Anaconda가 유료화 된 것을 알고계신가요? 무료로 쓸 수 있는지, 유료 대상자라면 어떻게 해야하는지 추가로 설명 드리겠습니다.
anaconda가 유료화 된 것을 알고 계신가요?
일반적으로 파이썬을 이용해서 머신러닝, 딥러닝 등을 구현할 때 가장 먼저 설치하는 것이 anaconda이다. 아래와 같이 anaconda는 2020년 9월 30일부터 유료화 됐다.(모두가 유료로 써야하는 것은 아니
leebaro.tistory.com
anaconda에서 가상환경을 만들고 나면 아래와 같은 명령어를 이용해서 삭제할 수 있다.
가상환경 확인하기
[root@ vm envs]# conda info --envs
# conda environments:
#
tensorflow35 /home/leebaro/anaconda3/envs/tensorflow35
keras_venv /home/leebaro/anaconda3/envs/keras_venv
root * /home/leebaro/anaconda3
가상환경 삭제하기
[root@vm envs]# conda remove --name tensorflow35 --all
Package plan for package removal in environment /home/leebaro/anaconda3/envs/tensorflow35:
The following packages will be REMOVED:
_license: 1.1-py35_1
alabaster: 0.7.10-py35_0
anaconda: 4.4.0-np112py35_0
anaconda-client: 1.6.3-py35_0
anaconda-navigator: 1.6.2-py35_0
anaconda-project: 0.6.0-py35_0
asn1crypto: 0.22.0-py35_0
astroid: 1.4.9-py35_0
astropy: 1.3.2-np112py35_0
babel: 2.4.0-py35_0
backports: 1.0-py35_0
beautifulsoup4: 4.6.0-py35_0
bitarray: 0.8.1-py35_0
blaze: 0.10.1-py35_0
bleach: 1.5.0-py35_0
bokeh: 0.12.5-py35_1
boto: 2.46.1-py35_0
bottleneck: 1.2.1-np112py35_0
cairo: 1.14.8-0
cffi: 1.10.0-py35_0
chardet: 3.0.3-py35_0
click: 6.7-py35_0
cloudpickle: 0.2.2-py35_0
clyent: 1.2.2-py35_0
colorama: 0.3.9-py35_0
contextlib2: 0.5.5-py35_0
cryptography: 1.8.1-py35_0
curl: 7.52.1-0
cycler: 0.10.0-py35_0
cython: 0.25.2-py35_0
cytoolz: 0.8.2-py35_0
dask: 0.14.3-py35_1
datashape: 0.5.4-py35_0
dbus: 1.10.10-0
decorator: 4.0.11-py35_0
distributed: 1.16.3-py35_0
docutils: 0.13.1-py35_0
entrypoints: 0.2.2-py35_1
et_xmlfile: 1.0.1-py35_0
expat: 2.1.0-0
fastcache: 1.0.2-py35_1
flask: 0.12.2-py35_0
flask-cors: 3.0.2-py35_0
fontconfig: 2.12.1-3
freetype: 2.5.5-2
get_terminal_size: 1.0.0-py35_0
gevent: 1.2.1-py35_0
glib: 2.50.2-1
greenlet: 0.4.12-py35_0
gst-plugins-base: 1.8.0-0
gstreamer: 1.8.0-0
h5py: 2.7.0-np112py35_0
harfbuzz: 0.9.39-2
hdf5: 1.8.17-1
heapdict: 1.0.0-py35_1
html5lib: 0.999-py35_0
icu: 54.1-0
idna: 2.5-py35_0
imagesize: 0.7.1-py35_0
ipykernel: 4.6.1-py35_0
ipython: 5.3.0-py35_0
ipython_genutils: 0.2.0-py35_0
ipywidgets: 6.0.0-py35_0
isort: 4.2.5-py35_0
itsdangerous: 0.24-py35_0
jbig: 2.1-0
jdcal: 1.3-py35_0
jedi: 0.10.2-py35_2
jinja2: 2.9.6-py35_0
jpeg: 9b-0
jsonschema: 2.6.0-py35_0
jupyter: 1.0.0-py35_3
jupyter_client: 5.0.1-py35_0
jupyter_console: 5.1.0-py35_0
jupyter_core: 4.3.0-py35_0
lazy-object-proxy: 1.2.2-py35_0
libffi: 3.2.1-1
libgcc: 4.8.5-2
libgfortran: 3.0.0-1
libiconv: 1.14-0
libpng: 1.6.27-0
libsodium: 1.0.10-0
libtiff: 4.0.6-3
libtool: 2.4.2-0
libxcb: 1.12-1
libxml2: 2.9.4-0
libxslt: 1.1.29-0
llvmlite: 0.18.0-py35_0
locket: 0.2.0-py35_1
lxml: 3.7.3-py35_0
markupsafe: 0.23-py35_2
matplotlib: 2.0.2-np112py35_0
mistune: 0.7.4-py35_0
mkl: 2017.0.1-0
mkl-service: 1.1.2-py35_3
mpmath: 0.19-py35_1
msgpack-python: 0.4.8-py35_0
multipledispatch: 0.4.9-py35_0
navigator-updater: 0.1.0-py35_0
nbconvert: 5.1.1-py35_0
nbformat: 4.3.0-py35_0
networkx: 1.11-py35_0
nltk: 3.2.3-py35_0
nose: 1.3.7-py35_1
notebook: 5.0.0-py35_0
numba: 0.33.0-np112py35_0
numexpr: 2.6.2-np112py35_0
numpy: 1.12.1-py35_0
numpydoc: 0.6.0-py35_0
odo: 0.5.0-py35_1
olefile: 0.44-py35_0
openpyxl: 2.4.7-py35_0
openssl: 1.0.2l-0
packaging: 16.8-py35_0
pandas: 0.20.1-np112py35_0
pandocfilters: 1.4.1-py35_0
pango: 1.40.3-1
partd: 0.3.8-py35_0
path.py: 10.3.1-py35_0
pathlib2: 2.2.1-py35_0
patsy: 0.4.1-py35_0
pcre: 8.39-1
pep8: 1.7.0-py35_0
pexpect: 4.2.1-py35_0
pickleshare: 0.7.4-py35_0
pillow: 4.1.1-py35_0
pip: 9.0.1-py35_1
pixman: 0.34.0-0
ply: 3.10-py35_0
prompt_toolkit: 1.0.14-py35_0
psutil: 5.2.2-py35_0
ptyprocess: 0.5.1-py35_0
py: 1.4.33-py35_0
pycosat: 0.6.2-py35_0
pycparser: 2.17-py35_0
pycrypto: 2.6.1-py35_6
pycurl: 7.43.0-py35_2
pyflakes: 1.5.0-py35_0
pygments: 2.2.0-py35_0
pylint: 1.6.4-py35_1
pyodbc: 4.0.16-py35_0
pyopenssl: 17.0.0-py35_0
pyparsing: 2.1.4-py35_0
pyqt: 5.6.0-py35_2
pytables: 3.3.0-np112py35_0
pytest: 3.0.7-py35_0
python: 3.5.3-1
python-dateutil: 2.6.0-py35_0
pytz: 2017.2-py35_0
pywavelets: 0.5.2-np112py35_0
pyyaml: 3.12-py35_0
pyzmq: 16.0.2-py35_0
qt: 5.6.2-4
qtawesome: 0.4.4-py35_0
qtconsole: 4.3.0-py35_0
qtpy: 1.2.1-py35_0
readline: 6.2-2
requests: 2.14.2-py35_0
rope: 0.9.4-py35_1
ruamel_yaml: 0.11.14-py35_1
scikit-image: 0.13.0-np112py35_0
scikit-learn: 0.18.1-np112py35_1
scipy: 0.19.0-np112py35_0
seaborn: 0.7.1-py35_0
setuptools: 27.2.0-py35_0
simplegeneric: 0.8.1-py35_1
singledispatch: 3.4.0.3-py35_0
sip: 4.18-py35_0
six: 1.10.0-py35_0
snowballstemmer: 1.2.1-py35_0
sortedcollections: 0.5.3-py35_0
sortedcontainers: 1.5.7-py35_0
sphinx: 1.5.6-py35_0
spyder: 3.1.4-py35_0
sqlalchemy: 1.1.9-py35_0
sqlite: 3.13.0-0
statsmodels: 0.8.0-np112py35_0
sympy: 1.0-py35_0
tblib: 1.3.2-py35_0
terminado: 0.6-py35_0
testpath: 0.3-py35_0
tk: 8.5.18-0
toolz: 0.8.2-py35_0
tornado: 4.5.1-py35_0
traitlets: 4.3.2-py35_0
unicodecsv: 0.14.1-py35_0
unixodbc: 2.3.4-0
wcwidth: 0.1.7-py35_0
werkzeug: 0.12.2-py35_0
wheel: 0.29.0-py35_0
widgetsnbextension: 2.0.0-py35_0
wrapt: 1.10.10-py35_0
xlrd: 1.0.0-py35_0
xlsxwriter: 0.9.6-py35_0
xlwt: 1.2.0-py35_0
xz: 5.2.2-1
yaml: 0.1.6-0
zeromq: 4.1.5-0
zict: 0.1.2-py35_0
zlib: 1.2.8-3
Proceed ([y]/n)? y
[root@vm envs]#
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