I am trying to use DeepAR for forecasting time series. I install gluonts, but when i import the module i get the error with absence mxnet.
Use python version 3.9.7, numpy version 1.20.3
As I understand it, the error is related to the version? mxnet install only with numpy 1.16.6?
Error wit install mxnet:
Collecting mxnet
Using cached mxnet-1.7.0.post2-py2.py3-none-win_amd64.whl (33.1 MB)
Collecting graphviz<0.9.0,>=0.8.1
Using cached graphviz-0.8.4-py2.py3-none-any.whl (16 kB)
Requirement already satisfied: requests<2.19.0,>=2.18.4 in c:\users\tred1\anaconda3\lib\site-packages (from mxnet) (2.18.4)
Collecting numpy<1.17.0,>=1.8.2
Using cached numpy-1.16.6.zip (5.1 MB)
Requirement already satisfied: certifi>=2017.4.17 in c:\users\tred1\anaconda3\lib\site-packages (from requests<2.19.0,>=2.18.4->mxnet) (2021.10.8)
Requirement already satisfied: urllib3<1.23,>=1.21.1 in c:\users\tred1\anaconda3\lib\site-packages (from requests<2.19.0,>=2.18.4->mxnet) (1.22)
Requirement already satisfied: idna<2.7,>=2.5 in c:\users\tred1\anaconda3\lib\site-packages (from requests<2.19.0,>=2.18.4->mxnet) (2.6)
Requirement already satisfied: chardet<3.1.0,>=3.0.2 in c:\users\tred1\anaconda3\lib\site-packages (from requests<2.19.0,>=2.18.4->mxnet) (3.0.4)
Building wheels for collected packages: numpy
Building wheel for numpy (setup.py): started
Building wheel for numpy (setup.py): finished with status 'error'
Running setup.py clean for numpy
Failed to build numpy
Installing collected packages: numpy, graphviz, mxnet
Attempting uninstall: numpy
Found existing installation: numpy 1.20.3
Uninstalling numpy-1.20.3:
Successfully uninstalled numpy-1.20.3
Running setup.py install for numpy: started
Running setup.py install for numpy: finished with status 'error'
Rolling back uninstall of numpy
Moving to c:\users\tred1\anaconda3\lib\site-packages\numpy-1.20.3.dist-info\
from C:\Users\tred1\anaconda3\Lib\site-packages\~umpy-1.20.3.dist-info
Moving to c:\users\tred1\anaconda3\lib\site-packages\numpy\
from C:\Users\tred1\anaconda3\Lib\site-packages\~umpy
Moving to c:\users\tred1\anaconda3\scripts\f2py-script.py
from C:\Users\tred1\AppData\Local\Temp\pip-uninstall-5bceooxs\f2py-script.py
Moving to c:\users\tred1\anaconda3\scripts\f2py.exe
from C:\Users\tred1\AppData\Local\Temp\pip-uninstall-5bceooxs\f2py.exe
Note: you may need to restart the kernel to use updated packages
I have Cygwin installed on my PC and I am trying to install pandas via the pip installer.
Below are some of the messages I get when installing pandas.
$ pip install pandas
Collecting pandas
Using cached https://files.pythonhosted.org/packages/07/cf/1b6917426a9a16fd79d56385d0d907f344188558337d6b81196792f857e9/pandas-0.25.1.tar.gz
Requirement already satisfied: python-dateutil>=2.6.1 in /usr/lib/python3.7/site-packages (from pandas) (2.8.0)
Requirement already satisfied: pytz>=2017.2 in /usr/lib/python3.7/site-packages (from pandas) (2019.2)
Requirement already satisfied: numpy>=1.13.3 in /usr/lib/python3.7/site-packages (from pandas) (1.16.2)
Requirement already satisfied: six>=1.5 in /usr/lib/python3.7/site-packages (from python-dateutil>=2.6.1->pandas) (1.12.0)
Building wheels for collected packages: pandas
Building wheel for pandas (setup.py): started
Building wheel for pandas (setup.py): finished with status 'error'
Running setup.py clean for pandas
Failed to build pandas
Installing collected packages: pandas
Running setup.py install for pandas: started
If anyone can suggest what I should do to get around this error, it would be greatly appreciated.
I am trying to install the "MLBox" python package on anaconda (Python 3.6).
This package needs "xgboost" so I download the wheel file from this link and I did a pip install wheel-file. I had no issue with it. But when I use the pip install for installing "mlbox" I have this error:
Collecting pandas==0.20.3 (from mlbox)
Using cached pandas-0.20.3-cp36-cp36m-win_amd64.whl
Requirement already satisfied: joblib==0.11 in c:\users\amira ayadi\anaconda3\lib\site-packages (from mlbox)
Collecting scikit-learn==0.19.0 (from mlbox)
Using cached scikit_learn-0.19.0-cp36-cp36m-win_amd64.whl
Requirement already satisfied: Theano==0.9.0 in c:\users\amira ayadi\anaconda3\lib\site-packages (from mlbox)
Collecting xgboost==0.6a2 (from mlbox)
Using cached xgboost-0.6a2.tar.gz
No files/directories in C:\Users\AMIRAA~1\AppData\Local\Temp\pip-build-6ytmh20a\xgboost\pip-egg-info (from PKG-INFO)
I also tired to install xgboost with anaconda solution (https://anaconda.org/anaconda/py-xgboost)
But same error.
Do you have some ideas?
I am on Windows 10
I am part of a small team that is trying to install Python's 'fancyimpute' package. Three of us have different Windows machines. One of us has Mac.
fancyimpute's page says: 'Operating System :: OS Independent'.
My teammate has no problems installing it on his Mac: pip install fancyimpute works as it should.
When we, Windows users, try to do the same, we are getting this error:
"error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools"
One we've installed "Visual C++ 2015 Build Tools", we still can't install fancyimpute. The error we are getting is as following:
'NAN'
ecos/src/ecos.c(1093): warning C4013: '_set_output_format' undefined; assuming extern returning int
ecos/src/ecos.c(1093): error C2065: '_TWO_DIGIT_EXPONENT': undeclared identifier
error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio 14.0\\VC\\BIN\\x86_amd64\\cl.exe' failed with exit status 2
Failed building wheel for ecos
Is it possible that it's a hopeless case for Windows machine owners? Or is there a solution?
I have just installed fancyimpute on windows 10 machine and it was successful. Can you please try running pip command from command prompt in case if you're doing it from pycharm console.
C:\Users\USER>pip install fancyimpute
Collecting fancyimpute
Downloading fancyimpute-0.2.0.tar.gz
Requirement already satisfied: six in c:\python27\lib\site-packages (from fancyimpute)
Collecting knnimpute (from fancyimpute)
Downloading knnimpute-0.1.0.tar.gz
Requirement already satisfied: numpy>=1.10 in c:\python27\lib\site-packages (from fancyimpute)
Requirement already satisfied: scipy in c:\python27\lib\site-packages (from fancyimpute)
Collecting cvxpy (from fancyimpute)
Downloading cvxpy-0.4.11-py2-none-any.whl (379kB)
100% |################################| 389kB 439kB/s
Requirement already satisfied: scikit-learn>=0.17.1 in c:\python27\lib\site-packages (from fancyimpute)
Collecting downhill (from fancyimpute)
Downloading downhill-0.4.0-py2.py3-none-any.whl
Collecting climate (from fancyimpute)
Downloading climate-0.4.6.tar.gz
Collecting theano (from fancyimpute)
Downloading Theano-0.9.0.tar.gz (3.1MB)
100% |################################| 3.1MB 65kB/s
Collecting ecos>=2 (from cvxpy->fancyimpute)
Downloading ecos-2.0.4-cp27-none-win32.whl (44kB)
100% |################################| 51kB 96kB/s
Collecting CVXcanon>=0.0.22 (from cvxpy->fancyimpute)
Downloading CVXcanon-0.1.1.tar.gz (694kB)
100% |################################| 696kB 105kB/s
Requirement already satisfied: toolz in c:\python27\lib\site-packages (from cvxpy->fancyimpute)
Collecting fastcache (from cvxpy->fancyimpute)
Downloading fastcache-1.0.2.tar.gz
Collecting multiprocess (from cvxpy->fancyimpute)
Downloading multiprocess-0.70.5.zip (1.5MB)
100% |################################| 1.5MB 73kB/s
Collecting scs>=1.1.3 (from cvxpy->fancyimpute)
Downloading scs-1.2.7.tar.gz (280kB)
100% |################################| 286kB 107kB/s
Requirement already satisfied: click in c:\python27\lib\site-packages (from downhill->fancyimpute)
Collecting plac (from climate->fancyimpute)
Downloading plac-0.9.6-py2.py3-none-any.whl
Collecting dill>=0.2.6 (from multiprocess->cvxpy->fancyimpute)
Downloading dill-0.2.7.1.tar.gz (64kB)
100% |################################| 71kB 109kB/s
Collecting pyreadline>=1.7.1 (from dill>=0.2.6->multiprocess->cvxpy->fancyimpute)
Downloading pyreadline-2.1.zip (109kB)
100% |################################| 112kB 127kB/s
Building wheels for collected packages: fancyimpute, knnimpute, climate, theano, CVXcanon, fastcache, multiprocess, scs, dill, pyreadline
Running setup.py bdist_wheel for fancyimpute ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\46\9d\78\a49d65bb66557f705de636d1a21f9310993a4342670add3f9e
Running setup.py bdist_wheel for knnimpute ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\66\a0\1c\ed41cf540d0bd6d4ae368e9554b77753da154e7d8974c4435f
Running setup.py bdist_wheel for climate ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\90\1f\17\51ca46dd7c3b0be854c63468b50b3d24c443d149244cc4bb19
Running setup.py bdist_wheel for theano ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\d5\5b\93\433299b86e3e9b25f0f600e4e4ebf18e38eb7534ea518eba13
Running setup.py bdist_wheel for CVXcanon ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\1b\f6\dd\14f66c64621bddd6b92a3cfc995fa2a21b134fcf4122402b30
Running setup.py bdist_wheel for fastcache ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\1b\ce\51\0614c8aaab5c0893ed5a2098a15673a4949cba59cfa04ceace
Running setup.py bdist_wheel for multiprocess ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\28\ef\9f\5cc70b5d92fc4641b68dc23b3583f2b6ec1d153cb71985aeaf
Running setup.py bdist_wheel for scs ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\de\bb\5c\5efaf95dbe8b2a87650a9a1061aeefcd5b16353b98afbac789
Running setup.py bdist_wheel for dill ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\e5\88\fe\7e290ce5bb39d531eb9bee5cf254ba1c3e3c7ba3339ce67bee
Running setup.py bdist_wheel for pyreadline ... done
Stored in directory: C:\Users\USER\AppData\Local\pip\Cache\wheels\9a\c7\45\fd424eb3d7875d7a61221accd593e17c7953ed5ece5ee60be9
Successfully built fancyimpute knnimpute climate theano CVXcanon fastcache multiprocess scs dill pyreadline
Installing collected packages: knnimpute, ecos, CVXcanon, fastcache, pyreadline, dill, multiprocess, scs, cvxpy, theano, downhill, plac, climate, fancyimpute
Successfully installed CVXcanon-0.1.1 climate-0.4.6 cvxpy-0.4.11 dill-0.2.7.1 downhill-0.4.0 ecos-2.0.4 fancyimpute-0.2.0 fastcache-1.0.2 knnimpute-0.1.0 multiprocess-0.70.5 plac-0.9.6 pyreadline-2.1 scs-1.2.7 theano-0.9.0
I found the solution here: Fancyimpute pip install error
Solved the problem by manually downloading the appropriate .whl file (Python version and Windows architecture): Windows binaries
Navigated to the downloaded file (in terminal) and ran pip install filename.whl.
Pip doesn't seem to build dependencies from source on my Ubuntu server, while it always does that on my OS X machine. For example, when I try to install package qiime in a conda or virtualenv (I tried both) environment it takes seconds to install a hell lot of things that take loads of time to compile on my Mac.
(qiime)user#server:~$ pip install qiime
Collecting qiime
Collecting qiime-default-reference<0.2.0,>=0.1.2 (from qiime)
Collecting burrito<1.0.0,>=0.9.1 (from qiime)
Collecting pandas>=0.13.1 (from qiime)
Collecting natsort<4.0.0 (from qiime)
Using cached natsort-3.5.6-py2.py3-none-any.whl
Collecting matplotlib!=1.4.2,>=1.1.0 (from qiime)
Collecting numpy>=1.9.0 (from qiime)
Collecting gdata (from qiime)
Collecting scikit-bio<0.3.0,>=0.2.3 (from qiime)
Collecting pynast==1.2.2 (from qiime)
Collecting biom-format<2.2.0,>=2.1.4 (from qiime)
Collecting burrito-fillings<0.2.0,>=0.1.1 (from qiime)
Collecting qcli<0.2.0,>=0.1.1 (from qiime)
Collecting scipy>=0.14.0 (from qiime)
Collecting cogent==1.5.3 (from qiime)
Collecting emperor<1.0.0,>=0.9.51 (from qiime)
Collecting six (from qiime-default-reference<0.2.0,>=0.1.2->qiime)
Using cached six-1.10.0-py2.py3-none-any.whl
Collecting future (from burrito<1.0.0,>=0.9.1->qiime)
Collecting pytz>=2011k (from pandas>=0.13.1->qiime)
Using cached pytz-2015.7-py2.py3-none-any.whl
Collecting python-dateutil (from pandas>=0.13.1->qiime)
Using cached python_dateutil-2.4.2-py2.py3-none-any.whl
Collecting cycler (from matplotlib!=1.4.2,>=1.1.0->qiime)
Using cached cycler-0.9.0-py2.py3-none-any.whl
Collecting pyparsing!=2.0.0,!=2.0.4,>=1.5.6 (from matplotlib!=1.4.2,>=1.1.0->qiime)
Using cached pyparsing-2.0.6-py2.py3-none-any.whl
Collecting IPython (from scikit-bio<0.3.0,>=0.2.3->qiime)
Using cached ipython-4.0.0-py2-none-any.whl
Collecting click (from biom-format<2.2.0,>=2.1.4->qiime)
Using cached click-5.1-py2.py3-none-any.whl
Collecting pyqi (from biom-format<2.2.0,>=2.1.4->qiime)
Collecting decorator (from IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Using cached decorator-4.0.4-py2.py3-none-any.whl
Collecting simplegeneric>0.8 (from IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Collecting pexpect (from IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Collecting traitlets (from IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Using cached traitlets-4.0.0-py2.py3-none-any.whl
Collecting pickleshare (from IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Collecting ptyprocess>=0.5 (from pexpect->IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Collecting ipython-genutils (from traitlets->IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Using cached ipython_genutils-0.1.0-py2.py3-none-any.whl
Collecting path.py (from pickleshare->IPython->scikit-bio<0.3.0,>=0.2.3->qiime)
Using cached path.py-8.1.2-py2.py3-none-any.whl
Installing collected packages: six, qiime-default-reference, future, burrito, pytz, python-dateutil, numpy, pandas, natsort, cycler, pyparsing, matplotlib, gdata, scipy, decorator, simplegeneric, ptyprocess, pexpect, ipython-genutils, traitlets, path.py, pickleshare, IPython, scikit-bio, cogent, pynast, click, pyqi, biom-format, burrito-fillings, qcli, emperor, qiime
Successfully installed IPython-4.0.0 biom-format-2.1.5 burrito-0.9.1 burrito-fillings-0.1.1 click-5.1 cogent-1.5.3 cycler-0.9.0 decorator-4.0.4 emperor-0.9.51 future-0.15.2 gdata-2.0.18 ipython-genutils-0.1.0 matplotlib-1.5.0 natsort-3.5.6 numpy-1.10.1 pandas-0.17.0 path.py-8.1.2 pexpect-4.0.1 pickleshare-0.5 ptyprocess-0.5 pynast-1.2.2 pyparsing-2.0.6 pyqi-0.3.2 python-dateutil-2.4.2 pytz-2015.7 qcli-0.1.1 qiime-1.9.1 qiime-default-reference-0.1.3 scikit-bio-0.2.3 scipy-0.16.1 simplegeneric-0.8.1 six-1.10.0 traitlets-4.0.0
When I try to use the package I get various errors that prove that pip hasn't really compiled any dependencies. What should I do with that? For example, let's try to import pandas
In [1]: import pandas
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-1-d6ac987968b6> in <module>()
----> 1 import pandas
/home/user/.conda/envs/qiime/lib/python2.7/site-packages/pandas/__init__.py in <module>()
11 "pandas from the source directory, you may need to run "
12 "'python setup.py build_ext --inplace' to build the C "
---> 13 "extensions first.".format(module))
14
15 from datetime import datetime
ImportError: C extension: /home/user/.conda/envs/qiime/lib/python2.7/site-packages/pandas/hashtable.so: undefined symbol: PyFPE_jbuf not built. If you want to import pandas from the source directory, you may need to run 'python setup.py build_ext --inplace' to build the C extensions first.
I know I can build everything manually, but I really want to fix pip.
Passing --no-cache-dir to pip during installation seems to solve the issue, though I don't understand what caches have to do with compilation.