1029 lines
33 KiB
Python
1029 lines
33 KiB
Python
"""
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Processors are little transformation blocks that transform the fragments list
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from a buffer before the BufferControl will render it to the screen.
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They can insert fragments before or after, or highlight fragments by replacing the
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fragment types.
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"""
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import re
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from abc import ABCMeta, abstractmethod
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from typing import (
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TYPE_CHECKING,
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Callable,
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Hashable,
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List,
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Optional,
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Tuple,
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Type,
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Union,
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cast,
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)
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from prompt_toolkit.application.current import get_app
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from prompt_toolkit.cache import SimpleCache
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from prompt_toolkit.document import Document
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from prompt_toolkit.filters import FilterOrBool, to_filter, vi_insert_multiple_mode
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from prompt_toolkit.formatted_text import (
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AnyFormattedText,
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StyleAndTextTuples,
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to_formatted_text,
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)
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from prompt_toolkit.formatted_text.utils import fragment_list_len, fragment_list_to_text
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from prompt_toolkit.search import SearchDirection
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from prompt_toolkit.utils import to_int, to_str
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from .utils import explode_text_fragments
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if TYPE_CHECKING:
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from .controls import BufferControl, UIContent
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__all__ = [
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"Processor",
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"TransformationInput",
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"Transformation",
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"DummyProcessor",
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"HighlightSearchProcessor",
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"HighlightIncrementalSearchProcessor",
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"HighlightSelectionProcessor",
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"PasswordProcessor",
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"HighlightMatchingBracketProcessor",
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"DisplayMultipleCursors",
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"BeforeInput",
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"ShowArg",
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"AfterInput",
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"AppendAutoSuggestion",
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"ConditionalProcessor",
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"ShowLeadingWhiteSpaceProcessor",
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"ShowTrailingWhiteSpaceProcessor",
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"TabsProcessor",
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"ReverseSearchProcessor",
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"DynamicProcessor",
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"merge_processors",
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]
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class Processor(metaclass=ABCMeta):
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"""
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Manipulate the fragments for a given line in a
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:class:`~prompt_toolkit.layout.controls.BufferControl`.
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"""
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@abstractmethod
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def apply_transformation(
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self, transformation_input: "TransformationInput"
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) -> "Transformation":
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"""
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Apply transformation. Returns a :class:`.Transformation` instance.
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:param transformation_input: :class:`.TransformationInput` object.
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"""
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return Transformation(transformation_input.fragments)
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SourceToDisplay = Callable[[int], int]
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DisplayToSource = Callable[[int], int]
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class TransformationInput:
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"""
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:param control: :class:`.BufferControl` instance.
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:param lineno: The number of the line to which we apply the processor.
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:param source_to_display: A function that returns the position in the
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`fragments` for any position in the source string. (This takes
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previous processors into account.)
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:param fragments: List of fragments that we can transform. (Received from the
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previous processor.)
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"""
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def __init__(
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self,
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buffer_control: "BufferControl",
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document: Document,
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lineno: int,
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source_to_display: SourceToDisplay,
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fragments: StyleAndTextTuples,
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width: int,
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height: int,
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) -> None:
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self.buffer_control = buffer_control
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self.document = document
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self.lineno = lineno
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self.source_to_display = source_to_display
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self.fragments = fragments
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self.width = width
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self.height = height
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def unpack(
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self,
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) -> Tuple[
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"BufferControl", Document, int, SourceToDisplay, StyleAndTextTuples, int, int
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]:
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return (
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self.buffer_control,
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self.document,
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self.lineno,
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self.source_to_display,
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self.fragments,
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self.width,
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self.height,
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)
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class Transformation:
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"""
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Transformation result, as returned by :meth:`.Processor.apply_transformation`.
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Important: Always make sure that the length of `document.text` is equal to
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the length of all the text in `fragments`!
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:param fragments: The transformed fragments. To be displayed, or to pass to
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the next processor.
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:param source_to_display: Cursor position transformation from original
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string to transformed string.
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:param display_to_source: Cursor position transformed from source string to
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original string.
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"""
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def __init__(
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self,
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fragments: StyleAndTextTuples,
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source_to_display: Optional[SourceToDisplay] = None,
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display_to_source: Optional[DisplayToSource] = None,
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) -> None:
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self.fragments = fragments
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self.source_to_display = source_to_display or (lambda i: i)
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self.display_to_source = display_to_source or (lambda i: i)
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class DummyProcessor(Processor):
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"""
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A `Processor` that doesn't do anything.
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"""
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def apply_transformation(
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self, transformation_input: TransformationInput
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) -> Transformation:
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return Transformation(transformation_input.fragments)
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class HighlightSearchProcessor(Processor):
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"""
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Processor that highlights search matches in the document.
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Note that this doesn't support multiline search matches yet.
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The style classes 'search' and 'search.current' will be applied to the
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content.
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"""
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_classname = "search"
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_classname_current = "search.current"
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def _get_search_text(self, buffer_control: "BufferControl") -> str:
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"""
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The text we are searching for.
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"""
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return buffer_control.search_state.text
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def apply_transformation(
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self, transformation_input: TransformationInput
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) -> Transformation:
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(
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buffer_control,
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document,
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lineno,
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source_to_display,
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fragments,
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_,
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_,
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) = transformation_input.unpack()
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search_text = self._get_search_text(buffer_control)
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searchmatch_fragment = " class:%s " % (self._classname,)
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searchmatch_current_fragment = " class:%s " % (self._classname_current,)
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if search_text and not get_app().is_done:
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# For each search match, replace the style string.
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line_text = fragment_list_to_text(fragments)
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fragments = explode_text_fragments(fragments)
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if buffer_control.search_state.ignore_case():
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flags = re.IGNORECASE
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else:
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flags = re.RegexFlag(0)
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# Get cursor column.
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cursor_column: Optional[int]
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if document.cursor_position_row == lineno:
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cursor_column = source_to_display(document.cursor_position_col)
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else:
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cursor_column = None
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for match in re.finditer(re.escape(search_text), line_text, flags=flags):
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if cursor_column is not None:
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on_cursor = match.start() <= cursor_column < match.end()
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else:
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on_cursor = False
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for i in range(match.start(), match.end()):
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old_fragment, text, *_ = fragments[i]
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if on_cursor:
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fragments[i] = (
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old_fragment + searchmatch_current_fragment,
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fragments[i][1],
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)
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else:
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fragments[i] = (
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old_fragment + searchmatch_fragment,
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fragments[i][1],
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)
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return Transformation(fragments)
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class HighlightIncrementalSearchProcessor(HighlightSearchProcessor):
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"""
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Highlight the search terms that are used for highlighting the incremental
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search. The style class 'incsearch' will be applied to the content.
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Important: this requires the `preview_search=True` flag to be set for the
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`BufferControl`. Otherwise, the cursor position won't be set to the search
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match while searching, and nothing happens.
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"""
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_classname = "incsearch"
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_classname_current = "incsearch.current"
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def _get_search_text(self, buffer_control: "BufferControl") -> str:
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"""
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The text we are searching for.
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"""
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# When the search buffer has focus, take that text.
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search_buffer = buffer_control.search_buffer
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if search_buffer is not None and search_buffer.text:
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return search_buffer.text
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return ""
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class HighlightSelectionProcessor(Processor):
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"""
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Processor that highlights the selection in the document.
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"""
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def apply_transformation(
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self, transformation_input: TransformationInput
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) -> Transformation:
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(
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buffer_control,
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document,
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lineno,
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source_to_display,
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fragments,
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_,
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_,
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) = transformation_input.unpack()
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selected_fragment = " class:selected "
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# In case of selection, highlight all matches.
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selection_at_line = document.selection_range_at_line(lineno)
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if selection_at_line:
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from_, to = selection_at_line
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from_ = source_to_display(from_)
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to = source_to_display(to)
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fragments = explode_text_fragments(fragments)
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if from_ == 0 and to == 0 and len(fragments) == 0:
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# When this is an empty line, insert a space in order to
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# visualise the selection.
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return Transformation([(selected_fragment, " ")])
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else:
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for i in range(from_, to):
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if i < len(fragments):
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old_fragment, old_text, *_ = fragments[i]
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fragments[i] = (old_fragment + selected_fragment, old_text)
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elif i == len(fragments):
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fragments.append((selected_fragment, " "))
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return Transformation(fragments)
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|
|
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class PasswordProcessor(Processor):
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"""
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Processor that turns masks the input. (For passwords.)
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:param char: (string) Character to be used. "*" by default.
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"""
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def __init__(self, char: str = "*") -> None:
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self.char = char
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def apply_transformation(self, ti: TransformationInput) -> Transformation:
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fragments: StyleAndTextTuples = cast(
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StyleAndTextTuples,
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[
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(style, self.char * len(text), *handler)
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for style, text, *handler in ti.fragments
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],
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)
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return Transformation(fragments)
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|
|
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class HighlightMatchingBracketProcessor(Processor):
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"""
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When the cursor is on or right after a bracket, it highlights the matching
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bracket.
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:param max_cursor_distance: Only highlight matching brackets when the
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cursor is within this distance. (From inside a `Processor`, we can't
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know which lines will be visible on the screen. But we also don't want
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to scan the whole document for matching brackets on each key press, so
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we limit to this value.)
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"""
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_closing_braces = "])}>"
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def __init__(
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self, chars: str = "[](){}<>", max_cursor_distance: int = 1000
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) -> None:
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self.chars = chars
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self.max_cursor_distance = max_cursor_distance
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self._positions_cache: SimpleCache[
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Hashable, List[Tuple[int, int]]
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] = SimpleCache(maxsize=8)
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def _get_positions_to_highlight(self, document: Document) -> List[Tuple[int, int]]:
|
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"""
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Return a list of (row, col) tuples that need to be highlighted.
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"""
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pos: Optional[int]
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# Try for the character under the cursor.
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if document.current_char and document.current_char in self.chars:
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pos = document.find_matching_bracket_position(
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start_pos=document.cursor_position - self.max_cursor_distance,
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end_pos=document.cursor_position + self.max_cursor_distance,
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)
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# Try for the character before the cursor.
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elif (
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document.char_before_cursor
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and document.char_before_cursor in self._closing_braces
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and document.char_before_cursor in self.chars
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):
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document = Document(document.text, document.cursor_position - 1)
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pos = document.find_matching_bracket_position(
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start_pos=document.cursor_position - self.max_cursor_distance,
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end_pos=document.cursor_position + self.max_cursor_distance,
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)
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else:
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pos = None
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# Return a list of (row, col) tuples that need to be highlighted.
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if pos:
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pos += document.cursor_position # pos is relative.
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row, col = document.translate_index_to_position(pos)
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return [
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(row, col),
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(document.cursor_position_row, document.cursor_position_col),
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]
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else:
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return []
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|
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def apply_transformation(
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self, transformation_input: TransformationInput
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) -> Transformation:
|
|
|
|
(
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buffer_control,
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document,
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lineno,
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source_to_display,
|
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fragments,
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_,
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_,
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) = transformation_input.unpack()
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# When the application is in the 'done' state, don't highlight.
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if get_app().is_done:
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return Transformation(fragments)
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|
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# Get the highlight positions.
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key = (get_app().render_counter, document.text, document.cursor_position)
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positions = self._positions_cache.get(
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key, lambda: self._get_positions_to_highlight(document)
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)
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# Apply if positions were found at this line.
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if positions:
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for row, col in positions:
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if row == lineno:
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col = source_to_display(col)
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fragments = explode_text_fragments(fragments)
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style, text, *_ = fragments[col]
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if col == document.cursor_position_col:
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style += " class:matching-bracket.cursor "
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else:
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style += " class:matching-bracket.other "
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fragments[col] = (style, text)
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return Transformation(fragments)
|
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|
|
|
|
class DisplayMultipleCursors(Processor):
|
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"""
|
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When we're in Vi block insert mode, display all the cursors.
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"""
|
|
|
|
def apply_transformation(
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self, transformation_input: TransformationInput
|
|
) -> Transformation:
|
|
|
|
(
|
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buffer_control,
|
|
document,
|
|
lineno,
|
|
source_to_display,
|
|
fragments,
|
|
_,
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|
_,
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|
) = transformation_input.unpack()
|
|
|
|
buff = buffer_control.buffer
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|
|
|
if vi_insert_multiple_mode():
|
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cursor_positions = buff.multiple_cursor_positions
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fragments = explode_text_fragments(fragments)
|
|
|
|
# If any cursor appears on the current line, highlight that.
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start_pos = document.translate_row_col_to_index(lineno, 0)
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end_pos = start_pos + len(document.lines[lineno])
|
|
|
|
fragment_suffix = " class:multiple-cursors"
|
|
|
|
for p in cursor_positions:
|
|
if start_pos <= p <= end_pos:
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column = source_to_display(p - start_pos)
|
|
|
|
# Replace fragment.
|
|
try:
|
|
style, text, *_ = fragments[column]
|
|
except IndexError:
|
|
# Cursor needs to be displayed after the current text.
|
|
fragments.append((fragment_suffix, " "))
|
|
else:
|
|
style += fragment_suffix
|
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fragments[column] = (style, text)
|
|
|
|
return Transformation(fragments)
|
|
else:
|
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return Transformation(fragments)
|
|
|
|
|
|
class BeforeInput(Processor):
|
|
"""
|
|
Insert text before the input.
|
|
|
|
:param text: This can be either plain text or formatted text
|
|
(or a callable that returns any of those).
|
|
:param style: style to be applied to this prompt/prefix.
|
|
"""
|
|
|
|
def __init__(self, text: AnyFormattedText, style: str = "") -> None:
|
|
self.text = text
|
|
self.style = style
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
source_to_display: Optional[SourceToDisplay]
|
|
display_to_source: Optional[DisplayToSource]
|
|
|
|
if ti.lineno == 0:
|
|
# Get fragments.
|
|
fragments_before = to_formatted_text(self.text, self.style)
|
|
fragments = fragments_before + ti.fragments
|
|
|
|
shift_position = fragment_list_len(fragments_before)
|
|
source_to_display = lambda i: i + shift_position
|
|
display_to_source = lambda i: i - shift_position
|
|
else:
|
|
fragments = ti.fragments
|
|
source_to_display = None
|
|
display_to_source = None
|
|
|
|
return Transformation(
|
|
fragments,
|
|
source_to_display=source_to_display,
|
|
display_to_source=display_to_source,
|
|
)
|
|
|
|
def __repr__(self) -> str:
|
|
return "BeforeInput(%r, %r)" % (self.text, self.style)
|
|
|
|
|
|
class ShowArg(BeforeInput):
|
|
"""
|
|
Display the 'arg' in front of the input.
|
|
|
|
This was used by the `PromptSession`, but now it uses the
|
|
`Window.get_line_prefix` function instead.
|
|
"""
|
|
|
|
def __init__(self) -> None:
|
|
super().__init__(self._get_text_fragments)
|
|
|
|
def _get_text_fragments(self) -> StyleAndTextTuples:
|
|
app = get_app()
|
|
if app.key_processor.arg is None:
|
|
return []
|
|
else:
|
|
arg = app.key_processor.arg
|
|
|
|
return [
|
|
("class:prompt.arg", "(arg: "),
|
|
("class:prompt.arg.text", str(arg)),
|
|
("class:prompt.arg", ") "),
|
|
]
|
|
|
|
def __repr__(self) -> str:
|
|
return "ShowArg()"
|
|
|
|
|
|
class AfterInput(Processor):
|
|
"""
|
|
Insert text after the input.
|
|
|
|
:param text: This can be either plain text or formatted text
|
|
(or a callable that returns any of those).
|
|
:param style: style to be applied to this prompt/prefix.
|
|
"""
|
|
|
|
def __init__(self, text: AnyFormattedText, style: str = "") -> None:
|
|
self.text = text
|
|
self.style = style
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
# Insert fragments after the last line.
|
|
if ti.lineno == ti.document.line_count - 1:
|
|
# Get fragments.
|
|
fragments_after = to_formatted_text(self.text, self.style)
|
|
return Transformation(fragments=ti.fragments + fragments_after)
|
|
else:
|
|
return Transformation(fragments=ti.fragments)
|
|
|
|
def __repr__(self) -> str:
|
|
return "%s(%r, style=%r)" % (self.__class__.__name__, self.text, self.style)
|
|
|
|
|
|
class AppendAutoSuggestion(Processor):
|
|
"""
|
|
Append the auto suggestion to the input.
|
|
(The user can then press the right arrow the insert the suggestion.)
|
|
"""
|
|
|
|
def __init__(self, style: str = "class:auto-suggestion") -> None:
|
|
self.style = style
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
# Insert fragments after the last line.
|
|
if ti.lineno == ti.document.line_count - 1:
|
|
buffer = ti.buffer_control.buffer
|
|
|
|
if buffer.suggestion and ti.document.is_cursor_at_the_end:
|
|
suggestion = buffer.suggestion.text
|
|
else:
|
|
suggestion = ""
|
|
|
|
return Transformation(fragments=ti.fragments + [(self.style, suggestion)])
|
|
else:
|
|
return Transformation(fragments=ti.fragments)
|
|
|
|
|
|
class ShowLeadingWhiteSpaceProcessor(Processor):
|
|
"""
|
|
Make leading whitespace visible.
|
|
|
|
:param get_char: Callable that returns one character.
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
get_char: Optional[Callable[[], str]] = None,
|
|
style: str = "class:leading-whitespace",
|
|
) -> None:
|
|
def default_get_char() -> str:
|
|
if "\xb7".encode(get_app().output.encoding(), "replace") == b"?":
|
|
return "."
|
|
else:
|
|
return "\xb7"
|
|
|
|
self.style = style
|
|
self.get_char = get_char or default_get_char
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
fragments = ti.fragments
|
|
|
|
# Walk through all te fragments.
|
|
if fragments and fragment_list_to_text(fragments).startswith(" "):
|
|
t = (self.style, self.get_char())
|
|
fragments = explode_text_fragments(fragments)
|
|
|
|
for i in range(len(fragments)):
|
|
if fragments[i][1] == " ":
|
|
fragments[i] = t
|
|
else:
|
|
break
|
|
|
|
return Transformation(fragments)
|
|
|
|
|
|
class ShowTrailingWhiteSpaceProcessor(Processor):
|
|
"""
|
|
Make trailing whitespace visible.
|
|
|
|
:param get_char: Callable that returns one character.
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
get_char: Optional[Callable[[], str]] = None,
|
|
style: str = "class:training-whitespace",
|
|
) -> None:
|
|
def default_get_char() -> str:
|
|
if "\xb7".encode(get_app().output.encoding(), "replace") == b"?":
|
|
return "."
|
|
else:
|
|
return "\xb7"
|
|
|
|
self.style = style
|
|
self.get_char = get_char or default_get_char
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
fragments = ti.fragments
|
|
|
|
if fragments and fragments[-1][1].endswith(" "):
|
|
t = (self.style, self.get_char())
|
|
fragments = explode_text_fragments(fragments)
|
|
|
|
# Walk backwards through all te fragments and replace whitespace.
|
|
for i in range(len(fragments) - 1, -1, -1):
|
|
char = fragments[i][1]
|
|
if char == " ":
|
|
fragments[i] = t
|
|
else:
|
|
break
|
|
|
|
return Transformation(fragments)
|
|
|
|
|
|
class TabsProcessor(Processor):
|
|
"""
|
|
Render tabs as spaces (instead of ^I) or make them visible (for instance,
|
|
by replacing them with dots.)
|
|
|
|
:param tabstop: Horizontal space taken by a tab. (`int` or callable that
|
|
returns an `int`).
|
|
:param char1: Character or callable that returns a character (text of
|
|
length one). This one is used for the first space taken by the tab.
|
|
:param char2: Like `char1`, but for the rest of the space.
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
tabstop: Union[int, Callable[[], int]] = 4,
|
|
char1: Union[str, Callable[[], str]] = "|",
|
|
char2: Union[str, Callable[[], str]] = "\u2508",
|
|
style: str = "class:tab",
|
|
) -> None:
|
|
|
|
self.char1 = char1
|
|
self.char2 = char2
|
|
self.tabstop = tabstop
|
|
self.style = style
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
tabstop = to_int(self.tabstop)
|
|
style = self.style
|
|
|
|
# Create separator for tabs.
|
|
separator1 = to_str(self.char1)
|
|
separator2 = to_str(self.char2)
|
|
|
|
# Transform fragments.
|
|
fragments = explode_text_fragments(ti.fragments)
|
|
|
|
position_mappings = {}
|
|
result_fragments: StyleAndTextTuples = []
|
|
pos = 0
|
|
|
|
for i, fragment_and_text in enumerate(fragments):
|
|
position_mappings[i] = pos
|
|
|
|
if fragment_and_text[1] == "\t":
|
|
# Calculate how many characters we have to insert.
|
|
count = tabstop - (pos % tabstop)
|
|
if count == 0:
|
|
count = tabstop
|
|
|
|
# Insert tab.
|
|
result_fragments.append((style, separator1))
|
|
result_fragments.append((style, separator2 * (count - 1)))
|
|
pos += count
|
|
else:
|
|
result_fragments.append(fragment_and_text)
|
|
pos += 1
|
|
|
|
position_mappings[len(fragments)] = pos
|
|
# Add `pos+1` to mapping, because the cursor can be right after the
|
|
# line as well.
|
|
position_mappings[len(fragments) + 1] = pos + 1
|
|
|
|
def source_to_display(from_position: int) -> int:
|
|
" Maps original cursor position to the new one. "
|
|
return position_mappings[from_position]
|
|
|
|
def display_to_source(display_pos: int) -> int:
|
|
" Maps display cursor position to the original one. "
|
|
position_mappings_reversed = {v: k for k, v in position_mappings.items()}
|
|
|
|
while display_pos >= 0:
|
|
try:
|
|
return position_mappings_reversed[display_pos]
|
|
except KeyError:
|
|
display_pos -= 1
|
|
return 0
|
|
|
|
return Transformation(
|
|
result_fragments,
|
|
source_to_display=source_to_display,
|
|
display_to_source=display_to_source,
|
|
)
|
|
|
|
|
|
class ReverseSearchProcessor(Processor):
|
|
"""
|
|
Process to display the "(reverse-i-search)`...`:..." stuff around
|
|
the search buffer.
|
|
|
|
Note: This processor is meant to be applied to the BufferControl that
|
|
contains the search buffer, it's not meant for the original input.
|
|
"""
|
|
|
|
_excluded_input_processors: List[Type[Processor]] = [
|
|
HighlightSearchProcessor,
|
|
HighlightSelectionProcessor,
|
|
BeforeInput,
|
|
AfterInput,
|
|
]
|
|
|
|
def _get_main_buffer(
|
|
self, buffer_control: "BufferControl"
|
|
) -> Optional["BufferControl"]:
|
|
from prompt_toolkit.layout.controls import BufferControl
|
|
|
|
prev_control = get_app().layout.search_target_buffer_control
|
|
if (
|
|
isinstance(prev_control, BufferControl)
|
|
and prev_control.search_buffer_control == buffer_control
|
|
):
|
|
return prev_control
|
|
return None
|
|
|
|
def _content(
|
|
self, main_control: "BufferControl", ti: TransformationInput
|
|
) -> "UIContent":
|
|
from prompt_toolkit.layout.controls import BufferControl
|
|
|
|
# Emulate the BufferControl through which we are searching.
|
|
# For this we filter out some of the input processors.
|
|
excluded_processors = tuple(self._excluded_input_processors)
|
|
|
|
def filter_processor(item: Processor) -> Optional[Processor]:
|
|
"""Filter processors from the main control that we want to disable
|
|
here. This returns either an accepted processor or None."""
|
|
# For a `_MergedProcessor`, check each individual processor, recursively.
|
|
if isinstance(item, _MergedProcessor):
|
|
accepted_processors = [filter_processor(p) for p in item.processors]
|
|
return merge_processors(
|
|
[p for p in accepted_processors if p is not None]
|
|
)
|
|
|
|
# For a `ConditionalProcessor`, check the body.
|
|
elif isinstance(item, ConditionalProcessor):
|
|
p = filter_processor(item.processor)
|
|
if p:
|
|
return ConditionalProcessor(p, item.filter)
|
|
|
|
# Otherwise, check the processor itself.
|
|
else:
|
|
if not isinstance(item, excluded_processors):
|
|
return item
|
|
|
|
return None
|
|
|
|
filtered_processor = filter_processor(
|
|
merge_processors(main_control.input_processors or [])
|
|
)
|
|
highlight_processor = HighlightIncrementalSearchProcessor()
|
|
|
|
if filtered_processor:
|
|
new_processors = [filtered_processor, highlight_processor]
|
|
else:
|
|
new_processors = [highlight_processor]
|
|
|
|
from .controls import SearchBufferControl
|
|
|
|
assert isinstance(ti.buffer_control, SearchBufferControl)
|
|
|
|
buffer_control = BufferControl(
|
|
buffer=main_control.buffer,
|
|
input_processors=new_processors,
|
|
include_default_input_processors=False,
|
|
lexer=main_control.lexer,
|
|
preview_search=True,
|
|
search_buffer_control=cast(SearchBufferControl, ti.buffer_control),
|
|
)
|
|
|
|
return buffer_control.create_content(ti.width, ti.height, preview_search=True)
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
from .controls import SearchBufferControl
|
|
|
|
assert isinstance(
|
|
ti.buffer_control, SearchBufferControl
|
|
), "`ReverseSearchProcessor` should be applied to a `SearchBufferControl` only."
|
|
|
|
source_to_display: Optional[SourceToDisplay]
|
|
display_to_source: Optional[DisplayToSource]
|
|
|
|
main_control = self._get_main_buffer(ti.buffer_control)
|
|
|
|
if ti.lineno == 0 and main_control:
|
|
content = self._content(main_control, ti)
|
|
|
|
# Get the line from the original document for this search.
|
|
line_fragments = content.get_line(content.cursor_position.y)
|
|
|
|
if main_control.search_state.direction == SearchDirection.FORWARD:
|
|
direction_text = "i-search"
|
|
else:
|
|
direction_text = "reverse-i-search"
|
|
|
|
fragments_before: StyleAndTextTuples = [
|
|
("class:prompt.search", "("),
|
|
("class:prompt.search", direction_text),
|
|
("class:prompt.search", ")`"),
|
|
]
|
|
|
|
fragments = (
|
|
fragments_before
|
|
+ [
|
|
("class:prompt.search.text", fragment_list_to_text(ti.fragments)),
|
|
("", "': "),
|
|
]
|
|
+ line_fragments
|
|
)
|
|
|
|
shift_position = fragment_list_len(fragments_before)
|
|
source_to_display = lambda i: i + shift_position
|
|
display_to_source = lambda i: i - shift_position
|
|
else:
|
|
source_to_display = None
|
|
display_to_source = None
|
|
fragments = ti.fragments
|
|
|
|
return Transformation(
|
|
fragments,
|
|
source_to_display=source_to_display,
|
|
display_to_source=display_to_source,
|
|
)
|
|
|
|
|
|
class ConditionalProcessor(Processor):
|
|
"""
|
|
Processor that applies another processor, according to a certain condition.
|
|
Example::
|
|
|
|
# Create a function that returns whether or not the processor should
|
|
# currently be applied.
|
|
def highlight_enabled():
|
|
return true_or_false
|
|
|
|
# Wrapped it in a `ConditionalProcessor` for usage in a `BufferControl`.
|
|
BufferControl(input_processors=[
|
|
ConditionalProcessor(HighlightSearchProcessor(),
|
|
Condition(highlight_enabled))])
|
|
|
|
:param processor: :class:`.Processor` instance.
|
|
:param filter: :class:`~prompt_toolkit.filters.Filter` instance.
|
|
"""
|
|
|
|
def __init__(self, processor: Processor, filter: FilterOrBool) -> None:
|
|
self.processor = processor
|
|
self.filter = to_filter(filter)
|
|
|
|
def apply_transformation(
|
|
self, transformation_input: TransformationInput
|
|
) -> Transformation:
|
|
# Run processor when enabled.
|
|
if self.filter():
|
|
return self.processor.apply_transformation(transformation_input)
|
|
else:
|
|
return Transformation(transformation_input.fragments)
|
|
|
|
def __repr__(self) -> str:
|
|
return "%s(processor=%r, filter=%r)" % (
|
|
self.__class__.__name__,
|
|
self.processor,
|
|
self.filter,
|
|
)
|
|
|
|
|
|
class DynamicProcessor(Processor):
|
|
"""
|
|
Processor class that can dynamically returns any Processor.
|
|
|
|
:param get_processor: Callable that returns a :class:`.Processor` instance.
|
|
"""
|
|
|
|
def __init__(self, get_processor: Callable[[], Optional[Processor]]) -> None:
|
|
self.get_processor = get_processor
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
processor = self.get_processor() or DummyProcessor()
|
|
return processor.apply_transformation(ti)
|
|
|
|
|
|
def merge_processors(processors: List[Processor]) -> Processor:
|
|
"""
|
|
Merge multiple `Processor` objects into one.
|
|
"""
|
|
if len(processors) == 0:
|
|
return DummyProcessor()
|
|
|
|
if len(processors) == 1:
|
|
return processors[0] # Nothing to merge.
|
|
|
|
return _MergedProcessor(processors)
|
|
|
|
|
|
class _MergedProcessor(Processor):
|
|
"""
|
|
Processor that groups multiple other `Processor` objects, but exposes an
|
|
API as if it is one `Processor`.
|
|
"""
|
|
|
|
def __init__(self, processors: List[Processor]):
|
|
self.processors = processors
|
|
|
|
def apply_transformation(self, ti: TransformationInput) -> Transformation:
|
|
source_to_display_functions = [ti.source_to_display]
|
|
display_to_source_functions = []
|
|
fragments = ti.fragments
|
|
|
|
def source_to_display(i: int) -> int:
|
|
"""Translate x position from the buffer to the x position in the
|
|
processor fragments list."""
|
|
for f in source_to_display_functions:
|
|
i = f(i)
|
|
return i
|
|
|
|
for p in self.processors:
|
|
transformation = p.apply_transformation(
|
|
TransformationInput(
|
|
ti.buffer_control,
|
|
ti.document,
|
|
ti.lineno,
|
|
source_to_display,
|
|
fragments,
|
|
ti.width,
|
|
ti.height,
|
|
)
|
|
)
|
|
fragments = transformation.fragments
|
|
display_to_source_functions.append(transformation.display_to_source)
|
|
source_to_display_functions.append(transformation.source_to_display)
|
|
|
|
def display_to_source(i: int) -> int:
|
|
for f in reversed(display_to_source_functions):
|
|
i = f(i)
|
|
return i
|
|
|
|
# In the case of a nested _MergedProcessor, each processor wants to
|
|
# receive a 'source_to_display' function (as part of the
|
|
# TransformationInput) that has everything in the chain before
|
|
# included, because it can be called as part of the
|
|
# `apply_transformation` function. However, this first
|
|
# `source_to_display` should not be part of the output that we are
|
|
# returning. (This is the most consistent with `display_to_source`.)
|
|
del source_to_display_functions[:1]
|
|
|
|
return Transformation(fragments, source_to_display, display_to_source)
|