make token analyzers configurable modules

Adds a mandatory section 'analyzer' to the token-analysis entries
which define, which analyser to use. Currently there is exactly
one, generic, which implements the former ICUNameProcessor.

nominatim/tokenizer/token_analysis/generic.py

@@ -0,0 +1,110 @@
+"""
+Generic processor for names that creates abbreviation variants.
+"""
+from collections import defaultdict
+import itertools
+
+from icu import Transliterator
+import datrie
+
+### Analysis section
+
+def create(norm_rules, trans_rules, config):
+    """ Create a new token analysis instance for this module.
+    """
+    return GenericTokenAnalysis(norm_rules, trans_rules, config['variants'])
+
+
+class GenericTokenAnalysis:
+    """ Collects the different transformation rules for normalisation of names
+        and provides the functions to apply the transformations.
+    """
+
+    def __init__(self, norm_rules, trans_rules, replacements):
+        self.normalizer = Transliterator.createFromRules("icu_normalization",
+                                                         norm_rules)
+        self.to_ascii = Transliterator.createFromRules("icu_to_ascii",
+                                                       trans_rules +
+                                                       ";[:Space:]+ > ' '")
+        self.search = Transliterator.createFromRules("icu_search",
+                                                     norm_rules + trans_rules)
+
+        # Intermediate reorder by source. Also compute required character set.
+        immediate = defaultdict(list)
+        chars = set()
+        for variant in replacements:
+            if variant.source[-1] == ' ' and variant.replacement[-1] == ' ':
+                replstr = variant.replacement[:-1]
+            else:
+                replstr = variant.replacement
+            immediate[variant.source].append(replstr)
+            chars.update(variant.source)
+        # Then copy to datrie
+        self.replacements = datrie.Trie(''.join(chars))
+        for src, repllist in immediate.items():
+            self.replacements[src] = repllist
+
+
+    def get_normalized(self, name):
+        """ Normalize the given name, i.e. remove all elements not relevant
+            for search.
+        """
+        return self.normalizer.transliterate(name).strip()
+
+    def get_variants_ascii(self, norm_name):
+        """ Compute the spelling variants for the given normalized name
+            and transliterate the result.
+        """
+        baseform = '^ ' + norm_name + ' ^'
+        partials = ['']
+
+        startpos = 0
+        pos = 0
+        force_space = False
+        while pos < len(baseform):
+            full, repl = self.replacements.longest_prefix_item(baseform[pos:],
+                                                               (None, None))
+            if full is not None:
+                done = baseform[startpos:pos]
+                partials = [v + done + r
+                            for v, r in itertools.product(partials, repl)
+                            if not force_space or r.startswith(' ')]
+                if len(partials) > 128:
+                    # If too many variants are produced, they are unlikely
+                    # to be helpful. Only use the original term.
+                    startpos = 0
+                    break
+                startpos = pos + len(full)
+                if full[-1] == ' ':
+                    startpos -= 1
+                    force_space = True
+                pos = startpos
+            else:
+                pos += 1
+                force_space = False
+
+        # No variants detected? Fast return.
+        if startpos == 0:
+            trans_name = self.to_ascii.transliterate(norm_name).strip()
+            return [trans_name] if trans_name else []
+
+        return self._compute_result_set(partials, baseform[startpos:])
+
+
+    def _compute_result_set(self, partials, prefix):
+        results = set()
+
+        for variant in partials:
+            vname = variant + prefix
+            trans_name = self.to_ascii.transliterate(vname[1:-1]).strip()
+            if trans_name:
+                results.add(trans_name)
+
+        return list(results)
+
+
+    def get_search_normalized(self, name):
+        """ Return the normalized version of the name (including transliteration)
+            to be applied at search time.
+        """
+        return self.search.transliterate(' ' + name + ' ').strip()