통일된 DataScience 폴더 구조 제공 및 가상환경 작업의 부담감 해소

Related tags

Deep LearningLucas
Overview


Lucas

Hits


coded by linux shell

목차


Patch Note 📜


Team member

Contributors/People

ympark gbhwang cbchun
https://github.com/pym7857 https://github.com/gbhwang https://github.com/bermmie1000
  • You can see team member and github profile
  • You should probably find team member's lastest project



Requirements

  • python 3.xx



Mac버전 CookieCutter (autoenv)

🚫 주의
$> brew install autoenv 로 다운로드 받아서 실행시키면 터미널 고장납니다.
반드시 autoenv Github 에서 git clone 으로 다운받아 주세요. (현재 시점 21.3.24)

⚠️ mac버전만 소개합니다.

1. How to Install autoenv

$ git clone git://github.com/inishchith/autoenv.git ~/.autoenv

2.폴더 진입 시, activate 구현하기

$ echo 'source ~/.autoenv/activate.sh' >> ~/.zshrc
$ source ~/.zshrc

🔔 하단의.env파일은 현재 repo의 cookiecutter에서 자동으로 생성해줍니다. (스킵)

# .env 파일
echo "HELLO autoenv"
{
    source .dev-venv/bin/activate
    echo "virtual env is successfully activated!"
} ||
{
    echo "[virtual env start] is failed!"
}

.env파일 설정 후 첫 폴더 진입시 .env파일을 신뢰하고 실행할지 않을 지에 대한 동의가 나타납니다. autoenv 이 부분은 .env파일이 악의적으로 변경되었을때 사용자에게 알리기 위해서 있기 때문에 즐거운 마음으로 Y를 눌러줍시다.
이제 정상적으로 가상환경이 activate된 것을 확인할 수 있습니다.

3.폴더 탈출 시, deactivate 구현하기

$> vi ~/.zshrc

마지막줄에 다음의 명령어를 추가해줍니다.

export AUTOENV_ENABLE_LEAVE='"enabled"' 

🔔 하단의.env.leave파일은 현재 repo의 cookiecutter에서 자동으로 생성해줍니다. (스킵)

# .env.leave 파일
echo "BYEBYE"
{
    deactivate
    echo "virtual env is successfully deactivated!"
} ||
{
    echo "[virtual env quit] is failed!"
}

.env.leave파일 설정 후 해당 폴더에서 나가면
정상적으로 가상환경이 deactivate 되는 것을 확인할 수 있습니다.

4.Alias 설정하기

echo 'alias cookie="bash [각자 컴퓨터의 상대경로/cookie_cutter_project_dir.sh]"' >> ~/.zshrc
ex) echo 'alias cookie="bash /Users/gbhwang/Desktop/Project/Test/Lucas/mac/cookie_cutter_project_dir.sh"' >> ~/.zshrc

맥 파일경로 확인법을 참고하여
각자 mac폴더안의 cookie_cutter_project_dir.sh 파일의 경로를 확인하여 zshrc에 넣어주시면 됩니다.

이렇게 하면 cookie 명령어 만으로 간단하게 스크립트를 실행시킬 수 있게 됩니다.
위와 같이 설정하면 cookie [프로젝트 생성할 경로] [프로젝트 이름] 명령어로 프로젝트를 생성할 수 있게 됩니다.

5.How to Use

$> cd "where-you-want"
$> git clone https://github.com/LS-ELLO/Lucas.git
$> cd Lucas
$> cd mac

$> cookie [where-you-want] [your-project-name]
ex) $> cookie . test111



Windows버전 CookieCutter (ps-autoenv)

도움 주신 규본님 감사합니다.
ps-autoenv를 사용합니다.

1.How to install ps-autoenv

Powershell 실행 (관리자 권한 실행)

PS> Install-Module ps-autoenv
PS> Add-Content $PROFILE @("`n", "import-module ps-autoenv")

2.Alias 설정하기 (git-bash)

참조

  1. C:/Program Files/Git/etc/profile.d/aliases.sh 파일을 관리자 권한으로 Text Editor에 실행시킵니다.

  2. 다음의 명령어를 추가합니다.
    alias cookie='bash cookie_cutter_project_dir.sh의 상대경로'
    ex) alias cookie='bash D:/Lucas/windows/cookie_cutter_project_dir.sh'

    (aliases.sh)

    # Some good standards, which are not used if the user
    # creates his/her own .bashrc/.bash_profile
    
    # --show-control-chars: help showing Korean or accented characters
    alias ls='ls -F --color=auto --show-control-chars'
    alias ll='ls -l'
    alias cookie='bash [where-your-cookie_cutter_project_dir.sh]'
    
    case "$TERM" in
    ...

3.How to Use

Git Bash 실행

bash> cd "where-this-repo-downloaded"
bash> cd windows
bash> cookie [where-you-want] [your-project-name]
ex) cookie . 1bot

Powershell 실행

PS> Import-Module ps-autoenv
PS> cd "where-your-cookiecutter-project"
ex. PS> cd "C:\Users\ympark4\Documents\1bot"
PS> press 'Y'
🚫 PSSecurityException 오류 발생할때

https://extbrain.tistory.com/118 를 참조해서 해결주세요.



The resulting directory structure

The directory structure of your new project looks like this:

├── LICENSE
├── Makefile
├── README.md          ← The top-level README for developers using this project.
├── data
│   ├── external       ← Data from third party sources.
│   ├── interim        ← Intermediate data that has been transformed.
│   ├── processed      ← The final, canonical data sets for modeling.
│   └── raw            ← The original, immutable data dump.
├── docs               ← A default Sphinx project; see sphinx-doc.org for details
├── models             ← Trained and serialized models, model predictions, or model summaries
├── notebooks          ← Jupyter notebooks. Naming convention is a number (for ordering), the creator's initials, and a short `-` delimited description, e.g. `1.0-jqp-initial-data-exploration`.
├── references         ← Data dictionaries, manuals, and all other explanatory materials.
├── reports            ← Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        ← Generated graphics and figures to be used in reporting
├── requirements.txt   ← The requirements file for reproducing the analysis environment, e.g. generated with `pip freeze > requirements.txt`
├── setup.py           ← makes project pip installable (pip install -e .) so src can be imported
├── src                ← Source code for use in this project.
│   ├── __init__.py  
│   ├── dataread      
│   │   └── __init__.py
│   │   └── example.py
│   │
│   ├── features       
│   │   └── __init__.py
│   │   └── example.py
│   │
│   ├── models     
│   │   └── __init__.py
│   │   └── example.py
│   │
│   ├── visualization    
│   │   └── __init__.py
│   │   └── example.py
├── App               
│   ├── android       
│   ├── ios           
│   ├── lib            
│   │   └── models
│   │   └── main.dart
│
└── .gitignore        



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