python-prompt-toolkit README

The project's README from github.com/prompt-toolkit/python-prompt-toolkit. As one markdown file: README.md.

Python Prompt Toolkit

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.. image :: /docs/images/logo_400px.png

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

Read the documentation on readthedocs <http://python-prompt-toolkit.readthedocs.io/en/stable/>_.

Gallery


ptpython <http://github.com/prompt-toolkit/ptpython/>_ is an interactive Python Shell, build on top of prompt_toolkit.

.. image :: /docs/images/ptpython.png

More examples <https://python-prompt-toolkit.readthedocs.io/en/stable/pages/gallery.html>_

prompt_toolkit features


prompt_toolkit could be a replacement for GNU readline <https://tiswww.case.edu/php/chet/readline/rltop.html>_, but it can be much more than that.

Some features:

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.

Installation


::

pip install prompt_toolkit

For Conda, do:

::

conda install -c https://conda.anaconda.org/conda-forge prompt_toolkit

About Windows support


prompt_toolkit is cross platform, and everything that you build on top should run fine on both Unix and Windows systems. Windows support is best on recent Windows 10 builds, for which the command line window supports vt100 escape sequences. (If not supported, we fall back to using Win32 APIs for color and cursor movements).

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.

Getting started


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

.. code:: python

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.

Philosophy


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.

Projects using prompt_toolkit <PROJECTS.rst>_


Special thanks to


.. |PyPI| image:: https://img.shields.io/pypi/v/prompt_toolkit.svg :target: https://pypi.python.org/pypi/prompt-toolkit/ :alt: Latest Version

.. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/32r7s2skrgm9ubva?svg=true :target: https://ci.appveyor.com/project/prompt-toolkit/python-prompt-toolkit/

.. |RTD| image:: https://readthedocs.org/projects/python-prompt-toolkit/badge/ :target: https://python-prompt-toolkit.readthedocs.io/en/master/

.. |License| image:: https://img.shields.io/github/license/prompt-toolkit/python-prompt-toolkit.svg :target: https://github.com/prompt-toolkit/python-prompt-toolkit/blob/master/LICENSE

.. |Codecov| image:: https://codecov.io/gh/prompt-toolkit/python-prompt-toolkit/branch/master/graphs/badge.svg?style=flat :target: https://codecov.io/gh/prompt-toolkit/python-prompt-toolkit/

python-prompt-toolkit (prompt-toolkit/python-prompt-toolkit)

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这是什么?prompt_toolkit 是一个 Python 库,用于构建功能强大的交互式命令行应用——它是用来编写你自己的终端应用的,不能直接运行。
这是一个我写代码时用的库,还是一个安装后直接运行的程序?它是一个库:你需要把它导入到自己的 Python 项目里,用来开发交互式命令行应用。它本身不提供任何面向最终用户的程序。
怎么把它装到我的 Python 项目里?从 PyPI 获取这个包(pip install prompt_toolkit),然后照着 Read the Docs 上的文档一步步学就行。
除了 Python 之外还需要什么?Python 是基本要求。在底层,它依靠 Pygments 实现语法高亮,用 wcwidth 来计算宽字符占用的列宽。
这是个刚起步的实验项目,还是成熟的老项目?很成熟——代码仓库创建于 2014 年 1 月,在 GitHub 上有大约 10,600 颗星。
中文、日文这类宽字符文字能正确对齐吗?可以——它会计算宽字符所需的列数,所以中日韩(CJK)等全角字符都能保持对齐。
它能在终端里给代码做语法高亮吗?语法高亮来自 Pygments,README 里也提到了这个高亮工具——具体细节可以看文档。
它可以免费使用吗,包括商业用途?可以——它采用宽松的 BSD-3-Clause 许可证发布,商用完全没问题。
What are similar projects?rich, tview, fish-shell, ink, ratatui, Inquirer.js, click, FTXUI
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