.3.1=py36h74b6da3_0
  - cudatoolkit=9.0=1
  - cudnn=7.1.4=cuda9.0_0
  - cycler=0.10.0=py36h009560c_0
  - decorator=4.3.0=py36_0
  - entrypoints=0.2.3=py36_2
  - freetype=2.9.1=ha9979f8_1
  - gast=0.2.0=py36_0
  - grpcio=1.12.1=py36h1a1b453_0
  - h5py=2.8.0=py36hf7173ca_2
  - hdf5=1.8.20=hac2f561_1
  - html5lib=1.0.1=py36_0
  - hyperlink=18.0.0=py36_0
  - icc_rt=2017.0.4=h97af966_0
  - icu=58.2=ha66f8fd_1
  - idna=2.7=py36_0
  - incremental=17.5.0=py36_0
  - intel-openmp=2019.0=118
  - ipykernel=4.9.0=py36_0
  - ipython=6.5.0=py36_0
  - ipython_genutils=0.2.0=py36h3c5d0ee_0
  - ipywidgets=7.4.1=py36_0
  - jedi=0.12.1=py36_0
  - jinja2=2.10=py36_0
  - jpeg=9b=hb83a4c4_2
  - jsonschema=2.6.0=py36h7636477_0
  - jupyter=1.0.0=py36_6
  - jupyter_client=5.2.3=py36_0
  - jupyter_console=5.2.0=py36_1
  - jupyter_core=4.4.0=py36_0
  - jupyterlab=0.34.9=py36_0
  - jupyterlab_launcher=0.13.1=py36_0
  - keras=2.2.2=0
  - keras-applications=1.0.4=py36_1
  - keras-base=2.2.2=py36_0
  - keras-preprocessing=1.0.2=py36_1
  - kiwisolver=1.0.1=py36h6538335_0
  - libopencv=3.4.2=h20b85fd_0
  - libpng=1.6.34=h79bbb47_0
  - libprotobuf=3.6.0=h1a1b453_0
  - libsodium=1.0.16=h9d3ae62_0
  - libtiff=4.0.9=h36446d0_2
  - m2w64-gcc-libgfortran=5.3.0=6
  - m2w64-gcc-libs=5.3.0=7
  - m2w64-gcc-libs-core=5.3.0=7
  - m2w64-gmp=6.1.0=2
  - m2w64-libwinpthread-git=5.0.0.4634.697f757=2
  - markdown=2.6.11=py36_0
  - markupsafe=1.0=py36hfa6e2cd_1
  - matplotlib=2.2.3=py36hd159220_0
  - mistune=0.8.3=py36hfa6e2cd_1
  - mkl=2019.0=118
  - mkl_fft=1.0.4=py36h1e22a9b_1
  - mkl_random=1.0.1=py36h77b88f5_1
  - msys2-conda-epoch=20160418=1
  - nbconvert=5.3.1=py36_0
  - nbformat=4.4.0=py36h3a5bc1b_0
  - notebook=5.6.0=py36_0
  - numpy=1.15.1=py36ha559c80_0
  - numpy-base=1.15.1=py36h8128ebf_0
  - olefile=0.46=py36_0
  - opencv=3.4.2=py36h40b0b35_0
  - openssl=1.0.2p=hfa6e2cd_0
  - pandoc=2.2.3.2=0
  - pandocfilters=1.4.2=py36_1
  - parso=0.3.1=py36_0
  - pickleshare=0.7.4=py36h9de030f_0
  - pillow=5.2.0=py36h08bbbbd_0
  - pip=10.0.1=py36_0
  - prometheus_client=0.3.1=py36h28b3542_0
  - prompt_toolkit=1.0.15=py36h60b8f86_0
  - protobuf=3.6.0=py36he025d50_0
  - py-opencv=3.4.2=py36hc319ecb_0
  - pyasn1=0.4.4=py36h28b3542_0
  - pyasn1-modules=0.2.2=py36_0
  - pycparser=2.18=py36_1
  - pygments=2.2.0=py36hb010967_0
  - pyopenssl=18.0.0=py36_0
  - pyparsing=2.2.0=py36_1
  - pyqt=5.9.2=py36ha878b3d_0
  - python=3.6.6=hea74fb7_0
  - python-dateutil=2.7.3=py36_0
  - pytz=2018.5=py36_0
  - pywin32=223=py36hfa6e2cd_1
  - pywinpty=0.5.4=py36_0
  - pyyaml=3.13=py36hfa6e2cd_0
  - pyzmq=17.1.2=py36hfa6e2cd_0
  - qt=5.9.6=vc14h62aca36_0
  - qtconsole=4.4.1=py36_0
  - scikit-learn=0.19.1=py36hae9bb9f_0
  - scipy=1.1.0=py36h4f6bf74_1
  - send2trash=1.5.0=py36_0
  - service_identity=17.0.0=py36h28b3542_0
  - setuptools=40.2.0=py36_0
  - simplegeneric=0.8.1=py36_2
  - sip=4.19.12=py36h6538335_0
  - six=1.11.0=py36_1
  - sqlite=3.24.0=h7602738_0
  - tensorflow=1.10.0
  - termcolor=1.1.0=py36_1
  - terminado=0.8.1=py36_1
  - testpath=0.3.1=py36h2698cfe_0
  - tk=8.6.8=hfa6e2cd_0
  - tornado=5.1=py36hfa6e2cd_0
  - traitlets=4.3.2=py36h096827d_0
  - twisted=18.7.0=py36hfa6e2cd_1
  - vc=14=h0510ff6_3
  - vs2015_runtime=14.0.25123=3
  - wcwidth=0.1.7=py36h3d5aa90_0
  - webencodings=0.5.1=py36_1
  - werkzeug=0.14.1=py36_0
  - wheel=0.31.1=py36_0
  - widgetsnbextension=3.4.1=py36_0
  - wincertstore=0.2=py36h7fe50ca_0
  - winpty=0.4.3=4
  - yaml=0.1.7=hc54c509_2
  - zeromq=4.2.5=he025d50_1
  - zlib=1.2.11=h8395fce_2
  - zope=1.0=py36_1
  - zope.interface=4.5.0=py36hfa6e2cd_0
  - opencv-contrib=3.3.1=py36_1
prefix: C:\Users\Marcial\Anaconda3\envs\cvcourse_windows

这是我的命令

conda env create -f cvcourse_windows.yml -n cv_python

我试图删除那些软件包，但其他软件包冲突却出现了，我还重新安装了conda

2 个答案:

答案 0 :(得分：0)

使用此

def detail(request, product_id):
    product = get_object_or_404(Product, pk=product_id)
    return render(request, 'product/detail.html', {'product': product})

针对OP的错误

  

无法满足的错误：发现以下规范存在冲突：-mkl == 2019.0 = 118-scipy == 1.1.0 = py36h4f6bf74_1-> numpy [version ='> = 1.15.1，<2.0a0']- > mkl [version ='> = 2019.1，<2020.0a0']使用“ conda search --info”查看每个软件包的依赖关系。

它说你有 mkl版本2019.0内部版本118 但您有一个scipy-1.1.0-py36h4f6bf74_1，需要numpy> = 1.15.1，需要mkl> = 2019.1

解决方案是将您的mkl升级到2019.1或更高版本，并早于2020.0a0

您可以使用name: python-cvcourse channels: - michael_wild - defaults dependencies: - absl-py=0.4.1=py36_0 - appdirs=1.4.3=py36h28b3542_0 - asn1crypto=0.24.0=py36_0 - astor=0.7.1=py36_0 - attrs=18.2.0=py36h28b3542_0 - automat=0.7.0=py36_0 - backcall=0.1.0=py36_0 - blas=1.0=mkl - bleach=2.1.4=py36_0 - ca-certificates=2018.03.07=0 - certifi=2018.10.15=py36_0 - cffi=1.11.5=py36h74b6da3_1 - colorama=0.3.9=py36h029ae33_0 - constantly=15.1.0=py36h28b3542_0 - cryptography=2.3.1=py36h74b6da3_0 - cudatoolkit=9.0=1 - cudnn=7.1.4=cuda9.0_0 - cycler=0.10.0=py36h009560c_0 - decorator=4.3.0=py36_0 - entrypoints=0.2.3=py36_2 - freetype=2.9.1=ha9979f8_1 - gast=0.2.0=py36_0 - grpcio=1.12.1=py36h1a1b453_0 - h5py=2.8.0=py36hf7173ca_2 - hdf5=1.8.20=hac2f561_1 - html5lib=1.0.1=py36_0 - hyperlink=18.0.0=py36_0 - icc_rt=2017.0.4=h97af966_0 - icu=58.2=ha66f8fd_1 - idna=2.7=py36_0 - incremental=17.5.0=py36_0 - intel-openmp=2019.0=118 - ipykernel=4.9.0=py36_0 - ipython=6.5.0=py36_0 - ipython_genutils=0.2.0=py36h3c5d0ee_0 - ipywidgets=7.4.1=py36_0 - jedi=0.12.1=py36_0 - jinja2=2.10=py36_0 - jpeg=9b=hb83a4c4_2 - jsonschema=2.6.0=py36h7636477_0 - jupyter=1.0.0=py36_6 - jupyter_client=5.2.3=py36_0 - jupyter_console=5.2.0=py36_1 - jupyter_core=4.4.0=py36_0 - jupyterlab=0.34.9=py36_0 - jupyterlab_launcher=0.13.1=py36_0 - keras=2.2.2=0 - keras-applications=1.0.4=py36_1 - keras-base=2.2.2=py36_0 - keras-preprocessing=1.0.2=py36_1 - kiwisolver=1.0.1=py36h6538335_0 - libopencv=3.4.2=h20b85fd_0 - libpng=1.6.34=h79bbb47_0 - libprotobuf=3.6.0=h1a1b453_0 - libsodium=1.0.16=h9d3ae62_0 - libtiff=4.0.9=h36446d0_2 - m2w64-gcc-libgfortran=5.3.0=6 - m2w64-gcc-libs=5.3.0=7 - m2w64-gcc-libs-core=5.3.0=7 - m2w64-gmp=6.1.0=2 - m2w64-libwinpthread-git=5.0.0.4634.697f757=2 - markdown=2.6.11=py36_0 - markupsafe=1.0=py36hfa6e2cd_1 - matplotlib=2.2.3=py36hd159220_0 - mistune=0.8.3=py36hfa6e2cd_1 - mkl=2018.0.3=1 - mkl_fft=1.0.4=py36h1e22a9b_1 - mkl_random=1.0.1=py36h77b88f5_1 - msys2-conda-epoch=20160418=1 - nbconvert=5.3.1=py36_0 - nbformat=4.4.0=py36h3a5bc1b_0 - notebook=5.6.0=py36_0 - numpy=1.15.4=py36ha559c80_0 - numpy-base=1.15.4=py36h8128ebf_0 - olefile=0.46=py36_0 - opencv=3.4.2=py36h40b0b35_0 - openssl=1.0.2p=hfa6e2cd_0 - pandoc=2.2.3.2=0 - pandocfilters=1.4.2=py36_1 - parso=0.3.1=py36_0 - pickleshare=0.7.4=py36h9de030f_0 - pillow=5.2.0=py36h08bbbbd_0 - pip=10.0.1=py36_0 - prometheus_client=0.3.1=py36h28b3542_0 - prompt_toolkit=1.0.15=py36h60b8f86_0 - protobuf=3.6.0=py36he025d50_0 - py-opencv=3.4.2=py36hc319ecb_0 - pyasn1=0.4.4=py36h28b3542_0 - pyasn1-modules=0.2.2=py36_0 - pycparser=2.18=py36_1 - pygments=2.2.0=py36hb010967_0 - pyopenssl=18.0.0=py36_0 - pyparsing=2.2.0=py36_1 - pyqt=5.9.2=py36ha878b3d_0 - python=3.6.6=hea74fb7_0 - python-dateutil=2.7.3=py36_0 - pytz=2018.5=py36_0 - pywin32=223=py36hfa6e2cd_1 - pywinpty=0.5.4=py36_0 - pyyaml=3.13=py36hfa6e2cd_0 - pyzmq=17.1.2=py36hfa6e2cd_0 - qt=5.9.6=vc14h62aca36_0 - qtconsole=4.4.1=py36_0 - scikit-learn=0.19.1=py36hae9bb9f_0 - scipy=1.1.0=py36h4f6bf74_1 - send2trash=1.5.0=py36_0 - service_identity=17.0.0=py36h28b3542_0 - setuptools=40.2.0=py36_0 - simplegeneric=0.8.1=py36_2 - sip=4.19.8=py36h6538335_0 - six=1.11.0=py36_1 - sqlite=3.24.0=h7602738_0 - tensorflow=1.10.0 - termcolor=1.1.0=py36_1 - terminado=0.8.1=py36_1 - testpath=0.3.1=py36h2698cfe_0 - tk=8.6.8=hfa6e2cd_0 - tornado=5.1=py36hfa6e2cd_0 - traitlets=4.3.2=py36h096827d_0 - twisted=18.7.0=py36hfa6e2cd_1 - vc=14=h0510ff6_3 - vs2015_runtime=14.0.25123=3 - wcwidth=0.1.7=py36h3d5aa90_0 - webencodings=0.5.1=py36_1 - werkzeug=0.14.1=py36_0 - wheel=0.31.1=py36_0 - widgetsnbextension=3.4.1=py36_0 - wincertstore=0.2=py36h7fe50ca_0 - winpty=0.4.3=4 - yaml=0.1.7=hc54c509_2 - zeromq=4.2.5=he025d50_1 - zlib=1.2.11=h8395fce_2 - zope=1.0=py36_1 - zope.interface=4.5.0=py36hfa6e2cd_0 - opencv-contrib=3.3.1=py36_1 prefix: C:\Users\Marcial\Anaconda3\envs\cvcourse_windows 查看2019年的所有版本

您还会遇到其他错误，请继续阅读解决方案

对我来说，我无法产生相同的问题。 每次尝试构建env时，都会遇到一个与numpy有关的问题，尽管其所有依赖项都是有效的，但一直显示错误，因此我将其更改为

conda seach mkl=2019

我也遇到其他错误

  

UnsatisfiableError：发现以下规范存在冲突：    -qtconsole == 4.4.1 = py36_0-> pyqt [version ='> = 5.9.2，<5.10.0a0']-> sip [version =   '> = 4.19.4，<= 4.19.8']    -sip == 4.19.12 = py36h6538335_0

几乎一样 qtconsole-4.4.1-py36_0需要嵌套的sip <4.19.8，而您的sip为4.19.12

相同的解决方案，将您的饮酒等级降为 - numpy=1.15.4=py36ha559c80_0 - numpy-base=1.15.4=py36h8128ebf_0

如果以相同的方式进行修复，您会遇到很多错误

最后，使用keras-base和mkl会出错，只是将mkl降级为sip=4.19.8=py36h6538335_0

该文件充满了缺少匹配项的依赖关系，您说它是python教程，但看起来像是故障排除测试？

答案 1 :(得分：0)

对于无法在同一教程中创建环境的人， 我在当前win-64频道中丢失了所有软件包的软件包

更新Anaconda后我能够安装软件包 使用命令：conda update conda

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