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8e4433a487
`blueprint-compiler port` interactively ports a project to blueprint. It will create the subproject wrap file, add it to .gitignore, decompile your GtkBuilder XML files, emit code to copy and paste into your meson.build file, and update POTFILES.in. It can't quite handle all of the features the forward compiler can, so it will skip those files.
106 lines
3 KiB
Python
106 lines
3 KiB
Python
# utils.py
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#
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# Copyright 2021 James Westman <james@jwestman.net>
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#
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# This file is free software; you can redistribute it and/or modify it
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# under the terms of the GNU Lesser General Public License as
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# published by the Free Software Foundation; either version 3 of the
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# License, or (at your option) any later version.
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#
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# This file is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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# Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with this program. If not, see <http://www.gnu.org/licenses/>.
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#
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# SPDX-License-Identifier: LGPL-3.0-or-later
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import typing as T
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class Colors:
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RED = '\033[91m'
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GREEN = '\033[92m'
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YELLOW = '\033[33m'
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FAINT = '\033[2m'
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BOLD = '\033[1m'
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BLUE = '\033[34m'
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UNDERLINE = '\033[4m'
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NO_UNDERLINE = '\033[24m'
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CLEAR = '\033[0m'
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def lazy_prop(func):
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key = "_lazy_prop_" + func.__name__
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@property
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def real_func(self):
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if key not in self.__dict__:
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self.__dict__[key] = func(self)
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return self.__dict__[key]
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return real_func
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def did_you_mean(word: str, options: T.List[str]) -> T.Optional[str]:
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if len(options) == 0:
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return None
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def levenshtein(a, b):
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# see https://en.wikipedia.org/wiki/Levenshtein_distance
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m = len(a)
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n = len(b)
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distances = [[0 for j in range(n)] for i in range(m)]
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for i in range(m):
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distances[i][0] = i
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for j in range(n):
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distances[0][j] = j
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for j in range(1, n):
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for i in range(1, m):
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cost = 0
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if a[i] != b[j]:
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if a[i].casefold() == b[j].casefold():
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cost = 1
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else:
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cost = 2
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distances[i][j] = min(distances[i-1][j] + 2, distances[i][j-1] + 2, distances[i-1][j-1] + cost)
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return distances[m-1][n-1]
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distances = [(option, levenshtein(word, option)) for option in options]
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closest = min(distances, key=lambda item:item[1])
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if closest[1] <= 5:
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return closest[0]
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return None
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def idx_to_pos(idx: int, text: str) -> T.Tuple[int, int]:
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if idx == 0:
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return (0, 0)
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sp = text[:idx].splitlines(keepends=True)
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line_num = len(sp)
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col_num = len(sp[-1])
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return (line_num - 1, col_num)
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def pos_to_idx(line: int, col: int, text: str) -> int:
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lines = text.splitlines(keepends=True)
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return sum([len(line) for line in lines[:line]]) + col
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def idxs_to_range(start: int, end: int, text: str):
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start_l, start_c = idx_to_pos(start, text)
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end_l, end_c = idx_to_pos(end, text)
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return {
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"start": {
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"line": start_l,
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"character": start_c,
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},
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"end": {
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"line": end_l,
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"character": end_c,
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},
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}
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