6e3f1a1194
* Upgrade syntax with pyupgrade --py38-plus Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> * Convert to f-strings with flynt Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> * Format with Black Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> * Remove redundant mock backport dependency Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> * isort imports Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> * Add changelog entry Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com> --------- Signed-off-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com>
309 lines
8.7 KiB
Python
309 lines
8.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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#
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# The OpenSearch Contributors require contributions made to
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# this file be licensed under the Apache-2.0 license or a
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# compatible open source license.
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#
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# Modifications Copyright OpenSearch Contributors. See
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# GitHub history for details.
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#
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# Licensed to Elasticsearch B.V. under one or more contributor
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# license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright
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# ownership. Elasticsearch B.V. licenses this file to you under
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# the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from typing import Any, Optional
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from opensearchpy.connection.connections import get_connection
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from .utils import AttrDict, DslBase, merge
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class AnalysisBase:
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@classmethod
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def _type_shortcut(
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cls: Any, name_or_instance: Any, type: Any = None, **kwargs: Any
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) -> Any:
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if isinstance(name_or_instance, cls):
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if type or kwargs:
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raise ValueError(f"{cls.__name__}() cannot accept parameters.")
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return name_or_instance
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if not (type or kwargs):
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return cls.get_dsl_class("builtin")(name_or_instance)
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return cls.get_dsl_class(type, "custom")(
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name_or_instance, type or "custom", **kwargs
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)
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class CustomAnalysis:
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name: Optional[str] = "custom"
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def __init__(
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self, filter_name: str, builtin_type: str = "custom", **kwargs: Any
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) -> None:
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self._builtin_type = builtin_type
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self._name = filter_name
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super().__init__(**kwargs)
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def to_dict(self) -> Any:
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# only name to present in lists
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return self._name
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def get_definition(self) -> Any:
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d = super().to_dict() # type: ignore
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d = d.pop(self.name)
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d["type"] = self._builtin_type
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return d
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class CustomAnalysisDefinition(CustomAnalysis):
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def get_analysis_definition(self: Any) -> Any:
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out = {self._type_name: {self._name: self.get_definition()}}
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t: Any = getattr(self, "tokenizer", None)
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if "tokenizer" in self._param_defs and hasattr(t, "get_definition"):
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out["tokenizer"] = {t._name: t.get_definition()}
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filters = {
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f._name: f.get_definition()
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for f in self.filter
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if hasattr(f, "get_definition")
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}
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if filters:
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out["filter"] = filters
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# any sub filter definitions like multiplexers etc?
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for f in self.filter:
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if hasattr(f, "get_analysis_definition"):
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d = f.get_analysis_definition()
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if d:
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merge(out, d, True)
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char_filters = {
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f._name: f.get_definition()
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for f in self.char_filter
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if hasattr(f, "get_definition")
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}
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if char_filters:
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out["char_filter"] = char_filters
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return out
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class BuiltinAnalysis:
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name: Optional[str] = "builtin"
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def __init__(self, name: Any) -> None:
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self._name = name
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super().__init__()
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def to_dict(self) -> Any:
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# only name to present in lists
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return self._name
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class Analyzer(AnalysisBase, DslBase):
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_type_name: str = "analyzer"
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name: Optional[str] = None
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class BuiltinAnalyzer(BuiltinAnalysis, Analyzer):
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def get_analysis_definition(self) -> Any:
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return {}
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class CustomAnalyzer(CustomAnalysisDefinition, Analyzer):
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_param_defs = {
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"filter": {"type": "token_filter", "multi": True},
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"char_filter": {"type": "char_filter", "multi": True},
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"tokenizer": {"type": "tokenizer"},
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}
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def simulate(
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self,
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text: Any,
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using: str = "default",
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explain: bool = False,
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attributes: Any = None,
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) -> Any:
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"""
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Use the Analyze API of opensearch to test the outcome of this analyzer.
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:arg text: Text to be analyzed
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:arg using: connection alias to use, defaults to ``'default'``
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:arg explain: will output all token attributes for each token. You can
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filter token attributes you want to output by setting ``attributes``
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option.
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:arg attributes: if ``explain`` is specified, filter the token
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attributes to return.
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"""
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opensearch = get_connection(using)
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body = {"text": text, "explain": explain}
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if attributes:
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body["attributes"] = attributes
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definition = self.get_analysis_definition()
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analyzer_def = self.get_definition()
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for section in ("tokenizer", "char_filter", "filter"):
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if section not in analyzer_def:
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continue
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sec_def = definition.get(section, {})
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sec_names = analyzer_def[section]
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if isinstance(sec_names, str):
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body[section] = sec_def.get(sec_names, sec_names)
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else:
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body[section] = [
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sec_def.get(sec_name, sec_name) for sec_name in sec_names
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]
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if self._builtin_type != "custom":
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body["analyzer"] = self._builtin_type
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return AttrDict(opensearch.indices.analyze(body=body))
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class Normalizer(AnalysisBase, DslBase):
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_type_name: str = "normalizer"
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name: Optional[str] = None
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class BuiltinNormalizer(BuiltinAnalysis, Normalizer):
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def get_analysis_definition(self) -> Any:
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return {}
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class CustomNormalizer(CustomAnalysisDefinition, Normalizer):
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_param_defs = {
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"filter": {"type": "token_filter", "multi": True},
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"char_filter": {"type": "char_filter", "multi": True},
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}
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class Tokenizer(AnalysisBase, DslBase):
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_type_name: str = "tokenizer"
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name: Optional[str] = None
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class BuiltinTokenizer(BuiltinAnalysis, Tokenizer):
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pass
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class CustomTokenizer(CustomAnalysis, Tokenizer):
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pass
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class TokenFilter(AnalysisBase, DslBase):
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_type_name: str = "token_filter"
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name: Optional[str] = None
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class BuiltinTokenFilter(BuiltinAnalysis, TokenFilter):
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pass
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class CustomTokenFilter(CustomAnalysis, TokenFilter):
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pass
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class MultiplexerTokenFilter(CustomTokenFilter):
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name = "multiplexer"
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def get_definition(self) -> Any:
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d = super(CustomTokenFilter, self).get_definition()
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if "filters" in d:
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d["filters"] = [
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# comma delimited string given by user
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(
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fs
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if isinstance(fs, str)
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else
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# list of strings or TokenFilter objects
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", ".join(f.to_dict() if hasattr(f, "to_dict") else f for f in fs)
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)
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for fs in self.filters
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]
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return d
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def get_analysis_definition(self) -> Any:
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if not hasattr(self, "filters"):
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return {}
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fs: Any = {}
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d = {"filter": fs}
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for filters in self.filters:
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if isinstance(filters, str):
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continue
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fs.update(
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{
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f._name: f.get_definition()
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for f in filters
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if hasattr(f, "get_definition")
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}
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)
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return d
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class ConditionalTokenFilter(CustomTokenFilter):
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name = "condition"
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def get_definition(self) -> Any:
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d = super(CustomTokenFilter, self).get_definition()
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if "filter" in d:
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d["filter"] = [
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f.to_dict() if hasattr(f, "to_dict") else f for f in self.filter
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]
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return d
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def get_analysis_definition(self) -> Any:
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if not hasattr(self, "filter"):
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return {}
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return {
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"filter": {
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f._name: f.get_definition()
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for f in self.filter
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if hasattr(f, "get_definition")
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}
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}
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class CharFilter(AnalysisBase, DslBase):
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_type_name: str = "char_filter"
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name: Optional[str] = None
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class BuiltinCharFilter(BuiltinAnalysis, CharFilter):
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pass
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class CustomCharFilter(CustomAnalysis, CharFilter):
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pass
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# shortcuts for direct use
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analyzer = Analyzer._type_shortcut
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tokenizer = Tokenizer._type_shortcut
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token_filter = TokenFilter._type_shortcut
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char_filter = CharFilter._type_shortcut
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normalizer = Normalizer._type_shortcut
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__all__ = ["tokenizer", "analyzer", "char_filter", "token_filter", "normalizer"]
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