所有这些软件包都已安装，环境为Windows 7.1
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py36he6757f0_0
alabaster 0.7.10 py36hcd07829_0
anaconda 5.1.0 py36_2
anaconda-client 1.6.9 py36_0
anaconda-navigator 1.7.0 py36_0
anaconda-project 0.8.2 py36hfad2e28_0
asn1crypto 0.24.0 py36_0
astroid 1.6.1 py36_0
astropy 2.0.3 py36hfa6e2cd_0
attrs 17.4.0 py36_0
babel 2.5.3 py36_0
backports 1.0 py36h81696a8_1
backports.shutil_get_terminal_size 1.0.0 py36h79ab834_2
beautifulsoup4 4.6.0 py36hd4cc5e8_1
bitarray 0.8.1 py36hfa6e2cd_1
bkcharts 0.2 py36h7e685f7_0
blaze 0.11.3 py36h8a29ca5_0
bleach 2.1.2 py36_0
bokeh 0.12.13 py36h047fa9f_0
boto 2.48.0 py36h1a776d2_1
boto3 1.9.42 <pip>
botocore 1.12.42 <pip>
bottleneck 1.2.1 py36hd119dfa_0
bzip2 1.0.6 hbe05fcf_4
ca-certificates 2017.08.26 h94faf87_0
certifi 2018.1.18 py36_0
cffi 1.11.4 py36hfa6e2cd_0
chardet 3.0.4 py36h420ce6e_1
click 6.7 py36hec8c647_0
cloudpickle 0.5.2 py36_1
clyent 1.2.2 py36hb10d595_1
colorama 0.3.9 py36h029ae33_0
comtypes 1.1.4 py36_0
conda 4.4.10 py36_0
conda-build 3.4.1 py36_0
conda-env 2.6.0 h36134e3_1
conda-verify 2.0.0 py36h065de53_0
console_shortcut 0.1.1 h6bb2dd7_3
contextlib2 0.5.5 py36he5d52c0_0
cryptography 2.1.4 py36he1d7878_0
curl 7.58.0 h7602738_0
cycler 0.10.0 py36h009560c_0
cython 0.27.3 py36h22f4c84_0
cytoolz 0.9.0 py36hfa6e2cd_0
dask 0.16.1 py36_0
dask 0.20.1 <pip>
dask-core 0.16.1 py36_0
datashape 0.5.4 py36h5770b85_0
decorator 4.2.1 py36_0
distributed 1.20.2 py36_0
distributed 1.24.1 <pip>
docutils 0.14 py36h6012d8f_0
entrypoints 0.2.3 py36hfd66bb0_2
et_xmlfile 1.0.1 py36h3d2d736_0
fastcache 1.0.2 py36hfa6e2cd_2
featuretools 0.4.0 <pip>
filelock 2.0.13 py36h20000bf_0
flask 0.12.2 py36h98b5e8f_0
flask-cors 3.0.3 py36h8a3855d_0
freetype 2.8 h51f8f2c_1
future 0.17.1 <pip>
get_terminal_size 1.0.0 h38e98db_0
gevent 1.2.2 py36h342a76c_0
glob2 0.6 py36hdf76b57_0
greenlet 0.4.12 py36ha00ad21_0
h5py 2.7.1 py36he54a1c3_0
hdf5 1.10.1 h98b8871_1
heapdict 1.0.0 py36_2
html5lib 1.0.1 py36h047fa9f_0
icc_rt 2017.0.4 h97af966_0
icu 58.2 ha66f8fd_1
idna 2.6 py36h148d497_1
imageio 2.2.0 py36had6c2d2_0
imagesize 0.7.1 py36he29f638_0
intel-openmp 2018.0.0 hd92c6cd_8
ipykernel 4.8.0 py36_0
ipython 6.2.1 py36h9cf0123_1
ipython_genutils 0.2.0 py36h3c5d0ee_0
ipywidgets 7.1.1 py36_0
isort 4.2.15 py36h6198cc5_0
itsdangerous 0.24 py36hb6c5a24_1
jdcal 1.3 py36h64a5255_0
jedi 0.11.1 py36_0
jinja2 2.10 py36h292fed1_0
jmespath 0.9.3 <pip>
jpeg 9b hb83a4c4_2
jsonschema 2.6.0 py36h7636477_0
jupyter 1.0.0 py36_4
jupyter_client 5.2.2 py36_0
jupyter_console 5.2.0 py36h6d89b47_1
jupyter_core 4.4.0 py36h56e9d50_0
jupyterlab 0.31.4 py36_0
jupyterlab_launcher 0.10.2 py36_0
lazy-object-proxy 1.3.1 py36hd1c21d2_0
libcurl 7.58.0 h7602738_0
libiconv 1.15 h1df5818_7
libpng 1.6.34 h79bbb47_0
libssh2 1.8.0 hd619d38_4
libtiff 4.0.9 h0f13578_0
libxml2 2.9.7 h79bbb47_0
libxslt 1.1.32 hf6f1972_0
llvmlite 0.21.0 py36he0b0552_0
locket 0.2.0 py36hfed976d_1
lxml 4.1.1 py36hef2cd61_1
lzo 2.10 h6df0209_2
markupsafe 1.0 py36h0e26971_1
matplotlib 2.1.2 py36h016c42a_0
mccabe 0.6.1 py36hb41005a_1
menuinst 1.4.11 py36hfa6e2cd_0
mistune 0.8.3 py36_0
mkl 2018.0.1 h2108138_4
mkl-service 1.1.2 py36h57e144c_4
mpmath 1.0.0 py36hacc8adf_2
msgpack 0.5.6 <pip>
msgpack-python 0.5.1 py36he980bc4_0
multipledispatch 0.4.9 py36he44c36e_0
navigator-updater 0.1.0 py36h8a7b86b_0
nbconvert 5.3.1 py36h8dc0fde_0
nbformat 4.4.0 py36h3a5bc1b_0
networkx 2.1 py36_0
nltk 3.2.5 py36h76d52bb_0
nose 1.3.7 py36h1c3779e_2
notebook 5.4.0 py36_0
numba 0.36.2 np114py36h12cb543_0
numexpr 2.6.4 py36h30784b8_0
numpy 1.14.0 py36h4a99626_1
numpydoc 0.7.0 py36ha25429e_0
odo 0.5.1 py36h7560279_0
olefile 0.45.1 py36_0
openpyxl 2.4.10 py36_0
openssl 1.0.2n h74b6da3_0
packaging 16.8 py36ha0986f6_1
pandas 0.23.4 <pip>
pandas 0.22.0 py36h6538335_0
pandoc 1.19.2.1 hb2460c7_1
pandocfilters 1.4.2 py36h3ef6317_1
parso 0.1.1 py36hae3edee_0
partd 0.3.8 py36hc8e763b_0
path.py 10.5 py36h2b94a8f_0
pathlib2 2.3.0 py36h7bfb78b_0
patsy 0.5.0 py36_0
pep8 1.7.1 py36_0
pickleshare 0.7.4 py36h9de030f_0
pillow 5.0.0 py36h0738816_0
pip 18.1 <pip>
pip 9.0.1 py36h226ae91_4
pkginfo 1.4.1 py36hb0f9cfa_1
pluggy 0.6.0 py36hc7daf1e_0
ply 3.10 py36h1211beb_0
prompt_toolkit 1.0.15 py36h60b8f86_0
psutil 5.4.8 <pip>
psutil 5.4.3 py36hfa6e2cd_0
py 1.5.2 py36hbcfbabc_0
pycodestyle 2.3.1 py36h7cc55cd_0
pycosat 0.6.3 py36h413d8a4_0
pycparser 2.18 py36hd053e01_1
pycrypto 2.6.1 py36hfa6e2cd_7
pycurl 7.43.0.1 py36h74b6da3_0
pyflakes 1.6.0 py36h0b975d6_0
pygments 2.2.0 py36hb010967_0
pylint 1.8.2 py36_0
pyodbc 4.0.22 py36h6538335_0
pyopenssl 17.5.0 py36h5b7d817_0
pyparsing 2.2.0 py36h785a196_1
pyqt 5.6.0 py36hb5ed885_5
pysocks 1.6.7 py36h698d350_1
pytables 3.4.2 py36h71138e3_2
pytest 3.3.2 py36_0
python 3.6.4 h6538335_1
python-dateutil 2.6.1 py36h509ddcb_1
pytz 2017.3 py36h1d3fa6b_0
pywavelets 0.5.2 py36hc649158_0
pywin32 222 py36hfa6e2cd_0
pywinpty 0.5 py36h6538335_1
pyyaml 3.12 py36h1d1928f_1
pyzmq 16.0.3 py36he714bf5_0
qt 5.6.2 vc14h6f8c307_12 [vc14]
qtawesome 0.4.4 py36h5aa48f6_0
qtconsole 4.3.1 py36h99a29a9_0
qtpy 1.3.1 py36hb8717c5_0
requests 2.18.4 py36h4371aae_1
rope 0.10.7 py36had63a69_0
ruamel_yaml 0.15.35 py36hfa6e2cd_1
s3fs 0.1.6 <pip>
s3transfer 0.1.13 <pip>
scikit-image 0.13.1 py36hfa6e2cd_1
scikit-learn 0.19.1 py36h53aea1b_0
scipy 1.0.0 py36h1260518_0
seaborn 0.8.1 py36h9b69545_0
send2trash 1.4.2 py36_0
setuptools 38.4.0 py36_0
simplegeneric 0.8.1 py36_2
singledispatch 3.4.0.3 py36h17d0c80_0
sip 4.18.1 py36h9c25514_2
six 1.11.0 py36h4db2310_1
snowballstemmer 1.2.1 py36h763602f_0
sortedcollections 0.5.3 py36hbefa0ab_0
sortedcontainers 1.5.9 py36_0
sphinx 1.6.6 py36_0
sphinxcontrib 1.0 py36hbbac3d2_1
sphinxcontrib-websupport 1.0.1 py36hb5e5916_1
spyder 3.2.6 py36_0
sqlalchemy 1.2.1 py36hfa6e2cd_0
sqlite 3.22.0 h9d3ae62_0
statsmodels 0.8.0 py36h6189b4c_0
sympy 1.1.1 py36h96708e0_0
tblib 1.3.2 py36h30f5020_0
terminado 0.8.1 py36_1
testpath 0.3.1 py36h2698cfe_0
tk 8.6.7 hcb92d03_3
toolz 0.9.0 py36_0
tornado 4.5.3 py36_0
tqdm 4.28.1 <pip>
traitlets 4.3.2 py36h096827d_0
typing 3.6.2 py36hb035bda_0
unicodecsv 0.14.1 py36h6450c06_0
urllib3 1.22 py36h276f60a_0
vc 14 h0510ff6_3
vs2015_runtime 14.0.25123 3
wcwidth 0.1.7 py36h3d5aa90_0
webencodings 0.5.1 py36h67c50ae_1
werkzeug 0.14.1 py36_0
wheel 0.30.0 py36h6c3ec14_1
widgetsnbextension 3.1.0 py36_0
win_inet_pton 1.0.1 py36he67d7fd_1
win_unicode_console 0.5 py36hcdbd4b5_0
wincertstore 0.2 py36h7fe50ca_0
winpty 0.4.3 4
wrapt 1.10.11 py36he5f5981_0
xlrd 1.1.0 py36h1cb58dc_1
xlsxwriter 1.0.2 py36hf723b7d_0
xlwings 0.11.5 py36_0
xlwt 1.3.0 py36h1a4751e_0
yaml 0.1.7 hc54c509_2
zict 0.1.3 py36h2d8e73e_0
zlib 1.2.11 h8395fce_2
当我在Jupyter笔记本上导入featuretools时，它引发了一个错误。
有人知道如何解决吗？
-------------------------------------------------- ---------------------------- AttributeError Traceback（最近一次调用 最后）在（） 1＃自动化特征工程 ----> 2个以ft形式导入特征工具
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools__init __。py 在（）中 5从.entityset.api import * 来自的6。导入原语 ----> 7从.synthesis.api导入* 8从.primitives导入功能，list_primitives 9从.computational_backends.api导入*
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools \ synthesis__init __。py 在（）中 1个来自未来进口的absolute_import 2＃flake8：noqa ----> 3从.api import *
D：\ Program 文件\ Anaconda3 \ lib \ site-packages \ featuretools \ synthesis \ api.py （） 3＃flake8：noqa 4从.deep_feature_synthesis导入DeepFeatureSynthesis ----> 5从.dfs导入dfs 从.encode_features中导入6导入encode_features
D：\ Program 文件\ Anaconda3 \ lib \ site-packages \ featuretools \ synthesis \ dfs.py在 （） 3从.deep_feature_synthesis导入DeepFeatureSynthesis 4 ---->从featuretools.computational_backends中导入5 6从featuretools.entityset导入EntitySet 7
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools \ computational_backends__init __。py 在（）中 1＃flake8：noqa ----> 2从.api import *
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools \ computational_backends \ api.py 在（）中 1＃flake8：noqa ----> 2从.calculate_feature_matrix导入（ 3个roximate_features， 4calculate_feature_matrix 5）
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools \ computational_backends \ calculate_feature_matrix.py 在（）中 15 从.pandas_backend 16导入PandasBackend ---> 17从.utils导入（ 18 bin_cutoff_times， 19 calc_num_per_chunk，
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ featuretools \ computational_backends \ utils.py 在（）中 8个进口大熊猫作为PD 9导入psutil ---> 10从分布式导入客户端LocalCluster 从pandas.tseries.frequencies中导入11 to_offset 12
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed__init __。py 在（）中 3个。导入配置 4从dask.config导入配置 ----> 5 from .actor import Actor，ActorFuture 6从.core import connect，rpc 从.deploy导入7，自适应
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ actor.py在 （） 2个导入功能工具 3 ----> 4从.client导入Future，default_client 5从.compatibility导入get_thread_identity，队列 6从.protocol导入to_serialize
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ client.py在 （） 来自tornado.queues的42导入队列 43 ---> 44从.batched导入BatchedSend 45从.utils_comm导入（WrappedKey，unpack_remotedata，pack_data， 46 scatter_to_workers，collect_from_workers）
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ batched.py在 （） 8从tornado.ioloop导入IOLoop 9 ---> 10从.core导入CommClosedError 从.utils导入11 parse_timedelta 12
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ core.py在 （） 18岁 19从.compatibility导入get_thread_identity ---> 20从.comm导入（连接，监听，CommClosedError， 21 normalize_address， 22 unparse_host_port，get_address_host_port）
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ comm__init __。py在 （） 7 get_local_address_for， 8） ----> 9从.core导入连接，监听，Comm，CommClosedError 10 11
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ comm \ core.py 在（）中 10 从..metrics导入时间开始11 -> 12从..utils导入parse_timedelta 来自的13。导入注册表 14从.addressing导入parse_address
D：\ Program Files \ Anaconda3 \ lib \ site-packages \ distributed \ utils.py在 （）1388导入asyncio 1389导入 龙卷风平台异步 -> 1390 asyncio.set_event_loop_policy（tornado.platform.asyncio.AnyThreadEventLoopPolicy（）） 1391 1392
AttributeError：模块'tornado.platform.asyncio'没有属性 'AnyThreadEventLoopPolicy'
答案 0 :(得分：2)
我有同样的问题。 我在龙卷风的版本“ 4.5.1”的tornado / platform / asyncio.py中找不到类“ AnyThreadEventLoopPolicy”，但是在github的龙卷风母版的源代码中找不到。 这样您就可以安装最新的龙卷风。
现在，pip无法安装龙卷风5.1.1 您可以按照以下步骤操作： 1：下载tornado-5.1.1 2：pip安装* .whl或cd file_dir python setup.py install