(Environment) (Window) Anaconda 환경 설정 및 자주 사용되는 명령어

 Anaconda  환경 설정 및 자주 사용되는 명령어 


Python 설치와 이에 기반한 프로젝트를 수행을 위해서는 버전을 고려한 Anaconda 설치는 물론 확보 하고자 하는 기술 또는 서비스를 효율적으로 개발 가능하게 하는 Opensource , library 의 활용 조건에 맞는 다양한 환경 설정 작업이 요구 됩니다.

개인적으로는 이것이 Python 의 장점이자 단점이라 생각 합니다.

이에 ML/DL은 물론 강화 학습 이나, 자연어 처리, 컴퓨터 비전 프로젝트 수행을 위해 사용되는 환경 설정 방법과 명령어를 정리 하고 공유 하고자 합니다.


Anaconda  환경 설정 및 자주 사용되는 명령어 




1. Anaconda 설치 

  • 설치 파일 다운로드 :  https://www.anaconda.com/products/individual 
    • 각자의 환경 (본인은 윈도우10 6bit) 에 맞는 파일 다운로드 후 설치
      • Windows 항목에 있는 "64-Bit Graphical Installer"
  • Anaconda 설치후
    • 필요한  모듈을 설치 하는 방법
      • "시작 메뉴" > "Anaconda3" > "Anaconda Powershell Prompt" 클릭
      • 파이썬의 pip 사용
        • 일반 : pip install opencv
        • 권한 오류 발생 시: pip install opencv--user



2. 가상 환경 설정 (윈도우 환경)
  • 콘다 설치 확인: conda -V
  • 가상 환경
    •  생성 : conda create -n 가상 환경 이름 python=3.6 (파이썬버전)
      • conda create -n test python=3.6 //파이썬 버전 3.5인 test 라는 이름의 env
    • 가상환경 나가기 : source deactivate
    • 가상환경 리스트 확인: conda info --envs
    • 가상 환경 활성화 : conda activate 가상환경 이름 
      • 진입하면 (base) -> (가상환경이름) 으로 명령 대기창 이름 변경 됨
    • 가상 환경 비활성화  : conda deactivat         
  • 가상환경 삭제 : conda env remove -n myenv 

  • 패키지 search : conda search package         
  • 패키지 설치 :
    • 기본 : conda install -n yourenvname package
    • 버전 지정 : conda install scipy=0.15.0
    • 사용자 채널 '-cv': conda install -c plotly plotly 
    • 설치 확인: conda list
    • 패키지업데이트 : conda update biopython
    • 패키지 제거 : conda remove -n myenv scipy
  • 가상환경에서 패키지가 conda install 패키지이름 으로 다운되지 않을 떄
    •  conda install -c conda-forge 패키지이름 //  -c conda-forge 는 다운로드 받을 때 다른 channel 로 받는 것임 

            




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