@classmethod
    def validate(cls, value, params):
        if value is None:
            return False
        split = params.split(',')
        func = split[0].strip()
        if func == 'isLength':
            if len(split) == 2:
                return cls.isLength(value, split[1])
            else:
                return cls.isLength(value, split[1], split[2])
        if func == 'isempty':
            return value == ''
        if func == 'isRange':
            return cls.isRange(value, split[1], split[2])
        if func == 'isin':
            return cls.isin(value, split[1:])
        if func == 'isPattern':
            return cls.isPattern(value, ','.join(split[1:]))
    
        # Now we know that we look for single value validators
        validators = {
            'isnumber':        cls.isnumber,
            'isinteger':    cls.isinteger,
            'isDate':        cls.isDate,
            'isfuture':        cls.isfuture,
            'ispast':        cls.ispast,
            'isEmail':         cls.isEmail,
            'isTwitter':     cls.isTwitter,
            'isUrl':         cls.isUrl,
            'isImage':        cls.isImage,
            'isBank':         cls.isBank,
            'isgiro':         cls.isgiro,
            'isBankgiro':     cls.isBankgiro,
            'isZipcode':    cls.isZipcode,
            'isTelephone':    cls.isTelephone,
        }
        return validators[func](value)
Returns the maximum distance between any non-singleton cluster.
dataset/ETHPy150Open petrvanblokland/Xierpa3/xierpa3/toolbox/parsers/validator.py/Validator.validate--crossover with--dataset/ETHPy150Open scipy/scipy/scipy/cluster/hierarchy.py/maxdists