Conda：当前 osx-64 通道中缺少依赖项

Question

(*) 问题：我正在尝试在 MacOS 上为我的 coursera 课程安装 GraphLab Create。尝试创建新的 conda 环境时安装程序失败。

(*) 尝试的解决方案：

(1) 在当前版本的 conda 的错误消息中列出的已安装包：./conda install conda=4.0

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

（*） 错误信息：

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

你可以在 anaconda.org 上搜索这个包

anaconda search -t conda blas * mkl

（其他包也类似）

(*) 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

是外国系统：假

(*) 安装的软件包版本：

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)

我也尝试手动创建 conda 环境，但收到相同的错误，从这里开始的最佳方式有什么想法吗？

Answer 1

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

conda update conda