[SPARKNLP-1109] Adding Cleaner annotator

python/sparknlp/annotator/cleaners/__init__.py

@@ -11,4 +11,5 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
-from sparknlp.annotator.cleaners.extractor import *
+from sparknlp.annotator.cleaners.extractor import *
+from sparknlp.annotator.cleaners.cleaner import *

python/sparknlp/annotator/cleaners/cleaner.py

@@ -0,0 +1,201 @@
+#  Copyright 2017-2025 John Snow Labs
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+"""Contains classes for Cleaner."""
+from sparknlp.common import *
+
+class Cleaner(AnnotatorModel):
+    name = "Cleaner"
+
+    inputAnnotatorTypes = [AnnotatorType.TOKEN]
+
+    outputAnnotatorType = AnnotatorType.CHUNK
+
+    encoding = Param(Params._dummy(),
+                   "encoding",
+                   "The encoding to be used for decoding the byte string (default is utf-8)",
+                   typeConverter=TypeConverters.toString)
+
+    cleanPrefixPattern = Param(Params._dummy(),
+                     "cleanPrefixPattern",
+                     "The pattern for the prefix. Can be a simple string or a regex pattern.",
+                     typeConverter=TypeConverters.toString)
+
+    cleanPostfixPattern = Param(Params._dummy(),
+                               "cleanPostfixPattern",
+                               "The pattern for the postfix. Can be a simple string or a regex pattern.",
+                               typeConverter=TypeConverters.toString)
+
+    cleanerMode = Param(
+        Params._dummy(),
+        "cleanerMode",
+        "possible values: " +
+        "clean, bytes_string_to_string, clean_non_ascii_chars, clean_ordered_bullets, clean_postfix, clean_prefix, remove_punctuation, replace_unicode_quotes",
+        typeConverter=TypeConverters.toString
+    )
+
+    extraWhitespace = Param(Params._dummy(),
+                    "extraWhitespace",
+                    "Whether to remove extra whitespace.",
+                    typeConverter=TypeConverters.toBoolean)
+
+    dashes = Param(Params._dummy(),
+                "dashes",
+                "Whether to handle dashes in text.",
+                typeConverter=TypeConverters.toBoolean)
+
+    bullets = Param(Params._dummy(),
+                   "bullets",
+                   "Whether to handle bullets in text.",
+                   typeConverter=TypeConverters.toBoolean)
+
+    trailingPunctuation = Param(Params._dummy(),
+                    "trailingPunctuation",
+                    "Whether to remove trailing punctuation from text.",
+                    typeConverter=TypeConverters.toBoolean)
+
+    lowercase = Param(Params._dummy(),
+                "lowercase",
+                "Whether to convert text to lowercase.",
+                typeConverter=TypeConverters.toBoolean)
+
+    ignoreCase = Param(Params._dummy(),
+                      "ignoreCase",
+                      "If true, ignores case in the pattern.",
+                      typeConverter=TypeConverters.toBoolean)
+
+    strip = Param(Params._dummy(),
+               "strip",
+               "If true, removes leading or trailing whitespace from the cleaned string.",
+               typeConverter=TypeConverters.toBoolean)
+
+    def setEncoding(self, value):
+        """Sets the encoding to be used for decoding the byte string (default is utf-8).
+
+        Parameters
+        ----------
+        value : str
+            The encoding to be used for decoding the byte string (default is utf-8)
+        """
+        return self._set(encoding=value)
+
+    def setCleanPrefixPattern(self, value):
+        """Sets the pattern for the prefix. Can be a simple string or a regex pattern.
+
+        Parameters
+        ----------
+        value : str
+            The pattern for the prefix. Can be a simple string or a regex pattern.
+        """
+        return self._set(cleanPrefixPattern=value)
+
+    def setCleanPostfixPattern(self, value):
+        """Sets the pattern for the postfix. Can be a simple string or a regex pattern.
+
+        Parameters
+        ----------
+        value : str
+            The pattern for the postfix. Can be a simple string or a regex pattern.
+        """
+        return self._set(cleanPostfixPattern=value)
+
+    def setCleanerMode(self, value):
+        """Sets the cleaner mode.
+
+        Possible values:
+            clean, bytes_string_to_string, clean_non_ascii_chars, clean_ordered_bullets,
+            clean_postfix, clean_prefix, remove_punctuation, replace_unicode_quotes
+
+        Parameters
+        ----------
+        value : str
+            The mode for cleaning operations.
+        """
+        return self._set(cleanerMode=value)
+
+    def setExtraWhitespace(self, value):
+        """Sets whether to remove extra whitespace.
+
+        Parameters
+        ----------
+        value : bool
+            Whether to remove extra whitespace.
+        """
+        return self._set(extraWhitespace=value)
+
+    def setDashes(self, value):
+        """Sets whether to handle dashes in text.
+
+        Parameters
+        ----------
+        value : bool
+            Whether to handle dashes in text.
+        """
+        return self._set(dashes=value)
+
+    def setBullets(self, value):
+        """Sets whether to handle bullets in text.
+
+        Parameters
+        ----------
+        value : bool
+            Whether to handle bullets in text.
+        """
+        return self._set(bullets=value)
+
+    def setTrailingPunctuation(self, value):
+        """Sets whether to remove trailing punctuation from text.
+
+        Parameters
+        ----------
+        value : bool
+            Whether to remove trailing punctuation from text.
+        """
+        return self._set(trailingPunctuation=value)
+
+    def setLowercase(self, value):
+        """Sets whether to convert text to lowercase.
+
+        Parameters
+        ----------
+        value : bool
+            Whether to convert text to lowercase.
+        """
+        return self._set(lowercase=value)
+
+    def setIgnoreCase(self, value):
+        """Sets whether to ignore case in the pattern.
+
+        Parameters
+        ----------
+        value : bool
+            If true, ignores case in the pattern.
+        """
+        return self._set(ignoreCase=value)
+
+    def setStrip(self, value):
+        """Sets whether to remove leading or trailing whitespace from the cleaned string.
+
+        Parameters
+        ----------
+        value : bool
+            If true, removes leading or trailing whitespace from the cleaned string.
+        """
+        return self._set(strip=value)
+
+    @keyword_only
+    def __init__(self, classname="com.johnsnowlabs.nlp.annotators.cleaners.Cleaner", java_model=None):
+        super(Cleaner, self).__init__(
+            classname=classname,
+            java_model=java_model
+        )

python/test/annotator/cleaners/cleaner_test.py

@@ -0,0 +1,47 @@
+#  Copyright 2017-2025 John Snow Labs
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+import unittest
+
+import pytest
+
+from sparknlp.annotator.cleaners import *
+from sparknlp.base import *
+from test.util import SparkContextForTest
+
+
+@pytest.mark.slow
+class CleanerTestSpec(unittest.TestCase):
+
+    def setUp(self):
+        self.spark = SparkContextForTest.spark
+        eml_data = """Hello ð\x9f\x98\x80"""
+        self.data_set = self.spark.createDataFrame([[eml_data]]).toDF("text")
+
+    def runTest(self):
+        document_assembler = DocumentAssembler().setInputCol("text").setOutputCol("document")
+
+        extractor = Cleaner() \
+            .setInputCols(["document"]) \
+            .setOutputCol("cleaned") \
+            .setCleanerMode("bytes_string_to_string")
+
+        pipeline = Pipeline().setStages([
+            document_assembler,
+            extractor
+        ])
+
+        model = pipeline.fit(self.data_set)
+        result = model.transform(self.data_set)
+        result.show(truncate=False)
+