IPython
Overview
IPython에 대한 기술 문서입니다.
Summary
- 무엇인가? - IPython
- 왜 필요한가? - HPC 및 서버 환경에서 필수 개념
- 언제 사용하는가? - 서버 구성, 성능 튜닝, 문제 해결 시
Purpose
이 문서가 존재하는 이유
- Goal: IPython에 대한 기술 정보 제공
- Scope: IPython의 개념, 사용법, 설정
- Non-goals: 다른 주제로의 확장
Key Concepts
| Concept | Description | Related |
|---|---|---|
| IPython | HPC/서버 환경에서 중요한 기술 개념 | Linux, Server |
Detailed Explanation
IPython provides a rich architecture for interactive computing. IPython itself is focused on interactive Python, part of which is providing a Python kernel for Jupyter. This URL describes more about features by version of IPython.
IPykernel(IPython kernel) is a Jupyter kernel for Python code execution. Jupyter, and other compatible notebooks, use the IPython kernel for executing Python notebook code. pip show command shows the relationship ipython and ipykernel.
DLS$ pip show ipython
Name: ipython
Version: 8.15.0
Summary: IPython: Productive Interactive Computing
...
Requires: backcall, decorator, jedi, matplotlib-inline, pexpect, pickleshare, prompt-toolkit, pygments, stack-data, traitlets
Required-by: ipykernel
HM DLS framework utilize IPython to connect Jupyter and Conda/Mamba based on the Architecture Guides — Jupyter Documentation which shows IPython and Jupyter are connected and related.
This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. Beginning with version 6.0, IPython stopped supporting compatibility with Python versions lower than 3.3 including all versions of Python 2.7. If you are looking for an IPython version compatible with Python 2.7, need to use the IPython 5.x LTS release and refer to its documentation (LTS is the long term support release)[1]
Best Practices
- 최신 버전 사용 권장
- 공식 문서 참고
- 테스트 환경에서 먼저 검증
References
Related Pages
Knowledge Graph
Related