Skip to main content
Join the official 2019 Python Developers SurveyStart the survey!

Library for building powerful interactive command lines in Python

Project description

Build Status AppVeyor Latest Version RTD License Codecov

``prompt_toolkit`` is a library for building powerful interactive command line applications in Python.

Read the documentation on readthedocs.

NOTICE: prompt_toolkit 2.0

Please notice that this is prompt_toolkit 2.0. It is incompatible with the 1.0 branch, but much better in many regards. Many applications are still using prompt_toolkit 1.0, but upgrading is strongly recommended. Feel free to open a new issue if you don’t manage to upgrade to prompt_toolkit 2.0.


ptpython is an interactive Python Shell, build on top of prompt_toolkit.

prompt_toolkit features

prompt_toolkit could be a replacement for GNU readline, but it can be much more than that.

Some features:

  • Pure Python.
  • Syntax highlighting of the input while typing. (For instance, with a Pygments lexer.)
  • Multi-line input editing.
  • Advanced code completion.
  • Both Emacs and Vi key bindings. (Similar to readline.)
  • Even some advanced Vi functionality, like named registers and digraphs.
  • Reverse and forward incremental search.
  • Runs on all Python versions from 2.6 up to 3.7.
  • Works well with Unicode double width characters. (Chinese input.)
  • Selecting text for copy/paste. (Both Emacs and Vi style.)
  • Support for bracketed paste.
  • Mouse support for cursor positioning and scrolling.
  • Auto suggestions. (Like fish shell.)
  • Multiple input buffers.
  • No global state.
  • Lightweight, the only dependencies are Pygments, six and wcwidth.
  • Runs on Linux, OS X, FreeBSD, OpenBSD and Windows systems.
  • And much more…

Feel free to create tickets for bugs and feature requests, and create pull requests if you have nice patches that you would like to share with others.

About Windows support

prompt_toolkit is cross platform, and everything that you build on top should run fine on both Unix and Windows systems. On Windows, it uses a different event loop (WaitForMultipleObjects instead of select), and another input and output system. (Win32 APIs instead of pseudo-terminals and VT100.)

It’s worth noting that the implementation is a “best effort of what is possible”. Both Unix and Windows terminals have their limitations. But in general, the Unix experience will still be a little better.

For Windows, it’s recommended to use either cmder or conemu.


pip install prompt_toolkit

For Conda, do:

conda install -c prompt_toolkit

Getting started

The most simple example of the library would look like this:

from prompt_toolkit import prompt

if __name__ == '__main__':
    answer = prompt('Give me some input: ')
    print('You said: %s' % answer)

For more complex examples, have a look in the examples directory. All examples are chosen to demonstrate only one thing. Also, don’t be afraid to look at the source code. The implementation of the prompt function could be a good start.

Note for Python 2: all strings are expected to be unicode strings. So, either put a small u in front of every string or put from __future__ import unicode_literals at the start of the above example.

Projects using prompt_toolkit


  • ptpython: Python REPL
  • ptpdb: Python debugger (pdb replacement)
  • pgcli: Postgres client.
  • mycli: MySql client.
  • litecli: SQLite client.
  • wharfee: A Docker command line.
  • xonsh: A Python-ish, BASHwards-compatible shell.
  • saws: A Supercharged AWS Command Line Interface.
  • cycli: A Command Line Interface for Cypher.
  • crash: Crate command line client.
  • vcli: Vertica client.
  • aws-shell: An integrated shell for working with the AWS CLI.
  • softlayer-python: A command-line interface to manage various SoftLayer products and services.
  • ipython: The IPython REPL
  • click-repl: Subcommand REPL for click apps.
  • haxor-news: A Hacker News CLI.
  • gitsome: A Git/Shell Autocompleter with GitHub Integration.
  • http-prompt: An interactive command-line HTTP client.
  • coconut: Functional programming in Python.
  • Ergonomica: A Bash alternative written in Python.
  • Kube-shell: Kubernetes shell: An integrated shell for working with the Kubernetes CLI
  • mssql-cli: A command-line client for Microsoft SQL Server.
  • robotframework-debuglibrary: A debug library and REPL for RobotFramework.
  • ptrepl: Run any command as REPL
  • clipwdmgr: Command Line Password Manager.
  • slacker: Easy access to the Slack API and admin of workspaces via REPL.
  • EdgeDB: The next generation object-relational database.
  • pywit: Python library for
  • objection: Runtime Mobile Exploration.
  • habu: Python Network Hacking Toolkit.
  • nawano: Nano cryptocurrency wallet
  • athenacli: A CLI for AWS Athena.
  • vulcano: A framework for creating command-line applications that also runs in REPL mode.

Full screen applications:

  • pymux: A terminal multiplexer (like tmux) in pure Python.
  • pyvim: A Vim clone in pure Python.
  • freud: REST client backed by SQLite for storing servers
  • pypager: A $PAGER in pure Python (like “less”).
  • kubeterminal: Kubectl helper tool.


  • ptterm: A terminal emulator widget for prompt_toolkit.
  • PyInquirer: A Python library that wants to make it easy for existing Inquirer.js users to write immersive command line applications in Python.

(Want your own project to be listed here? Please create a GitHub issue.)


The source code of prompt_toolkit should be readable, concise and efficient. We prefer short functions focusing each on one task and for which the input and output types are clearly specified. We mostly prefer composition over inheritance, because inheritance can result in too much functionality in the same object. We prefer immutable objects where possible (objects don’t change after initialization). Reusability is important. We absolutely refrain from having a changing global state, it should be possible to have multiple independent instances of the same code in the same process. The architecture should be layered: the lower levels operate on primitive operations and data structures giving – when correctly combined – all the possible flexibility; while at the higher level, there should be a simpler API, ready-to-use and sufficient for most use cases. Thinking about algorithms and efficiency is important, but avoid premature optimization.

Special thanks to

  • Pygments: Syntax highlighter.
  • wcwidth: Determine columns needed for a wide characters.

Other libraries and implementations in other languages

  • go-prompt: building a powerful interactive prompt in Go, inspired by python-prompt-toolkit.
  • urwid: Console user interface library for Python.

Project details

Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for prompt-toolkit-dob, version 2.0.9
Filename, size File type Python version Upload date Hashes
Filename, size prompt_toolkit_dob-2.0.9-py3-none-any.whl (340.6 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size prompt_toolkit-dob-2.0.9.tar.gz (348.7 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page