Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to content
Python Land
  • Python Tutorial
  • Shop
  • Blog
  • Login / Register
  • Contact
0
Home » Tips & Tricks » Using IPython
IPython

Using IPython

April 30, 2022

IPython is an enhanced Python REPL, and it’s actually the core for Jupyter notebook. In short, Jupyter is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. If you use the interactive shell a lot and you don’t know IPython, you should really check this one out!

Table of Contents

  • 1 IPython features
  • 2 Magic commands
  • 3 Referencing previous input and output
  • 4 Install IPython

IPython features

Some of the features the IPython shell offers are:

  • Comprehensive object introspection.
  • Input history, persistent across sessions.
  • Caching of output results during a session with automatically generated references.
  • Tab completion, with support for completion of python variables and keywords, filenames, and Python functions.
  • Magic commands for controlling the environment and performing many tasks.
  • Session logging and reloading.
  • Integrated access to the pdb debugger and the Python profiler.
  • A less known feature of IPython: its architecture also allows for parallel and distributed computing.

Magic commands

These are just a selection of the magic commands that are built into IPython that I think you’ll like:

  • %cd — change the current working directory
  • %edit — open an editor and execute the code you typed in after closing the editor
  • %env — show the current environment variables
  • %pip install [pkgs] — install packages without leaving the interactive shell
  • %time and %timeit — time the execution of Python code

Read the full list in the documentation here.

Referencing previous input and output

Another useful feature is referencing the input and output of a previous command. In and Out are actual objects. You can use the output of the 3rd command by using Out[3]. You can re-execute the third command with In[3].

Install IPython

You probably know the drill, but just to be complete, here’s how you install IPython with pip install:

$ pip install ipython

Although it’s often better to use a virtual environment, in this case you may want to install it system-wide or for your entire user account with pip install --user.

Get certified with our courses

Learn Python properly through small, easy-to-digest lessons, progress tracking, quizzes to test your knowledge, and practice sessions. Each course will earn you a downloadable course certificate.

  • Sale Product on sale
    The Python Course for Beginners
    Beginners Python Course (2024)
    € 59.00 Original price was: € 59.00.€ 39.00Current price is: € 39.00.
  • Sale Product on sale
    Computer Fundamentals
    Files, Folders, And The Command Line (2024)
    € 39.00 Original price was: € 39.00.€ 19.00Current price is: € 19.00.
  • Sale Product on sale
    Modules, Packages, And Virtual Environments (2024)
    Modules, Packages, And Virtual Environments (2024)
    € 59.00 Original price was: € 59.00.€ 39.00Current price is: € 39.00.

Leave a Comment Cancel reply

You must be logged in to post a comment.

Subscribe to my newsletter for Python news, tips, and tricks!

Footer subscribe

  • Home
  • Python Courses
  • Privacy Policy
  • About Us
  • Contact us
©2025 Python Land - All rights reserved
Python Land is not affiliated with Python.org or the Python Software Foundation
  • Free Tutorial
    • Install Python
      • Online Python Interpreter
      • How To Open Python on Windows, Mac, Linux
    • Introduction to Python
      • The Python REPL
      • Python Variable
      • Python String
      • Python Print function
      • Python Booleans
      • For-loop and While-loop
      • Python Functions
      • Your First Python Program
      • Python Comments
    • Creating Python Programs
      • The Best Python IDE
      • Installing VSCode
      • VSCode Python Extensions
      • VSCode GUI Tour
      • Python in VSCode: Running and Debugging
    • Classes and Objects in Python
      • Python Constructor
      • Python Inheritance
    • Structure Your Project
      • Python Modules And Importing
      • Python Packages
    • Python Data Types
      • Python Integer
      • Python Float
      • Python Tuple
      • Python List
      • Python Set
      • Python Dictionary
    • Language Deep Dives
      • Python Try Except (Exceptions)
      • Python Functions: Advanced Concepts
      • List Comprehension
      • Python Iterator
      • Python Range
      • Python Docstrings
      • Python pass (Do Nothing)
    • Interaction with the OS
      • Python Read And Write File
      • Python Subprocess: Run External Commands
    • Venvs / Package Management
      • Working With Python’s venv
      • Pip install: the Python package manager
      • Python Poetry: Package and venv Management Made Easy
      • Python Pipenv: Another Package Manager
      • Pipx: Safely Install Packages Globally
    • Python Concurrency
      • The Python GIL (Global Interpreter Lock)
      • Setting the Baseline
      • Python Threading
      • Python Multiprocessing
    • Data Processing with Python
      • Working With JSON
        • JMESPath Python: JSON Query Language
      • Python YAML: How to Load, Read, and Write YAML
      • Python CSV: Read And Write CSV Files
    • Migrating From Python 2 to 3
      • Check Python Version On The Command-Line
      • How to Migrate To Python 3
      • Python 3 Advantages
    • Using The Unix Shell
      • Basic Linux Commands
      • Bash Scripts
      • Using the Find Command in Linux
      • Unix Pipes
      • Process and Highlight JSON with jq
      • Using the Bash History
      • Bash Multiprocessing
    • Deployment
      • PyInstaller: Create An Executable From Python Code
      • How To Use Docker To Containerize Your Python Project
      • Automatically Build and Deploy Your Python Application with CI/CD
      • Guerrilla Scale Your Web Application
    • Data Science
      • Jupyter Notebook
      • NumPy: Getting Started Tutorial
    • Python Learning Resources
  • Python Courses
  • Blog
  • Login / Register