What is Jupyter Notebook (1)
Definition & Installation
When working with Python, you will need an interactive computing and development environment. The tax editor or the original Python shell is not enough due to the lack of functionality. A lot of people choose an Integrated Development Environment(IDE) because of their functions and supports. In scientific Python computing area, Jupyter Notebook(used to be called “iPython”) is one of the most important part of workflow. Many IDEs provide integration with Jupyter Notebook as well. Normally, you will use IDE or a text editor to stores all the codes, and use Jupyter Notebook to test pieces. Jupyter Notebook provides an interactive environment to code and compute. It will show the results immediately.
Since Python has a lot of modules, and it will be hard to install one-by-one. Anaconda is probably one of the best options to install Python and Jupyter Notebook to your computer. You can use this link to download, and simply follow the instructions to install to your computer. Since I am using a MAC, all the examples in this article will be written in Bash. Other than using Jupyter Notebook shell, you can also use Jupyter Notebook website for better presentation.
After installing, you can simply type
iPython in terminal. You can type quit() to exit Jupyter Notebook if you need.
Launch & Quit
Python 3.5.2 |Anaconda custom (x86_64)| (default, Jul 2 2016, 17:52:12)
Type "copyright", "credits" or "license" for more information.
IPython 5.1.0 -- 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 : quit()
One of the key features of Jupyter is the tab completion. When you type the first few letters of a function, objects or other variables, after hitting , jupyter will show all the possible variables you can choose.
In : s + <tab>
%save %set_env sorted sum %%sx
%sc setattr staticmethod super %system
%%script %%sh %store %%svg %%system
set slice str %sx
When you are working in Jupyter Notebook, and want to find the documentation of some variables. You do not need to search on the website. You can simply use a question mark (?) after that variable to find the documentation directly.
In : list?
Init signature: list(self, /, *args, **kwargs)
list() -> new empty list
list(iterable) -> new list initialized from iterable's items
Use two question marks (??) can show the source code of a function if possible.
When combining ? with *, you can search for names matching the expression.
In : m*?