樹莓派、樹莓派之學習、樹莓派之教育

學習新天地

初九麻生

IPython provides a rich architecture for interactive computing with:

  • A powerful interactive shell.
  • A kernel for Jupyter.
  • Support for interactive data visualization and use of GUI toolkits.
  • Flexible, embeddable interpreters to load into your own projects.
  • Easy to use, high performance tools for parallel computing.

IPython clients

To get started with IPython in the Jupyter Notebook, see our official example collection. Our notebook gallery is an excellent way to see the many things you can do with IPython while learning about a variety of topics, from basic programming to advanced statistics or quantum mechanics.

To learn more about IPython, you can download our talks and presentations, or read our extensive documentation. IPython is open source (BSD license), and is used by a range of other projects; add your project to that list if it uses IPython as a library, and please don’t forget to cite the project.

IPython supports Python 2.7 and 3.3 or newer. Our older 1.x series supports Python 2.6 and 3.2.

Jupyter and the future of IPython

IPython is a growing project, with increasingly language-agnostic components. IPython 3.x was the last monolithic release of IPython, containing the notebook server, qtconsole, etc. As of IPython 4.0, the language-agnostic parts of the project: the notebook format, message protocol, qtconsole, notebook web application, etc. have moved to new projects under the name Jupyter. IPython itself is focused on interactive Python, part of which is providing a Python kernel for Jupyter.

 

初十豆。

About Project Jupyter

Project Jupyter was born out of the IPython Project in 2014 as it evolved to support interactive data science and scientific computing across all programming languages.

 

notebook iconThe Jupyter Notebook

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.

 

打造樹莓派學習新天地！

Jupyter Notebook Server on Raspberry Pi 2 and 3

Intro

Sliderules are a thing of the past, decent calculators are hard to get by these days and spreadsheets are somewhat cumbersome, at times outright dangerous or just not the right tool for many tasks. Project Jupyter not only revolutionizes data-heavy research in all domains – it also boosts personal productivity for problems on a much smaller scale.

This repository documents my efforts to set up and configure a Jupyter Notebook Server on a Raspberry Pi 2 or 3 complete with Python 3.6.0, fully functioning nbconvert and a basic scientific stack with version 4.0 or later of all components making up the brilliant Jupyter interactive computing environment.

Requirements

  • a Raspberry Pi 2 or 3 complete with 5V micro-usb power-supply
  • a blank 16 GB micro SD card
  • an ethernet cable to connect the Pi to your network *)
  • an internet connection
  • a computer to carry out the installation connected to the same network as the Pi
  • a fair amount of time – user feedback suggestst that a full installation takes in the order of 6 hours…

 

若問工具如何用？溫故知新兩相宜。

學習『工具』最簡單的方法，就是『使用』它︰

pi@raspberrypi:~ $ ipython3
Python 3.4.2 (default, Oct 19 2014, 13:31:11) 
Type "copyright", "credits" or "license" for more information.

IPython 2.3.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]:

 

不過對此『工具』是什麼□○都尚且不知，又將如何『使用』呢？通常『工具』的『使用』始於閱讀『概觀』︰

─── 摘自《光的世界︰派生科學計算一》