def apply_transformation(self, cli, document, lineno, source_to_display, tokens):
if (lineno < self._lines_before or
lineno >= self._lines_before + len(self.history_mapping.selected_lines)):
text = token_list_to_text(tokens)
return Transformation(tokens=[(Token.History.ExistingInput, text)])
else:
return Transformation(tokens=tokens)
def apply_transformation(self, cli, document, lineno, source_to_display,
tokens):
search_text = self._get_search_text(cli)
if search_text and not cli.is_returning:
# For each search match, replace the Token.
line_text = token_list_to_text(tokens)
tokens = explode_tokens(tokens)
flags = re.IGNORECASE if cli.is_ignoring_case else 0
# Get cursor column.
if document.cursor_position_row == lineno:
cursor_column = source_to_display(document.cursor_position_col)
else:
cursor_column = None
for match in re.finditer(re.escape(search_text),
line_text,
flags=flags):
if cursor_column is not None:
on_cursor = match.start() <= cursor_column < match.end()
else:
on_cursor = False
for i in range(match.start(), match.end()):
if on_cursor:
tokens[i] = (Token.SearchMatch.Current, tokens[i][1])
else:
tokens[i] = (Token.SearchMatch, tokens[i][1])
return Transformation(tokens)
def apply_transformation(self, cli, document, lineno, source_to_display, tokens):
search_text = self._get_search_text(cli)
searchmatch_current_token = (':', ) + Token.SearchMatch.Current
searchmatch_token = (':', ) + Token.SearchMatch
if search_text and not cli.is_returning:
# For each search match, replace the Token.
line_text = token_list_to_text(tokens)
tokens = explode_tokens(tokens)
flags = re.IGNORECASE if cli.is_ignoring_case else 0
# Get cursor column.
if document.cursor_position_row == lineno:
cursor_column = source_to_display(document.cursor_position_col)
else:
cursor_column = None
for match in re.finditer(re.escape(search_text), line_text, flags=flags):
if cursor_column is not None:
on_cursor = match.start() <= cursor_column < match.end()
else:
on_cursor = False
for i in range(match.start(), match.end()):
old_token, text = tokens[i]
if on_cursor:
tokens[i] = (old_token + searchmatch_current_token, tokens[i][1])
else:
tokens[i] = (old_token + searchmatch_token, tokens[i][1])
return Transformation(tokens)
def apply_transformation(self, cli, document, tokens):
tokens_before = self.get_tokens(cli)
shift_position = token_list_len(tokens_before)
return Transformation(document=document.insert_before(
token_list_to_text(tokens_before)),
tokens=tokens_before + tokens,
source_to_display=lambda i: i + shift_position,
display_to_source=lambda i: i - shift_position)
def apply_transformation(self, cli, document, tokens):
tokens_before = self.get_tokens(cli)
shift_position = token_list_len(tokens_before)
return Transformation(
document=document.insert_before(token_list_to_text(tokens_before)),
tokens=tokens_before + tokens,
source_to_display=lambda i: i + shift_position,
display_to_source=lambda i: i - shift_position)
def apply_transformation(self, cli, document, lineno, source_to_display, tokens):
# Walk through all te tokens.
if tokens and token_list_to_text(tokens).startswith(' '):
t = (self.token, self.get_char(cli))
tokens = explode_tokens(tokens)
for i in range(len(tokens)):
if tokens[i][1] == ' ':
tokens[i] = t
else:
break
return Transformation(tokens)
def apply_transformation(self, cli, document, lineno, source_to_display, tokens):
# Walk through all te tokens.
if tokens and token_list_to_text(tokens).startswith(' '):
t = (self.token, self.get_char(cli))
tokens = explode_tokens(tokens)
for i in range(len(tokens)):
if tokens[i][1] == ' ':
tokens[i] = t
else:
break
return Transformation(tokens)
def apply_transformation(self, cli, document, tokens):
# Get text before cursor.
if cli.is_searching:
before = _get_isearch_tokens(cli)
elif cli.input_processor.arg is not None:
before = _get_arg_tokens(cli)
else:
before = self.get_tokens(cli)
# Insert before buffer text.
shift_position = token_list_len(before)
return Transformation(
document=document.insert_before(token_list_to_text(before)),
tokens=before + tokens,
source_to_display=lambda i: i + shift_position,
display_to_source=lambda i: i - shift_position)
def apply_transformation(self, cli, document, tokens):
# Get text before cursor.
if cli.is_searching:
before = _get_isearch_tokens(cli)
elif cli.input_processor.arg is not None:
before = _get_arg_tokens(cli)
else:
before = self.get_tokens(cli)
# Insert before buffer text.
shift_position = token_list_len(before)
return Transformation(
document=document.insert_before(token_list_to_text(before)),
tokens=before + tokens,
source_to_display=lambda i: i + shift_position,
display_to_source=lambda i: i - shift_position)
def apply_transformation(self, cli, document, tokens):
tokens_after = self.get_tokens(cli)
return Transformation(document=document.insert_after(
token_list_to_text(tokens_after)),
tokens=tokens + self.get_tokens(cli))
def apply_transformation(self, cli, document, tokens):
tokens_after = self.get_tokens(cli)
return Transformation(
document=document.insert_after(token_list_to_text(tokens_after)),
tokens=tokens + self.get_tokens(cli))
