Rename to blueprint-compiler

This isn't an official GTK project so better to avoid using "GTK" in the
name.

gtkblueprinttool/utils.py

@@ -1,94 +0,0 @@
-# utils.py
-#
-# Copyright 2021 James Westman <james@jwestman.net>
-#
-# This file is free software; you can redistribute it and/or modify it
-# under the terms of the GNU Lesser General Public License as
-# published by the Free Software Foundation; either version 3 of the
-# License, or (at your option) any later version.
-#
-# This file is distributed in the hope that it will be useful, but
-# WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-# Lesser General Public License for more details.
-#
-# You should have received a copy of the GNU Lesser General Public
-# License along with this program.  If not, see <http://www.gnu.org/licenses/>.
-#
-# SPDX-License-Identifier: LGPL-3.0-or-later
-
-import typing as T
-
-
-def lazy_prop(func):
-    key = "_lazy_prop_" + func.__name__
-
-    @property
-    def real_func(self):
-        if key not in self.__dict__:
-            self.__dict__[key] = func(self)
-        return self.__dict__[key]
-
-    return real_func
-
-
-def did_you_mean(word: str, options: T.List[str]) -> T.Optional[str]:
-    if len(options) == 0:
-        return None
-
-    def levenshtein(a, b):
-        # see https://en.wikipedia.org/wiki/Levenshtein_distance
-        m = len(a)
-        n = len(b)
-
-        distances = [[0 for j in range(n)] for i in range(m)]
-
-        for i in range(m):
-            distances[i][0] = i
-        for j in range(n):
-            distances[0][j] = j
-
-        for j in range(1, n):
-            for i in range(1, m):
-                cost = 0
-                if a[i] != b[j]:
-                    if a[i].casefold() == b[j].casefold():
-                        cost = 1
-                    else:
-                        cost = 2
-                distances[i][j] = min(distances[i-1][j] + 2, distances[i][j-1] + 2, distances[i-1][j-1] + cost)
-
-        return distances[m-1][n-1]
-
-    distances = [(option, levenshtein(word, option)) for option in options]
-    closest = min(distances, key=lambda item:item[1])
-    if closest[1] <= 5:
-        return closest[0]
-    return None
-
-
-def idx_to_pos(idx: int, text: str) -> T.Tuple[int, int]:
-    if idx == 0:
-        return (0, 0)
-    sp = text[:idx].splitlines(keepends=True)
-    line_num = len(sp)
-    col_num = len(sp[-1])
-    return (line_num - 1, col_num)
-
-def pos_to_idx(line: int, col: int, text: str) -> int:
-    lines = text.splitlines(keepends=True)
-    return sum([len(line) for line in lines[:line]]) + col
-
-def idxs_to_range(start: int, end: int, text: str):
-    start_l, start_c = idx_to_pos(start, text)
-    end_l, end_c = idx_to_pos(end, text)
-    return {
-        "start": {
-            "line": start_l,
-            "character": start_c,
-        },
-        "end": {
-            "line": end_l,
-            "character": end_c,
-        },
-    }