RegexTokenizer#
- classpyspark.ml.feature.RegexTokenizer(*,minTokenLength=1,gaps=True,pattern='\\s+',inputCol=None,outputCol=None,toLowercase=True)[source]#
A regex based tokenizer that extracts tokens either by using theprovided regex pattern (in Java dialect) to split the text(default) or repeatedly matching the regex (if gaps is false).Optional parameters also allow filtering tokens using a minimallength.It returns an array of strings that can be empty.
New in version 1.4.0.
Examples
>>>df=spark.createDataFrame([("A B c",)],["text"])>>>reTokenizer=RegexTokenizer()>>>reTokenizer.setInputCol("text")RegexTokenizer...>>>reTokenizer.setOutputCol("words")RegexTokenizer...>>>reTokenizer.transform(df).head()Row(text='A B c', words=['a', 'b', 'c'])>>># Change a parameter.>>>reTokenizer.setParams(outputCol="tokens").transform(df).head()Row(text='A B c', tokens=['a', 'b', 'c'])>>># Temporarily modify a parameter.>>>reTokenizer.transform(df,{reTokenizer.outputCol:"words"}).head()Row(text='A B c', words=['a', 'b', 'c'])>>>reTokenizer.transform(df).head()Row(text='A B c', tokens=['a', 'b', 'c'])>>># Must use keyword arguments to specify params.>>>reTokenizer.setParams("text")Traceback (most recent call last):...TypeError:Method setParams forces keyword arguments.>>>regexTokenizerPath=temp_path+"/regex-tokenizer">>>reTokenizer.save(regexTokenizerPath)>>>loadedReTokenizer=RegexTokenizer.load(regexTokenizerPath)>>>loadedReTokenizer.getMinTokenLength()==reTokenizer.getMinTokenLength()True>>>loadedReTokenizer.getGaps()==reTokenizer.getGaps()True>>>loadedReTokenizer.transform(df).take(1)==reTokenizer.transform(df).take(1)True
Methods
clear(param)Clears a param from the param map if it has been explicitly set.
copy([extra])Creates a copy of this instance with the same uid and some extra params.
explainParam(param)Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
Returns the documentation of all params with their optionally default values and user-supplied values.
extractParamMap([extra])Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
getGaps()Gets the value of gaps or its default value.
Gets the value of inputCol or its default value.
Gets the value of minTokenLength or its default value.
getOrDefault(param)Gets the value of a param in the user-supplied param map or its default value.
Gets the value of outputCol or its default value.
getParam(paramName)Gets a param by its name.
Gets the value of pattern or its default value.
Gets the value of toLowercase or its default value.
hasDefault(param)Checks whether a param has a default value.
hasParam(paramName)Tests whether this instance contains a param with a given (string) name.
isDefined(param)Checks whether a param is explicitly set by user or has a default value.
isSet(param)Checks whether a param is explicitly set by user.
load(path)Reads an ML instance from the input path, a shortcut ofread().load(path).
read()Returns an MLReader instance for this class.
save(path)Save this ML instance to the given path, a shortcut of 'write().save(path)'.
set(param, value)Sets a parameter in the embedded param map.
setGaps(value)Sets the value of
gaps.setInputCol(value)Sets the value of
inputCol.setMinTokenLength(value)Sets the value of
minTokenLength.setOutputCol(value)Sets the value of
outputCol.setParams(self, \*[, minTokenLength, gaps, ...])Sets params for this RegexTokenizer.
setPattern(value)Sets the value of
pattern.setToLowercase(value)Sets the value of
toLowercase.transform(dataset[, params])Transforms the input dataset with optional parameters.
write()Returns an MLWriter instance for this ML instance.
Attributes
Returns all params ordered by name.
Methods Documentation
- clear(param)#
Clears a param from the param map if it has been explicitly set.
- copy(extra=None)#
Creates a copy of this instance with the same uid and someextra params. This implementation first calls Params.copy andthen make a copy of the companion Java pipeline component withextra params. So both the Python wrapper and the Java pipelinecomponent get copied.
- Parameters
- extradict, optional
Extra parameters to copy to the new instance
- Returns
JavaParamsCopy of this instance
- explainParam(param)#
Explains a single param and returns its name, doc, and optionaldefault value and user-supplied value in a string.
- explainParams()#
Returns the documentation of all params with their optionallydefault values and user-supplied values.
- extractParamMap(extra=None)#
Extracts the embedded default param values and user-suppliedvalues, and then merges them with extra values from input intoa flat param map, where the latter value is used if there existconflicts, i.e., with ordering: default param values <user-supplied values < extra.
- Parameters
- extradict, optional
extra param values
- Returns
- dict
merged param map
- getInputCol()#
Gets the value of inputCol or its default value.
- getMinTokenLength()[source]#
Gets the value of minTokenLength or its default value.
New in version 1.4.0.
- getOrDefault(param)#
Gets the value of a param in the user-supplied param map or itsdefault value. Raises an error if neither is set.
- getOutputCol()#
Gets the value of outputCol or its default value.
- getParam(paramName)#
Gets a param by its name.
- hasDefault(param)#
Checks whether a param has a default value.
- hasParam(paramName)#
Tests whether this instance contains a param with a given(string) name.
- isDefined(param)#
Checks whether a param is explicitly set by user or hasa default value.
- isSet(param)#
Checks whether a param is explicitly set by user.
- classmethodload(path)#
Reads an ML instance from the input path, a shortcut ofread().load(path).
- classmethodread()#
Returns an MLReader instance for this class.
- save(path)#
Save this ML instance to the given path, a shortcut of ‘write().save(path)’.
- set(param,value)#
Sets a parameter in the embedded param map.
- setMinTokenLength(value)[source]#
Sets the value of
minTokenLength.New in version 1.4.0.
- setParams(self,\*,minTokenLength=1,gaps=True,pattern="\s+",inputCol=None,outputCol=None,toLowercase=True)[source]#
Sets params for this RegexTokenizer.
New in version 1.4.0.
- setToLowercase(value)[source]#
Sets the value of
toLowercase.New in version 2.0.0.
- transform(dataset,params=None)#
Transforms the input dataset with optional parameters.
New in version 1.3.0.
- Parameters
- dataset
pyspark.sql.DataFrame input dataset
- paramsdict, optional
an optional param map that overrides embedded params.
- dataset
- Returns
pyspark.sql.DataFrametransformed dataset
- write()#
Returns an MLWriter instance for this ML instance.
Attributes Documentation
- gaps=Param(parent='undefined',name='gaps',doc='whetherregexsplitsongaps(True)ormatchestokens(False)')#
- inputCol=Param(parent='undefined',name='inputCol',doc='inputcolumnname.')#
- minTokenLength=Param(parent='undefined',name='minTokenLength',doc='minimumtokenlength(>=0)')#
- outputCol=Param(parent='undefined',name='outputCol',doc='outputcolumnname.')#
- params#
Returns all params ordered by name. The default implementationuses
dir()to get all attributes of typeParam.
- pattern=Param(parent='undefined',name='pattern',doc='regexpattern(Javadialect)usedfortokenizing')#
- toLowercase=Param(parent='undefined',name='toLowercase',doc='whethertoconvertallcharacterstolowercasebeforetokenizing')#
- uid#
A unique id for the object.