replace datrie library with a more simple pure-Python class

src/nominatim_db/tokenizer/token_analysis/simple_trie.py

@@ -0,0 +1,84 @@
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2025 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Simple dict-based implementation of a trie structure.
+"""
+from typing import TypeVar, Generic, Tuple, Optional, List, Dict
+from collections import defaultdict
+
+T = TypeVar('T')
+
+
+class SimpleTrie(Generic[T]):
+    """ A simple read-only trie structure.
+        This structure supports examply one lookup operation,
+        which is longest-prefix lookup.
+    """
+
+    def __init__(self, data: Optional[List[Tuple[str, T]]] = None) -> None:
+        self._tree: Dict[str, 'SimpleTrie[T]'] = defaultdict(SimpleTrie[T])
+        self._value: Optional[T] = None
+        self._prefix = ''
+
+        if data:
+            for key, value in data:
+                self._add(key, 0, value)
+
+            self._make_compact()
+
+    def _add(self, word: str, pos: int, value: T) -> None:
+        """ (Internal) Add a sub-word to the trie.
+            The word is added from index 'pos'. If the sub-word to add
+            is empty, then the trie saves the given value.
+        """
+        if pos < len(word):
+            self._tree[word[pos]]._add(word, pos + 1, value)
+        else:
+            self._value = value
+
+    def _make_compact(self) -> None:
+        """ (Internal) Compress tree where there is exactly one subtree
+            and no value.
+
+            Compression works recursively starting at the leaf.
+        """
+        for t in self._tree.values():
+            t._make_compact()
+
+        if len(self._tree) == 1 and self._value is None:
+            assert not self._prefix
+            for k, v in self._tree.items():
+                self._prefix = k + v._prefix
+                self._tree = v._tree
+                self._value = v._value
+
+    def longest_prefix(self, word: str, start: int = 0) -> Tuple[Optional[T], int]:
+        """ Return the longest prefix match for the given word starting at
+            the position 'start'.
+
+            The function returns a tuple with the value for the longest match and
+            the position of the word after the match. If no match was found at
+            all, the function returns (None, start).
+        """
+        cur = self
+        pos = start
+        result: Tuple[Optional[T], int] = None, start
+
+        while True:
+            if cur._prefix:
+                if not word.startswith(cur._prefix, pos):
+                    return result
+                pos += len(cur._prefix)
+
+            if cur._value:
+                result = cur._value, pos
+
+            if pos >= len(word) or word[pos] not in cur._tree:
+                return result
+
+            cur = cur._tree[word[pos]]
+            pos += 1