使用conda包管理器通过命令行创建环境
文章目录
- 命令
- 总结
命令
#创建环境
conda activate base
conda init
vim ~/.bashrc
source ~/.bashrc
conda create -n env python=3.9
conda activate env
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.6 -c pytorch -c conda-forge
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.6 -c pytorch -c conda-forge
conda install pytorch==1.13.0 torchvision==0.14.0 torchaudio==0.13.0 pytorch-cuda=11.6 -c pytorch -c nvidia
# 安装jupyterlab
python -m pip install jupyterlab
# 安装fortran compiler
#conda install -c conda-forge fortran-compiler
conda install -c anaconda fortran-compiler
# 安装jupyter-fortran-kernel
git clone [email protected]:ZedThree/jupyter-fortran-kernel.git
python -m pip install --user jupyter-fortran-kernel
pip install -e --user jupyter-fortran-kernel
cd jupyter-fortran-kernel
jupyter-kernelspec install fortran_spec/
# 启动jupyter lab
jupyter lab --allow-root
# 查看环境内的内核
jupyter kernelspec list
# 安装jupyter-ipykernel内核
## 内核的作用相当于告诉jupyter去哪里找代码对应的编辑器
# 查看是否有ipykernel内核
python -m ipykernel --version
# 安装ipykernel内核
python -m pip install ipykernel
# 给环境添加内核
python -m ipykernel install --user --name=python3 --display-name py37
# 删除内核
jupyter kernelspec remove kernelname
# 安装fortran内核
conda install -c conda-forge fortran-compiler
# 添加内核到环境中
jupyter kernelspec install --user fortran_spec/
参考：
- Github：jupyter-fortran-kernel
注意命令格式为：
# Python命令格式
Usage:
/home/env/.conda/envs/env/bin/python -m pip install [options] <requirement specifier> [package-index-options] ...
/home/env/.conda/envs/env/bin/python -m pip install [options] -r <requirements file> [package-index-options] ...
/home/env/.conda/envs/env/bin/python -m pip install [options] [-e] <vcs project url> ...
/home/env/.conda/envs/env/bin/python -m pip install [options] [-e] <local project path> ...
/home/env/.conda/envs/env/bin/python -m pip install [options] <archive url/path> ...
# fortran命令格式
Usage: x86_64-conda_cos6-linux-gnu-gfortran.bin [options] file...
总结
# 新建环境
conda create -n name python=*
# 安装编译器
conda install -c conda-forge fortran-compiler
# python中安装jupyter-fortran内核
python -m pip install --user jupyter-fortran-kernel
# 为了使用jupyter kernelspec，安装jupyter kernelspec
python -m pip install jupyter kernelspec
# 使用jupyter kernelspec创建fortran环境
python -m jupyter kernelspec install --user fortran_spec/
# 启动jupyterlab
python -m jupyterlab --allow-root
查看conda安装的包：
# packages in environment at /home/env/.conda/envs/fortran:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
binutils 2.40 hdd6e379_0 conda-forge
binutils_impl_linux-64 2.40 hf600244_0 conda-forge
binutils_linux-64 2.40 hbdbef99_1 conda-forge
c-compiler 1.6.0 hd590300_0 conda-forge
fortran-compiler 1.6.0 heb67821_0 conda-forge
gcc 12.3.0 h8d2909c_1 conda-forge
gcc_impl_linux-64 12.3.0 he2b93b0_0 conda-forge
gcc_linux-64 12.3.0 h76fc315_1 conda-forge
gfortran 12.3.0 h499e0f7_1 conda-forge
gfortran_impl_linux-64 12.3.0 hfcedea8_0 conda-forge
gfortran_linux-64 12.3.0 h7fe76b4_1 conda-forge
kernel-headers_linux-64 2.6.32 he073ed8_16 conda-forge
ld_impl_linux-64 2.40 h41732ed_0 conda-forge
libgcc-devel_linux-64 12.3.0 h8bca6fd_0 conda-forge
libgcc-ng 13.1.0 he5830b7_0 conda-forge
libgfortran5 13.1.0 h15d22d2_0 conda-forge
libgomp 13.1.0 he5830b7_0 conda-forge
libsanitizer 12.3.0 h0f45ef3_0 conda-forge
libstdcxx-ng 13.1.0 hfd8a6a1_0 conda-forge
sysroot_linux-64 2.12 he073ed8_16 conda-forge
$ conda env list
# conda environments:
#
fortran * /home/env/.conda/envs/fortran
hph /home/env/.conda/envs/hph
myfortran /home/env/.conda/envs/myfortran
base /home/ubuntu/anaconda3
python包：
$ python -m pip list
Package Version
---------------------------------- --------------------
alabaster 0.7.12
anaconda-client 1.9.0
anaconda-navigator 2.1.1
anaconda-project 0.10.1
anyio 2.2.0
appdirs 1.4.4
argh 0.26.2
argon2-cffi 20.1.0
arrow 0.13.1
asn1crypto 1.4.0
astroid 2.6.6
astropy 4.3.1
async-generator 1.10
atomicwrites 1.4.0
attrs 21.2.0
autopep8 1.5.7
Babel 2.9.1
backcall 0.2.0
backports.functools-lru-cache 1.6.4
backports.shutil-get-terminal-size 1.0.0
backports.tempfile 1.0
backports.weakref 1.0.post1
beautifulsoup4 4.10.0
binaryornot 0.4.4
bitarray 2.3.0
bkcharts 0.2
black 19.10b0
bleach 4.0.0
bokeh 2.4.1
boto 2.49.0
Bottleneck 1.3.2
brotlipy 0.7.0
cached-property 1.5.2
certifi 2021.10.8
cffi 1.14.6
chardet 4.0.0
charset-normalizer 2.0.4
click 8.0.3
cloudpickle 2.0.0
clyent 1.2.2
colorama 0.4.4
conda 4.10.3
conda-build 3.21.5
conda-content-trust 0+unknown
conda-pack 0.6.0
conda-package-handling 1.7.3
conda-repo-cli 1.0.4
conda-token 0.3.0
conda-verify 3.4.2
contextlib2 0.6.0.post1
cookiecutter 1.7.2
cryptography 3.4.8
cycler 0.10.0
Cython 0.29.24
cytoolz 0.11.0
daal4py 2021.3.0
dask 2021.10.0
debugpy 1.4.1
decorator 5.1.0
defusedxml 0.7.1
diff-match-patch 20200713
distributed 2021.10.0
docutils 0.17.1
entrypoints 0.3
et-xmlfile 1.1.0
fastcache 1.1.0
filelock 3.3.1
findent 4.2.6
flake8 3.9.2
Flask 1.1.2
fonttools 4.25.0
fortls 2.13.0
fsspec 2021.8.1
future 0.18.2
gevent 21.8.0
glob2 0.7
gmpy2 2.0.8
greenlet 1.1.1
h5py 3.3.0
HeapDict 1.0.1
html5lib 1.1
idna 3.2
imagecodecs 2021.8.26
imageio 2.9.0
imagesize 1.2.0
importlib-metadata 4.8.1
inflection 0.5.1
iniconfig 1.1.1
intervaltree 3.1.0
ipykernel 6.4.1
ipython 7.29.0
ipython-genutils 0.2.0
ipywidgets 7.6.5
isort 5.9.3
itsdangerous 2.0.1
jdcal 1.4.1
jedi 0.18.0
jeepney 0.7.1
Jinja2 2.11.3
jinja2-time 0.2.0
joblib 1.1.0
json5 0.9.6
jsonschema 3.2.0
jupyter 1.0.0
jupyter-client 6.1.12
jupyter-console 6.4.0
jupyter-core 4.8.1
jupyter-fortran-kernel 0.1.0
jupyter-server 1.4.1
jupyterlab 3.2.1
jupyterlab-pygments 0.1.2
jupyterlab-server 2.8.2
jupyterlab-widgets 1.0.0
keyring 23.1.0
kiwisolver 1.3.1
lazy-object-proxy 1.6.0
libarchive-c 2.9
llvmlite 0.37.0
locket 0.2.1
lxml 4.6.3
MarkupSafe 1.1.1
matplotlib 3.4.3
matplotlib-inline 0.1.2
mccabe 0.6.1
mistune 0.8.4
mkl-fft 1.3.1
mkl-random 1.2.2
mkl-service 2.4.0
mock 4.0.3
more-itertools 8.10.0
mpmath 1.2.1
msgpack 1.0.2
multipledispatch 0.6.0
munkres 1.1.4
mypy-extensions 0.4.3
navigator-updater 0.2.1
nbclassic 0.2.6
nbclient 0.5.3
nbconvert 6.1.0
nbformat 5.1.3
nest-asyncio 1.5.1
networkx 2.6.3
nltk 3.6.5
nose 1.3.7
notebook 6.4.5
numba 0.54.1
numexpr 2.7.3
numpy 1.20.3
numpydoc 1.1.0
olefile 0.46
openpyxl 3.0.9
packaging 21.0
pandas 1.3.4
pandocfilters 1.4.3
parso 0.8.2
partd 1.2.0
path 16.0.0
pathlib2 2.3.6
pathspec 0.7.0
patsy 0.5.2
pep8 1.7.1
pexpect 4.8.0
pickleshare 0.7.5
Pillow 8.4.0
pip 21.2.4
pkginfo 1.7.1
pluggy 0.13.1
ply 3.11
poyo 0.5.0
prometheus-client 0.11.0
prompt-toolkit 3.0.20
psutil 5.8.0
ptyprocess 0.7.0
py 1.10.0
pycodestyle 2.7.0
pycosat 0.6.3
pycparser 2.20
pycurl 7.44.1
pydocstyle 6.1.1
pyerfa 2.0.0
pyflakes 2.3.1
Pygments 2.10.0
PyJWT 2.1.0
pylint 2.9.6
pyls-spyder 0.4.0
pyodbc 4.0.0-unsupported
pyOpenSSL 21.0.0
pyparsing 3.0.4
pyrsistent 0.18.0
PySocks 1.7.1
pytest 6.2.4
python-dateutil 2.8.2
python-lsp-black 1.0.0
python-lsp-jsonrpc 1.0.0
python-lsp-server 1.2.4
python-slugify 5.0.2
pytz 2021.3
PyWavelets 1.1.1
pyxdg 0.27
PyYAML 6.0
pyzmq 22.2.1
QDarkStyle 3.0.2
qstylizer 0.1.10
QtAwesome 1.0.2
qtconsole 5.1.1
QtPy 1.10.0
regex 2021.8.3
requests 2.26.0
rope 0.19.0
Rtree 0.9.7
ruamel-yaml-conda 0.15.100
scikit-image 0.18.3
scikit-learn 0.24.2
scikit-learn-intelex 2021.20210714.170444
scipy 1.7.1
seaborn 0.11.2
SecretStorage 3.3.1
Send2Trash 1.8.0
setuptools 58.0.4
simplegeneric 0.8.1
singledispatch 3.7.0
sip 4.19.13
six 1.16.0
sniffio 1.2.0
snowballstemmer 2.1.0
sortedcollections 2.1.0
sortedcontainers 2.4.0
soupsieve 2.2.1
Sphinx 4.2.0
sphinxcontrib-applehelp 1.0.2
sphinxcontrib-devhelp 1.0.2
sphinxcontrib-htmlhelp 2.0.0
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.3
sphinxcontrib-serializinghtml 1.1.5
sphinxcontrib-websupport 1.2.4
spyder 5.1.5
spyder-kernels 2.1.3
SQLAlchemy 1.4.22
statsmodels 0.12.2
sympy 1.9
tables 3.6.1
TBB 0.2
tblib 1.7.0
terminado 0.9.4
testpath 0.5.0
text-unidecode 1.3
textdistance 4.2.1
threadpoolctl 2.2.0
three-merge 0.1.1
tifffile 2021.7.2
tinycss 0.4
toml 0.10.2
toolz 0.11.1
tornado 6.1
tqdm 4.62.3
traitlets 5.1.0
typed-ast 1.4.3
typing-extensions 3.10.0.2
ujson 4.0.2
unicodecsv 0.14.1
Unidecode 1.2.0
urllib3 1.26.7
watchdog 2.1.3
wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 2.0.2
wheel 0.37.0
whichcraft 0.6.1
widgetsnbextension 3.5.1
wrapt 1.12.1
wurlitzer 2.1.1
xlrd 2.0.1
XlsxWriter 3.0.1
xlwt 1.3.0
xmltodict 0.12.0
yapf 0.31.0
zict 2.0.0
zipp 3.6.0
zope.event 4.5.0
zope.interface 5.4.0
经过反复安装试错，我发现了conda创建环境的一些细节，首先在任何时候conda下载安装的东西都应该安装在各自的环境中，如果把文件安装在了base环境中，就会很麻烦，创建的其他环境都会默认参考base环境的配置信息，包括安装的安装包，所以这样的话，安装包可能只具有一个配置，不会根据环境的名字设置各自独特的内容，这样就导致各个子环境无法访问插件所具有的内容，所以需要把base环境中的内容删除。其次对于jupyter内核的安装应该是在各自环境中单独设置，如果在主环境中有jupyter kernelspec，那么在各个环境中也安装jupyter kernelspec进行install安装内核时会出现在jupyter的内核列表中。