康达更新InvalidSpecError [英] conda update InvalidSpecError
本文介绍了康达更新InvalidSpecError的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我正在尝试更新conda环境:
I am trying to update a conda environment:
conda update --all
但是得到以下内容
Fetching package metadata .............
InvalidSpecError: Invalid spec: =20190808
conda list 的
输出如下:
alabaster 0.7.10 py36h174008c_0
anaconda custom py36ha4fed55_0
anaconda-client 1.6.14 py36_0
anaconda-navigator 1.6.4 py36_0
anaconda-project 0.8.2 py36h9ee5d53_0
apipkg 1.5 <pip>
appnope 0.1.0 py36hf537a9a_0
appnope 0.1.0 <pip>
appscript 1.0.1 py36h9e71e49_1
arrow-cpp 0.8.0 py36_4 conda-forge
asn1crypto 0.24.0 py36_0
astroid 1.6.3 py36_0
astropy 3.0.2 py36h917ab60_1
attrs 18.1.0 py36_0
babel 2.5.3 py36_0
backcall 0.1.0 <pip>
backcall 0.1.0 py36_0
backports 1.0 py36ha3c1827_1
backports.shutil_get_terminal_size 1.0.0 py36hd7a2ee4_2
bash_kernel 0.7.1 <pip>
bctpy 0.5.0 <pip>
beautifulsoup4 4.6.0 py36h72d3c9f_1
billiard 3.5.0.4 <pip>
biopython 1.72 py36h6440ff4_0 anaconda
bitarray 0.8.1 py36h1de35cc_1
bkcharts 0.2 py36h073222e_0
blas 1.0 mkl
blaze 0.11.3 py36h02e7a37_0
bleach 2.1.3 py36_0
bleach 2.1.3 <pip>
blosc 1.14.3 hd9629dc_0
bokeh 0.12.16 py36_0
boto 2.48.0 py36hdbc59ac_1
bottleneck 1.2.1 py36hbd380ad_0
brainnetworks 0.3.2 <pip>
bz2file 0.98 py_0 conda-forge
bzip2 1.0.6 h1de35cc_5
ca-certificates 2018.03.07 0
cairo 1.14.12 he60d9cb_2
certifi 2018.4.16 py36_0
cffi 1.11.5 py36h342bebf_0
cffi 1.13.2 <pip>
chardet 3.0.4 py36h96c241c_1
click 6.7 py36hec950be_0
click-plugins 1.0.3 <pip>
cligj 0.4.0 <pip>
cloog 0.18.0 0
cloudpickle 0.5.3 py36_0
clyent 1.2.2 py36hae3ad88_0
colorama 0.3.9 py36hd29a30c_0
configparser 3.5.0 <pip>
connectome-builder 1.21 <pip>
contextlib2 0.5.5 py36hd66e5e7_0
cryptography 2.2.2 py36h1de35cc_0
curl 7.60.0 ha441bb4_0
cvxopt 1.2.0 py36hb579ef3_0
cycler 0.10.0 py36hfc81398_0
cython 0.28.2 py36h1de35cc_0
cytoolz 0.9.0.1 py36h1de35cc_0
dask 0.17.5 py36_0
dask-core 0.17.5 py36_0
datashape 0.5.4 py36hfb22df8_0
dbus 1.13.2 h760590f_1
decorator 4.3.0 <pip>
decorator 4.3.0 py36_0
descartes 1.1.0 <pip>
dipy 0.15.0 py36h7eb728f_0 conda-forge
distributed 1.21.8 py36_0
docutils 0.14 py36hbfde631_0
entropy-estimators 1.0 <pip>
entrypoints 0.2.3 py36hd81d71f_2
entrypoints 0.2.3 <pip>
et_xmlfile 1.0.1 py36h1315bdc_0
execnet 1.5.0 <pip>
expat 2.2.5 hb8e80ba_0
fastcache 1.0.2 py36h1de35cc_2
fasteners 0.14.1 <pip>
feather-format 0.4.0 py36_2 conda-forge
feather-format 0.4.0 <pip>
ffmpeg 4.0 hc84425e_0
filelock 3.0.4 py36_0
Fiona 1.7.13 <pip>
flake8 3.5.0 py36_1
flask 1.0.2 py36_1
flask-cors 3.0.4 py36_0
fontconfig 2.12.6 h9850fc5_0
freetype 2.8 h12048fb_1
funcsigs 1.0.2 <pip>
future 0.16.0 <pip>
future 0.17.1 py36_0
futures 3.1.1 <pip>
gast 0.2.2 <pip>
gcc 4.8.5 8
geopandas 0.4.0 <pip>
get_terminal_size 1.0.0 h7520d66_0
gettext 0.19.8.1 h15daf44_3
gevent 1.3.0 py36h1de35cc_0
glib 2.56.1 h35bc53a_0
glob2 0.6 py36h94c9186_0
glpk 4.65 h0a95893_1001 conda-forge
gmp 6.1.2 hb37e062_1
gmpy2 2.0.8 py36hf9c35bd_2
gnutls 3.5.17 0 conda-forge
greenlet 0.4.13 py36h1de35cc_0
gsl 2.4 h1de35cc_4
h5py 2.8.0 py36h967a92a_0
hdf5 1.8.18 h017327d_1
heapdict 1.0.0 py36_2
hide-code 0.5.2 <pip>
html5lib 1.0.1 <pip>
html5lib 1.0.1 py36h2f9c1c0_0
icu 58.2 h4b95b61_1
idna 2.6 py36h8628d0a_1
igraph 0.7.1 h0a67f88_1005 conda-forge
imageio 2.3.0 py36_0
imagesize 1.0.0 py36_0
infomap 1.0.0b8 <pip>
intel-openmp 2018.0.0 8
ipykernel 4.8.2 py36_0
ipykernel 4.8.2 <pip>
ipython 6.5.0 <pip>
ipython 6.4.0 py36_0
ipython-genutils 0.2.0 <pip>
ipython_genutils 0.2.0 py36h241746c_0
ipywidgets 7.2.1 <pip>
ipywidgets 7.2.1 py36_0
isl 0.12.2 1
isodate 0.6.0 <pip>
isort 4.3.4 py36_0
itsdangerous 0.24 py36h49fbb8d_1
jbig 2.1 h4d881f8_0
jdcal 1.4 py36_0
jedi 0.12.0 <pip>
jedi 0.12.0 py36_1
jinja2 2.10 py36hd36f9c5_0
Jinja2 2.10 <pip>
jpeg 9b he5867d9_2
jsoncpp 1.8.4 h04f5b5a_0
jsonschema 2.6.0 <pip>
jsonschema 2.6.0 py36hb385e00_0
jupyter 1.0.0 py36_4
jupyter 1.0.0 <pip>
jupyter-client 5.2.3 <pip>
jupyter-console 5.2.0 <pip>
jupyter-core 4.4.0 <pip>
jupyter_client 5.2.3 py36_0
jupyter_console 5.2.0 py36hccf5b1c_1
jupyter_core 4.4.0 py36h79cf704_0
jupyterlab 0.32.1 py36_0
jupyterlab_launcher 0.10.5 py36_0
Keras 2.3.1 <pip>
Keras-Applications 1.0.8 <pip>
Keras-Preprocessing 1.1.0 <pip>
kiwisolver 1.0.1 py36h792292d_0
lazy-object-proxy 1.3.1 py36h2fbbe47_0
libcurl 7.60.0 hf30b1f0_0
libcxx 4.0.1 h579ed51_0
libcxxabi 4.0.1 hebd6815_0
libedit 3.1.20170329 hb402a30_2
libffi 3.2.1 h475c297_4
libgfortran 3.0.1 h93005f0_2
libiconv 1.15 hdd342a3_7
libidn11 1.33 0 conda-forge
libopus 1.2.1 h169cedb_0
libpng 1.6.34 he12f830_0
libsodium 1.0.16 h3efe00b_0
libssh2 1.8.0 h322a93b_4
libtiff 4.0.9 hcb84e12_1
libvpx 1.7.0 h378b8a2_0
libxml2 2.9.8 hab757c2_1
libxslt 1.1.32 hb819dd2_0
line-profiler 2.1.2 <pip>
llvmlite 0.23.1 py36hc454e04_0
locket 0.2.0 py36hca03003_1
lxml 4.2.1 py36h7166777_0
lzo 2.10 h362108e_2
Markdown 2.6.11 <pip>
MarkupSafe 1.0 <pip>
markupsafe 1.0 py36h3a1e703_1
matplotlib 2.2.3 <pip>
matplotlib 2.2.2 py36ha7267d0_0
mccabe 0.6.1 py36hdaeb55d_0
metakernel 0.20.14 py_0 conda-forge
metis 5.1.0 h0a44026_1003 conda-forge
mistune 0.8.3 py36h1de35cc_1
mistune 0.8.3 <pip>
mizani 0.4.6 <pip>
mkl 2018.0.3 1
mkl-service 1.1.2 py36h7ea6df4_4
mkl_fft 1.0.1 py36h917ab60_0
mkl_random 1.0.1 py36h78cc56f_0
mock 2.0.0 <pip>
monotonic 1.5 <pip>
more-itertools 4.1.0 py36_0
mpc 1.0.3 h7a72875_5
mpfr 3.1.5 h711e7fd_2
mpmath 1.0.0 py36hf1b8295_2
msgpack 1.0.0 <pip>
msgpack-python 0.5.6 py36h04f5b5a_0
multipledispatch 0.5.0 py36_0
munch 2.3.2 <pip>
navigator-updater 0.1.0 py36_0
nbconvert 5.3.1 py36h810822e_0
nbconvert 5.3.1 <pip>
nbformat 4.4.0 <pip>
nbformat 4.4.0 py36h827af21_0
ncurses 6.1 h0a44026_0
nettle 3.3 0 conda-forge
networkx 2.1 py36_0
neurdflib 5.0.0.post1 <pip>
nibabel 2.3.3 py_0 conda-forge
nibabel 2.3.0 <pip>
nilearn 0.4.1 <pip>
nilearn 0.5.0 pyh24bf2e0_0 conda-forge
nipy 0.4.2 <pip>
nipy 0.4.1 py36h917ab60_1001 conda-forge
nipype 1.1.9.dev0 <pip>
nltk 3.3.0 py36_0
nose 1.3.7 py36h73fae2b_2
notebook 5.5.0 py36_0
notebook 5.6.0 <pip>
numba 0.38.0 py36h1702cab_0
numexpr 2.6.5 py36h057f876_0
numpy 1.14.3 py36h9bb19eb_1
numpy 1.16.2 <pip>
numpy-base 1.14.3 py36h479e554_1
numpydoc 0.8.0 py36_0
oct2py 4.0.6 py_1 conda-forge
octave_kernel 0.28.4 py_1 conda-forge
odo 0.5.1 py36hc1af34a_0
olefile 0.45.1 py36_0
openpyxl 2.5.3 py36_0
openssl 1.0.2o h26aff7b_0
packaging 17.1 py36_0
palettable 3.1.1 <pip>
pandas 0.23.0 py36h1702cab_0
pandas 0.23.4 <pip>
pandoc 1.19.2.1 ha5e8f32_1
pandocfilters 1.4.2 <pip>
pandocfilters 1.4.2 py36h3b0b094_1
parquet-cpp 1.4.0.pre 2 conda-forge
parso 0.2.0 py36_0
parso 0.2.0 <pip>
partd 0.3.8 py36hf5c4cb8_0
path.py 11.0.1 py36_0
pathlib2 2.3.2 py36_0
patsy 0.5.0 py36_0
pbr 4.2.0 <pip>
pcre 8.42 h378b8a2_0
pdfkit 0.6.1 <pip>
pep8 1.7.1 py36_0
pexpect 4.5.0 <pip>
pexpect 4.5.0 py36_0
pfile-tools 0.3.2 <pip>
pickleshare 0.7.4 py36hf512f8e_0
pickleshare 0.7.4 <pip>
pillow 5.1.0 py36hfcce615_0
pip 18.0 <pip>
pip 10.0.1 py36_0
pixman 0.34.0 h1de35cc_1003 conda-forge
pkginfo 1.4.2 py36_1
plotnine 0.4.0 <pip>
pluggy 0.6.0 py36hb1d0581_0
ply 3.11 py36_0
prometheus-client 0.3.1 <pip>
prompt-toolkit 1.0.15 <pip>
prompt_toolkit 1.0.15 py36haeda067_0
prov 1.5.3 <pip>
psutil 5.4.5 py36h1de35cc_0
ptitprince 0.1.5 <pip>
ptyprocess 0.5.2 <pip>
ptyprocess 0.5.2 py36he6521c3_0
py 1.5.3 py36_0
pyarrow 0.9.0.post1 <pip>
pyarrow 0.8.0 py36_0 conda-forge
pycairo 1.18.0 py36ha54c0a8_1000 conda-forge
pycodestyle 2.3.1 py36h83e8646_0
pycodestyle_magic 0.1 <pip>
pycosat 0.6.3 py36hee92d8f_0
pycparser 2.18 py36h724b2fc_1
pycrypto 2.6.1 py36h1de35cc_8
pycurl 7.43.0.1 py36hdbc3d79_0
pydicom 1.2.2 py_0 conda-forge
pydicom 1.1.0 <pip>
pydot 1.2.4 <pip>
pydotplus 2.0.2 <pip>
pyevtk 1.1.0 <pip>
pyflakes 1.6.0 py36hea45e83_0
pygments 2.2.0 py36h240cd3f_0
Pygments 2.2.0 <pip>
PyHamcrest 1.9.0 <pip>
pylint 1.8.4 py36_0
pyodbc 4.0.23 py36h0a44026_0
pyopenssl 18.0.0 py36_0
pyparsing 2.2.0 py36hb281f35_0
pyproj 1.9.5.1 <pip>
pyqt 5.9.2 py36h11d3b92_0
pysocks 1.6.8 py36_0
pytables 3.4.4 py36hca30cd5_0
pytest 3.5.1 py36_0
pytest-arraydiff 0.2 py36_0
pytest-astropy 0.3.0 py36_0
pytest-doctestplus 0.1.3 py36_0
pytest-forked 0.2 <pip>
pytest-openfiles 0.3.0 py36_0
pytest-remotedata 0.2.1 py36_0
pytest-xdist 1.22.5 <pip>
python 3.6.5 hc167b69_1
python-dateutil 2.7.2 <pip>
python-dateutil 2.7.3 py36_0
python-igraph 0.7.1.post6 py36h1de35cc_1005 conda-forge
python-louvain 0.13 <pip>
python.app 2 py36_8
pytz 2018.4 py36_0
pywavelets 0.5.2 py36h2710a04_0
pyyaml 3.12 py36h2ba1e63_1
pyzmq 17.0.0 <pip>
pyzmq 17.0.0 py36h1de35cc_1
qt 5.9.5 h02808f3_0
qtawesome 0.4.4 py36h468c6fb_0
qtconsole 4.3.1 py36hd96c0ff_0
qtconsole 4.3.1 <pip>
qtpy 1.4.1 py36_0
rdflib 4.2.2 <pip>
readline 7.0 hc1231fa_4
redis 2.10.6 <pip>
requests 2.18.4 py36h4516966_1
rope 0.10.7 py36h68959ac_0
rpy2 3.2.2 <pip>
rq 0.12.0 <pip>
ruamel_yaml 0.15.35 py36h1de35cc_1
sas7bdat 2.1.1 <pip>
saspy 2.2.6 <pip>
scikit-image 0.13.1 py36h1de35cc_1
scikit-learn 0.19.1 py36hffbff8c_0
scipy 1.4.1 <pip>
scipy 1.1.0 py36hcaad992_0
scipy 1.0.1 <pip>
seaborn 0.9.0 py36_0
send2trash 1.5.0 py36_0
Send2Trash 1.5.0 <pip>
setuptools 39.1.0 <pip>
setuptools 39.1.0 py36_0
Shapely 1.6.4.post2 <pip>
simplegeneric 0.8.1 py36_2
simplegeneric 0.8.1 <pip>
SimpleITK 1.2.0 <pip>
simplejson 3.16.0 <pip>
singledispatch 3.4.0.3 py36hf20db9d_0
sip 4.19.8 py36h0a44026_0
six 1.11.0 <pip>
six 1.11.0 py36h0e22d5e_1
snappy 1.1.7 he62c110_3
snowballstemmer 1.2.1 py36h6c7b616_0
sortedcollections 0.6.1 py36_0
sortedcontainers 1.5.10 py36_0
sos 0.9.16.1 <pip>
sos-bash 0.9.12.2 <pip>
sos-bioinfo 0.9.10.1 <pip>
sos-javascript 0.9.12.2 <pip>
sos-julia 0.9.12.1 <pip>
sos-matlab 0.9.12.1 <pip>
sos-notebook 0.9.16.0 <pip>
sos-pbs 0.9.16.0 <pip>
sos-python 0.9.12.1 <pip>
sos-r 0.9.12.3 <pip>
sos-rq 0.9.16.1 <pip>
sos-ruby 0.9.15.0 <pip>
sos-sas 0.9.12.3 <pip>
sphinx 1.7.4 py36_0
sphinxcontrib 1.0 py36h9364dc8_1
sphinxcontrib-websupport 1.0.1 py36h92f4a7a_1
spyder 3.2.8 py36_0
sqlalchemy 1.2.7 py36hb402a30_0
sqlite 3.23.1 hf1716c9_0
statsmodels 0.9.0 py36h1d22016_0
suitesparse 5.2.0 he235d88_0
sympy 1.1.1 py36h7f3cf04_0
tableone 0.5.13 <pip>
tabulate 0.8.2 <pip>
tbb 2018_20171205 0 conda-forge
tblib 1.3.2 py36hda67792_0
tensorflow-estimator 2.1.0 <pip>
termcolor 1.1.0 <pip>
terminado 0.8.1 <pip>
terminado 0.8.1 py36_1
testpath 0.3.1 <pip>
testpath 0.3.1 py36h625a49b_0
tk 8.6.7 h35a86e2_3
toolz 0.9.0 py36_0
tornado 5.0.2 py36_0
tornado 5.0.2 <pip>
tqdm 4.24.0 <pip>
traitlets 4.3.2 py36h65bd3ce_0
traitlets 4.3.2 <pip>
traits 4.6.0 <pip>
typing 3.6.4 py36_0
tzlocal 2.0.0 <pip>
unicodecsv 0.14.1 py36he531d66_0
unixodbc 2.3.6 h3efe00b_0
urllib3 1.22 py36h68b9469_0
vtk 8.1.0 py36h04d9db9_201
Wand 0.4.4 <pip>
wcwidth 0.1.7 py36h8c6ec74_0
wcwidth 0.1.7 <pip>
webencodings 0.5.1 py36h3b9701d_1
webencodings 0.5.1 <pip>
werkzeug 0.14.1 py36_0
wheel 0.31.1 py36_0
widgetsnbextension 3.2.1 py36_0
widgetsnbextension 3.2.1 <pip>
wrapt 1.10.11 py36hc29e774_0
x264 20131217 3 conda-forge
xlrd 1.2.0 py_0 conda-forge
xlsxwriter 1.0.4 py36_0
xlwings 0.11.8 py36_0
xlwt 1.2.0 py36h5ad1178_0
xxhash 1.2.0 <pip>
xz 5.2.4 h1de35cc_4
yaml 0.1.7 hc338f04_2
zeromq 4.2.5 h378b8a2_0
zict 0.1.3 py36h71da714_0
zlib 1.2.11 hf3cbc9b_2
推荐答案
虽然不是解决方案，但我们想出了一种解决方法，因此我想将其发布在这里.
While not a solution, we came up with a workaround, so I figured I'd post it here.
在替代位置安装conda的较新版本，并使用此特定的激活二进制文件激活环境可以使安装再次起作用.
Installing a newer version of conda in an alternative location, and using this specific activate binary to activate the environment allows installs to be functional once again.
这篇关于康达更新InvalidSpecError的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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