【发布时间】：2023-04-10 08:58:02
【问题描述】：
我指的是这个特定的 Python 库：https://github.com/antoinecarme/pyaf
我的机器由 Anaconda3-4.4.0 和一个运行 Python 3.5 的单独环境组成，因为 pyAF 库需要 Python 3.5 才能工作。
我已经使用推荐的选项在我的笔记本电脑上安装了这个库 在上面的 Github 页面上，基于以下命令：
pip install scipy pandas sklearn matplotlib pydot dill pathos sqlalchemy
pip install --upgrade git+git://github.com/antoinecarme/pyaf.git
为了执行上述操作，我将我的 Github bash 上的环境更改为在 Python 3.5 上运行它，我观察到以下安装结果：
**Dinesh@DESKTOP-O5O752M MINGW64 ~**
$ source activate python35
(python35)
**Dinesh@DESKTOP-O5O752M MINGW64 ~**
$ pip install scipy pandas sklearn matplotlib pydot dill pathos sqlalchemy
Requirement already satisfied: scipy in c:\toolkits\anaconda3-4.4.0\envs\python3 5\lib\site-packages
Requirement already satisfied: pandas in c:\toolkits\anaconda3-4.4.0\envs\python 35\lib\site-packages
Requirement already satisfied: sklearn in c:\toolkits\anaconda3-4.4.0\envs\pytho n35\lib\site-packages
Requirement already satisfied: matplotlib in c:\toolkits\anaconda3-4.4.0\envs\py thon35\lib\site-packages
Requirement already satisfied: pydot in c:\toolkits\anaconda3-4.4.0\envs\python3 5\lib\site-packages
Requirement already satisfied: dill in c:\toolkits\anaconda3-4.4.0\envs\python35 \lib\site-packages
Requirement already satisfied: pathos in c:\toolkits\anaconda3-4.4.0\envs\python 35\lib\site-packages
Requirement already satisfied: sqlalchemy in c:\toolkits\anaconda3-4.4.0\envs\py thon35\lib\site-packages
Requirement already satisfied: numpy>=1.8.2 in c:\toolkits\anaconda3-4.4.0\envs\ python35\lib\site-packages (from scipy)
Requirement already satisfied: python-dateutil>=2 in c:\toolkits\anaconda3-4.4.0 \envs\python35\lib\site-packages (from pandas)
Requirement already satisfied: pytz>=2011k in c:\toolkits\anaconda3-4.4.0\envs\p ython35\lib\site-packages (from pandas)
Requirement already satisfied: scikit-learn in c:\toolkits\anaconda3-4.4.0\envs\ python35\lib\site-packages (from sklearn)
Requirement already satisfied: six>=1.10 in c:\toolkits\anaconda3-4.4.0\envs\pyt hon35\lib\site-packages (from matplotlib)
Requirement already satisfied: cycler>=0.10 in c:\toolkits\anaconda3-4.4.0\envs\ python35\lib\site-packages (from matplotlib)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=1.5.6 in c:\to olkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from matplotlib)
Requirement already satisfied: pyreadline>=1.7.1 in c:\toolkits\anaconda3-4.4.0\ envs\python35\lib\site-packages (from dill)
Requirement already satisfied: pox>=0.2.3 in c:\toolkits\anaconda3-4.4.0\envs\py thon35\lib\site-packages (from pathos)
Requirement already satisfied: ppft>=1.6.4.7 in c:\toolkits\anaconda3-4.4.0\envs \python35\lib\site-packages (from pathos)
Requirement already satisfied: multiprocess>=0.70.5 in c:\toolkits\anaconda3-4.4 .0\envs\python35\lib\site-packages (from pathos)
(python35)
**Dinesh@DESKTOP-O5O752M MINGW64 ~**
$ pip install --upgrade git+git://github.com/antoinecarme/pyaf.git
Collecting git+git://github.com/antoinecarme/pyaf.git
Cloning git://github.com/antoinecarme/pyaf.git to c:\users\dines\appdata\local\temp\pip-_upr_c25-build
Requirement already up-to-date: scipy in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Collecting pandas (from pyaf==1.0)
Using cached pandas-0.20.3-cp35-cp35m-win_amd64.whl
Requirement already up-to-date: sklearn in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Requirement already up-to-date: matplotlib in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Requirement already up-to-date: pydot in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Requirement already up-to-date: dill in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Requirement already up-to-date: pathos in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pyaf==1.0)
Collecting sqlalchemy (from pyaf==1.0)
Requirement already up-to-date: numpy>=1.8.2 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from scipy->pyaf==1.0)
Collecting python-dateutil>=2 (from pandas->pyaf==1.0)
Using cached python_dateutil-2.6.1-py2.py3-none-any.whl
Requirement already up-to-date: pytz>=2011k in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pandas->pyaf==1.0)
Collecting scikit-learn (from sklearn->pyaf==1.0)
Using cached scikit_learn-0.19.0-cp35-cp35m-win_amd64.whl
Requirement already up-to-date: six>=1.10 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from matplotlib->pyaf==1.0)
Requirement already up-to-date: cycler>=0.10 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from matplotlib->pyaf==1.0)
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=1.5.6 (from matplotlib->pyaf==1.0)
Using cached pyparsing-2.2.0-py2.py3-none-any.whl
Requirement already up-to-date: pyreadline>=1.7.1 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from dill->pyaf==1.0)
Requirement already up-to-date: ppft>=1.6.4.7 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pathos->pyaf==1.0)
Requirement already up-to-date: pox>=0.2.3 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pathos->pyaf==1.0)
Requirement already up-to-date: multiprocess>=0.70.5 in c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages (from pathos->pyaf==1.0)
Installing collected packages: python-dateutil, pandas, sqlalchemy, pyaf, scikit-learn, pyparsing
Found existing installation: python-dateutil 2.6.0
Uninstalling python-dateutil-2.6.0:
Successfully uninstalled python-dateutil-2.6.0
Found existing installation: pandas 0.20.1
Uninstalling pandas-0.20.1:
Successfully uninstalled pandas-0.20.1
Found existing installation: SQLAlchemy 1.1.9
Uninstalling SQLAlchemy-1.1.9:
Successfully uninstalled SQLAlchemy-1.1.9
Found existing installation: pyaf 1.0
Uninstalling pyaf-1.0:
Successfully uninstalled pyaf-1.0
Running setup.py install for pyaf: started
Running setup.py install for pyaf: finished with status 'done'
Found existing installation: scikit-learn 0.18.1
DEPRECATION: Uninstalling a distutils installed project (scikit-learn) has been deprecated and will be removed in a future version. This is due to the fact that uninstalling a distutils project will only partially uninstall the project.
Uninstalling scikit-learn-0.18.1:
Successfully uninstalled scikit-learn-0.18.1
Found existing installation: pyparsing 2.1.4
Uninstalling pyparsing-2.1.4:
Successfully uninstalled pyparsing-2.1.4
Successfully installed pandas-0.20.3 pyaf-1.0 pyparsing-2.2.0 python-dateutil-2.6.1 scikit-learn-0.19.0 sqlalchemy-1.1.13
Traceback (most recent call last):
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\Scripts\pip-script.py", line 5, in <module>
sys.exit(pip.main())
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\__init__.py", line 249, in main
return command.main(cmd_args)
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\basecommand.py", line 252, in main
pip_version_check(session)
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\utils\outdated.py", line 102, in pip_version_check
installed_version = get_installed_version("pip")
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\utils\__init__.py", line 838, in get_installed_version
working_set = pkg_resources.WorkingSet()
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 644, in __init__
self.add_entry(entry)
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 700, in add_entry
for dist in find_distributions(entry, True):
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 1949, in find_eggs_in_zip
if metadata.has_metadata('PKG-INFO'):
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 1463, in has_metadata
return self.egg_info and self._has(self._fn(self.egg_info, name))
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 1823, in _has
return zip_path in self.zipinfo or zip_path in self._index()
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 1703, in zipinfo
return self._zip_manifests.load(self.loader.archive)
File "C:\Toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pip\_vendor\pkg_resources\__init__.py", line 1643, in load
mtime = os.stat(path).st_mtime
FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\Toolkits\\anaconda3-4.4.0\\envs\\python35\\lib\\site-packages\\pyaf-1.0-py3.5.egg'
(python35)
使用第一种方法，我可以看到输出末尾有错误。因此，我在我的桌面上从 Github 下载了整个 pyAF 包，并尝试按如下方式安装该库：
**(python35) C:\Users\dines\Desktop>** cd pyaf-master
**(python35) C:\Users\dines\Desktop\pyaf-master>** python setup.py install
running install
running bdist_egg
running egg_info
writing pyaf.egg-info\PKG-INFO
writing dependency_links to pyaf.egg-info\dependency_links.txt
writing requirements to pyaf.egg-info\requires.txt
writing top-level names to pyaf.egg-info\top_level.txt
package init file 'pyaf\__init__.py' not found (or not a regular file)
package init file 'pyaf\TS\__init__.py' not found (or not a regular file)
package init file 'pyaf\CodeGen\__init__.py' not found (or not a regular file)
package init file 'pyaf\Bench\__init__.py' not found (or not a regular file)
reading manifest file 'pyaf.egg-info\SOURCES.txt'
writing manifest file 'pyaf.egg-info\SOURCES.txt'
installing library code to build\bdist.win-amd64\egg
running install_lib
running build_py
copying pyaf\ForecastEngine.py -> build\lib\pyaf
copying pyaf\HierarchicalForecastEngine.py -> build\lib\pyaf
copying pyaf\TS\Exogenous.py -> build\lib\pyaf\TS
copying pyaf\TS\Keras_Models.py -> build\lib\pyaf\TS
copying pyaf\TS\Options.py -> build\lib\pyaf\TS
copying pyaf\TS\Perf.py -> build\lib\pyaf\TS
copying pyaf\TS\Plots.py -> build\lib\pyaf\TS
copying pyaf\TS\PredictionIntervals.py -> build\lib\pyaf\TS
copying pyaf\TS\Scikit_Models.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalDecomposition.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalDecomposition_AR.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalDecomposition_Cycle.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalDecomposition_Quant.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalDecomposition_Trend.py -> build\lib\pyaf\TS
copying pyaf\TS\SignalHierarchy.py -> build\lib\pyaf\TS
copying pyaf\TS\Signal_Grouping.py -> build\lib\pyaf\TS
copying pyaf\TS\Signal_Transformation.py -> build\lib\pyaf\TS
copying pyaf\TS\Time.py -> build\lib\pyaf\TS
copying pyaf\TS\TimeSeriesModel.py -> build\lib\pyaf\TS
copying pyaf\TS\Utils.py -> build\lib\pyaf\TS
copying pyaf\CodeGen\TS_CodeGenerator.py -> build\lib\pyaf\CodeGen
copying pyaf\CodeGen\TS_CodeGen_Objects.py -> build\lib\pyaf\CodeGen
copying pyaf\Bench\Artificial.py -> build\lib\pyaf\Bench
copying pyaf\Bench\download_all_stock_prices.py -> build\lib\pyaf\Bench
copying pyaf\Bench\GenericBenchmark.py -> build\lib\pyaf\Bench
copying pyaf\Bench\MComp.py -> build\lib\pyaf\Bench
copying pyaf\Bench\NN3.py -> build\lib\pyaf\Bench
copying pyaf\Bench\stocks_symbol_list.py -> build\lib\pyaf\Bench
copying pyaf\Bench\TS_datasets.py -> build\lib\pyaf\Bench
copying pyaf\Bench\YahooStocks.py -> build\lib\pyaf\Bench
creating build\bdist.win-amd64\egg
creating build\bdist.win-amd64\egg\pyaf
creating build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\Artificial.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\download_all_stock_prices.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\GenericBenchmark.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\MComp.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\NN3.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\stocks_symbol_list.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\TS_datasets.py -> build\bdist.win-amd64\egg\pyaf\Bench
copying build\lib\pyaf\Bench\YahooStocks.py -> build\bdist.win-amd64\egg\pyaf\Bench
creating build\bdist.win-amd64\egg\pyaf\CodeGen
copying build\lib\pyaf\CodeGen\TS_CodeGenerator.py -> build\bdist.win-amd64\egg\pyaf\CodeGen
copying build\lib\pyaf\CodeGen\TS_CodeGen_Objects.py -> build\bdist.win-amd64\egg\pyaf\CodeGen
copying build\lib\pyaf\ForecastEngine.py -> build\bdist.win-amd64\egg\pyaf
copying build\lib\pyaf\HierarchicalForecastEngine.py -> build\bdist.win-amd64\egg\pyaf
creating build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Exogenous.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Keras_Models.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Options.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Perf.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Plots.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\PredictionIntervals.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Scikit_Models.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalDecomposition.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalDecomposition_AR.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalDecomposition_Cycle.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalDecomposition_Quant.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalDecomposition_Trend.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\SignalHierarchy.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Signal_Grouping.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Signal_Transformation.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Time.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\TimeSeriesModel.py -> build\bdist.win-amd64\egg\pyaf\TS
copying build\lib\pyaf\TS\Utils.py -> build\bdist.win-amd64\egg\pyaf\TS
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\Artificial.py to Artificial.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\download_all_stock_prices.py to download_all_stock_prices.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\GenericBenchmark.py to GenericBenchmark.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\MComp.py to MComp.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\NN3.py to NN3.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\stocks_symbol_list.py to stocks_symbol_list.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\TS_datasets.py to TS_datasets.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\Bench\YahooStocks.py to YahooStocks.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\CodeGen\TS_CodeGenerator.py to TS_CodeGenerator.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\CodeGen\TS_CodeGen_Objects.py to TS_CodeGen_Objects.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\ForecastEngine.py to ForecastEngine.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\HierarchicalForecastEngine.py to HierarchicalForecastEngine.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Exogenous.py to Exogenous.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Keras_Models.py to Keras_Models.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Options.py to Options.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Perf.py to Perf.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Plots.py to Plots.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\PredictionIntervals.py to PredictionIntervals.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Scikit_Models.py to Scikit_Models.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalDecomposition.py to SignalDecomposition.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalDecomposition_AR.py to SignalDecomposition_AR.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalDecomposition_Cycle.py to SignalDecomposition_Cycle.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalDecomposition_Quant.py to SignalDecomposition_Quant.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalDecomposition_Trend.py to SignalDecomposition_Trend.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\SignalHierarchy.py to SignalHierarchy.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Signal_Grouping.py to Signal_Grouping.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Signal_Transformation.py to Signal_Transformation.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Time.py to Time.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\TimeSeriesModel.py to TimeSeriesModel.cpython-35.pyc
byte-compiling build\bdist.win-amd64\egg\pyaf\TS\Utils.py to Utils.cpython-35.pyc
creating build\bdist.win-amd64\egg\EGG-INFO
copying pyaf.egg-info\PKG-INFO -> build\bdist.win-amd64\egg\EGG-INFO
copying pyaf.egg-info\SOURCES.txt -> build\bdist.win-amd64\egg\EGG-INFO
copying pyaf.egg-info\dependency_links.txt -> build\bdist.win-amd64\egg\EGG-INFO
copying pyaf.egg-info\requires.txt -> build\bdist.win-amd64\egg\EGG-INFO
copying pyaf.egg-info\top_level.txt -> build\bdist.win-amd64\egg\EGG-INFO
zip_safe flag not set; analyzing archive contents...
creating 'dist\pyaf-1.0-py3.5.egg' and adding 'build\bdist.win-amd64\egg' to it
removing 'build\bdist.win-amd64\egg' (and everything under it)
Processing pyaf-1.0-py3.5.egg
Copying pyaf-1.0-py3.5.egg to c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Adding pyaf 1.0 to easy-install.pth file
Installed c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages\pyaf-1.0-py3.5.egg
Processing dependencies for pyaf==1.0
Searching for SQLAlchemy==1.1.13
Best match: SQLAlchemy 1.1.13
Adding SQLAlchemy 1.1.13 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pathos==0.2.1
Best match: pathos 0.2.1
Adding pathos 0.2.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for dill==0.2.7.1
Best match: dill 0.2.7.1
Adding dill 0.2.7.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pydot==1.2.3
Best match: pydot 1.2.3
Adding pydot 1.2.3 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for matplotlib==2.0.2
Best match: matplotlib 2.0.2
Adding matplotlib 2.0.2 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for sklearn==0.0
Best match: sklearn 0.0
Adding sklearn 0.0 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pandas==0.20.3
Best match: pandas 0.20.3
Adding pandas 0.20.3 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for scipy==0.19.1
Best match: scipy 0.19.1
Adding scipy 0.19.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for ppft==1.6.4.7.1
Best match: ppft 1.6.4.7.1
Adding ppft 1.6.4.7.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pox==0.2.3
Best match: pox 0.2.3
Adding pox 0.2.3 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for multiprocess==0.70.5
Best match: multiprocess 0.70.5
Adding multiprocess 0.70.5 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pyreadline==2.1
Best match: pyreadline 2.1
Adding pyreadline 2.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pyparsing==2.2.0
Best match: pyparsing 2.2.0
Adding pyparsing 2.2.0 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for cycler==0.10.0
Best match: cycler 0.10.0
Adding cycler 0.10.0 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for pytz==2017.2
Best match: pytz 2017.2
Adding pytz 2017.2 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for python-dateutil==2.6.1
Best match: python-dateutil 2.6.1
Adding python-dateutil 2.6.1 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for six==1.10.0
Best match: six 1.10.0
Adding six 1.10.0 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for numpy==1.13.1+mkl
Best match: numpy 1.13.1+mkl
Adding numpy 1.13.1+mkl to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Searching for scikit-learn==0.19.0
Best match: scikit-learn 0.19.0
Adding scikit-learn 0.19.0 to easy-install.pth file
Using c:\toolkits\anaconda3-4.4.0\envs\python35\lib\site-packages
Finished processing dependencies for pyaf==1.0
(python35) C:\Users\dines\Desktop\pyaf-master>
我认为pyAF库已经安装成功了。现在，我尝试使用以下代码在 Jupyter 上导入它来运行：
import pandas as pd
csvfile_link = "https://raw.githubusercontent.com/antoinecarme/TimeSeriesData/master/ozone-la.csv"
ozone_dataframe = pd.read_csv(csvfile_link);
import datetime
ozone_dataframe['Month'] = ozone_dataframe['Month'].apply(lambda x : datetime.datetime.strptime(x, "%Y-%m"))
ozone_dataframe.head()
%matplotlib inline
ozone_dataframe.plot.line('Month', ['Ozone'], grid = True, figsize=(12, 8))
然后，当我导入以下库时：
import pyaf.ForecastEngine as autof
lEngine = autof.cForecastEngine()
lEngine.train(ozone_dataframe , 'Month' , 'Ozone', 12);
我收到错误提示：
The procedure entry point mkl_dnn_BatchNormalizationCreateBackward_v2_F32
could not be located in the dynamic link library C:\Toolkits\anaconda3-
4.4.0\envs\python35\lib\site-packages\numpy\core\mkl_intel_thread.dll
此错误仅在我连续单击确定按钮 3 次时才会消失。
谁能帮助我成功运行这个库需要做什么？我什至不知道这个问题的根本原因是什么。请帮忙。
执行 numpy as np 和 np.show_config()
(python35) C:\Users\dines>python
Python 3.5.3 |Anaconda custom (64-bit)| (default, May 15 2017, 10:43:23) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.show_config()
lapack_mkl_info:
include_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/include']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
library_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/lib/intel64_win']
libraries = ['mkl_lapack95_lp64', 'mkl_blas95_lp64', 'mkl_rt']
blas_mkl_info:
include_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/include']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
library_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/lib/intel64_win']
libraries = ['mkl_lapack95_lp64', 'mkl_blas95_lp64', 'mkl_rt']
blas_opt_info:
include_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/include']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
library_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/lib/intel64_win']
libraries = ['mkl_lapack95_lp64', 'mkl_blas95_lp64', 'mkl_rt']
lapack_opt_info:
include_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/include']
define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
library_dirs = ['C:/Program Files (x86)/IntelSWTools/compilers_and_libraries_2017/windows/mkl/lib/intel64_win']
libraries = ['mkl_lapack95_lp64', 'mkl_blas95_lp64', 'mkl_rt']
>>>
【问题讨论】：
-
如果你运行下面的
import numpy as np和np.show_config()，你会得到什么结果？ -
@neurite，请查看编辑后的帖子（底部）以获取结果。非常感谢您的帮助。
-
好的。感谢更新。我 Mac 上的线性代数库指向一个 conda 安装文件夹，
/Users/neurite/Applications/miniconda3/envs/temp/lib。只是一个快速的猜测，如果您在激活的 conda 环境中使用conda install（与pip install）安装 numpy 和 scipy 会有所不同吗？它看起来像一个不兼容的 MKL 库。另请查看此链接：docs.continuum.io/mkl-optimizations -
好的，谢谢您的回复，只是一个问题。在尝试安装 conda 之前，我应该卸载以前安装的 numpy 和 scipy 吗？顺便说一句，Anaconda 预装了 numpy 和 scipy - 我猜。有什么特殊的卸载方法吗？
-
在新的 conda 环境中尝试可能会容易得多。您需要使用
conda install numpy在任何 conda 环境中显式安装 numpy。不要认为它是预装的。我的一般建议是尝试通过conda install安装所需的任何软件包。仅对不在 conda 中的少数软件包使用pip install。让我知道这是否可以解决您的问题。如果是，我会将其扩展为答案。
标签： python python-3.5