Upgrading to prompt_toolkit 2.0¶
Prompt_toolkit 2.0 is not compatible with 1.0, however you probably want to upgrade your applications. This page explains why we have these differences and how to upgrade.
If you experience some difficulties or you feel that some information is missing from this page, don’t hesitate to open a GitHub issue for help.
Why all these breaking changes?¶
After more and more custom prompt_toolkit applications were developed, it became clear that prompt_toolkit 1.0 was not flexible enough for certain use cases. Mostly, the development of full screen applications was not really natural. All the important components, like the rendering, key bindings, input and output handling were present, but the API was in the first place designed for simple command line prompts. This was mostly notably in the following two places:
- First, there was the focus which was always pointing to a
Buffer(or text input widget), but in full screen applications there are other widgets, like menus and buttons which can be focused.
- And secondly, it was impossible to make reusable UI components. All the key
bindings for the entire applications were stored together in one
KeyBindingsobject, and similar, all
Bufferobjects were stored together in one dictionary. This didn’t work well. You want reusable components to define their own key bindings and everything. It’s the idea of encapsulation.
For simple prompts, the changes wouldn’t be that invasive, but given that there would be some, I took the opportunity to fix a couple of other things. For instance:
- In prompt_toolkit 1.0, we translated \r into \n during the input processing. This was not a good idea, because some people wanted to handle these keys individually. This makes sense if you keep in mind that they correspond to Control-M and Control-J. However, we couldn’t fix this without breaking everyone’s enter key, which happens to be the most important key in prompts.
Given that we were going to break compatibility anyway, we changed a couple of other important things that effect both simple prompt applications and full screen applications. These are the most important:
We no longer depend on Pygments for styling. While we like Pygments, it was not flexible enough to provide all the styling options that we need, and the Pygments tokens were not ideal for styling anything besides tokenized text.
Instead we created something similar to CSS. All UI components can attach classnames to themselves, as well as define an inline style. The final style is then computed by combining the inline styles, the classnames and the style sheet.
There are still adaptors available for using Pygments lexers as well as for Pygments styles.
The way that key bindings were defined was too complex.
KeyBindingsManagerwas too complex and no longer exists. Every set of key bindings is now a
KeyBindingsobject and multiple of these can be merged together at any time. The runtime performance remains the same, but it’s now easier for users.
The separation between the
Applicationclass was confusing and in the end, didn’t really had an advantage. These two are now merged together in one
We no longer pass around the active
CommandLineInterface. This was one of the most annoying things. Key bindings need it in order to change anything and filters need it in order to evaluate their state. It was pretty annoying, especially because there was usually only one application active at a time. So,
TaskLocal. That is like a global variable, but scoped in the current coroutine or context. The way this works is still not 100% correct, but good enough for the projects that need it (like Pymux), and hopefully Python will get support for this in the future thanks to PEP521, PEP550 or PEP555.
All of these changes have been tested for many months, and I can say with confidence that prompt_toolkit 2.0 is a better prompt_toolkit.
Some new features¶
Apart from the breaking changes above, there are also some exciting new features.
We now support vt100 escape codes for Windows consoles on Windows 10. This means much faster rendering, and full color support.
We have a concept of formatted text. This is an object that evaluates to styled text. Every input that expects some text, like the message in a prompt, or the text in a toolbar, can take any kind of formatted text as input. This means you can pass in a plain string, but also a list of (style, text) tuples (similar to a Pygments tokenized string), or an
HTMLobject. This simplifies many APIs.
New utilities were added. We now have function for printing formatted text and an experimental module for displaying progress bars.
Autocompletion, input validation, and auto suggestion can now either be asynchronous or synchronous. By default they are synchronous, but by wrapping them in
ThreadedAutoSuggest, they will become asynchronous by running in a background thread.
Further, if the autocompletion code runs in a background thread, we will show the completions as soon as they arrive. This means that the autocompletion algorithm could for instance first yield the most trivial completions and then take time to produce the completions that take more time.
More guidelines on how to upgrade will follow.
AbortAction has been removed¶
Prompt_toolkit 1.0 had an argument
abort_action for both the
Application class as well as for the
prompt function. This has been
removed. The recommended way to handle this now is by capturing
Calling create_eventloop usually not required anymore¶
Prompt_toolkit 2.0 will automatically create the appropriate event loop when
it’s needed for the first time. There is no need to create one and pass it
around. If you want to run an application on top of asyncio (without using an
executor), it still needs to be activated by calling
use_asyncio_event_loop() at the beginning.
Pygments styles and tokens¶
prompt_toolkit 2.0 no longer depends on Pygments, but that definitely doesn’t mean that you can’t use any Pygments functionality anymore. The only difference is that Pygments stuff needs to be wrapped in an adaptor to make it compatible with the native prompt_toolkit objects.
For instance, if you have a list of
(pygments.Token, text)tuples for formatting, then this needs to be wrapped in a
PygmentsTokensobject. This is an adaptor that turns it into prompt_toolkit “formatted text”. Feel free to keep using this.
Pygments lexers need to be wrapped in a
PygmentsLexer. This will convert the list of Pygments tokens into prompt_toolkit formatted text.
If you have a Pygments style, then this needs to be converted as well. A Pygments style class can be converted in a prompt_toolkit
style_from_pygments_cls()function (which used to be called
style_from_pygments). A Pygments style dictionary can be converted using
Multiple styles can be merged together using
WordCompleter was moved from
By default, prompt_toolkit 2.0 completion is now synchronous. If you still want
asynchronous auto completion (which is often good thing), then you have to wrap
the completer in a
We don’t distiguish anymore between CLIFilter and SimpleFilter, because the application object is no longer passed around. This means that all filters are a Filter from now on.
All filters have been turned into functions. For instance, IsDone became is_done and HasCompletions became has_completions.
This was done because almost all classes were called without any arguments in the __init__ causing additional braces everywhere. This means that HasCompletions() has to be replaced by has_completions (without parenthesis).
The few filters that took arguments as input, became functions, but still have to be called with the given arguments.
For new filters, it is recommended to use the @Condition decorator, rather then inheriting from Filter. For instance:
from prompt_toolkit.filters import Condition @Condition def my_filter(); return True # Or False