이번 장에서는 파이썬을 개발하는데 유용한 도구에 대해 설명합니다.
1. Jupyter Notebook
Jupyter Notebook은 웹 형태로 파이썬 프로그램을 개발하고 테스트 해 볼 수 있는 편리한 도구입니다.
Jupyter Notebook은 cell 이라고 하는 블럭 단위로 Python 코드를 작성하고 실행하는데 편리한 기능을 제공합니다. 셀 단위로 코드를 작성하면 코드 전체를 한번에 개발하고 실행하는 것보다 개발과 테스트가 편리합니다. 원하는 부분만 수정하고 해당 부분만 다시 실행하고 결과를 확인해가며 데이터 분석을 할 수 있기 때문에 탐색적 분석(Exploratory Data Analysis) 방법에 매우 적합하다.
ipython 이라는 도구로 시작하여 현재의 jupyter notebook의 모습을 갖추고 있고 최근에는 Jupyter Lab이라고 하는 좀더 개선된 UI를 갖는 도구도 제공합니다.
최근에는 각 클라우드 서비스 기업(CSP)에서 도구 형태로 제공하기도 하며 구글에서는 Colab이라는 이름으로 무료로 CPU와 GPU를 사용해 개발 및 테스트 해볼 수 있는 도구를 제공하기도 합니다.
1.1 Jupyter Notebook 설치
Jupyter Notebook을 설치하는 가장 쉬운 방법은 Anaconda Navigator를 이용하는 것입니다. 만일 파이썬 개발 환경을 구성하기 위해 Anaconda를 설치 했다면 Anaconda Navigator를 실행해 Jupyter Notebook이나 Jupyter Lab을 설치(Install)하고 실행(Launch) 하면 됩니다. 만일 Anaconda를 설치하지 않았다면 직접 설치해야 합니다.
Jupyter Notebook 직접 설치
먼저 사용할 파이썬 가상 환경을 활성화 합니다.
$ cd d:devmy_venv
$ pip install jupyter
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Installing collected packages: webencodings, wcwidth, Send2Trash, pywin32, pure-eval, pickleshare, mistune, ipython-genutils, fastjsonschema, executing, backcall, widgetsnbextension, websocket-client, webcolors, uri-template, traitlets, tornado, tinycss2, soupsieve, sniffio, six, rfc3986-validator, pyzmq, pyyaml, pywinpty, python-json-logger, pyrsistent, pygments, pycparser, psutil, prompt-toolkit, prometheus-client, platformdirs, parso, pandocfilters, packaging, nest-asyncio, markupsafe, jupyterlab-widgets, jupyterlab-pygments, jsonpointer, idna, fqdn, defusedxml, decorator, debugpy, colorama, attrs, terminado, rfc3339-validator, qtpy, python-dateutil, matplotlib-inline, jupyter-core, jsonschema, jinja2, jedi, comm, cffi, bleach, beautifulsoup4, asttokens, anyio, stack-data, nbformat, jupyter-server-terminals, jupyter-client, arrow, argon2-cffi-bindings, nbclient, isoduration, ipython, argon2-cffi, nbconvert, ipykernel, qtconsole, jupyter-events, jupyter-console, ipywidgets, jupyter-server, notebook-shim, nbclassic, notebook, jupyter
Successfully installed Send2Trash-1.8.0 anyio-3.6.2 argon2-cffi-21.3.0 argon2-cffi-bindings-21.2.0 arrow-1.2.3 asttokens-2.2.1 attrs-22.2.0 backcall-0.2.0 beautifulsoup4-4.11.1 bleach-6.0.0 cffi-1.15.1 colorama-0.4.6 comm-0.1.2 debugpy-1.6.6 decorator-5.1.1 defusedxml-0.7.1 executing-1.2.0 fastjsonschema-2.16.2 fqdn-1.5.1 idna-3.4 ipykernel-6.20.2 ipython-8.9.0 ipython-genutils-0.2.0 ipywidgets-8.0.4 isoduration-20.11.0 jedi-0.18.2 jinja2-3.1.2 jsonpointer-2.3 jsonschema-4.17.3 jupyter-1.0.0 jupyter-client-8.0.1 jupyter-console-6.4.4 jupyter-core-5.1.5 jupyter-events-0.6.3 jupyter-server-2.1.0 jupyter-server-terminals-0.4.4 jupyterlab-pygments-0.2.2 jupyterlab-widgets-3.0.5 markupsafe-2.1.2 matplotlib-inline-0.1.6 mistune-2.0.4 nbclassic-0.5.1 nbclient-0.7.2 nbconvert-7.2.9 nbformat-5.7.3 nest-asyncio-1.5.6 notebook-6.5.2 notebook-shim-0.2.2 packaging-23.0 pandocfilters-1.5.0 parso-0.8.3 pickleshare-0.7.5 platformdirs-2.6.2 prometheus-client-0.16.0 prompt-toolkit-3.0.36 psutil-5.9.4 pure-eval-0.2.2 pycparser-2.21 pygments-2.14.0 pyrsistent-0.19.3 python-dateutil-2.8.2 python-json-logger-2.0.4 pywin32-305 pywinpty-2.0.10 pyyaml-6.0 pyzmq-25.0.0 qtconsole-5.4.0 qtpy-2.3.0 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 six-1.16.0 sniffio-1.3.0 soupsieve-2.3.2.post1 stack-data-0.6.2 terminado-0.17.1 tinycss2-1.2.1 tornado-6.2 traitlets-5.8.1 uri-template-1.2.0 wcwidth-0.2.6 webcolors-1.12 webencodings-0.5.1 websocket-client-1.5.0 widgetsnbextension-4.0.5설치가 완료 되었으면 다음 명령을 이용해 Jupyter Notebook을 실행합니다.
$ python -m notebook주피터 노트북을 실행하면 아래와 같이 웹서버가 실행되고 자동으로 웹 브라우저가 실행됩니다.
접속 주소는 http://localhost:8888이 기본이며, 기존에 해당 포트를 사용중이라면 다른 포트로 열리기도 합니다.
실행중인 Jupyter Notebook을 중단하려면 Jupyter Notebook을 실행한 명령창에서 Ctrl + C 키를 여러번 클릭하면 됩니다.
Anaconda에서 Jupyter Notebook 설치
Anaconda에서 Jupyter Notebook을 설치하는 방법은 매우 간단합니다.
우선 Anaconda Navigator를 실행합니다. 그리고 Home 화면 우측에서 Jupyter Notebook을 찾아 설치(Install)을 클릭해 설치합니다.
Jupyter Notebook을 실행하려면 Anaconda Navigator의 Home 화면에서 Jupyter Notebook의 Launch 버튼을 클릭하면 됩니다.
