为什么 Anaconda 在我的基础环境中显示模块？
[英]Why is Anaconda showing modules in my base environment?
问题描述
I have been using Anaconda to build various environments.
我一直在用Anaconda搭建各种环境。 I noticed that if I use conda list in my base, Anaconda outputs many installed modules.我注意到如果我在我的基础中使用conda list ，Anaconda 会输出许多已安装的模块。
What are all of these modules?所有这些模块是什么？
Were they installed during the initial installation of the Anaconda?它们是在 Anaconda 的初始安装期间安装的吗？ If so, how can you tell?如果是这样，你怎么知道？
Does having modules in my base create problems?我的基地中有模块会产生问题吗？ If so, how do I properly remove them?如果是这样，我该如何正确删除它们？
(base) C:\WINDOWS\system32>conda list
# packages in environment at C:\Program Files\Anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0
alabaster 0.7.12 py37_0
anaconda 2019.07 py37_0
anaconda-client 1.7.2 py37_0
anaconda-navigator 1.9.7 py37_0
anaconda-project 0.8.3 py_0
asn1crypto 0.24.0 py37_0
astroid 2.2.5 py37_0
astropy 3.2.1 py37he774522_0
atomicwrites 1.3.0 py37_1
attrs 19.1.0 py37_1
babel 2.7.0 py_0
backcall 0.1.0 py37_0
backports 1.0 py_2
backports.functools_lru_cache 1.5 py_2
backports.os 0.1.1 py37_0
backports.shutil_get_terminal_size 1.0.0 py37_2
backports.tempfile 1.0 py_1
backports.weakref 1.0.post1 py_1
beautifulsoup4 4.7.1 py37_1
bitarray 0.9.3 py37he774522_0
bkcharts 0.2 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
blosc 1.16.3 h7bd577a_0
bokeh 1.2.0 py37_0
boto 2.49.0 py37_0
bottleneck 1.2.1 py37h452e1ab_1
bzip2 1.0.8 he774522_0
ca-certificates 2019.5.15 0
certifi 2019.6.16 py37_0
cffi 1.12.3 py37h7a1dbc1_0
chardet 3.0.4 py37_1
click 7.0 py37_0
cloudpickle 1.2.1 py_0
clyent 1.2.2 py37_1
colorama 0.4.1 py37_0
comtypes 1.1.7 py37_0
conda 4.7.10 py37_0
conda-build 3.18.8 py37_0
conda-env 2.6.0 1
conda-package-handling 1.3.11 py37_0
conda-verify 3.4.2 py_1
console_shortcut 0.1.1 3
contextlib2 0.5.5 py37_0
cryptography 2.7 py37h7a1dbc1_0
curl 7.65.2 h2a8f88b_0
cycler 0.10.0 py37_0
cython 0.29.12 py37ha925a31_0
cytoolz 0.10.0 py37he774522_0
dask 2.1.0 py_0
dask-core 2.1.0 py_0
decorator 4.4.0 py37_1
defusedxml 0.6.0 py_0
distributed 2.1.0 py_0
docutils 0.14 py37_0
entrypoints 0.3 py37_0
et_xmlfile 1.0.1 py37_0
fastcache 1.1.0 py37he774522_0
filelock 3.0.12 py_0
flask 1.1.1 py_0
freetype 2.9.1 ha9979f8_1
future 0.17.1 py37_0
get_terminal_size 1.0.0 h38e98db_0
gevent 1.4.0 py37he774522_0
glob2 0.7 py_0
greenlet 0.4.15 py37hfa6e2cd_0
h5py 2.9.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
heapdict 1.0.0 py37_2
html5lib 1.0.1 py37_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
idna 2.8 py37_0
imageio 2.5.0 py37_0
imagesize 1.1.0 py37_0
importlib_metadata 0.17 py37_1
intel-openmp 2019.4 245
ipykernel 5.1.1 py37h39e3cac_0
ipython 7.6.1 py37h39e3cac_0
ipython_genutils 0.2.0 py37_0
ipywidgets 7.5.0 py_0
isort 4.3.21 py37_0
itsdangerous 1.1.0 py37_0
jdcal 1.4.1 py_0
jedi 0.13.3 py37_0
jinja2 2.10.1 py37_0
joblib 0.13.2 py37_0
jpeg 9b hb83a4c4_2
json5 0.8.4 py_0
jsonschema 3.0.1 py37_0
jupyter 1.0.0 py37_7
jupyter_client 5.3.1 py_0
jupyter_console 6.0.0 py37_0
jupyter_core 4.5.0 py_0
jupyterlab 1.0.2 py37hf63ae98_0
jupyterlab_server 1.0.0 py_0
keyring 18.0.0 py37_0
kiwisolver 1.1.0 py37ha925a31_0
krb5 1.16.1 hc04afaa_7
lazy-object-proxy 1.4.1 py37he774522_0
libarchive 3.3.3 h0643e63_5
libcurl 7.65.2 h2a8f88b_0
libiconv 1.15 h1df5818_7
liblief 0.9.0 ha925a31_2
libpng 1.6.37 h2a8f88b_0
libsodium 1.0.16 h9d3ae62_0
libssh2 1.8.2 h7a1dbc1_0
libtiff 4.0.10 hb898794_2
libxml2 2.9.9 h464c3ec_0
libxslt 1.1.33 h579f668_0
llvmlite 0.29.0 py37ha925a31_0
locket 0.2.0 py37_1
lxml 4.3.4 py37h1350720_0
lz4-c 1.8.1.2 h2fa13f4_0
lzo 2.10 h6df0209_2
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
markupsafe 1.1.1 py37he774522_0
matlabengineforpython R2018a pypi_0 pypi
matplotlib 3.1.0 py37hc8f65d3_0
mccabe 0.6.1 py37_1
menuinst 1.4.16 py37he774522_0
mistune 0.8.4 py37he774522_0
mkl 2019.4 245
mkl-service 2.0.2 py37he774522_0
mkl_fft 1.0.12 py37h14836fe_0
mkl_random 1.0.2 py37h343c172_0
mock 3.0.5 py37_0
more-itertools 7.0.0 py37_0
mpmath 1.1.0 py37_0
msgpack-python 0.6.1 py37h74a9793_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0
navigator-updater 0.2.1 py37_0
nbconvert 5.5.0 py_0
nbformat 4.4.0 py37_0
networkx 2.3 py_0
nltk 3.4.4 py37_0
nose 1.3.7 py37_2
notebook 6.0.0 py37_0
numba 0.44.1 py37hf9181ef_0
numexpr 2.6.9 py37hdce8814_0
numpy 1.16.4 py37h19fb1c0_0
numpy-base 1.16.4 py37hc3f5095_0
numpydoc 0.9.1 py_0
olefile 0.46 py37_0
openpyxl 2.6.2 py_0
openssl 1.1.1c he774522_1
packaging 19.0 py37_0
pandas 0.24.2 py37ha925a31_0
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
parso 0.5.0 py_0
partd 1.0.0 py_0
path.py 12.0.1 py_0
pathlib2 2.3.4 py37_0
patsy 0.5.1 py37_0
pep8 1.7.1 py37_0
pickleshare 0.7.5 py37_0
pillow 6.1.0 py37hdc69c19_0
pip 19.0.3 pypi_0 pypi
pkginfo 1.5.0.1 py37_0
pluggy 0.12.0 py_0
ply 3.11 py37_0
powershell_shortcut 0.0.1 2
prometheus_client 0.7.1 py_0
prompt_toolkit 2.0.9 py37_0
psutil 5.6.3 py37he774522_0
py 1.8.0 py37_0
py-lief 0.9.0 py37ha925a31_2
pycodestyle 2.5.0 py37_0
pycosat 0.6.3 py37hfa6e2cd_0
pycparser 2.19 py37_0
pycrypto 2.6.1 py37hfa6e2cd_9
pycurl 7.43.0.3 py37h7a1dbc1_0
pyflakes 2.1.1 py37_0
pygments 2.4.2 py_0
pylint 2.3.1 py37_0
pyodbc 4.0.26 py37ha925a31_0
pyopenssl 19.0.0 py37_0
pyparsing 2.4.0 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.14.11 py37he774522_0
pysocks 1.7.0 py37_0
pytables 3.5.2 py37h1da0976_1
pytest 5.0.1 py37_0
pytest-arraydiff 0.3 py37h39e3cac_0
pytest-astropy 0.5.0 py37_0
pytest-doctestplus 0.3.0 py37_0
pytest-openfiles 0.3.2 py37_0
pytest-remotedata 0.3.1 py37_0
python 3.7.3 h8c8aaf0_1
python-dateutil 2.8.0 py37_0
python-libarchive-c 2.8 py37_11
pytz 2019.1 py_0
pywavelets 1.0.3 py37h8c2d366_1
pywin32 223 py37hfa6e2cd_1
pywinpty 0.5.5 py37_1000
pyyaml 5.1.1 py37he774522_0
pyzmq 18.0.0 py37ha925a31_0
qt 5.9.7 vc14h73c81de_0
qtawesome 0.5.7 py37_1
qtconsole 4.5.1 py_0
qtpy 1.8.0 py_0
requests 2.22.0 py37_0
rope 0.14.0 py_0
ruamel_yaml 0.15.46 py37hfa6e2cd_0
scikit-image 0.15.0 py37ha925a31_0
scikit-learn 0.21.2 py37h6288b17_0
scipy 1.2.1 py37h29ff71c_0
seaborn 0.9.0 py37_0
send2trash 1.5.0 py37_0
setuptools 41.0.1 py37_0
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.12.0 py37_0
snappy 1.1.7 h777316e_3
snowballstemmer 1.9.0 py_0
sortedcollections 1.1.2 py37_0
sortedcontainers 2.1.0 py37_0
soupsieve 1.8 py37_0
sphinx 2.1.2 py_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
sphinxcontrib-websupport 1.1.2 py_0
spyder 3.3.6 py37_0
spyder-kernels 0.5.1 py37_0
sqlalchemy 1.3.5 py37he774522_0
sqlite 3.29.0 he774522_0
statsmodels 0.10.0 py37h8c2d366_0
sympy 1.4 py37_0
tblib 1.4.0 py_0
terminado 0.8.2 py37_0
testpath 0.4.2 py37_0
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
tornado 6.0.3 py37he774522_0
tqdm 4.32.1 py_0
traitlets 4.3.2 py37_0
unicodecsv 0.14.1 py37_0
urllib3 1.24.2 py37_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.15.26706 h3a45250_4
wcwidth 0.1.7 py37_0
webencodings 0.5.1 py37_1
werkzeug 0.15.4 py_0
wheel 0.33.4 py37_0
widgetsnbextension 3.5.0 py37_0
win_inet_pton 1.1.0 py37_0
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_0
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xlrd 1.2.0 py37_0
xlsxwriter 1.1.8 py_0
xlwings 0.15.8 py37_0
xlwt 1.3.0 py37_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 hc54c509_2
zeromq 4.3.1 h33f27b4_3
zict 1.0.0 py_0
zipp 0.5.1 py_0
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0```
1 个解决方案
解决方案1
0 2022-02-04 05:14:36
Yes, this is normal and most of these are installed in the base environment with a default Anaconda installation.是的，这是正常的，其中大部分都安装在基本环境中，默认安装 Anaconda。 The anaconda package includes many packages, 1 which I won't output all here, but you can check those that come with your specific version ( anaconda=2019.07=py37_0 for win-64 ) with: anaconda D8Z包括许多包装，其中1个不包括anaconda=2019.07=py37_0 .
> conda search --info anaconda/win-64::anaconda=2019.07=py37_0
anaconda 2019.07 py37_0
-----------------------
file name : anaconda-2019.07-py37_0.tar.bz2
name : anaconda
version : 2019.07
build : py37_0
build number: 0
size : 11 KB
license : BSD
subdir : win-64
url : https://conda.anaconda.org/anaconda/win-64/anaconda-2019.07-py37_0.tar.bz2
md5 : c685b18b8c564f802374f5e407785b1f
timestamp : 2019-07-21 19:38:47 UTC
dependencies:
- alabaster 0.7.12 py37_0
- anaconda-client 1.7.2 py37_0
- anaconda-project 0.8.3 py_0
- asn1crypto 0.24.0 py37_0
- astroid 2.2.5 py37_0
- astropy 3.2.1 py37he774522_0
...
- yaml 0.1.7 hc54c509_2
- zeromq 4.3.1 h33f27b4_3
- zict 1.0.0 py_0
- zipp 0.5.1 py_0
- zlib 1.2.11 h62dcd97_3
- zstd 1.3.7 h508b16e_0
Having packages installed in base is not a problem, though many users prefer a minimal base installation, such as Miniconda or a Miniforge variant, which only include what is essential to run the conda (or mamba ) CLI.在base中安装软件包不是问题，尽管许多用户更喜欢最小的基本安装，例如 Miniconda 或 Miniforge 变体，它们只包含运行conda （或mamba ）CLI 所必需的内容。
Mutating 2 packages in base is prone to breaking the Conda installation .改变base中的2 个包很容易破坏 Conda 安装。 So, I don't recommend using the base for work (especially not the Python in there), and recommend Mambaforge for fresh installs.因此，我不建议使用基础进行工作（尤其不是其中的 Python），并建议使用 Mambaforge 进行全新安装。
[1] Note that Conda installs packages , not modules . [1]请注意，Conda 安装的是包，而不是模块。 The term modules refers to what Python packages bundle, but many of the Conda packages are non-Python dependencies.术语模块是指 Python 包捆绑的内容，但许多 Conda 包是非 Python 依赖项。
[2] That is, any conda (install|remove|update) -n base operations. [2]即任何conda (install|remove|update) -n base操作。 Though it definitely is recommended to keep the conda package updated, ie, conda update -n base conda .虽然绝对建议保持conda package 更新，即 conda conda update -n base conda 。
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