Features

Discover what makes IPython powerful

Smart Tab Completion

IPython's intelligent tab completion is powered by Jedi, providing context-aware suggestions for:

Object attributes and methods
Function parameters and arguments
File and directory paths
Module names and packages

In [1]: import numpy

In [2]: numpy.array.[press TAB]
append    astype    base      byteswap  ...

Magic Commands

Built-in special commands for interactive computing:

%timeit - Time code execution
%debug - Enter debugger on exception
%run - Execute Python scripts
%prun - Profile code performance
%matplotlib - Enable matplotlib integration

In [1]: %timeit sum(range(1000))
14.2 µs ± 245 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)

In [2]: %run my_script.py
Script executed successfully

In [3]: %matplotlib inline

Object Introspection

Explore objects and code interactively:

? - Show object documentation
?? - Show source code
help() - Access Python help system

In [1]: import numpy

In [2]: numpy.array?
Type:      type
String form: <class 'numpy.ndarray'>
Docstring:
ndarray(shape, dtype=float, buffer=None, offset=0,
        strides=None, order=None)

In [3]: numpy.array??
Source code for numpy.ndarray...

Rich Display System

Display rich output including:

HTML, Markdown, and LaTeX rendering
PNG, JPEG, and SVG images
Interactive plots and visualizations
Data tables and formatted output

Rich History System

Powerful command history with:

Persistent history across sessions
Search and filter history
Access previous input/output with _ and _ih
History persistence to SQLite database

In [1]: x = 10

In [2]: y = 20

In [3]: x + y
Out[3]: 30

In [4]: _
Out[4]: 30

In [5]: _ih
['x = 10', 'y = 20', 'x + y', '_', '_ih']

System Integration

Seamlessly integrate shell commands:

Run shell commands with !
Capture command output to variables
Access environment variables
Change directory with %cd

In [1]: !ls

In [2]: files = !ls *.py

In [3]: len(files)
Out[3]: 42

In [4]: %cd /tmp

Jupyter Kernel

IPython powers the Jupyter ecosystem:

Backend for Jupyter Notebook
Powers JupyterLab interactive environment
Enables remote code execution
Supports multiple programming languages through custom kernels

Features | IPython