Reference

Application

class prompt_toolkit.application.AppSession(input: Optional[Input] = None, output: Optional[Output] = None)

An AppSession is an interactive session, usually connected to one terminal. Within one such session, interaction with many applications can happen, one after the other.

The input/output device is not supposed to change during one session.

Warning: Always use the create_app_session function to create an instance, so that it gets activated correctly.

Parameters
  • input – Use this as a default input for all applications running in this session, unless an input is passed to the Application explicitely.

  • output – Use this as a default output.

class prompt_toolkit.application.Application(layout: Optional[prompt_toolkit.layout.layout.Layout] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, include_default_pygments_style: Union[prompt_toolkit.filters.base.Filter, bool] = True, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, clipboard: Optional[prompt_toolkit.clipboard.base.Clipboard] = None, full_screen: bool = False, color_depth: Optional[Union[prompt_toolkit.output.color_depth.ColorDepth, Callable[[], Optional[prompt_toolkit.output.color_depth.ColorDepth]]]] = None, mouse_support: Union[prompt_toolkit.filters.base.Filter, bool] = False, enable_page_navigation_bindings: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, paste_mode: Union[prompt_toolkit.filters.base.Filter, bool] = False, editing_mode: prompt_toolkit.enums.EditingMode = EditingMode.EMACS, erase_when_done: bool = False, reverse_vi_search_direction: Union[prompt_toolkit.filters.base.Filter, bool] = False, min_redraw_interval: Optional[Union[float, int]] = None, max_render_postpone_time: Optional[Union[float, int]] = 0.01, refresh_interval: Optional[float] = None, terminal_size_polling_interval: Optional[float] = 0.5, on_reset: Optional[ApplicationEventHandler[_AppResult]] = None, on_invalidate: Optional[ApplicationEventHandler[_AppResult]] = None, before_render: Optional[ApplicationEventHandler[_AppResult]] = None, after_render: Optional[ApplicationEventHandler[_AppResult]] = None, input: Optional[prompt_toolkit.input.base.Input] = None, output: Optional[prompt_toolkit.output.base.Output] = None)

The main Application class! This glues everything together.

Parameters
  • layout – A Layout instance.

  • key_bindingsKeyBindingsBase instance for the key bindings.

  • clipboardClipboard to use.

  • full_screen – When True, run the application on the alternate screen buffer.

  • color_depth – Any ColorDepth value, a callable that returns a ColorDepth or None for default.

  • erase_when_done – (bool) Clear the application output when it finishes.

  • reverse_vi_search_direction – Normally, in Vi mode, a ‘/’ searches forward and a ‘?’ searches backward. In Readline mode, this is usually reversed.

  • min_redraw_interval

    Number of seconds to wait between redraws. Use this for applications where invalidate is called a lot. This could cause a lot of terminal output, which some terminals are not able to process.

    None means that every invalidate will be scheduled right away (which is usually fine).

    When one invalidate is called, but a scheduled redraw of a previous invalidate call has not been executed yet, nothing will happen in any case.

  • max_render_postpone_time – When there is high CPU (a lot of other scheduled calls), postpone the rendering max x seconds. ‘0’ means: don’t postpone. ‘.5’ means: try to draw at least twice a second.

  • refresh_interval – Automatically invalidate the UI every so many seconds. When None (the default), only invalidate when invalidate has been called.

  • terminal_size_polling_interval – Poll the terminal size every so many seconds. Useful if the applications runs in a thread other then then main thread where SIGWINCH can’t be handled, or on Windows.

Filters:

Parameters
  • mouse_support – (Filter or boolean). When True, enable mouse support.

  • paste_modeFilter or boolean.

  • editing_modeEditingMode.

  • enable_page_navigation_bindings – When True, enable the page navigation key bindings. These include both Emacs and Vi bindings like page-up, page-down and so on to scroll through pages. Mostly useful for creating an editor or other full screen applications. Probably, you don’t want this for the implementation of a REPL. By default, this is enabled if full_screen is set.

Callbacks (all of these should accept an Application object as input.)

Parameters
  • on_reset – Called during reset.

  • on_invalidate – Called when the UI has been invalidated.

  • before_render – Called right before rendering.

  • after_render – Called right after rendering.

I/O: (Note that the preferred way to change the input/output is by creating an AppSession with the required input/output objects. If you need multiple applications running at the same time, you have to create a separate AppSession using a with create_app_session(): block.

Parameters
  • inputInput instance.

  • outputOutput instance. (Probably Vt100_Output or Win32Output.)

Usage:

app = Application(…) app.run()

# Or await app.run_async()

async cancel_and_wait_for_background_tasks() None

Cancel all background tasks, and wait for the cancellation to be done. If any of the background tasks raised an exception, this will also propagate the exception.

(If we had nurseries like Trio, this would be the __aexit__ of a nursery.)

property color_depth: prompt_toolkit.output.color_depth.ColorDepth

The active ColorDepth.

The current value is determined as follows:

  • If a color depth was given explicitly to this application, use that value.

  • Otherwise, fall back to the color depth that is reported by the Output implementation. If the Output class was created using output.defaults.create_output, then this value is coming from the $PROMPT_TOOLKIT_COLOR_DEPTH environment variable.

cpr_not_supported_callback() None

Called when we don’t receive the cursor position response in time.

create_background_task(coroutine: Awaitable[None]) asyncio.Task[None]

Start a background task (coroutine) for the running application. When the Application terminates, unfinished background tasks will be cancelled.

If asyncio had nurseries like Trio, we would create a nursery in Application.run_async, and run the given coroutine in that nursery.

Not threadsafe.

property current_buffer: prompt_toolkit.buffer.Buffer

The currently focused Buffer.

(This returns a dummy Buffer when none of the actual buffers has the focus. In this case, it’s really not practical to check for None values or catch exceptions every time.)

property current_search_state: prompt_toolkit.search.SearchState

Return the current SearchState. (The one for the focused BufferControl.)

exit() None
exit(*, result: prompt_toolkit.application.application._AppResult, style: str = "''") None
exit(*, exception: Union[BaseException, Type[BaseException]], style: str = "''") None

Exit application.

Note

If Application.exit is called before Application.run() is called, then the Application won’t exit (because the Application.future doesn’t correspond to the current run). Use a pre_run hook and an event to synchronize the closing if there’s a chance this can happen.

Parameters
  • result – Set this result for the application.

  • exception – Set this exception as the result for an application. For a prompt, this is often EOFError or KeyboardInterrupt.

  • style – Apply this style on the whole content when quitting, often this is ‘class:exiting’ for a prompt. (Used when erase_when_done is not set.)

get_used_style_strings() List[str]

Return a list of used style strings. This is helpful for debugging, and for writing a new Style.

invalidate() None

Thread safe way of sending a repaint trigger to the input event loop.

property invalidated: bool

True when a redraw operation has been scheduled.

property is_running: bool

True when the application is currently active/running.

key_processor

The InputProcessor instance.

print_text(text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]], style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) None

Print a list of (style_str, text) tuples to the output. (When the UI is running, this method has to be called through run_in_terminal, otherwise it will destroy the UI.)

Parameters
  • text – List of (style_str, text) tuples.

  • style – Style class to use. Defaults to the active style in the CLI.

quoted_insert

Quoted insert. This flag is set if we go into quoted insert mode.

render_counter

Render counter. This one is increased every time the UI is rendered. It can be used as a key for caching certain information during one rendering.

reset() None

Reset everything, for reading the next input.

run(pre_run: Optional[Callable[[], None]] = None, set_exception_handler: bool = True, in_thread: bool = False) prompt_toolkit.application.application._AppResult

A blocking ‘run’ call that waits until the UI is finished.

This will start the current asyncio event loop. If no loop is set for the current thread, then it will create a new loop. If a new loop was created, this won’t close the new loop (if in_thread=False).

Parameters
  • pre_run – Optional callable, which is called right after the “reset” of the application.

  • set_exception_handler – When set, in case of an exception, go out of the alternate screen and hide the application, display the exception, and wait for the user to press ENTER.

  • in_thread – When true, run the application in a background thread, and block the current thread until the application terminates. This is useful if we need to be sure the application won’t use the current event loop (asyncio does not support nested event loops). A new event loop will be created in this background thread, and that loop will also be closed when the background thread terminates. When this is used, it’s especially important to make sure that all asyncio background tasks are managed through get_appp().create_background_task(), so that unfinished tasks are properly cancelled before the event loop is closed. This is used for instance in ptpython.

async run_async(pre_run: Optional[Callable[[], None]] = None, set_exception_handler: bool = True) prompt_toolkit.application.application._AppResult

Run the prompt_toolkit Application until exit() has been called. Return the value that was passed to exit().

This is the main entry point for a prompt_toolkit Application and usually the only place where the event loop is actually running.

Parameters
  • pre_run – Optional callable, which is called right after the “reset” of the application.

  • set_exception_handler – When set, in case of an exception, go out of the alternate screen and hide the application, display the exception, and wait for the user to press ENTER.

async run_system_command(command: str, wait_for_enter: bool = True, display_before_text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', wait_text: str = 'Press ENTER to continue...') None

Run system command (While hiding the prompt. When finished, all the output will scroll above the prompt.)

Parameters
  • command – Shell command to be executed.

  • wait_for_enter – FWait for the user to press enter, when the command is finished.

  • display_before_text – If given, text to be displayed before the command executes.

Returns

A Future object.

suspend_to_background(suspend_group: bool = True) None

(Not thread safe – to be called from inside the key bindings.) Suspend process.

Parameters

suspend_group – When true, suspend the whole process group. (This is the default, and probably what you want.)

timeoutlen

Like Vim’s timeoutlen option. This can be None or a float. For instance, suppose that we have a key binding AB and a second key binding A. If the uses presses A and then waits, we don’t handle this binding yet (unless it was marked ‘eager’), because we don’t know what will follow. This timeout is the maximum amount of time that we wait until we call the handlers anyway. Pass None to disable this timeout.

ttimeoutlen

When to flush the input (For flushing escape keys.) This is important on terminals that use vt100 input. We can’t distinguish the escape key from for instance the left-arrow key, if we don’t know what follows after “x1b”. This little timer will consider “x1b” to be escape if nothing did follow in this time span. This seems to work like the ttimeoutlen option in Vim.

vi_state

Vi state. (For Vi key bindings.)

class prompt_toolkit.application.DummyApplication

When no Application is running, get_app() will run an instance of this DummyApplication instead.

run(pre_run: Optional[Callable[[], None]] = None, set_exception_handler: bool = True, in_thread: bool = False) None

A blocking ‘run’ call that waits until the UI is finished.

This will start the current asyncio event loop. If no loop is set for the current thread, then it will create a new loop. If a new loop was created, this won’t close the new loop (if in_thread=False).

Parameters
  • pre_run – Optional callable, which is called right after the “reset” of the application.

  • set_exception_handler – When set, in case of an exception, go out of the alternate screen and hide the application, display the exception, and wait for the user to press ENTER.

  • in_thread – When true, run the application in a background thread, and block the current thread until the application terminates. This is useful if we need to be sure the application won’t use the current event loop (asyncio does not support nested event loops). A new event loop will be created in this background thread, and that loop will also be closed when the background thread terminates. When this is used, it’s especially important to make sure that all asyncio background tasks are managed through get_appp().create_background_task(), so that unfinished tasks are properly cancelled before the event loop is closed. This is used for instance in ptpython.

async run_async(pre_run: Optional[Callable[[], None]] = None, set_exception_handler: bool = True) None

Run the prompt_toolkit Application until exit() has been called. Return the value that was passed to exit().

This is the main entry point for a prompt_toolkit Application and usually the only place where the event loop is actually running.

Parameters
  • pre_run – Optional callable, which is called right after the “reset” of the application.

  • set_exception_handler – When set, in case of an exception, go out of the alternate screen and hide the application, display the exception, and wait for the user to press ENTER.

async run_system_command(command: str, wait_for_enter: bool = True, display_before_text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', wait_text: str = '') None

Run system command (While hiding the prompt. When finished, all the output will scroll above the prompt.)

Parameters
  • command – Shell command to be executed.

  • wait_for_enter – FWait for the user to press enter, when the command is finished.

  • display_before_text – If given, text to be displayed before the command executes.

Returns

A Future object.

suspend_to_background(suspend_group: bool = True) None

(Not thread safe – to be called from inside the key bindings.) Suspend process.

Parameters

suspend_group – When true, suspend the whole process group. (This is the default, and probably what you want.)

prompt_toolkit.application.create_app_session(input: Optional[Input] = None, output: Optional[Output] = None) Generator[prompt_toolkit.application.current.AppSession, None, None]

Create a separate AppSession.

This is useful if there can be multiple individual `AppSession`s going on. Like in the case of an Telnet/SSH server. This functionality uses contextvars and requires at least Python 3.7.

prompt_toolkit.application.get_app() Application[Any]

Get the current active (running) Application. An Application is active during the Application.run_async() call.

We assume that there can only be one Application active at the same time. There is only one terminal window, with only one stdin and stdout. This makes the code significantly easier than passing around the Application everywhere.

If no Application is running, then return by default a DummyApplication. For practical reasons, we prefer to not raise an exception. This way, we don’t have to check all over the place whether an actual Application was returned.

(For applications like pymux where we can have more than one Application, we’ll use a work-around to handle that.)

prompt_toolkit.application.get_app_or_none() Optional[Application[Any]]

Get the current active (running) Application, or return None if no application is running.

prompt_toolkit.application.in_terminal(render_cli_done: bool = False) AsyncGenerator[None, None]

Asynchronous context manager that suspends the current application and runs the body in the terminal.

async def f():
    async with in_terminal():
        call_some_function()
        await call_some_async_function()
prompt_toolkit.application.run_in_terminal(func: Callable[[], prompt_toolkit.application.run_in_terminal._T], render_cli_done: bool = False, in_executor: bool = False) Awaitable[prompt_toolkit.application.run_in_terminal._T]

Run function on the terminal above the current application or prompt.

What this does is first hiding the prompt, then running this callable (which can safely output to the terminal), and then again rendering the prompt which causes the output of this function to scroll above the prompt.

func is supposed to be a synchronous function. If you need an asynchronous version of this function, use the in_terminal context manager directly.

Parameters
  • func – The callable to execute.

  • render_cli_done – When True, render the interface in the ‘Done’ state first, then execute the function. If False, erase the interface first.

  • in_executor – When True, run in executor. (Use this for long blocking functions, when you don’t want to block the event loop.)

Returns

A Future.

prompt_toolkit.application.set_app(app: Application[Any]) Generator[None, None, None]

Context manager that sets the given Application active in an AppSession.

This should only be called by the Application itself. The application will automatically be active while its running. If you want the application to be active in other threads/coroutines, where that’s not the case, use contextvars.copy_context(), or use Application.context to run it in the appropriate context.

Formatted text

Many places in prompt_toolkit can take either plain text, or formatted text. For instance the prompt() function takes either plain text or formatted text for the prompt. The FormattedTextControl can also take either plain text or formatted text.

In any case, there is an input that can either be just plain text (a string), an HTML object, an ANSI object or a sequence of (style_string, text) tuples. The to_formatted_text() conversion function takes any of these and turns all of them into such a tuple sequence.

class prompt_toolkit.formatted_text.ANSI(value: str)

ANSI formatted text. Take something ANSI escaped text, for use as a formatted string. E.g.

ANSI('\x1b[31mhello \x1b[32mworld')

Characters between \001 and \002 are supposed to have a zero width when printed, but these are literally sent to the terminal output. This can be used for instance, for inserting Final Term prompt commands. They will be translated into a prompt_toolkit ‘[ZeroWidthEscape]’ fragment.

format(*args: str, **kwargs: str) prompt_toolkit.formatted_text.ansi.ANSI

Like str.format, but make sure that the arguments are properly escaped. (No ANSI escapes can be injected.)

class prompt_toolkit.formatted_text.FormattedText(iterable=(), /)

A list of (style, text) tuples.

(In some situations, this can also be (style, text, mouse_handler) tuples.)

class prompt_toolkit.formatted_text.HTML(value: str)

HTML formatted text. Take something HTML-like, for use as a formatted string.

# Turn something into red.
HTML('<style fg="ansired" bg="#00ff44">...</style>')

# Italic, bold, underline and strike.
HTML('<i>...</i>')
HTML('<b>...</b>')
HTML('<u>...</u>')
HTML('<s>...</s>')

All HTML elements become available as a “class” in the style sheet. E.g. <username>...</username> can be styled, by setting a style for username.

format(*args: object, **kwargs: object) prompt_toolkit.formatted_text.html.HTML

Like str.format, but make sure that the arguments are properly escaped.

class prompt_toolkit.formatted_text.PygmentsTokens(token_list: List[Tuple[Token, str]])

Turn a pygments token list into a list of prompt_toolkit text fragments ((style_str, text) tuples).

class prompt_toolkit.formatted_text.Template(text: str)

Template for string interpolation with formatted text.

Example:

Template(' ... {} ... ').format(HTML(...))
Parameters

text – Plain text.

prompt_toolkit.formatted_text.fragment_list_len(fragments: List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]) int

Return the amount of characters in this text fragment list.

Parameters

fragments – List of (style_str, text) or (style_str, text, mouse_handler) tuples.

prompt_toolkit.formatted_text.fragment_list_to_text(fragments: List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]) str

Concatenate all the text parts again.

Parameters

fragments – List of (style_str, text) or (style_str, text, mouse_handler) tuples.

prompt_toolkit.formatted_text.fragment_list_width(fragments: List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]) int

Return the character width of this text fragment list. (Take double width characters into account.)

Parameters

fragments – List of (style_str, text) or (style_str, text, mouse_handler) tuples.

prompt_toolkit.formatted_text.is_formatted_text(value: object) TypeGuard[AnyFormattedText]

Check whether the input is valid formatted text (for use in assert statements). In case of a callable, it doesn’t check the return type.

prompt_toolkit.formatted_text.merge_formatted_text(items: Iterable[Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]) Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]

Merge (Concatenate) several pieces of formatted text together.

prompt_toolkit.formatted_text.split_lines(fragments: List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]) Iterable[List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]]

Take a single list of (style_str, text) tuples and yield one such list for each line. Just like str.split, this will yield at least one item.

Parameters

fragments – List of (style_str, text) or (style_str, text, mouse_handler) tuples.

prompt_toolkit.formatted_text.to_formatted_text(value: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]], style: str = '', auto_convert: bool = False) FormattedText

Convert the given value (which can be formatted text) into a list of text fragments. (Which is the canonical form of formatted text.) The outcome is always a FormattedText instance, which is a list of (style, text) tuples.

It can take a plain text string, an HTML or ANSI object, anything that implements __pt_formatted_text__ or a callable that takes no arguments and returns one of those.

Parameters
  • style – An additional style string which is applied to all text fragments.

  • auto_convert – If True, also accept other types, and convert them to a string first.

Buffer

Data structures for the Buffer. It holds the text, cursor position, history, etc…

class prompt_toolkit.buffer.Buffer(completer: Optional[prompt_toolkit.completion.base.Completer] = None, auto_suggest: Optional[prompt_toolkit.auto_suggest.AutoSuggest] = None, history: Optional[prompt_toolkit.history.History] = None, validator: Optional[prompt_toolkit.validation.Validator] = None, tempfile_suffix: Union[str, Callable[[], str]] = '', tempfile: Union[str, Callable[[], str]] = '', name: str = '', complete_while_typing: Union[prompt_toolkit.filters.base.Filter, bool] = False, validate_while_typing: Union[prompt_toolkit.filters.base.Filter, bool] = False, enable_history_search: Union[prompt_toolkit.filters.base.Filter, bool] = False, document: Optional[prompt_toolkit.document.Document] = None, accept_handler: Optional[Callable[[prompt_toolkit.buffer.Buffer], bool]] = None, read_only: Union[prompt_toolkit.filters.base.Filter, bool] = False, multiline: Union[prompt_toolkit.filters.base.Filter, bool] = True, on_text_changed: Optional[Callable[[prompt_toolkit.buffer.Buffer], None]] = None, on_text_insert: Optional[Callable[[prompt_toolkit.buffer.Buffer], None]] = None, on_cursor_position_changed: Optional[Callable[[prompt_toolkit.buffer.Buffer], None]] = None, on_completions_changed: Optional[Callable[[prompt_toolkit.buffer.Buffer], None]] = None, on_suggestion_set: Optional[Callable[[prompt_toolkit.buffer.Buffer], None]] = None)

The core data structure that holds the text and cursor position of the current input line and implements all text manipulations on top of it. It also implements the history, undo stack and the completion state.

Parameters
  • completerCompleter instance.

  • historyHistory instance.

  • tempfile_suffix – The tempfile suffix (extension) to be used for the “open in editor” function. For a Python REPL, this would be “.py”, so that the editor knows the syntax highlighting to use. This can also be a callable that returns a string.

  • tempfile – For more advanced tempfile situations where you need control over the subdirectories and filename. For a Git Commit Message, this would be “.git/COMMIT_EDITMSG”, so that the editor knows the syntax highlighting to use. This can also be a callable that returns a string.

  • name – Name for this buffer. E.g. DEFAULT_BUFFER. This is mostly useful for key bindings where we sometimes prefer to refer to a buffer by their name instead of by reference.

  • accept_handler

    Called when the buffer input is accepted. (Usually when the user presses enter.) The accept handler receives this Buffer as input and should return True when the buffer text should be kept instead of calling reset.

    In case of a PromptSession for instance, we want to keep the text, because we will exit the application, and only reset it during the next run.

Events:

Parameters
  • on_text_changed – When the buffer text changes. (Callable or None.)

  • on_text_insert – When new text is inserted. (Callable or None.)

  • on_cursor_position_changed – When the cursor moves. (Callable or None.)

  • on_completions_changed – When the completions were changed. (Callable or None.)

  • on_suggestion_set – When an auto-suggestion text has been set. (Callable or None.)

Filters:

Parameters
  • complete_while_typingFilter or bool. Decide whether or not to do asynchronous autocompleting while typing.

  • validate_while_typingFilter or bool. Decide whether or not to do asynchronous validation while typing.

  • enable_history_searchFilter or bool to indicate when up-arrow partial string matching is enabled. It is advised to not enable this at the same time as complete_while_typing, because when there is an autocompletion found, the up arrows usually browse through the completions, rather than through the history.

  • read_onlyFilter. When True, changes will not be allowed.

  • multilineFilter or bool. When not set, pressing Enter will call the accept_handler. Otherwise, pressing Esc-Enter is required.

append_to_history() None

Append the current input to the history.

apply_completion(completion: prompt_toolkit.completion.base.Completion) None

Insert a given completion.

Apply search. If something is found, set working_index and cursor_position.

auto_down(count: int = 1, go_to_start_of_line_if_history_changes: bool = False) None

If we’re not on the last line (of a multiline input) go a line down, otherwise go forward in history. (If nothing is selected.)

auto_up(count: int = 1, go_to_start_of_line_if_history_changes: bool = False) None

If we’re not on the first line (of a multiline input) go a line up, otherwise go back in history. (If nothing is selected.)

cancel_completion() None

Cancel completion, go back to the original text.

complete_next(count: int = 1, disable_wrap_around: bool = False) None

Browse to the next completions. (Does nothing if there are no completion.)

complete_previous(count: int = 1, disable_wrap_around: bool = False) None

Browse to the previous completions. (Does nothing if there are no completion.)

copy_selection(_cut: bool = False) prompt_toolkit.clipboard.base.ClipboardData

Copy selected text and return ClipboardData instance.

Notice that this doesn’t store the copied data on the clipboard yet. You can store it like this:

data = buffer.copy_selection()
get_app().clipboard.set_data(data)
cursor_down(count: int = 1) None

(for multiline edit). Move cursor to the next line.

cursor_up(count: int = 1) None

(for multiline edit). Move cursor to the previous line.

cut_selection() prompt_toolkit.clipboard.base.ClipboardData

Delete selected text and return ClipboardData instance.

delete(count: int = 1) str

Delete specified number of characters and Return the deleted text.

delete_before_cursor(count: int = 1) str

Delete specified number of characters before cursor and return the deleted text.

property document: prompt_toolkit.document.Document

Return Document instance from the current text, cursor position and selection state.

Return a Document instance that has the text/cursor position for this search, if we would apply it. This will be used in the BufferControl to display feedback while searching.

get_search_position(search_state: prompt_toolkit.search.SearchState, include_current_position: bool = True, count: int = 1) int

Get the cursor position for this search. (This operation won’t change the working_index. It’s won’t go through the history. Vi text objects can’t span multiple items.)

go_to_completion(index: Optional[int]) None

Select a completion from the list of current completions.

go_to_history(index: int) None

Go to this item in the history.

history_backward(count: int = 1) None

Move backwards through history.

history_forward(count: int = 1) None

Move forwards through the history.

Parameters

count – Amount of items to move forward.

insert_line_above(copy_margin: bool = True) None

Insert a new line above the current one.

insert_line_below(copy_margin: bool = True) None

Insert a new line below the current one.

insert_text(data: str, overwrite: bool = False, move_cursor: bool = True, fire_event: bool = True) None

Insert characters at cursor position.

Parameters

fire_event – Fire on_text_insert event. This is mainly used to trigger autocompletion while typing.

property is_returnable: bool

True when there is something handling accept.

join_next_line(separator: str = ' ') None

Join the next line to the current one by deleting the line ending after the current line.

join_selected_lines(separator: str = ' ') None

Join the selected lines.

load_history_if_not_yet_loaded() None

Create task for populating the buffer history (if not yet done).

Note:

This needs to be called from within the event loop of the
application, because history loading is async, and we need to be
sure the right event loop is active. Therefor, we call this method
in the `BufferControl.create_content`.

There are situations where prompt_toolkit applications are created
in one thread, but will later run in a different thread (Ptpython
is one example. The REPL runs in a separate thread, in order to
prevent interfering with a potential different event loop in the
main thread. The REPL UI however is still created in the main
thread.) We could decide to not support creating prompt_toolkit
objects in one thread and running the application in a different
thread, but history loading is the only place where it matters, and
this solves it.
newline(copy_margin: bool = True) None

Insert a line ending at the current position.

open_in_editor(validate_and_handle: bool = False) asyncio.Task[None]

Open code in editor.

This returns a future, and runs in a thread executor.

paste_clipboard_data(data: prompt_toolkit.clipboard.base.ClipboardData, paste_mode: prompt_toolkit.selection.PasteMode = PasteMode.EMACS, count: int = 1) None

Insert the data from the clipboard.

reset(document: Optional[prompt_toolkit.document.Document] = None, append_to_history: bool = False) None
Parameters

append_to_history – Append current input to history first.

save_to_undo_stack(clear_redo_stack: bool = True) None

Safe current state (input text and cursor position), so that we can restore it by calling undo.

set_document(value: prompt_toolkit.document.Document, bypass_readonly: bool = False) None

Set Document instance. Like the document property, but accept an bypass_readonly argument.

Parameters

bypass_readonly – When True, don’t raise an EditReadOnlyBuffer exception, even when the buffer is read-only.

Warning

When this buffer is read-only and bypass_readonly was not passed, the EditReadOnlyBuffer exception will be caught by the KeyProcessor and is silently suppressed. This is important to keep in mind when writing key bindings, because it won’t do what you expect, and there won’t be a stack trace. Use try/finally around this function if you need some cleanup code.

start_completion(select_first: bool = False, select_last: bool = False, insert_common_part: bool = False, complete_event: Optional[prompt_toolkit.completion.base.CompleteEvent] = None) None

Start asynchronous autocompletion of this buffer. (This will do nothing if a previous completion was still in progress.)

start_history_lines_completion() None

Start a completion based on all the other lines in the document and the history.

start_selection(selection_type: prompt_toolkit.selection.SelectionType = SelectionType.CHARACTERS) None

Take the current cursor position as the start of this selection.

swap_characters_before_cursor() None

Swap the last two characters before the cursor.

transform_current_line(transform_callback: Callable[[str], str]) None

Apply the given transformation function to the current line.

Parameters

transform_callback – callable that takes a string and return a new string.

transform_lines(line_index_iterator: Iterable[int], transform_callback: Callable[[str], str]) str

Transforms the text on a range of lines. When the iterator yield an index not in the range of lines that the document contains, it skips them silently.

To uppercase some lines:

new_text = transform_lines(range(5,10), lambda text: text.upper())
Parameters
  • line_index_iterator – Iterator of line numbers (int)

  • transform_callback – callable that takes the original text of a line, and return the new text for this line.

Returns

The new text.

transform_region(from_: int, to: int, transform_callback: Callable[[str], str]) None

Transform a part of the input string.

Parameters
  • from – (int) start position.

  • to – (int) end position.

  • transform_callback – Callable which accepts a string and returns the transformed string.

validate(set_cursor: bool = False) bool

Returns True if valid.

Parameters

set_cursor – Set the cursor position, if an error was found.

validate_and_handle() None

Validate buffer and handle the accept action.

yank_last_arg(n: Optional[int] = None) None

Like yank_nth_arg, but if no argument has been given, yank the last word by default.

yank_nth_arg(n: Optional[int] = None, _yank_last_arg: bool = False) None

Pick nth word from previous history entry (depending on current yank_nth_arg_state) and insert it at current position. Rotate through history if called repeatedly. If no n has been given, take the first argument. (The second word.)

Parameters

n – (None or int), The index of the word from the previous line to take.

class prompt_toolkit.buffer.CompletionState(original_document: prompt_toolkit.document.Document, completions: Optional[List[prompt_toolkit.completion.base.Completion]] = None, complete_index: Optional[int] = None)

Immutable class that contains a completion state.

complete_index

Position in the completions array. This can be None to indicate “no completion”, the original text.

completions

List of all the current Completion instances which are possible at this point.

property current_completion: Optional[prompt_toolkit.completion.base.Completion]

Return the current completion, or return None when no completion is selected.

go_to_index(index: Optional[int]) None

Create a new CompletionState object with the new index.

When index is None deselect the completion.

new_text_and_position() Tuple[str, int]

Return (new_text, new_cursor_position) for this completion.

original_document

Document as it was when the completion started.

exception prompt_toolkit.buffer.EditReadOnlyBuffer

Attempt editing of read-only Buffer.

prompt_toolkit.buffer.indent(buffer: prompt_toolkit.buffer.Buffer, from_row: int, to_row: int, count: int = 1) None

Indent text of a Buffer object.

prompt_toolkit.buffer.reshape_text(buffer: prompt_toolkit.buffer.Buffer, from_row: int, to_row: int) None

Reformat text, taking the width into account. to_row is included. (Vi ‘gq’ operator.)

prompt_toolkit.buffer.unindent(buffer: prompt_toolkit.buffer.Buffer, from_row: int, to_row: int, count: int = 1) None

Unindent text of a Buffer object.

Selection

Data structures for the selection.

class prompt_toolkit.selection.PasteMode(value)

An enumeration.

class prompt_toolkit.selection.SelectionState(original_cursor_position: int = 0, type: prompt_toolkit.selection.SelectionType = SelectionType.CHARACTERS)

State of the current selection.

Parameters
class prompt_toolkit.selection.SelectionType(value)

Type of selection.

BLOCK = 'BLOCK'

A block selection. (Visual-Block in Vi.)

CHARACTERS = 'CHARACTERS'

Characters. (Visual in Vi.)

LINES = 'LINES'

Whole lines. (Visual-Line in Vi.)

Clipboard

class prompt_toolkit.clipboard.Clipboard

Abstract baseclass for clipboards. (An implementation can be in memory, it can share the X11 or Windows keyboard, or can be persistent.)

abstract get_data() prompt_toolkit.clipboard.base.ClipboardData

Return clipboard data.

rotate() None

For Emacs mode, rotate the kill ring.

abstract set_data(data: prompt_toolkit.clipboard.base.ClipboardData) None

Set data to the clipboard.

Parameters

dataClipboardData instance.

set_text(text: str) None

Shortcut for setting plain text on clipboard.

class prompt_toolkit.clipboard.ClipboardData(text: str = '', type: prompt_toolkit.selection.SelectionType = SelectionType.CHARACTERS)

Text on the clipboard.

Parameters
class prompt_toolkit.clipboard.DummyClipboard

Clipboard implementation that doesn’t remember anything.

get_data() prompt_toolkit.clipboard.base.ClipboardData

Return clipboard data.

rotate() None

For Emacs mode, rotate the kill ring.

set_data(data: prompt_toolkit.clipboard.base.ClipboardData) None

Set data to the clipboard.

Parameters

dataClipboardData instance.

set_text(text: str) None

Shortcut for setting plain text on clipboard.

class prompt_toolkit.clipboard.DynamicClipboard(get_clipboard: Callable[[], Optional[prompt_toolkit.clipboard.base.Clipboard]])

Clipboard class that can dynamically returns any Clipboard.

Parameters

get_clipboard – Callable that returns a Clipboard instance.

get_data() prompt_toolkit.clipboard.base.ClipboardData

Return clipboard data.

rotate() None

For Emacs mode, rotate the kill ring.

set_data(data: prompt_toolkit.clipboard.base.ClipboardData) None

Set data to the clipboard.

Parameters

dataClipboardData instance.

set_text(text: str) None

Shortcut for setting plain text on clipboard.

class prompt_toolkit.clipboard.InMemoryClipboard(data: Optional[prompt_toolkit.clipboard.base.ClipboardData] = None, max_size: int = 60)

Default clipboard implementation. Just keep the data in memory.

This implements a kill-ring, for Emacs mode.

get_data() prompt_toolkit.clipboard.base.ClipboardData

Return clipboard data.

rotate() None

For Emacs mode, rotate the kill ring.

set_data(data: prompt_toolkit.clipboard.base.ClipboardData) None

Set data to the clipboard.

Parameters

dataClipboardData instance.

class prompt_toolkit.clipboard.pyperclip.PyperclipClipboard

Clipboard that synchronizes with the Windows/Mac/Linux system clipboard, using the pyperclip module.

get_data() prompt_toolkit.clipboard.base.ClipboardData

Return clipboard data.

set_data(data: prompt_toolkit.clipboard.base.ClipboardData) None

Set data to the clipboard.

Parameters

dataClipboardData instance.

Auto completion

class prompt_toolkit.completion.CompleteEvent(text_inserted: bool = False, completion_requested: bool = False)

Event that called the completer.

Parameters
  • text_inserted – When True, it means that completions are requested because of a text insert. (Buffer.complete_while_typing.)

  • completion_requested – When True, it means that the user explicitly pressed the Tab key in order to view the completions.

These two flags can be used for instance to implement a completer that shows some completions when Tab has been pressed, but not automatically when the user presses a space. (Because of complete_while_typing.)

completion_requested

Used explicitly requested completion by pressing ‘tab’.

text_inserted

Automatic completion while typing.

class prompt_toolkit.completion.Completer

Base class for completer implementations.

abstract get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
get_completions_async(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) AsyncGenerator[prompt_toolkit.completion.base.Completion, None]

Asynchronous generator for completions. (Probably, you won’t have to override this.)

Asynchronous generator of Completion objects.

class prompt_toolkit.completion.Completion(text: str, start_position: int = 0, display: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, display_meta: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, style: str = '', selected_style: str = '')
Parameters
  • text – The new string that will be inserted into the document.

  • start_position – Position relative to the cursor_position where the new text will start. The text will be inserted between the start_position and the original cursor position.

  • display – (optional string or formatted text) If the completion has to be displayed differently in the completion menu.

  • display_meta – (Optional string or formatted text) Meta information about the completion, e.g. the path or source where it’s coming from. This can also be a callable that returns a string.

  • style – Style string.

  • selected_style – Style string, used for a selected completion. This can override the style parameter.

property display_meta: List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]

Return meta-text. (This is lazy when using a callable).

property display_meta_text: str

The ‘meta’ field as plain text.

property display_text: str

The ‘display’ field as plain text.

new_completion_from_position(position: int) prompt_toolkit.completion.base.Completion

(Only for internal use!) Get a new completion by splitting this one. Used by Application when it needs to have a list of new completions after inserting the common prefix.

class prompt_toolkit.completion.ConditionalCompleter(completer: prompt_toolkit.completion.base.Completer, filter: Union[prompt_toolkit.filters.base.Filter, bool])

Wrapper around any other completer that will enable/disable the completions depending on whether the received condition is satisfied.

Parameters
get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
get_completions_async(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) AsyncGenerator[prompt_toolkit.completion.base.Completion, None]

Asynchronous generator for completions. (Probably, you won’t have to override this.)

Asynchronous generator of Completion objects.

class prompt_toolkit.completion.DeduplicateCompleter(completer: prompt_toolkit.completion.base.Completer)

Wrapper around a completer that removes duplicates. Only the first unique completions are kept.

Completions are considered to be a duplicate if they result in the same document text when they would be applied.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.DummyCompleter

A completer that doesn’t return any completion.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.DynamicCompleter(get_completer: Callable[[], Optional[prompt_toolkit.completion.base.Completer]])

Completer class that can dynamically returns any Completer.

Parameters

get_completer – Callable that returns a Completer instance.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
get_completions_async(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) AsyncGenerator[prompt_toolkit.completion.base.Completion, None]

Asynchronous generator for completions. (Probably, you won’t have to override this.)

Asynchronous generator of Completion objects.

class prompt_toolkit.completion.ExecutableCompleter

Complete only executable files in the current path.

class prompt_toolkit.completion.FuzzyCompleter(completer: prompt_toolkit.completion.base.Completer, WORD: bool = False, pattern: Optional[str] = None, enable_fuzzy: Union[prompt_toolkit.filters.base.Filter, bool] = True)

Fuzzy completion. This wraps any other completer and turns it into a fuzzy completer.

If the list of words is: [“leopard” , “gorilla”, “dinosaur”, “cat”, “bee”] Then trying to complete “oar” would yield “leopard” and “dinosaur”, but not the others, because they match the regular expression ‘o.*a.*r’. Similar, in another application “djm” could expand to “django_migrations”.

The results are sorted by relevance, which is defined as the start position and the length of the match.

Notice that this is not really a tool to work around spelling mistakes, like what would be possible with difflib. The purpose is rather to have a quicker or more intuitive way to filter the given completions, especially when many completions have a common prefix.

Fuzzy algorithm is based on this post: https://blog.amjith.com/fuzzyfinder-in-10-lines-of-python

Parameters
  • completer – A Completer instance.

  • WORD – When True, use WORD characters.

  • pattern – Regex pattern which selects the characters before the cursor that are considered for the fuzzy matching.

  • enable_fuzzy – (bool or Filter) Enabled the fuzzy behavior. For easily turning fuzzyness on or off according to a certain condition.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.FuzzyWordCompleter(words: Union[List[str], Callable[[], List[str]]], meta_dict: Optional[Dict[str, str]] = None, WORD: bool = False)

Fuzzy completion on a list of words.

(This is basically a WordCompleter wrapped in a FuzzyCompleter.)

Parameters
  • words – List of words or callable that returns a list of words.

  • meta_dict – Optional dict mapping words to their meta-information.

  • WORD – When True, use WORD characters.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.NestedCompleter(options: Dict[str, Optional[prompt_toolkit.completion.base.Completer]], ignore_case: bool = True)

Completer which wraps around several other completers, and calls any the one that corresponds with the first word of the input.

By combining multiple NestedCompleter instances, we can achieve multiple hierarchical levels of autocompletion. This is useful when WordCompleter is not sufficient.

If you need multiple levels, check out the from_nested_dict classmethod.

classmethod from_nested_dict(data: Mapping[str, Union[Any, Set[str], None, prompt_toolkit.completion.base.Completer]]) prompt_toolkit.completion.nested.NestedCompleter

Create a NestedCompleter, starting from a nested dictionary data structure, like this:

data = {
    'show': {
        'version': None,
        'interfaces': None,
        'clock': None,
        'ip': {'interface': {'brief'}}
    },
    'exit': None
    'enable': None
}

The value should be None if there is no further completion at some point. If all values in the dictionary are None, it is also possible to use a set instead.

Values in this data structure can be a completers as well.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.PathCompleter(only_directories: bool = False, get_paths: Optional[Callable[[], List[str]]] = None, file_filter: Optional[Callable[[str], bool]] = None, min_input_len: int = 0, expanduser: bool = False)

Complete for Path variables.

Parameters
  • get_paths – Callable which returns a list of directories to look into when the user enters a relative path.

  • file_filter – Callable which takes a filename and returns whether this file should show up in the completion. None when no filtering has to be done.

  • min_input_len – Don’t do autocompletion when the input string is shorter.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
class prompt_toolkit.completion.ThreadedCompleter(completer: prompt_toolkit.completion.base.Completer)

Wrapper that runs the get_completions generator in a thread.

(Use this to prevent the user interface from becoming unresponsive if the generation of completions takes too much time.)

The completions will be displayed as soon as they are produced. The user can already select a completion, even if not all completions are displayed.

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
get_completions_async(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) AsyncGenerator[prompt_toolkit.completion.base.Completion, None]

Asynchronous generator of completions.

class prompt_toolkit.completion.WordCompleter(words: Union[List[str], Callable[[], List[str]]], ignore_case: bool = False, display_dict: Optional[Mapping[str, Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]] = None, meta_dict: Optional[Mapping[str, Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]] = None, WORD: bool = False, sentence: bool = False, match_middle: bool = False, pattern: Optional[Pattern[str]] = None)

Simple autocompletion on a list of words.

Parameters
  • words – List of words or callable that returns a list of words.

  • ignore_case – If True, case-insensitive completion.

  • meta_dict – Optional dict mapping words to their meta-text. (This should map strings to strings or formatted text.)

  • WORD – When True, use WORD characters.

  • sentence – When True, don’t complete by comparing the word before the cursor, but by comparing all the text before the cursor. In this case, the list of words is just a list of strings, where each string can contain spaces. (Can not be used together with the WORD option.)

  • match_middle – When True, match not only the start, but also in the middle of the word.

  • pattern – Optional compiled regex for finding the word before the cursor to complete. When given, use this regex pattern instead of default one (see document._FIND_WORD_RE)

get_completions(document: prompt_toolkit.document.Document, complete_event: prompt_toolkit.completion.base.CompleteEvent) Iterable[prompt_toolkit.completion.base.Completion]

This should be a generator that yields Completion instances.

If the generation of completions is something expensive (that takes a lot of time), consider wrapping this Completer class in a ThreadedCompleter. In that case, the completer algorithm runs in a background thread and completions will be displayed as soon as they arrive.

Parameters
prompt_toolkit.completion.get_common_complete_suffix(document: prompt_toolkit.document.Document, completions: Sequence[prompt_toolkit.completion.base.Completion]) str

Return the common prefix for all completions.

prompt_toolkit.completion.merge_completers(completers: Sequence[prompt_toolkit.completion.base.Completer], deduplicate: bool = False) prompt_toolkit.completion.base.Completer

Combine several completers into one.

Parameters

deduplicate – If True, wrap the result in a DeduplicateCompleter so that completions that would result in the same text will be deduplicated.

Document

The Document that implements all the text operations/querying.

class prompt_toolkit.document.Document(text: str = '', cursor_position: Optional[int] = None, selection: Optional[prompt_toolkit.selection.SelectionState] = None)

This is a immutable class around the text and cursor position, and contains methods for querying this data, e.g. to give the text before the cursor.

This class is usually instantiated by a Buffer object, and accessed as the document property of that class.

Parameters
  • text – string

  • cursor_position – int

  • selectionSelectionState

property char_before_cursor: str

Return character before the cursor or an empty string.

property current_char: str

Return character under cursor or an empty string.

property current_line: str

Return the text on the line where the cursor is. (when the input consists of just one line, it equals text.

property current_line_after_cursor: str

Text from the cursor until the end of the line.

property current_line_before_cursor: str

Text from the start of the line until the cursor.

property cursor_position: int

The document cursor position.

property cursor_position_col: int

Current column. (0-based.)

property cursor_position_row: int

Current row. (0-based.)

cut_selection() Tuple[prompt_toolkit.document.Document, prompt_toolkit.clipboard.base.ClipboardData]

Return a (Document, ClipboardData) tuple, where the document represents the new document when the selection is cut, and the clipboard data, represents whatever has to be put on the clipboard.

empty_line_count_at_the_end() int

Return number of empty lines at the end of the document.

end_of_paragraph(count: int = 1, after: bool = False) int

Return the end of the current paragraph. (Relative cursor position.)

find(sub: str, in_current_line: bool = False, include_current_position: bool = False, ignore_case: bool = False, count: int = 1) Optional[int]

Find text after the cursor, return position relative to the cursor position. Return None if nothing was found.

Parameters

count – Find the n-th occurrence.

find_all(sub: str, ignore_case: bool = False) List[int]

Find all occurrences of the substring. Return a list of absolute positions in the document.

find_backwards(sub: str, in_current_line: bool = False, ignore_case: bool = False, count: int = 1) Optional[int]

Find text before the cursor, return position relative to the cursor position. Return None if nothing was found.

Parameters

count – Find the n-th occurrence.

find_boundaries_of_current_word(WORD: bool = False, include_leading_whitespace: bool = False, include_trailing_whitespace: bool = False) Tuple[int, int]

Return the relative boundaries (startpos, endpos) of the current word under the cursor. (This is at the current line, because line boundaries obviously don’t belong to any word.) If not on a word, this returns (0,0)

find_enclosing_bracket_left(left_ch: str, right_ch: str, start_pos: Optional[int] = None) Optional[int]

Find the left bracket enclosing current position. Return the relative position to the cursor position.

When start_pos is given, don’t look past the position.

find_enclosing_bracket_right(left_ch: str, right_ch: str, end_pos: Optional[int] = None) Optional[int]

Find the right bracket enclosing current position. Return the relative position to the cursor position.

When end_pos is given, don’t look past the position.

find_matching_bracket_position(start_pos: Optional[int] = None, end_pos: Optional[int] = None) int

Return relative cursor position of matching [, (, { or < bracket.

When start_pos or end_pos are given. Don’t look past the positions.

find_next_matching_line(match_func: Callable[[str], bool], count: int = 1) Optional[int]

Look downwards for empty lines. Return the line index, relative to the current line.

find_next_word_beginning(count: int = 1, WORD: bool = False) Optional[int]

Return an index relative to the cursor position pointing to the start of the next word. Return None if nothing was found.

find_next_word_ending(include_current_position: bool = False, count: int = 1, WORD: bool = False) Optional[int]

Return an index relative to the cursor position pointing to the end of the next word. Return None if nothing was found.

find_previous_matching_line(match_func: Callable[[str], bool], count: int = 1) Optional[int]

Look upwards for empty lines. Return the line index, relative to the current line.

find_previous_word_beginning(count: int = 1, WORD: bool = False) Optional[int]

Return an index relative to the cursor position pointing to the start of the previous word. Return None if nothing was found.

find_previous_word_ending(count: int = 1, WORD: bool = False) Optional[int]

Return an index relative to the cursor position pointing to the end of the previous word. Return None if nothing was found.

find_start_of_previous_word(count: int = 1, WORD: bool = False, pattern: Optional[Pattern[str]] = None) Optional[int]

Return an index relative to the cursor position pointing to the start of the previous word. Return None if nothing was found.

Parameters

pattern – (None or compiled regex). When given, use this regex pattern.

get_column_cursor_position(column: int) int

Return the relative cursor position for this column at the current line. (It will stay between the boundaries of the line in case of a larger number.)

get_cursor_down_position(count: int = 1, preferred_column: Optional[int] = None) int

Return the relative cursor position (character index) where we would be if the user pressed the arrow-down button.

Parameters

preferred_column – When given, go to this column instead of staying at the current column.

get_cursor_left_position(count: int = 1) int

Relative position for cursor left.

get_cursor_right_position(count: int = 1) int

Relative position for cursor_right.

get_cursor_up_position(count: int = 1, preferred_column: Optional[int] = None) int

Return the relative cursor position (character index) where we would be if the user pressed the arrow-up button.

Parameters

preferred_column – When given, go to this column instead of staying at the current column.

get_end_of_document_position() int

Relative position for the end of the document.

get_end_of_line_position() int

Relative position for the end of this line.

get_start_of_document_position() int

Relative position for the start of the document.

get_start_of_line_position(after_whitespace: bool = False) int

Relative position for the start of this line.

get_word_before_cursor(WORD: bool = False, pattern: Optional[Pattern[str]] = None) str

Give the word before the cursor. If we have whitespace before the cursor this returns an empty string.

Parameters

pattern – (None or compiled regex). When given, use this regex pattern.

get_word_under_cursor(WORD: bool = False) str

Return the word, currently below the cursor. This returns an empty string when the cursor is on a whitespace region.

has_match_at_current_position(sub: str) bool

True when this substring is found at the cursor position.

insert_after(text: str) prompt_toolkit.document.Document

Create a new document, with this text inserted after the buffer. It keeps selection ranges and cursor position in sync.

insert_before(text: str) prompt_toolkit.document.Document

Create a new document, with this text inserted before the buffer. It keeps selection ranges and cursor position in sync.

property is_cursor_at_the_end: bool

True when the cursor is at the end of the text.

property is_cursor_at_the_end_of_line: bool

True when the cursor is at the end of this line.

last_non_blank_of_current_line_position() int

Relative position for the last non blank character of this line.

property leading_whitespace_in_current_line: str

The leading whitespace in the left margin of the current line.

property line_count: int

Return the number of lines in this document. If the document ends with a trailing n, that counts as the beginning of a new line.

property lines: List[str]

Array of all the lines.

property lines_from_current: List[str]

Array of the lines starting from the current line, until the last line.

property on_first_line: bool

True when we are at the first line.

property on_last_line: bool

True when we are at the last line.

paste_clipboard_data(data: prompt_toolkit.clipboard.base.ClipboardData, paste_mode: prompt_toolkit.selection.PasteMode = PasteMode.EMACS, count: int = 1) prompt_toolkit.document.Document

Return a new Document instance which contains the result if we would paste this data at the current cursor position.

Parameters
  • paste_mode – Where to paste. (Before/after/emacs.)

  • count – When >1, Paste multiple times.

property selection: Optional[prompt_toolkit.selection.SelectionState]

SelectionState object.

selection_range() Tuple[int, int]

Return (from, to) tuple of the selection. start and end position are included.

This doesn’t take the selection type into account. Use selection_ranges instead.

selection_range_at_line(row: int) Optional[Tuple[int, int]]

If the selection spans a portion of the given line, return a (from, to) tuple.

The returned upper boundary is not included in the selection, so (0, 0) is an empty selection. (0, 1), is a one character selection.

Returns None if the selection doesn’t cover this line at all.

selection_ranges() Iterable[Tuple[int, int]]

Return a list of (from, to) tuples for the selection or none if nothing was selected. The upper boundary is not included.

This will yield several (from, to) tuples in case of a BLOCK selection. This will return zero ranges, like (8,8) for empty lines in a block selection.

start_of_paragraph(count: int = 1, before: bool = False) int

Return the start of the current paragraph. (Relative cursor position.)

property text: str

The document text.

translate_index_to_position(index: int) Tuple[int, int]

Given an index for the text, return the corresponding (row, col) tuple. (0-based. Returns (0, 0) for index=0.)

translate_row_col_to_index(row: int, col: int) int

Given a (row, col) tuple, return the corresponding index. (Row and col params are 0-based.)

Negative row/col values are turned into zero.

Enums

prompt_toolkit.enums.DEFAULT_BUFFER = 'DEFAULT_BUFFER'

Name of the default buffer.

class prompt_toolkit.enums.EditingMode(value)

An enumeration.

prompt_toolkit.enums.SEARCH_BUFFER = 'SEARCH_BUFFER'

Name of the search buffer.

prompt_toolkit.enums.SYSTEM_BUFFER = 'SYSTEM_BUFFER'

Name of the system buffer.

History

Implementations for the history of a Buffer.

NOTE: There is no DynamicHistory:

This doesn’t work well, because the Buffer needs to be able to attach an event handler to the event when a history entry is loaded. This loading can be done asynchronously and making the history swappable would probably break this.

class prompt_toolkit.history.DummyHistory

History object that doesn’t remember anything.

append_string(string: str) None

Add string to the history.

load_history_strings() Iterable[str]

This should be a generator that yields str instances.

It should yield the most recent items first, because they are the most important. (The history can already be used, even when it’s only partially loaded.)

store_string(string: str) None

Store the string in persistent storage.

class prompt_toolkit.history.FileHistory(filename: str)

History class that stores all strings in a file.

load_history_strings() Iterable[str]

This should be a generator that yields str instances.

It should yield the most recent items first, because they are the most important. (The history can already be used, even when it’s only partially loaded.)

store_string(string: str) None

Store the string in persistent storage.

class prompt_toolkit.history.History

Base History class.

This also includes abstract methods for loading/storing history.

append_string(string: str) None

Add string to the history.

get_strings() List[str]

Get the strings from the history that are loaded so far. (In order. Oldest item first.)

load() AsyncGenerator[str, None]

Load the history and yield all the entries in reverse order (latest, most recent history entry first).

This method can be called multiple times from the Buffer to repopulate the history when prompting for a new input. So we are responsible here for both caching, and making sure that strings that were were appended to the history will be incorporated next time this method is called.

abstract load_history_strings() Iterable[str]

This should be a generator that yields str instances.

It should yield the most recent items first, because they are the most important. (The history can already be used, even when it’s only partially loaded.)

abstract store_string(string: str) None

Store the string in persistent storage.

class prompt_toolkit.history.InMemoryHistory(history_strings: Optional[Sequence[str]] = None)

History class that keeps a list of all strings in memory.

In order to prepopulate the history, it’s possible to call either append_string for all items or pass a list of strings to __init__ here.

load_history_strings() Iterable[str]

This should be a generator that yields str instances.

It should yield the most recent items first, because they are the most important. (The history can already be used, even when it’s only partially loaded.)

store_string(string: str) None

Store the string in persistent storage.

class prompt_toolkit.history.ThreadedHistory(history: prompt_toolkit.history.History)

Wrapper around History implementations that run the load() generator in a thread.

Use this to increase the start-up time of prompt_toolkit applications. History entries are available as soon as they are loaded. We don’t have to wait for everything to be loaded.

append_string(string: str) None

Add string to the history.

load() AsyncGenerator[str, None]

Like History.load(), but call `self.load_history_strings() in a background thread.

load_history_strings() Iterable[str]

This should be a generator that yields str instances.

It should yield the most recent items first, because they are the most important. (The history can already be used, even when it’s only partially loaded.)

store_string(string: str) None

Store the string in persistent storage.

Keys

class prompt_toolkit.keys.Keys(value)

List of keys for use in key bindings.

Note that this is an “StrEnum”, all values can be compared against strings.

Style

Styling for prompt_toolkit applications.

class prompt_toolkit.styles.AdjustBrightnessStyleTransformation(min_brightness: Union[Callable[[], float], float] = 0.0, max_brightness: Union[Callable[[], float], float] = 1.0)

Adjust the brightness to improve the rendering on either dark or light backgrounds.

For dark backgrounds, it’s best to increase min_brightness. For light backgrounds it’s best to decrease max_brightness. Usually, only one setting is adjusted.

This will only change the brightness for text that has a foreground color defined, but no background color. It works best for 256 or true color output.

Note

Notice that there is no universal way to detect whether the application is running in a light or dark terminal. As a developer of an command line application, you’ll have to make this configurable for the user.

Parameters
  • min_brightness – Float between 0.0 and 1.0 or a callable that returns a float.

  • max_brightness – Float between 0.0 and 1.0 or a callable that returns a float.

invalidation_hash() Hashable

When this changes, the cache should be invalidated.

transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Take an Attrs object and return a new Attrs object.

Remember that the color formats can be either “ansi…” or a 6 digit lowercase hexadecimal color (without ‘#’ prefix).

class prompt_toolkit.styles.Attrs(color, bgcolor, bold, underline, strike, italic, blink, reverse, hidden)
Parameters
  • color – Hexadecimal string. E.g. ‘000000’ or Ansi color name: e.g. ‘ansiblue’

  • bgcolor – Hexadecimal string. E.g. ‘ffffff’ or Ansi color name: e.g. ‘ansired’

  • bold – Boolean

  • underline – Boolean

  • strike – Boolean

  • italic – Boolean

  • blink – Boolean

  • reverse – Boolean

  • hidden – Boolean

property bgcolor

Alias for field number 1

Alias for field number 6

property bold

Alias for field number 2

property color

Alias for field number 0

property hidden

Alias for field number 8

property italic

Alias for field number 5

property reverse

Alias for field number 7

property strike

Alias for field number 4

property underline

Alias for field number 3

class prompt_toolkit.styles.BaseStyle

Abstract base class for prompt_toolkit styles.

abstract get_attrs_for_style_str(style_str: str, default: prompt_toolkit.styles.base.Attrs = Attrs(color='', bgcolor='', bold=False, underline=False, strike=False, italic=False, blink=False, reverse=False, hidden=False)) prompt_toolkit.styles.base.Attrs

Return Attrs for the given style string.

Parameters
  • style_str – The style string. This can contain inline styling as well as classnames (e.g. “class:title”).

  • defaultAttrs to be used if no styling was defined.

abstract invalidation_hash() Hashable

Invalidation hash for the style. When this changes over time, the renderer knows that something in the style changed, and that everything has to be redrawn.

abstract property style_rules: List[Tuple[str, str]]

The list of style rules, used to create this style. (Required for DynamicStyle and _MergedStyle to work.)

class prompt_toolkit.styles.ConditionalStyleTransformation(style_transformation: prompt_toolkit.styles.style_transformation.StyleTransformation, filter: Union[prompt_toolkit.filters.base.Filter, bool])

Apply the style transformation depending on a condition.

invalidation_hash() Hashable

When this changes, the cache should be invalidated.

transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Take an Attrs object and return a new Attrs object.

Remember that the color formats can be either “ansi…” or a 6 digit lowercase hexadecimal color (without ‘#’ prefix).

class prompt_toolkit.styles.DummyStyle

A style that doesn’t style anything.

get_attrs_for_style_str(style_str: str, default: prompt_toolkit.styles.base.Attrs = Attrs(color='', bgcolor='', bold=False, underline=False, strike=False, italic=False, blink=False, reverse=False, hidden=False)) prompt_toolkit.styles.base.Attrs

Return Attrs for the given style string.

Parameters
  • style_str – The style string. This can contain inline styling as well as classnames (e.g. “class:title”).

  • defaultAttrs to be used if no styling was defined.

invalidation_hash() Hashable

Invalidation hash for the style. When this changes over time, the renderer knows that something in the style changed, and that everything has to be redrawn.

property style_rules: List[Tuple[str, str]]

The list of style rules, used to create this style. (Required for DynamicStyle and _MergedStyle to work.)

class prompt_toolkit.styles.DummyStyleTransformation

Don’t transform anything at all.

invalidation_hash() Hashable

When this changes, the cache should be invalidated.

transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Take an Attrs object and return a new Attrs object.

Remember that the color formats can be either “ansi…” or a 6 digit lowercase hexadecimal color (without ‘#’ prefix).

class prompt_toolkit.styles.DynamicStyle(get_style: Callable[[], Optional[prompt_toolkit.styles.base.BaseStyle]])

Style class that can dynamically returns an other Style.

Parameters

get_style – Callable that returns a Style instance.

get_attrs_for_style_str(style_str: str, default: prompt_toolkit.styles.base.Attrs = Attrs(color='', bgcolor='', bold=False, underline=False, strike=False, italic=False, blink=False, reverse=False, hidden=False)) prompt_toolkit.styles.base.Attrs

Return Attrs for the given style string.

Parameters
  • style_str – The style string. This can contain inline styling as well as classnames (e.g. “class:title”).

  • defaultAttrs to be used if no styling was defined.

invalidation_hash() Hashable

Invalidation hash for the style. When this changes over time, the renderer knows that something in the style changed, and that everything has to be redrawn.

property style_rules: List[Tuple[str, str]]

The list of style rules, used to create this style. (Required for DynamicStyle and _MergedStyle to work.)

class prompt_toolkit.styles.DynamicStyleTransformation(get_style_transformation: Callable[[], Optional[prompt_toolkit.styles.style_transformation.StyleTransformation]])

StyleTransformation class that can dynamically returns any StyleTransformation.

Parameters

get_style_transformation – Callable that returns a StyleTransformation instance.

invalidation_hash() Hashable

When this changes, the cache should be invalidated.

transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Take an Attrs object and return a new Attrs object.

Remember that the color formats can be either “ansi…” or a 6 digit lowercase hexadecimal color (without ‘#’ prefix).

class prompt_toolkit.styles.Priority(value)

The priority of the rules, when a style is created from a dictionary.

In a Style, rules that are defined later will always override previous defined rules, however in a dictionary, the key order was arbitrary before Python 3.6. This means that the style could change at random between rules.

We have two options:

  • DICT_KEY_ORDER: This means, iterate through the dictionary, and take

    the key/value pairs in order as they come. This is a good option if you have Python >3.6. Rules at the end will override rules at the beginning.

  • MOST_PRECISE: keys that are defined with most precision will get higher priority. (More precise means: more elements.)

class prompt_toolkit.styles.Style(style_rules: List[Tuple[str, str]])

Create a Style instance from a list of style rules.

The style_rules is supposed to be a list of (‘classnames’, ‘style’) tuples. The classnames are a whitespace separated string of class names and the style string is just like a Pygments style definition, but with a few additions: it supports ‘reverse’ and ‘blink’.

Later rules always override previous rules.

Usage:

Style([
    ('title', '#ff0000 bold underline'),
    ('something-else', 'reverse'),
    ('class1 class2', 'reverse'),
])

The from_dict classmethod is similar, but takes a dictionary as input.

classmethod from_dict(style_dict: Dict[str, str], priority: prompt_toolkit.styles.style.Priority = Priority.DICT_KEY_ORDER) prompt_toolkit.styles.style.Style
Parameters
  • style_dict – Style dictionary.

  • priorityPriority value.

get_attrs_for_style_str(style_str: str, default: prompt_toolkit.styles.base.Attrs = Attrs(color='', bgcolor='', bold=False, underline=False, strike=False, italic=False, blink=False, reverse=False, hidden=False)) prompt_toolkit.styles.base.Attrs

Get Attrs for the given style string.

invalidation_hash() Hashable

Invalidation hash for the style. When this changes over time, the renderer knows that something in the style changed, and that everything has to be redrawn.

property style_rules: List[Tuple[str, str]]

The list of style rules, used to create this style. (Required for DynamicStyle and _MergedStyle to work.)

class prompt_toolkit.styles.StyleTransformation

Base class for any style transformation.

invalidation_hash() Hashable

When this changes, the cache should be invalidated.

abstract transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Take an Attrs object and return a new Attrs object.

Remember that the color formats can be either “ansi…” or a 6 digit lowercase hexadecimal color (without ‘#’ prefix).

class prompt_toolkit.styles.SwapLightAndDarkStyleTransformation

Turn dark colors into light colors and the other way around.

This is meant to make color schemes that work on a dark background usable on a light background (and the other way around).

Notice that this doesn’t swap foreground and background like “reverse” does. It turns light green into dark green and the other way around. Foreground and background colors are considered individually.

Also notice that when <reverse> is used somewhere and no colors are given in particular (like what is the default for the bottom toolbar), then this doesn’t change anything. This is what makes sense, because when the ‘default’ color is chosen, it’s what works best for the terminal, and reverse works good with that.

transform_attrs(attrs: prompt_toolkit.styles.base.Attrs) prompt_toolkit.styles.base.Attrs

Return the Attrs used when opposite luminosity should be used.

prompt_toolkit.styles.merge_style_transformations(style_transformations: Sequence[prompt_toolkit.styles.style_transformation.StyleTransformation]) prompt_toolkit.styles.style_transformation.StyleTransformation

Merge multiple transformations together.

prompt_toolkit.styles.merge_styles(styles: List[prompt_toolkit.styles.base.BaseStyle]) prompt_toolkit.styles.style._MergedStyle

Merge multiple Style objects.

prompt_toolkit.styles.pygments_token_to_classname(token: Token) str

Turn e.g. Token.Name.Exception into ‘pygments.name.exception’.

(Our Pygments lexer will also turn the tokens that pygments produces in a prompt_toolkit list of fragments that match these styling rules.)

prompt_toolkit.styles.style_from_pygments_cls(pygments_style_cls: Type[PygmentsStyle]) prompt_toolkit.styles.style.Style

Shortcut to create a Style instance from a Pygments style class and a style dictionary.

Example:

from prompt_toolkit.styles.from_pygments import style_from_pygments_cls
from pygments.styles import get_style_by_name
style = style_from_pygments_cls(get_style_by_name('monokai'))
Parameters

pygments_style_cls – Pygments style class to start from.

prompt_toolkit.styles.style_from_pygments_dict(pygments_dict: Dict[Token, str]) prompt_toolkit.styles.style.Style

Create a Style instance from a Pygments style dictionary. (One that maps Token objects to style strings.)

Shortcuts

class prompt_toolkit.shortcuts.CompleteStyle(value)

How to display autocompletions for the prompt.

class prompt_toolkit.shortcuts.ProgressBar(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, formatters: Optional[Sequence[prompt_toolkit.shortcuts.progress_bar.formatters.Formatter]] = None, bottom_toolbar: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindings] = None, file: Optional[TextIO] = None, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None, output: Optional[prompt_toolkit.output.base.Output] = None, input: Optional[prompt_toolkit.input.base.Input] = None)

Progress bar context manager.

Usage

with ProgressBar(...) as pb:
    for item in pb(data):
        ...
Parameters
  • title – Text to be displayed above the progress bars. This can be a callable or formatted text as well.

  • formatters – List of Formatter instances.

  • bottom_toolbar – Text to be displayed in the bottom toolbar. This can be a callable or formatted text.

  • styleprompt_toolkit.styles.BaseStyle instance.

  • key_bindingsKeyBindings instance.

  • file – The file object used for rendering, by default sys.stderr is used.

  • color_depthprompt_toolkit ColorDepth instance.

  • outputOutput instance.

  • inputInput instance.

class prompt_toolkit.shortcuts.PromptSession(message: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', *, multiline: Union[prompt_toolkit.filters.base.Filter, bool] = False, wrap_lines: Union[prompt_toolkit.filters.base.Filter, bool] = True, is_password: Union[prompt_toolkit.filters.base.Filter, bool] = False, vi_mode: bool = False, editing_mode: prompt_toolkit.enums.EditingMode = EditingMode.EMACS, complete_while_typing: Union[prompt_toolkit.filters.base.Filter, bool] = True, validate_while_typing: Union[prompt_toolkit.filters.base.Filter, bool] = True, enable_history_search: Union[prompt_toolkit.filters.base.Filter, bool] = False, search_ignore_case: Union[prompt_toolkit.filters.base.Filter, bool] = False, lexer: Optional[prompt_toolkit.lexers.base.Lexer] = None, enable_system_prompt: Union[prompt_toolkit.filters.base.Filter, bool] = False, enable_suspend: Union[prompt_toolkit.filters.base.Filter, bool] = False, enable_open_in_editor: Union[prompt_toolkit.filters.base.Filter, bool] = False, validator: Optional[prompt_toolkit.validation.Validator] = None, completer: Optional[prompt_toolkit.completion.base.Completer] = None, complete_in_thread: bool = False, reserve_space_for_menu: int = 8, complete_style: prompt_toolkit.shortcuts.prompt.CompleteStyle = CompleteStyle.COLUMN, auto_suggest: Optional[prompt_toolkit.auto_suggest.AutoSuggest] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, swap_light_and_dark_colors: Union[prompt_toolkit.filters.base.Filter, bool] = False, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None, include_default_pygments_style: Union[prompt_toolkit.filters.base.Filter, bool] = True, history: Optional[prompt_toolkit.history.History] = None, clipboard: Optional[prompt_toolkit.clipboard.base.Clipboard] = None, prompt_continuation: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[int, int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]]] = None, rprompt: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, bottom_toolbar: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, mouse_support: Union[prompt_toolkit.filters.base.Filter, bool] = False, input_processors: Optional[List[prompt_toolkit.layout.processors.Processor]] = None, placeholder: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, erase_when_done: bool = False, tempfile_suffix: Optional[Union[str, Callable[[], str]]] = '.txt', tempfile: Optional[Union[str, Callable[[], str]]] = None, refresh_interval: float = 0, input: Optional[prompt_toolkit.input.base.Input] = None, output: Optional[prompt_toolkit.output.base.Output] = None)

PromptSession for a prompt application, which can be used as a GNU Readline replacement.

This is a wrapper around a lot of prompt_toolkit functionality and can be a replacement for raw_input.

All parameters that expect “formatted text” can take either just plain text (a unicode object), a list of (style_str, text) tuples or an HTML object.

Example usage:

s = PromptSession(message='>')
text = s.prompt()
Parameters
  • message – Plain text or formatted text to be shown before the prompt. This can also be a callable that returns formatted text.

  • multilinebool or Filter. When True, prefer a layout that is more adapted for multiline input. Text after newlines is automatically indented, and search/arg input is shown below the input, instead of replacing the prompt.

  • wrap_linesbool or Filter. When True (the default), automatically wrap long lines instead of scrolling horizontally.

  • is_password – Show asterisks instead of the actual typed characters.

  • editing_modeEditingMode.VI or EditingMode.EMACS.

  • vi_modebool, if True, Identical to editing_mode=EditingMode.VI.

  • complete_while_typingbool or Filter. Enable autocompletion while typing.

  • validate_while_typingbool or Filter. Enable input validation while typing.

  • enable_history_searchbool or Filter. Enable up-arrow parting string matching.

  • search_ignore_caseFilter. Search case insensitive.

  • lexerLexer to be used for the syntax highlighting.

  • validatorValidator instance for input validation.

  • completerCompleter instance for input completion.

  • complete_in_threadbool or Filter. Run the completer code in a background thread in order to avoid blocking the user interface. For CompleteStyle.READLINE_LIKE, this setting has no effect. There we always run the completions in the main thread.

  • reserve_space_for_menu – Space to be reserved for displaying the menu. (0 means that no space needs to be reserved.)

  • auto_suggestAutoSuggest instance for input suggestions.

  • styleStyle instance for the color scheme.

  • include_default_pygments_stylebool or Filter. Tell whether the default styling for Pygments lexers has to be included. By default, this is true, but it is recommended to be disabled if another Pygments style is passed as the style argument, otherwise, two Pygments styles will be merged.

  • style_transformationStyleTransformation instance.

  • swap_light_and_dark_colorsbool or Filter. When enabled, apply SwapLightAndDarkStyleTransformation. This is useful for switching between dark and light terminal backgrounds.

  • enable_system_promptbool or Filter. Pressing Meta+’!’ will show a system prompt.

  • enable_suspendbool or Filter. Enable Control-Z style suspension.

  • enable_open_in_editorbool or Filter. Pressing ‘v’ in Vi mode or C-X C-E in emacs mode will open an external editor.

  • historyHistory instance.

  • clipboardClipboard instance. (e.g. InMemoryClipboard)

  • rprompt – Text or formatted text to be displayed on the right side. This can also be a callable that returns (formatted) text.

  • bottom_toolbar – Formatted text or callable which is supposed to return formatted text.

  • prompt_continuation – Text that needs to be displayed for a multiline prompt continuation. This can either be formatted text or a callable that takes a prompt_width, line_number and wrap_count as input and returns formatted text. When this is None (the default), then prompt_width spaces will be used.

  • complete_styleCompleteStyle.COLUMN, CompleteStyle.MULTI_COLUMN or CompleteStyle.READLINE_LIKE.

  • mouse_supportbool or Filter to enable mouse support.

  • placeholder – Text to be displayed when no input has been given yet. Unlike the default parameter, this won’t be returned as part of the output ever. This can be formatted text or a callable that returns formatted text.

  • refresh_interval – (number; in seconds) When given, refresh the UI every so many seconds.

  • inputInput object. (Note that the preferred way to change the input/output is by creating an AppSession.)

  • outputOutput object.

prompt(message: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, *, editing_mode: Optional[prompt_toolkit.enums.EditingMode] = None, refresh_interval: Optional[float] = None, vi_mode: Optional[bool] = None, lexer: Optional[prompt_toolkit.lexers.base.Lexer] = None, completer: Optional[prompt_toolkit.completion.base.Completer] = None, complete_in_thread: Optional[bool] = None, is_password: Optional[bool] = None, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, bottom_toolbar: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None, include_default_pygments_style: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, swap_light_and_dark_colors: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, rprompt: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, multiline: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, prompt_continuation: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[int, int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]]] = None, wrap_lines: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_history_search: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, search_ignore_case: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, complete_while_typing: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, validate_while_typing: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, complete_style: Optional[prompt_toolkit.shortcuts.prompt.CompleteStyle] = None, auto_suggest: Optional[prompt_toolkit.auto_suggest.AutoSuggest] = None, validator: Optional[prompt_toolkit.validation.Validator] = None, clipboard: Optional[prompt_toolkit.clipboard.base.Clipboard] = None, mouse_support: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, input_processors: Optional[List[prompt_toolkit.layout.processors.Processor]] = None, placeholder: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, reserve_space_for_menu: Optional[int] = None, enable_system_prompt: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_suspend: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_open_in_editor: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, tempfile_suffix: Optional[Union[str, Callable[[], str]]] = None, tempfile: Optional[Union[str, Callable[[], str]]] = None, default: Union[str, prompt_toolkit.document.Document] = '', accept_default: bool = False, pre_run: Optional[Callable[[], None]] = None, set_exception_handler: bool = True, in_thread: bool = False) prompt_toolkit.shortcuts.prompt._T

Display the prompt.

The first set of arguments is a subset of the PromptSession class itself. For these, passing in None will keep the current values that are active in the session. Passing in a value will set the attribute for the session, which means that it applies to the current, but also to the next prompts.

Note that in order to erase a Completer, Validator or AutoSuggest, you can’t use None. Instead pass in a DummyCompleter, DummyValidator or DummyAutoSuggest instance respectively. For a Lexer you can pass in an empty SimpleLexer.

Additional arguments, specific for this prompt:

Parameters
  • default – The default input text to be shown. (This can be edited by the user).

  • accept_default – When True, automatically accept the default value without allowing the user to edit the input.

  • pre_run – Callable, called at the start of Application.run.

  • in_thread – Run the prompt in a background thread; block the current thread. This avoids interference with an event loop in the current thread. Like Application.run(in_thread=True).

This method will raise KeyboardInterrupt when control-c has been pressed (for abort) and EOFError when control-d has been pressed (for exit).

prompt_toolkit.shortcuts.button_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', buttons: List[Tuple[str, prompt_toolkit.shortcuts.dialogs._T]] = [], style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[prompt_toolkit.shortcuts.dialogs._T]

Display a dialog with button choices (given as a list of tuples). Return the value associated with button.

prompt_toolkit.shortcuts.clear() None

Clear the screen.

prompt_toolkit.shortcuts.clear_title() None

Erase the current title.

prompt_toolkit.shortcuts.confirm(message: str = 'Confirm?', suffix: str = ' (y/n) ') bool

Display a confirmation prompt that returns True/False.

prompt_toolkit.shortcuts.create_confirm_session(message: str, suffix: str = ' (y/n) ') prompt_toolkit.shortcuts.prompt.PromptSession[bool]

Create a PromptSession object for the ‘confirm’ function.

prompt_toolkit.shortcuts.input_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', ok_text: str = 'OK', cancel_text: str = 'Cancel', completer: Optional[prompt_toolkit.completion.base.Completer] = None, validator: Optional[prompt_toolkit.validation.Validator] = None, password: Union[prompt_toolkit.filters.base.Filter, bool] = False, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[str]

Display a text input box. Return the given text, or None when cancelled.

prompt_toolkit.shortcuts.message_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', ok_text: str = 'Ok', style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[None]

Display a simple message box and wait until the user presses enter.

prompt_toolkit.shortcuts.print_formatted_text(*values: Any, sep: str = ' ', end: str = '\n', file: Optional[TextIO] = None, flush: bool = False, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, output: Optional[prompt_toolkit.output.base.Output] = None, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, include_default_pygments_style: bool = True) None
print_formatted_text(*values, sep=' ', end='\n', file=None, flush=False, style=None, output=None)

Print text to stdout. This is supposed to be compatible with Python’s print function, but supports printing of formatted text. You can pass a FormattedText, HTML or ANSI object to print formatted text.

  • Print HTML as follows:

    print_formatted_text(HTML('<i>Some italic text</i> <ansired>This is red!</ansired>'))
    
    style = Style.from_dict({
        'hello': '#ff0066',
        'world': '#884444 italic',
    })
    print_formatted_text(HTML('<hello>Hello</hello> <world>world</world>!'), style=style)
    
  • Print a list of (style_str, text) tuples in the given style to the output. E.g.:

    style = Style.from_dict({
        'hello': '#ff0066',
        'world': '#884444 italic',
    })
    fragments = FormattedText([
        ('class:hello', 'Hello'),
        ('class:world', 'World'),
    ])
    print_formatted_text(fragments, style=style)
    

If you want to print a list of Pygments tokens, wrap it in PygmentsTokens to do the conversion.

If a prompt_toolkit Application is currently running, this will always print above the application or prompt (similar to patch_stdout). So, print_formatted_text will erase the current application, print the text, and render the application again.

Parameters
  • values – Any kind of printable object, or formatted string.

  • sep – String inserted between values, default a space.

  • end – String appended after the last value, default a newline.

  • styleStyle instance for the color scheme.

  • include_default_pygments_stylebool. Include the default Pygments style when set to True (the default).

prompt_toolkit.shortcuts.progress_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', run_callback: Callable[[Callable[[int], None], Callable[[str], None]], None] = <function <lambda>>, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[None]
Parameters

run_callback – A function that receives as input a set_percentage function and it does the work.

prompt_toolkit.shortcuts.prompt(message: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, *, history: Optional[prompt_toolkit.history.History] = None, editing_mode: Optional[prompt_toolkit.enums.EditingMode] = None, refresh_interval: Optional[float] = None, vi_mode: Optional[bool] = None, lexer: Optional[prompt_toolkit.lexers.base.Lexer] = None, completer: Optional[prompt_toolkit.completion.base.Completer] = None, complete_in_thread: Optional[bool] = None, is_password: Optional[bool] = None, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, bottom_toolbar: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None, include_default_pygments_style: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, swap_light_and_dark_colors: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, rprompt: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, multiline: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, prompt_continuation: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[int, int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]]] = None, wrap_lines: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_history_search: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, search_ignore_case: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, complete_while_typing: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, validate_while_typing: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, complete_style: Optional[prompt_toolkit.shortcuts.prompt.CompleteStyle] = None, auto_suggest: Optional[prompt_toolkit.auto_suggest.AutoSuggest] = None, validator: Optional[prompt_toolkit.validation.Validator] = None, clipboard: Optional[prompt_toolkit.clipboard.base.Clipboard] = None, mouse_support: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, input_processors: Optional[List[prompt_toolkit.layout.processors.Processor]] = None, placeholder: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = None, reserve_space_for_menu: Optional[int] = None, enable_system_prompt: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_suspend: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, enable_open_in_editor: Optional[Union[prompt_toolkit.filters.base.Filter, bool]] = None, tempfile_suffix: Optional[Union[str, Callable[[], str]]] = None, tempfile: Optional[Union[str, Callable[[], str]]] = None, default: str = '', accept_default: bool = False, pre_run: Optional[Callable[[], None]] = None) str

Display the prompt.

The first set of arguments is a subset of the PromptSession class itself. For these, passing in None will keep the current values that are active in the session. Passing in a value will set the attribute for the session, which means that it applies to the current, but also to the next prompts.

Note that in order to erase a Completer, Validator or AutoSuggest, you can’t use None. Instead pass in a DummyCompleter, DummyValidator or DummyAutoSuggest instance respectively. For a Lexer you can pass in an empty SimpleLexer.

Additional arguments, specific for this prompt:

Parameters
  • default – The default input text to be shown. (This can be edited by the user).

  • accept_default – When True, automatically accept the default value without allowing the user to edit the input.

  • pre_run – Callable, called at the start of Application.run.

  • in_thread – Run the prompt in a background thread; block the current thread. This avoids interference with an event loop in the current thread. Like Application.run(in_thread=True).

This method will raise KeyboardInterrupt when control-c has been pressed (for abort) and EOFError when control-d has been pressed (for exit).

prompt_toolkit.shortcuts.radiolist_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', ok_text: str = 'Ok', cancel_text: str = 'Cancel', values: Optional[List[Tuple[prompt_toolkit.shortcuts.dialogs._T, Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]]] = None, style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[prompt_toolkit.shortcuts.dialogs._T]

Display a simple list of element the user can choose amongst.

Only one element can be selected at a time using Arrow keys and Enter. The focus can be moved between the list and the Ok/Cancel button with tab.

prompt_toolkit.shortcuts.set_title(text: str) None

Set the terminal title.

prompt_toolkit.shortcuts.yes_no_dialog(title: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', yes_text: str = 'Yes', no_text: str = 'No', style: Optional[prompt_toolkit.styles.base.BaseStyle] = None) prompt_toolkit.application.application.Application[bool]

Display a Yes/No dialog. Return a boolean.

Formatter classes for the progress bar. Each progress bar consists of a list of these formatters.

class prompt_toolkit.shortcuts.progress_bar.formatters.Bar(start: str = '[', end: str = ']', sym_a: str = '=', sym_b: str = '>', sym_c: str = ' ', unknown: str = '#')

Display the progress bar itself.

class prompt_toolkit.shortcuts.progress_bar.formatters.Formatter

Base class for any formatter.

class prompt_toolkit.shortcuts.progress_bar.formatters.IterationsPerSecond

Display the iterations per second.

class prompt_toolkit.shortcuts.progress_bar.formatters.Label(width: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, suffix: str = '')

Display the name of the current task.

Parameters
  • width – If a width is given, use this width. Scroll the text if it doesn’t fit in this width.

  • suffix – String suffix to be added after the task name, e.g. ‘: ‘. If no task name was given, no suffix will be added.

class prompt_toolkit.shortcuts.progress_bar.formatters.Percentage

Display the progress as a percentage.

class prompt_toolkit.shortcuts.progress_bar.formatters.Progress

Display the progress as text. E.g. “8/20”

class prompt_toolkit.shortcuts.progress_bar.formatters.Rainbow(formatter: prompt_toolkit.shortcuts.progress_bar.formatters.Formatter)

For the fun. Add rainbow colors to any of the other formatters.

class prompt_toolkit.shortcuts.progress_bar.formatters.SpinningWheel

Display a spinning wheel.

class prompt_toolkit.shortcuts.progress_bar.formatters.Text(text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]], style: str = '')

Display plain text.

class prompt_toolkit.shortcuts.progress_bar.formatters.TimeElapsed

Display the elapsed time.

class prompt_toolkit.shortcuts.progress_bar.formatters.TimeLeft

Display the time left.

prompt_toolkit.shortcuts.progress_bar.formatters.create_default_formatters() List[prompt_toolkit.shortcuts.progress_bar.formatters.Formatter]

Return the list of default formatters.

Validation

Input validation for a Buffer. (Validators will be called before accepting input.)

class prompt_toolkit.validation.ConditionalValidator(validator: prompt_toolkit.validation.Validator, filter: Union[prompt_toolkit.filters.base.Filter, bool])

Validator that can be switched on/off according to a filter. (This wraps around another validator.)

validate(document: prompt_toolkit.document.Document) None

Validate the input. If invalid, this should raise a ValidationError.

Parameters

documentDocument instance.

class prompt_toolkit.validation.DummyValidator

Validator class that accepts any input.

validate(document: prompt_toolkit.document.Document) None

Validate the input. If invalid, this should raise a ValidationError.

Parameters

documentDocument instance.

class prompt_toolkit.validation.DynamicValidator(get_validator: Callable[[], Optional[prompt_toolkit.validation.Validator]])

Validator class that can dynamically returns any Validator.

Parameters

get_validator – Callable that returns a Validator instance.

validate(document: prompt_toolkit.document.Document) None

Validate the input. If invalid, this should raise a ValidationError.

Parameters

documentDocument instance.

async validate_async(document: prompt_toolkit.document.Document) None

Return a Future which is set when the validation is ready. This function can be overloaded in order to provide an asynchronous implementation.

class prompt_toolkit.validation.ThreadedValidator(validator: prompt_toolkit.validation.Validator)

Wrapper that runs input validation in a thread. (Use this to prevent the user interface from becoming unresponsive if the input validation takes too much time.)

validate(document: prompt_toolkit.document.Document) None

Validate the input. If invalid, this should raise a ValidationError.

Parameters

documentDocument instance.

async validate_async(document: prompt_toolkit.document.Document) None

Run the validate function in a thread.

exception prompt_toolkit.validation.ValidationError(cursor_position: int = 0, message: str = '')

Error raised by Validator.validate().

Parameters
  • cursor_position – The cursor position where the error occurred.

  • message – Text.

class prompt_toolkit.validation.Validator

Abstract base class for an input validator.

A validator is typically created in one of the following two ways:

  • Either by overriding this class and implementing the validate method.

  • Or by passing a callable to Validator.from_callable.

If the validation takes some time and needs to happen in a background thread, this can be wrapped in a ThreadedValidator.

classmethod from_callable(validate_func: Callable[[str], bool], error_message: str = 'Invalid input', move_cursor_to_end: bool = False) prompt_toolkit.validation.Validator

Create a validator from a simple validate callable. E.g.:

def is_valid(text):
    return text in ['hello', 'world']
Validator.from_callable(is_valid, error_message='Invalid input')
Parameters
  • validate_func – Callable that takes the input string, and returns True if the input is valid input.

  • error_message – Message to be displayed if the input is invalid.

  • move_cursor_to_end – Move the cursor to the end of the input, if the input is invalid.

abstract validate(document: prompt_toolkit.document.Document) None

Validate the input. If invalid, this should raise a ValidationError.

Parameters

documentDocument instance.

async validate_async(document: prompt_toolkit.document.Document) None

Return a Future which is set when the validation is ready. This function can be overloaded in order to provide an asynchronous implementation.

Auto suggestion

Fish-style like auto-suggestion.

While a user types input in a certain buffer, suggestions are generated (asynchronously.) Usually, they are displayed after the input. When the cursor presses the right arrow and the cursor is at the end of the input, the suggestion will be inserted.

If you want the auto suggestions to be asynchronous (in a background thread), because they take too much time, and could potentially block the event loop, then wrap the AutoSuggest instance into a ThreadedAutoSuggest.

class prompt_toolkit.auto_suggest.AutoSuggest

Base class for auto suggestion implementations.

abstract get_suggestion(buffer: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
async get_suggestion_async(buff: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return a Future which is set when the suggestions are ready. This function can be overloaded in order to provide an asynchronous implementation.

class prompt_toolkit.auto_suggest.AutoSuggestFromHistory

Give suggestions based on the lines in the history.

get_suggestion(buffer: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
class prompt_toolkit.auto_suggest.ConditionalAutoSuggest(auto_suggest: prompt_toolkit.auto_suggest.AutoSuggest, filter: Union[bool, prompt_toolkit.filters.base.Filter])

Auto suggest that can be turned on and of according to a certain condition.

get_suggestion(buffer: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
class prompt_toolkit.auto_suggest.DummyAutoSuggest

AutoSuggest class that doesn’t return any suggestion.

get_suggestion(buffer: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
class prompt_toolkit.auto_suggest.DynamicAutoSuggest(get_auto_suggest: Callable[[], Optional[prompt_toolkit.auto_suggest.AutoSuggest]])

Validator class that can dynamically returns any Validator.

Parameters

get_validator – Callable that returns a Validator instance.

get_suggestion(buff: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
async get_suggestion_async(buff: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return a Future which is set when the suggestions are ready. This function can be overloaded in order to provide an asynchronous implementation.

class prompt_toolkit.auto_suggest.Suggestion(text: str)

Suggestion returned by an auto-suggest algorithm.

Parameters

text – The suggestion text.

class prompt_toolkit.auto_suggest.ThreadedAutoSuggest(auto_suggest: prompt_toolkit.auto_suggest.AutoSuggest)

Wrapper that runs auto suggestions in a thread. (Use this to prevent the user interface from becoming unresponsive if the generation of suggestions takes too much time.)

get_suggestion(buff: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Return None or a Suggestion instance.

We receive both Buffer and Document. The reason is that auto suggestions are retrieved asynchronously. (Like completions.) The buffer text could be changed in the meantime, but document contains the buffer document like it was at the start of the auto suggestion call. So, from here, don’t access buffer.text, but use document.text instead.

Parameters
async get_suggestion_async(buff: Buffer, document: prompt_toolkit.document.Document) Optional[prompt_toolkit.auto_suggest.Suggestion]

Run the get_suggestion function in a thread.

Renderer

Renders the command line on the console. (Redraws parts of the input line that were changed.)

class prompt_toolkit.renderer.Renderer(style: prompt_toolkit.styles.base.BaseStyle, output: prompt_toolkit.output.base.Output, full_screen: bool = False, mouse_support: Union[prompt_toolkit.filters.base.Filter, bool] = False, cpr_not_supported_callback: Optional[Callable[[], None]] = None)

Typical usage:

output = Vt100_Output.from_pty(sys.stdout)
r = Renderer(style, output)
r.render(app, layout=...)
clear() None

Clear screen and go to 0,0

erase(leave_alternate_screen: bool = True) None

Hide all output and put the cursor back at the first line. This is for instance used for running a system command (while hiding the CLI) and later resuming the same CLI.)

Parameters

leave_alternate_screen – When True, and when inside an alternate screen buffer, quit the alternate screen.

property height_is_known: bool

True when the height from the cursor until the bottom of the terminal is known. (It’s often nicer to draw bottom toolbars only if the height is known, in order to avoid flickering when the CPR response arrives.)

property last_rendered_screen: Optional[prompt_toolkit.layout.screen.Screen]

The Screen class that was generated during the last rendering. This can be None.

render(app: Application[Any], layout: Layout, is_done: bool = False) None

Render the current interface to the output.

Parameters

is_done – When True, put the cursor at the end of the interface. We won’t print any changes to this part.

report_absolute_cursor_row(row: int) None

To be called when we know the absolute cursor position. (As an answer of a “Cursor Position Request” response.)

request_absolute_cursor_position() None

Get current cursor position.

We do this to calculate the minimum available height that we can consume for rendering the prompt. This is the available space below te cursor.

For vt100: Do CPR request. (answer will arrive later.) For win32: Do API call. (Answer comes immediately.)

property rows_above_layout: int

Return the number of rows visible in the terminal above the layout.

async wait_for_cpr_responses(timeout: int = 1) None

Wait for a CPR response.

property waiting_for_cpr: bool

Waiting for CPR flag. True when we send the request, but didn’t got a response.

prompt_toolkit.renderer.print_formatted_text(output: prompt_toolkit.output.base.Output, formatted_text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]], style: prompt_toolkit.styles.base.BaseStyle, style_transformation: Optional[prompt_toolkit.styles.style_transformation.StyleTransformation] = None, color_depth: Optional[prompt_toolkit.output.color_depth.ColorDepth] = None) None

Print a list of (style_str, text) tuples in the given style to the output.

Lexers

Lexer interface and implementations. Used for syntax highlighting.

class prompt_toolkit.lexers.DynamicLexer(get_lexer: Callable[[], Optional[prompt_toolkit.lexers.base.Lexer]])

Lexer class that can dynamically returns any Lexer.

Parameters

get_lexer – Callable that returns a Lexer instance.

invalidation_hash() Hashable

When this changes, lex_document could give a different output. (Only used for DynamicLexer.)

lex_document(document: prompt_toolkit.document.Document) Callable[[int], List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]]

Takes a Document and returns a callable that takes a line number and returns a list of (style_str, text) tuples for that line.

XXX: Note that in the past, this was supposed to return a list

of (Token, text) tuples, just like a Pygments lexer.

class prompt_toolkit.lexers.Lexer

Base class for all lexers.

invalidation_hash() Hashable

When this changes, lex_document could give a different output. (Only used for DynamicLexer.)

abstract lex_document(document: prompt_toolkit.document.Document) Callable[[int], List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]]

Takes a Document and returns a callable that takes a line number and returns a list of (style_str, text) tuples for that line.

XXX: Note that in the past, this was supposed to return a list

of (Token, text) tuples, just like a Pygments lexer.

class prompt_toolkit.lexers.PygmentsLexer(pygments_lexer_cls: Type[PygmentsLexerCls], sync_from_start: Union[prompt_toolkit.filters.base.Filter, bool] = True, syntax_sync: Optional[prompt_toolkit.lexers.pygments.SyntaxSync] = None)

Lexer that calls a pygments lexer.

Example:

from pygments.lexers.html import HtmlLexer
lexer = PygmentsLexer(HtmlLexer)

Note: Don’t forget to also load a Pygments compatible style. E.g.:

from prompt_toolkit.styles.from_pygments import style_from_pygments_cls
from pygments.styles import get_style_by_name
style = style_from_pygments_cls(get_style_by_name('monokai'))
Parameters
  • pygments_lexer_cls – A Lexer from Pygments.

  • sync_from_start – Start lexing at the start of the document. This will always give the best results, but it will be slow for bigger documents. (When the last part of the document is display, then the whole document will be lexed by Pygments on every key stroke.) It is recommended to disable this for inputs that are expected to be more than 1,000 lines.

  • syntax_syncSyntaxSync object.

classmethod from_filename(filename: str, sync_from_start: Union[prompt_toolkit.filters.base.Filter, bool] = True) prompt_toolkit.lexers.base.Lexer

Create a Lexer from a filename.

lex_document(document: prompt_toolkit.document.Document) Callable[[int], List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]]

Create a lexer function that takes a line number and returns the list of (style_str, text) tuples as the Pygments lexer returns for that line.

class prompt_toolkit.lexers.RegexSync(pattern: str)

Synchronize by starting at a line that matches the given regex pattern.

classmethod from_pygments_lexer_cls(lexer_cls: PygmentsLexerCls) RegexSync

Create a RegexSync instance for this Pygments lexer class.

get_sync_start_position(document: prompt_toolkit.document.Document, lineno: int) Tuple[int, int]

Scan backwards, and find a possible position to start.

class prompt_toolkit.lexers.SimpleLexer(style: str = '')

Lexer that doesn’t do any tokenizing and returns the whole input as one token.

Parameters

style – The style string for this lexer.

lex_document(document: prompt_toolkit.document.Document) Callable[[int], List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]]

Takes a Document and returns a callable that takes a line number and returns a list of (style_str, text) tuples for that line.

XXX: Note that in the past, this was supposed to return a list

of (Token, text) tuples, just like a Pygments lexer.

class prompt_toolkit.lexers.SyncFromStart

Always start the syntax highlighting from the beginning.

get_sync_start_position(document: prompt_toolkit.document.Document, lineno: int) Tuple[int, int]

Return the position from where we can start lexing as a (row, column) tuple.

Parameters
  • documentDocument instance that contains all the lines.

  • lineno – The line that we want to highlight. (We need to return this line, or an earlier position.)

class prompt_toolkit.lexers.SyntaxSync

Syntax synchroniser. This is a tool that finds a start position for the lexer. This is especially important when editing big documents; we don’t want to start the highlighting by running the lexer from the beginning of the file. That is very slow when editing.

abstract get_sync_start_position(document: prompt_toolkit.document.Document, lineno: int) Tuple[int, int]

Return the position from where we can start lexing as a (row, column) tuple.

Parameters
  • documentDocument instance that contains all the lines.

  • lineno – The line that we want to highlight. (We need to return this line, or an earlier position.)

Layout

Command line layout definitions

The layout of a command line interface is defined by a Container instance. There are two main groups of classes here. Containers and controls:

  • A container can contain other containers or controls, it can have multiple children and it decides about the dimensions.

  • A control is responsible for rendering the actual content to a screen. A control can propose some dimensions, but it’s the container who decides about the dimensions – or when the control consumes more space – which part of the control will be visible.

Container classes:

- Container (Abstract base class)
   |- HSplit (Horizontal split)
   |- VSplit (Vertical split)
   |- FloatContainer (Container which can also contain menus and other floats)
   `- Window (Container which contains one actual control

Control classes:

- UIControl (Abstract base class)
   |- FormattedTextControl (Renders formatted text, or a simple list of text fragments)
   `- BufferControl (Renders an input buffer.)

Usually, you end up wrapping every control inside a Window object, because that’s the only way to render it in a layout.

There are some prepared toolbars which are ready to use:

- SystemToolbar (Shows the 'system' input buffer, for entering system commands.)
- ArgToolbar (Shows the input 'arg', for repetition of input commands.)
- SearchToolbar (Shows the 'search' input buffer, for incremental search.)
- CompletionsToolbar (Shows the completions of the current buffer.)
- ValidationToolbar (Shows validation errors of the current buffer.)

And one prepared menu:

  • CompletionsMenu

The layout class itself

class prompt_toolkit.layout.Layout(container: Union[prompt_toolkit.layout.containers.Container, MagicContainer], focused_element: Optional[Union[str, prompt_toolkit.buffer.Buffer, prompt_toolkit.layout.controls.UIControl, prompt_toolkit.layout.containers.Container, MagicContainer]] = None)

The layout for a prompt_toolkit Application. This also keeps track of which user control is focused.

Parameters
  • container – The “root” container for the layout.

  • focused_element – element to be focused initially. (Can be anything the focus function accepts.)

property buffer_has_focus: bool

Return True if the currently focused control is a BufferControl. (For instance, used to determine whether the default key bindings should be active or not.)

property current_buffer: Optional[prompt_toolkit.buffer.Buffer]

The currently focused Buffer or None.

property current_control: prompt_toolkit.layout.controls.UIControl

Get the UIControl to currently has the focus.

property current_window: prompt_toolkit.layout.containers.Window

Return the Window object that is currently focused.

find_all_windows() Generator[prompt_toolkit.layout.containers.Window, None, None]

Find all the UIControl objects in this layout.

focus(value: Union[str, prompt_toolkit.buffer.Buffer, prompt_toolkit.layout.controls.UIControl, prompt_toolkit.layout.containers.Container, MagicContainer]) None

Focus the given UI element.

value can be either:

  • a UIControl

  • a Buffer instance or the name of a Buffer

  • a Window

  • Any container object. In this case we will focus the Window from this container that was focused most recent, or the very first focusable Window of the container.

focus_last() None

Give the focus to the last focused control.

focus_next() None

Focus the next visible/focusable Window.

focus_previous() None

Focus the previous visible/focusable Window.

get_buffer_by_name(buffer_name: str) Optional[prompt_toolkit.buffer.Buffer]

Look in the layout for a buffer with the given name. Return None when nothing was found.

get_focusable_windows() Iterable[prompt_toolkit.layout.containers.Window]

Return all the Window objects which are focusable (in the ‘modal’ area).

get_parent(container: prompt_toolkit.layout.containers.Container) Optional[prompt_toolkit.layout.containers.Container]

Return the parent container for the given container, or None, if it wasn’t found.

get_visible_focusable_windows() List[prompt_toolkit.layout.containers.Window]

Return a list of Window objects that are focusable.

has_focus(value: Union[str, prompt_toolkit.buffer.Buffer, prompt_toolkit.layout.controls.UIControl, prompt_toolkit.layout.containers.Container, MagicContainer]) bool

Check whether the given control has the focus. :param value: UIControl or Window instance.

property is_searching: bool

True if we are searching right now.

property previous_control: prompt_toolkit.layout.controls.UIControl

Get the UIControl to previously had the focus.

property search_target_buffer_control: Optional[prompt_toolkit.layout.controls.BufferControl]

Return the BufferControl in which we are searching or None.

update_parents_relations() None

Update child->parent relationships mapping.

walk() Iterable[prompt_toolkit.layout.containers.Container]

Walk through all the layout nodes (and their children) and yield them.

walk_through_modal_area() Iterable[prompt_toolkit.layout.containers.Container]

Walk through all the containers which are in the current ‘modal’ part of the layout.

class prompt_toolkit.layout.InvalidLayoutError
class prompt_toolkit.layout.walk(container: prompt_toolkit.layout.containers.Container, skip_hidden: bool = False)

Walk through layout, starting at this container.

Containers

class prompt_toolkit.layout.Container

Base class for user interface layout.

abstract get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

get_key_bindings() Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase]

Returns a KeyBindings object. These bindings become active when any user control in this container has the focus, except if any containers between this container and the focused user control is modal.

is_modal() bool

When this container is modal, key bindings from parent containers are not taken into account if a user control in this container is focused.

abstract preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

abstract preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

abstract reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

abstract write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Write the actual content to the screen.

Parameters
  • screenScreen

  • mouse_handlersMouseHandlers.

  • parent_style – Style string to pass to the Window object. This will be applied to all content of the windows. VSplit and HSplit can use it to pass their style down to the windows that they contain.

  • z_index – Used for propagating z_index from parent to child.

class prompt_toolkit.layout.HSplit(children: Sequence[Union[prompt_toolkit.layout.containers.Container, MagicContainer]], window_too_small: Optional[prompt_toolkit.layout.containers.Container] = None, align: prompt_toolkit.layout.containers.VerticalAlign = VerticalAlign.JUSTIFY, padding: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = 0, padding_char: Optional[str] = None, padding_style: str = '', width: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, height: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, z_index: Optional[int] = None, modal: bool = False, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, style: Union[str, Callable[[], str]] = '')

Several layouts, one stacked above/under the other.

+--------------------+
|                    |
+--------------------+
|                    |
+--------------------+

By default, this doesn’t display a horizontal line between the children, but if this is something you need, then create a HSplit as follows:

HSplit(children=[ ... ], padding_char='-',
       padding=1, padding_style='#ffff00')
Parameters
  • children – List of child Container objects.

  • window_too_small – A Container object that is displayed if there is not enough space for all the children. By default, this is a “Window too small” message.

  • alignVerticalAlign value.

  • width – When given, use this width instead of looking at the children.

  • height – When given, use this height instead of looking at the children.

  • z_index – (int or None) When specified, this can be used to bring element in front of floating elements. None means: inherit from parent.

  • style – A style string.

  • modalTrue or False.

  • key_bindingsNone or a KeyBindings object.

  • padding – (Dimension or int), size to be used for the padding.

  • padding_char – Character to be used for filling in the padding.

  • padding_style – Style to applied to the padding.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Render the prompt to a Screen instance.

Parameters

screen – The Screen class to which the output has to be written.

class prompt_toolkit.layout.VSplit(children: Sequence[Union[prompt_toolkit.layout.containers.Container, MagicContainer]], window_too_small: Optional[prompt_toolkit.layout.containers.Container] = None, align: prompt_toolkit.layout.containers.HorizontalAlign = HorizontalAlign.JUSTIFY, padding: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = 0, padding_char: Optional[str] = None, padding_style: str = '', width: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, height: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, z_index: Optional[int] = None, modal: bool = False, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, style: Union[str, Callable[[], str]] = '')

Several layouts, one stacked left/right of the other.

+---------+----------+
|         |          |
|         |          |
+---------+----------+

By default, this doesn’t display a vertical line between the children, but if this is something you need, then create a HSplit as follows:

VSplit(children=[ ... ], padding_char='|',
       padding=1, padding_style='#ffff00')
Parameters
  • children – List of child Container objects.

  • window_too_small – A Container object that is displayed if there is not enough space for all the children. By default, this is a “Window too small” message.

  • alignHorizontalAlign value.

  • width – When given, use this width instead of looking at the children.

  • height – When given, use this height instead of looking at the children.

  • z_index – (int or None) When specified, this can be used to bring element in front of floating elements. None means: inherit from parent.

  • style – A style string.

  • modalTrue or False.

  • key_bindingsNone or a KeyBindings object.

  • padding – (Dimension or int), size to be used for the padding.

  • padding_char – Character to be used for filling in the padding.

  • padding_style – Style to applied to the padding.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Render the prompt to a Screen instance.

Parameters

screen – The Screen class to which the output has to be written.

class prompt_toolkit.layout.FloatContainer(content: Union[prompt_toolkit.layout.containers.Container, MagicContainer], floats: List[Float], modal: bool = False, key_bindings: Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase] = None, style: Union[str, Callable[[], str]] = '', z_index: Optional[int] = None)

Container which can contain another container for the background, as well as a list of floating containers on top of it.

Example Usage:

FloatContainer(content=Window(...),
               floats=[
                   Float(xcursor=True,
                        ycursor=True,
                        content=CompletionsMenu(...))
               ])
Parameters

z_index – (int or None) When specified, this can be used to bring element in front of floating elements. None means: inherit from parent. This is the z_index for the whole Float container as a whole.

get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

get_key_bindings() Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase]

Returns a KeyBindings object. These bindings become active when any user control in this container has the focus, except if any containers between this container and the focused user control is modal.

is_modal() bool

When this container is modal, key bindings from parent containers are not taken into account if a user control in this container is focused.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return the preferred height of the float container. (We don’t care about the height of the floats, they should always fit into the dimensions provided by the container.)

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Write the actual content to the screen.

Parameters
  • screenScreen

  • mouse_handlersMouseHandlers.

  • parent_style – Style string to pass to the Window object. This will be applied to all content of the windows. VSplit and HSplit can use it to pass their style down to the windows that they contain.

  • z_index – Used for propagating z_index from parent to child.

class prompt_toolkit.layout.Float(content: Union[prompt_toolkit.layout.containers.Container, MagicContainer], top: Optional[int] = None, right: Optional[int] = None, bottom: Optional[int] = None, left: Optional[int] = None, width: Optional[Union[int, Callable[[], int]]] = None, height: Optional[Union[int, Callable[[], int]]] = None, xcursor: bool = False, ycursor: bool = False, attach_to_window: Optional[Union[prompt_toolkit.layout.containers.Container, MagicContainer]] = None, hide_when_covering_content: bool = False, allow_cover_cursor: bool = False, z_index: int = 1, transparent: bool = False)

Float for use in a FloatContainer. Except for the content parameter, all other options are optional.

Parameters
  • contentContainer instance.

  • widthDimension or callable which returns a Dimension.

  • heightDimension or callable which returns a Dimension.

  • left – Distance to the left edge of the FloatContainer.

  • right – Distance to the right edge of the FloatContainer.

  • top – Distance to the top of the FloatContainer.

  • bottom – Distance to the bottom of the FloatContainer.

  • attach_to_window – Attach to the cursor from this window, instead of the current window.

  • hide_when_covering_content – Hide the float when it covers content underneath.

  • allow_cover_cursor – When False, make sure to display the float below the cursor. Not on top of the indicated position.

  • z_index – Z-index position. For a Float, this needs to be at least one. It is relative to the z_index of the parent container.

  • transparentFilter indicating whether this float needs to be drawn transparently.

class prompt_toolkit.layout.Window(content: Optional[prompt_toolkit.layout.controls.UIControl] = None, width: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, height: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, z_index: Optional[int] = None, dont_extend_width: Union[prompt_toolkit.filters.base.Filter, bool] = False, dont_extend_height: Union[prompt_toolkit.filters.base.Filter, bool] = False, ignore_content_width: Union[prompt_toolkit.filters.base.Filter, bool] = False, ignore_content_height: Union[prompt_toolkit.filters.base.Filter, bool] = False, left_margins: Optional[Sequence[prompt_toolkit.layout.margins.Margin]] = None, right_margins: Optional[Sequence[prompt_toolkit.layout.margins.Margin]] = None, scroll_offsets: Optional[prompt_toolkit.layout.containers.ScrollOffsets] = None, allow_scroll_beyond_bottom: Union[prompt_toolkit.filters.base.Filter, bool] = False, wrap_lines: Union[prompt_toolkit.filters.base.Filter, bool] = False, get_vertical_scroll: Optional[Callable[[Window], int]] = None, get_horizontal_scroll: Optional[Callable[[Window], int]] = None, always_hide_cursor: Union[prompt_toolkit.filters.base.Filter, bool] = False, cursorline: Union[prompt_toolkit.filters.base.Filter, bool] = False, cursorcolumn: Union[prompt_toolkit.filters.base.Filter, bool] = False, colorcolumns: Union[None, List[prompt_toolkit.layout.containers.ColorColumn], Callable[[], List[prompt_toolkit.layout.containers.ColorColumn]]] = None, align: Union[prompt_toolkit.layout.containers.WindowAlign, Callable[[], prompt_toolkit.layout.containers.WindowAlign]] = WindowAlign.LEFT, style: Union[str, Callable[[], str]] = '', char: Union[None, str, Callable[[], str]] = None, get_line_prefix: Optional[Callable[[int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]] = None)

Container that holds a control.

Parameters
  • contentUIControl instance.

  • widthDimension instance or callable.

  • heightDimension instance or callable.

  • z_index – When specified, this can be used to bring element in front of floating elements.

  • dont_extend_width – When True, don’t take up more width then the preferred width reported by the control.

  • dont_extend_height – When True, don’t take up more width then the preferred height reported by the control.

  • ignore_content_width – A bool or Filter instance. Ignore the UIContent width when calculating the dimensions.

  • ignore_content_height – A bool or Filter instance. Ignore the UIContent height when calculating the dimensions.

  • left_margins – A list of Margin instance to be displayed on the left. For instance: NumberedMargin can be one of them in order to show line numbers.

  • right_margins – Like left_margins, but on the other side.

  • scroll_offsetsScrollOffsets instance, representing the preferred amount of lines/columns to be always visible before/after the cursor. When both top and bottom are a very high number, the cursor will be centered vertically most of the time.

  • allow_scroll_beyond_bottom – A bool or Filter instance. When True, allow scrolling so far, that the top part of the content is not visible anymore, while there is still empty space available at the bottom of the window. In the Vi editor for instance, this is possible. You will see tildes while the top part of the body is hidden.

  • wrap_lines – A bool or Filter instance. When True, don’t scroll horizontally, but wrap lines instead.

  • get_vertical_scroll – Callable that takes this window instance as input and returns a preferred vertical scroll. (When this is None, the scroll is only determined by the last and current cursor position.)

  • get_horizontal_scroll – Callable that takes this window instance as input and returns a preferred vertical scroll.

  • always_hide_cursor – A bool or Filter instance. When True, never display the cursor, even when the user control specifies a cursor position.

  • cursorline – A bool or Filter instance. When True, display a cursorline.

  • cursorcolumn – A bool or Filter instance. When True, display a cursorcolumn.

  • colorcolumns – A list of ColorColumn instances that describe the columns to be highlighted, or a callable that returns such a list.

  • alignWindowAlign value or callable that returns an WindowAlign value. alignment of content.

  • style – A style string. Style to be applied to all the cells in this window. (This can be a callable that returns a string.)

  • char – (string) Character to be used for filling the background. This can also be a callable that returns a character.

  • get_line_prefix – None or a callable that returns formatted text to be inserted before a line. It takes a line number (int) and a wrap_count and returns formatted text. This can be used for implementation of line continuations, things like Vim “breakindent” and so on.

get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

get_key_bindings() Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase]

Returns a KeyBindings object. These bindings become active when any user control in this container has the focus, except if any containers between this container and the focused user control is modal.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Calculate the preferred height for this window.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Calculate the preferred width for this window.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Write window to screen. This renders the user control, the margins and copies everything over to the absolute position at the given screen.

class prompt_toolkit.layout.WindowAlign(value)

Alignment of the Window content.

Note that this is different from HorizontalAlign and VerticalAlign, which are used for the alignment of the child containers in respectively VSplit and HSplit.

class prompt_toolkit.layout.ConditionalContainer(content: Union[prompt_toolkit.layout.containers.Container, MagicContainer], filter: Union[prompt_toolkit.filters.base.Filter, bool])

Wrapper around any other container that can change the visibility. The received filter determines whether the given container should be displayed or not.

Parameters
get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Write the actual content to the screen.

Parameters
  • screenScreen

  • mouse_handlersMouseHandlers.

  • parent_style – Style string to pass to the Window object. This will be applied to all content of the windows. VSplit and HSplit can use it to pass their style down to the windows that they contain.

  • z_index – Used for propagating z_index from parent to child.

class prompt_toolkit.layout.DynamicContainer(get_container: Callable[[], Union[prompt_toolkit.layout.containers.Container, MagicContainer]])

Container class that dynamically returns any Container.

Parameters

get_container – Callable that returns a Container instance or any widget with a __pt_container__ method.

get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

get_key_bindings() Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase]

Returns a KeyBindings object. These bindings become active when any user control in this container has the focus, except if any containers between this container and the focused user control is modal.

is_modal() bool

When this container is modal, key bindings from parent containers are not taken into account if a user control in this container is focused.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Write the actual content to the screen.

Parameters
  • screenScreen

  • mouse_handlersMouseHandlers.

  • parent_style – Style string to pass to the Window object. This will be applied to all content of the windows. VSplit and HSplit can use it to pass their style down to the windows that they contain.

  • z_index – Used for propagating z_index from parent to child.

class prompt_toolkit.layout.ScrollablePane(content: prompt_toolkit.layout.containers.Container, scroll_offsets: Optional[prompt_toolkit.layout.containers.ScrollOffsets] = None, keep_cursor_visible: Union[prompt_toolkit.filters.base.Filter, bool] = True, keep_focused_window_visible: Union[prompt_toolkit.filters.base.Filter, bool] = True, max_available_height: int = 10000, width: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, height: Union[None, int, prompt_toolkit.layout.dimension.Dimension, Callable[[], Any]] = None, show_scrollbar: Union[prompt_toolkit.filters.base.Filter, bool] = True, display_arrows: Union[prompt_toolkit.filters.base.Filter, bool] = True, up_arrow_symbol: str = '^', down_arrow_symbol: str = 'v')

Container widget that exposes a larger virtual screen to its content and displays it in a vertical scrollbale region.

Typically this is wrapped in a large HSplit container. Make sure in that case to not specify a height dimension of the HSplit, so that it will scale according to the content.

Note

If you want to display a completion menu for widgets in this ScrollablePane, then it’s still a good practice to use a FloatContainer with a CompletionsMenu in a Float at the top-level of the layout hierarchy, rather then nesting a FloatContainer in this ScrollablePane. (Otherwise, it’s possible that the completion menu is clipped.)

Parameters
  • content – The content container.

  • scrolloffset – Try to keep the cursor within this distance from the top/bottom (left/right offset is not used).

  • keep_cursor_visible – When True, automatically scroll the pane so that the cursor (of the focused window) is always visible.

  • keep_focused_window_visible – When True, automatically scroll th e pane so that the focused window is visible, or as much visible as possible if it doen’t completely fit the screen.

  • max_available_height – Always constraint the height to this amount for performance reasons.

  • width – When given, use this width instead of looking at the children.

  • height – When given, use this height instead of looking at the children.

  • show_scrollbar – When True display a scrollbar on the right.

get_children() List[prompt_toolkit.layout.containers.Container]

Return the list of child Container objects.

get_key_bindings() Optional[prompt_toolkit.key_binding.key_bindings.KeyBindingsBase]

Returns a KeyBindings object. These bindings become active when any user control in this container has the focus, except if any containers between this container and the focused user control is modal.

is_modal() bool

When this container is modal, key bindings from parent containers are not taken into account if a user control in this container is focused.

preferred_height(width: int, max_available_height: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired height for this container.

preferred_width(max_available_width: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension that represents the desired width for this container.

reset() None

Reset the state of this container and all the children. (E.g. reset scroll offsets, etc…)

write_to_screen(screen: prompt_toolkit.layout.screen.Screen, mouse_handlers: prompt_toolkit.layout.mouse_handlers.MouseHandlers, write_position: prompt_toolkit.layout.screen.WritePosition, parent_style: str, erase_bg: bool, z_index: Optional[int]) None

Render scrollable pane content.

This works by rendering on an off-screen canvas, and copying over the visible region.

class prompt_toolkit.layout.ScrollOffsets(top: Union[int, Callable[[], int]] = 0, bottom: Union[int, Callable[[], int]] = 0, left: Union[int, Callable[[], int]] = 0, right: Union[int, Callable[[], int]] = 0)

Scroll offsets for the Window class.

Note that left/right offsets only make sense if line wrapping is disabled.

class prompt_toolkit.layout.ColorColumn(position: int, style: str = 'class:color-column')

Column for a Window to be colored.

class prompt_toolkit.layout.to_container(container: Union[prompt_toolkit.layout.containers.Container, MagicContainer])

Make sure that the given object is a Container.

class prompt_toolkit.layout.to_window(container: Union[prompt_toolkit.layout.containers.Container, MagicContainer])

Make sure that the given argument is a Window.

class prompt_toolkit.layout.is_container(value: object)

Checks whether the given value is a container object (for use in assert statements).

class prompt_toolkit.layout.HorizontalAlign(value)

Alignment for VSplit.

class prompt_toolkit.layout.VerticalAlign(value)

Alignment for HSplit.

Controls

class prompt_toolkit.layout.BufferControl(buffer: Optional[prompt_toolkit.buffer.Buffer] = None, input_processors: Optional[List[prompt_toolkit.layout.processors.Processor]] = None, include_default_input_processors: bool = True, lexer: Optional[prompt_toolkit.lexers.base.Lexer] = None, preview_search: Union[prompt_toolkit.filters.base.Filter, bool] = False, focusable: Union[prompt_toolkit.filters.base.Filter, bool] = True, search_buffer_control: Union[None, SearchBufferControl, Callable[[], SearchBufferControl]] = None, menu_position: Optional[Callable[[], Optional[int]]] = None, focus_on_click: Union[prompt_toolkit.filters.base.Filter, bool] = False, key_bindings: Optional[KeyBindingsBase] = None)

Control for visualising the content of a Buffer.

Parameters
  • buffer – The Buffer object to be displayed.

  • input_processors – A list of Processor objects.

  • include_default_input_processors – When True, include the default processors for highlighting of selection, search and displaying of multiple cursors.

  • lexerLexer instance for syntax highlighting.

  • preview_searchbool or Filter: Show search while typing. When this is True, probably you want to add a HighlightIncrementalSearchProcessor as well. Otherwise only the cursor position will move, but the text won’t be highlighted.

  • focusablebool or Filter: Tell whether this control is focusable.

  • focus_on_click – Focus this buffer when it’s click, but not yet focused.

  • key_bindings – a KeyBindings object.

create_content(width: int, height: int, preview_search: bool = False) prompt_toolkit.layout.controls.UIContent

Create a UIContent.

get_invalidate_events() Iterable[Event[object]]

Return the Window invalidate events.

get_key_bindings() Optional[KeyBindingsBase]

When additional key bindings are given. Return these.

is_focusable() bool

Tell whether this user control is focusable.

mouse_handler(mouse_event: prompt_toolkit.mouse_events.MouseEvent) NotImplementedOrNone

Mouse handler for this control.

move_cursor_down() None

Request to move the cursor down. This happens when scrolling down and the cursor is completely at the top.

move_cursor_up() None

Request to move the cursor up.

preferred_width(max_available_width: int) Optional[int]

This should return the preferred width.

Note: We don’t specify a preferred width according to the content,

because it would be too expensive. Calculating the preferred width can be done by calculating the longest line, but this would require applying all the processors to each line. This is unfeasible for a larger document, and doing it for small documents only would result in inconsistent behaviour.

property search_state: prompt_toolkit.search.SearchState

Return the SearchState for searching this BufferControl. This is always associated with the search control. If one search bar is used for searching multiple BufferControls, then they share the same SearchState.

class prompt_toolkit.layout.SearchBufferControl(buffer: Optional[prompt_toolkit.buffer.Buffer] = None, input_processors: Optional[List[prompt_toolkit.layout.processors.Processor]] = None, lexer: Optional[prompt_toolkit.lexers.base.Lexer] = None, focus_on_click: Union[prompt_toolkit.filters.base.Filter, bool] = False, key_bindings: Optional[KeyBindingsBase] = None, ignore_case: Union[prompt_toolkit.filters.base.Filter, bool] = False)

BufferControl which is used for searching another BufferControl.

Parameters

ignore_case – Search case insensitive.

class prompt_toolkit.layout.DummyControl

A dummy control object that doesn’t paint any content.

Useful for filling a Window. (The fragment and char attributes of the Window class can be used to define the filling.)

create_content(width: int, height: int) prompt_toolkit.layout.controls.UIContent

Generate the content for this user control.

Returns a UIContent instance.

is_focusable() bool

Tell whether this user control is focusable.

class prompt_toolkit.layout.FormattedTextControl(text: Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]] = '', style: str = '', focusable: Union[prompt_toolkit.filters.base.Filter, bool] = False, key_bindings: Optional[KeyBindingsBase] = None, show_cursor: bool = True, modal: bool = False, get_cursor_position: Optional[Callable[[], Optional[prompt_toolkit.data_structures.Point]]] = None)

Control that displays formatted text. This can be either plain text, an HTML object an ANSI object, a list of (style_str, text) tuples or a callable that takes no argument and returns one of those, depending on how you prefer to do the formatting. See prompt_toolkit.layout.formatted_text for more information.

(It’s mostly optimized for rather small widgets, like toolbars, menus, etc…)

When this UI control has the focus, the cursor will be shown in the upper left corner of this control by default. There are two ways for specifying the cursor position:

  • Pass a get_cursor_position function which returns a Point instance with the current cursor position.

  • If the (formatted) text is passed as a list of (style, text) tuples and there is one that looks like ('[SetCursorPosition]', ''), then this will specify the cursor position.

Mouse support:

The list of fragments can also contain tuples of three items, looking like: (style_str, text, handler). When mouse support is enabled and the user clicks on this fragment, then the given handler is called. That handler should accept two inputs: (Application, MouseEvent) and it should either handle the event or return NotImplemented in case we want the containing Window to handle this event.

Parameters
  • focusablebool or Filter: Tell whether this control is focusable.

  • text – Text or formatted text to be displayed.

  • style – Style string applied to the content. (If you want to style the whole Window, pass the style to the Window instead.)

  • key_bindings – a KeyBindings object.

  • get_cursor_position – A callable that returns the cursor position as a Point instance.

create_content(width: int, height: Optional[int]) prompt_toolkit.layout.controls.UIContent

Generate the content for this user control.

Returns a UIContent instance.

get_key_bindings() Optional[KeyBindingsBase]

The key bindings that are specific for this user control.

Return a KeyBindings object if some key bindings are specified, or None otherwise.

is_focusable() bool

Tell whether this user control is focusable.

mouse_handler(mouse_event: prompt_toolkit.mouse_events.MouseEvent) NotImplementedOrNone

Handle mouse events.

(When the fragment list contained mouse handlers and the user clicked on on any of these, the matching handler is called. This handler can still return NotImplemented in case we want the Window to handle this particular event.)

preferred_height(width: int, max_available_height: int, wrap_lines: bool, get_line_prefix: Optional[Callable[[int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]]) Optional[int]

Return the preferred height for this control.

preferred_width(max_available_width: int) int

Return the preferred width for this control. That is the width of the longest line.

class prompt_toolkit.layout.UIControl

Base class for all user interface controls.

abstract create_content(width: int, height: int) prompt_toolkit.layout.controls.UIContent

Generate the content for this user control.

Returns a UIContent instance.

get_invalidate_events() Iterable[Event[object]]

Return a list of Event objects. This can be a generator. (The application collects all these events, in order to bind redraw handlers to these events.)

get_key_bindings() Optional[KeyBindingsBase]

The key bindings that are specific for this user control.

Return a KeyBindings object if some key bindings are specified, or None otherwise.

is_focusable() bool

Tell whether this user control is focusable.

mouse_handler(mouse_event: prompt_toolkit.mouse_events.MouseEvent) NotImplementedOrNone

Handle mouse events.

When NotImplemented is returned, it means that the given event is not handled by the UIControl itself. The Window or key bindings can decide to handle this event as scrolling or changing focus.

Parameters

mouse_eventMouseEvent instance.

move_cursor_down() None

Request to move the cursor down. This happens when scrolling down and the cursor is completely at the top.

move_cursor_up() None

Request to move the cursor up.

class prompt_toolkit.layout.UIContent(get_line: Callable[[int], List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]] = <function UIContent.<lambda>>, line_count: int = 0, cursor_position: Optional[prompt_toolkit.data_structures.Point] = None, menu_position: Optional[prompt_toolkit.data_structures.Point] = None, show_cursor: bool = True)

Content generated by a user control. This content consists of a list of lines.

Parameters
  • get_line – Callable that takes a line number and returns the current line. This is a list of (style_str, text) tuples.

  • line_count – The number of lines.

  • cursor_position – a Point for the cursor position.

  • menu_position – a Point for the menu position.

  • show_cursor – Make the cursor visible.

get_height_for_line(lineno: int, width: int, get_line_prefix: Optional[Callable[[int, int], Optional[Union[str, MagicFormattedText, List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]], Callable[[], Any]]]]], slice_stop: Optional[int] = None) int

Return the height that a given line would need if it is rendered in a space with the given width (using line wrapping).

Parameters
  • get_line_prefix – None or a Window.get_line_prefix callable that returns the prefix to be inserted before this line.

  • slice_stop – Wrap only “line[:slice_stop]” and return that partial result. This is needed for scrolling the window correctly when line wrapping.

Returns

The computed height.

Other

Sizing

class prompt_toolkit.layout.Dimension(min: Optional[int] = None, max: Optional[int] = None, weight: Optional[int] = None, preferred: Optional[int] = None)

Specified dimension (width/height) of a user control or window.

The layout engine tries to honor the preferred size. If that is not possible, because the terminal is larger or smaller, it tries to keep in between min and max.

Parameters
  • min – Minimum size.

  • max – Maximum size.

  • weight – For a VSplit/HSplit, the actual size will be determined by taking the proportion of weights from all the children. E.g. When there are two children, one with a weight of 1, and the other with a weight of 2, the second will always be twice as big as the first, if the min/max values allow it.

  • preferred – Preferred size.

classmethod exact(amount: int) prompt_toolkit.layout.dimension.Dimension

Return a Dimension with an exact size. (min, max and preferred set to amount).

is_zero() bool

True if this Dimension represents a zero size.

classmethod zero() prompt_toolkit.layout.dimension.Dimension

Create a dimension that represents a zero size. (Used for ‘invisible’ controls.)

Margins

class prompt_toolkit.layout.Margin

Base interface for a margin.

abstract create_margin(window_render_info: WindowRenderInfo, width: int, height: int) List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]

Creates a margin. This should return a list of (style_str, text) tuples.

Parameters
  • window_render_infoWindowRenderInfo instance, generated after rendering and copying the visible part of the UIControl into the Window.

  • width – The width that’s available for this margin. (As reported by get_width().)

  • height – The height that’s available for this margin. (The height of the Window.)

abstract get_width(get_ui_content: Callable[[], prompt_toolkit.layout.controls.UIContent]) int

Return the width that this margin is going to consume.

Parameters

get_ui_content – Callable that asks the user control to create a UIContent instance. This can be used for instance to obtain the number of lines.

class prompt_toolkit.layout.NumberedMargin(relative: Union[prompt_toolkit.filters.base.Filter, bool] = False, display_tildes: Union[prompt_toolkit.filters.base.Filter, bool] = False)

Margin that displays the line numbers.

Parameters
  • relative – Number relative to the cursor position. Similar to the Vi ‘relativenumber’ option.

  • display_tildes – Display tildes after the end of the document, just like Vi does.

create_margin(window_render_info: WindowRenderInfo, width: int, height: int) List[Union[Tuple[str, str], Tuple[str, str, Callable[[prompt_toolkit.mouse_events.MouseEvent], None]]]]

Creates a margin. This should return a list of (style_str, text) tuples.

Parameters
  • window_render_infoWindowRenderInfo instance, generated after rendering and copying the visible part of the UIControl into the Window.

  • width – The width that’s available for this margin. (As reported by get_width().)

  • height – The height that’s available for this margin. (The height of the Window.)

get_width(get_ui_content: Callable[[], prompt_toolkit.layout.controls.UIContent]) int

Return the width that this margin is going to consume.

Parameters

get_ui_content – Callable that asks the user control to create a UIContent instance. This can be used for instance to obtain the number of lines.

class prompt_toolkit.layout.ScrollbarMargin(display_arrows: Union[prompt_toolkit.filters.base.Filter, bool] = False, up_arrow_symbol: str = '^', down_arrow_symbol: str = 'v')