Question

（*）问题：：我正在为我的Coursera类尝试在MacOS上安装GraphLab Create。尝试创建新的conda环境时，安装程序将失败。

（*）尝试的解决方案：

（1）错误消息中列出的conda当前版本的已安装软件包，其中包括： ./conda install conda = 4.0

（2）更新了conda本身，当我运行GrapLab安装程序时将其降级到4.0.8

（*）错误消息：

Did not find a broken "gl-env" environment.

Creating conda environment "gl-env".
Using Anaconda Cloud api site https://api.anaconda.org

Fetching package metadata: 

Solving package specifications: 

Error:  Dependencies missing in current osx-64 channels: 

  - anaconda 4.0|4.0.0* -> scipy 0.17.0 np110py27_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py27_1 -> numexpr 2.5* -> blas * mkl
  - anaconda 4.0|4.0.0* -> numpy 1.10.4 py27_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py35_1 -> numexpr 2.5* -> blas * openblas
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py27_1 -> numexpr 2.5* -> numpy 1.11* -> blas * openblas
  - anaconda 4.0|4.0.0* -> numexpr 2.5 np110py27_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py27_1 -> numexpr 2.5* -> blas * openblas
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py34_1 -> numexpr 2.5* -> numpy 1.11* -> blas * openblas
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py34_1 -> numexpr 2.5* -> numpy 1.11* -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py34_1 -> numexpr 2.5* -> blas * openblas
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py35_1 -> numexpr 2.5* -> numpy 1.11* -> blas * openblas
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py27_1 -> numexpr 2.5* -> numpy 1.11* -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py35_1 -> numexpr 2.5* -> numpy 1.11* -> blas * mkl
  - anaconda 4.0|4.0.0* -> numpy 1.10.4 py34_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py34_1 -> numexpr 2.5* -> blas * mkl
  - anaconda 4.0|4.0.0* -> numpy 1.10.4 py35_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> scipy 0.17.0 np110py34_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> numexpr 2.5 np110py35_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> scipy 0.17.0 np110py35_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> pytables 3.2.2 np110py35_1 -> numexpr 2.5* -> blas * mkl
  - anaconda 4.0|4.0.0* -> numexpr 2.5 np110py34_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> scikit-learn 0.17.1 np110py35_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> scikit-learn 0.17.1 np110py27_0 -> blas * mkl
  - anaconda 4.0|4.0.0* -> scikit-learn 0.17.1 np110py34_0 -> blas * mkl

您可以使用以下代码在anaconda.org上搜索该软件包：

anaconda search -t conda blas * mkl

（对于其他软件包也是如此）

（*）康达环境：

platform : osx-64

conda version : 4.0.8

conda-build version : 0+unknown

python version : 2.7.13.final.0

requests version : 2.9.1

channel URLs : https://repo.continuum.io/pkgs/free/osx-64/
            https://repo.continuum.io/pkgs/free/noarch/
            https://repo.continuum.io/pkgs/pro/osx-64/
            https://repo.continuum.io/pkgs/pro/noarch/
config file : None

是外来系统：False

（*）已安装的包装版本：

点8.1.1

点列表：

alabaster (0.7.7)
anaconda-client (1.4.0)
anaconda-navigator (1.1.0)
appnope (0.1.0)
appscript (1.0.1)
argcomplete (1.0.0)
astropy (1.1.2)
Babel (2.2.0)
backports-abc (0.4)
backports.ssl-match-hostname (3.4.0.2)
beautifulsoup4 (4.4.1)
bitarray (0.8.1)
blaze (0.9.1)
bokeh (0.11.1)
boto (2.39.0)
Bottleneck (1.0.0)
cdecimal (2.3)
cffi (1.5.2)
chest (0.2.3)
cloudpickle (0.1.1)
clyent (1.2.1)
colorama (0.3.7)
conda (4.0.8)
conda-build (0+unknown)
conda-env (2.4.5)
conda-manager (0.3.1)
configobj (5.0.6)
cryptography (1.3)
cycler (0.10.0)
Cython (0.23.4)
cytoolz (0.7.5)
dask (0.8.1)
datashape (0.5.1)
decorator (4.0.9)
dill (0.2.4)
docutils (0.12)
dynd (0.7.3.dev1)
enum34 (1.1.2)
et-xmlfile (1.0.1)
fastcache (1.0.2)
Flask (0.10.1)
Flask-Cors (2.1.2)
funcsigs (0.4)
futures (3.0.3)
gevent (1.1.0)
greenlet (0.4.9)
grin (1.2.1)
h5py (2.5.0)
HeapDict (1.0.0)
idna (2.0)
ipaddress (1.0.14)
ipykernel (4.3.1)
ipython (4.1.2)
ipython-genutils (0.1.0)
ipywidgets (4.1.1)
itsdangerous (0.24)
jdcal (1.2)
jedi (0.9.0)
Jinja2 (2.8)
jsonschema (2.4.0)
jupyter (1.0.0)
jupyter-client (4.2.2)
jupyter-console (4.1.1)
jupyter-core (4.1.0)
llvmlite (0.9.0)
locket (0.2.0)
lxml (3.6.0)
MarkupSafe (0.23)
matplotlib (1.5.1)
mistune (0.7.2)
mpmath (0.19)
multipledispatch (0.4.8)
nbconvert (4.1.0)
nbformat (4.0.1)
networkx (1.11)
nltk (3.2)
nose (1.3.7)
notebook (4.1.0)
numba (0.24.0)
numexpr (2.5)
numpy (1.10.4)
odo (0.4.2)
openpyxl (2.3.2)
pandas (0.18.0)
partd (0.3.2)
path.py (0.0.0)
patsy (0.4.0)
pep8 (1.7.0)
pexpect (4.0.1)
pickleshare (0.5)
Pillow (3.1.1)
pip (8.1.1)
ply (3.8)
psutil (4.1.0)
ptyprocess (0.5)
py (1.4.31)
pyasn1 (0.1.9)
PyAudio (0.2.7)
pycosat (0.6.1)
pycparser (2.14)
pycrypto (2.6.1)
pycurl (7.19.5.3)
pyflakes (1.1.0)
Pygments (2.1.1)
pyOpenSSL (0.15.1)
pyparsing (2.0.3)
pytest (2.8.5)
python-dateutil (2.5.1)
pytz (2016.2)
PyYAML (3.11)
pyzmq (15.2.0)
QtAwesome (0.3.2)
qtconsole (4.2.0)
QtPy (1.0)
redis (2.10.3)
requests (2.9.1)
rope (0.9.4)
scikit-image (0.12.3)
scikit-learn (0.17.1)
scipy (0.17.0)
setuptools (20.3)
simplegeneric (0.8.1)
singledispatch (3.4.0.3)
six (1.10.0)
snowballstemmer (1.2.1)
sockjs-tornado (1.0.1)
Sphinx (1.3.5)
sphinx-rtd-theme (0.1.9)
spyder (2.3.8)
SQLAlchemy (1.0.12)
statsmodels (0.6.1)
sympy (1.0)
tables (3.2.2)
terminado (0.5)
toolz (0.7.4)
tornado (4.3)
traitlets (4.2.1)
unicodecsv (0.14.1)
Werkzeug (0.11.4)
wheel (0.29.0)
xlrd (0.9.4)
XlsxWriter (0.8.4)
xlwings (0.7.0)
xlwt (1.0.0)

我还尝试过手动创建conda环境，但收到相同的错误，关于从此处进行最佳方法的任何想法吗？

Answer 1

我遇到了同样的问题，请尝试在conda环境中安装其中一些软件包。

运行：

conda install scikit-learn
conda install scipy

接受对程序包的更改，然后运行原始的conda create -n gl-env命令对我来说是有效的。

Answer 2

通常这种问题是由于版本不兼容所致，因此解决方案是在安装GraphLab之前更新conda：

conda update conda

Conda：当前osx-64通道中缺少依赖项

2 个答案: