python - 如何在不使用 Python 中的外部库的情况下解析 arff 文件

Question

我需要在不使用任何外部库的情况下解析如下所示的 arff 文件。我不确定如何将属性与数值相关联。就像我怎么能说每行中的第一个数值是年龄而第二个数值是性别？您还可以将我链接到一些用于解析类似场景的 python 代码吗？

@relation cleveland-14-heart-disease
@attribute 'age' real
@attribute 'sex' { female, male}
@attribute 'cp' { typ_angina, asympt, non_anginal, atyp_angina}
@attribute 'trestbps' real
@attribute 'chol' real
@attribute 'fbs' { t, f}
@attribute 'restecg' { left_vent_hyper, normal, st_t_wave_abnormality}
@attribute 'thalach' real
@attribute 'exang' { no, yes}
@attribute 'oldpeak' real
@attribute 'slope' { up, flat, down}
@attribute 'ca' real
@attribute 'thal' { fixed_defect, normal, reversable_defect}
@attribute 'class' { negative, positive}
@data
63,male,typ_angina,145,233,t,left_vent_hyper,150,no,2.3,down,0,fixed_defect,negative
37,male,non_anginal,130,250,f,normal,187,no,3.5,down,0,normal,negative
41,female,atyp_angina,130,204,f,left_vent_hyper,172,no,1.4,up,0,normal,negative
56,male,atyp_angina,120,236,f,normal,178,no,0.8,up,0,normal,negative
57,female,asympt,120,354,f,normal,163,yes,0.6,up,0,normal,negative
57,male,asympt,140,192,f,normal,148,no,0.4,flat,0,fixed_defect,negative
56,female,atyp_angina,140,294,f,left_vent_hyper,153,no,1.3,flat,0,normal,negative
44,male,atyp_angina,120,263,f,normal,173,no,0,up,0,reversable_defect,negative
52,male,non_anginal,172,199,t,normal,162,no,0.5,up,0,reversable_defect,negative

这是我编写的示例代码:

arr=[]
arff_file = open("heart_train.arff")
count=0
for line in arff_file:
        count+=1
        #line=line.strip("\n")
        #line=line.split(',')
        if not (line.startswith("@")):
                if not (line.startswith("%")):
                        line=line.strip("\n")
                        line=line.split(',')
                        arr.append(line)



print(arr[1:30])

但是输出与我预期的非常不同:

[['37', 'male', 'non_anginal', '130', '250', 'f', 'normal', '187', 'no', '3.5', 'down', '0', 'normal', 'negative'], ['41', 'female', 'atyp_angina', '130', '204', 'f', 'left_vent_hyper', '172', 'no', '1.4', 'up', '0', 'normal', 'negative'], ['56', 'male', 'atyp_angina', '120', '236', 'f', 'normal', '178', 'no', '0.8', 'up', '0', 'normal', 'negative'], ['57', 'female', 'asympt', '120', '354', 'f', 'normal', '163', 'yes', '0.6', 'up', '0', 'normal', 'negative'], ['57', 'male', 'asympt', '140', '192', 'f', 'normal', '148', 'no', '0.4', 'flat', '0', 'fixed_defect', 'negative'], ['56', 'female', 'atyp_angina', '140', '294', 'f', 'left_vent_hyper', '153', 'no', '1.3', 'flat', '0', 'normal', 'negative'], ['44', 'male', 'atyp_angina', '120', '263', 'f', 'normal', '173', 'no', '0', 'up', '0', 'reversable_defect', 'negative'], ['52', 'male', 'non_anginal', '172', '199', 't', 'normal', '162', 'no', '0.5', 'up', '0', 'reversable_defect', 'negative'], ['57', 'male', 'non_anginal', '150', '168', 'f', 'normal', '174', 'no', '1.6', 'up', '0', 'normal', 'negative'], ['54', 'male', 'asympt', '140', '239', 'f', 'normal', '160', 'no', '1.2', 'up', '0', 'normal', 'negative'], ['48', 'female', 'non_anginal', '130', '275', 'f', 'normal', '139', 'no', '0.2', 'up', '0', 'normal', 'negative'], ['49', 'male', 'atyp_angina', '130', '266', 'f', 'normal', '171', 'no', '0.6', 'up', '0', 'normal', 'negative'], ['64', 'male', 'typ_angina', '110', '211', 'f', 'left_vent_hyper', '144', 'yes', '1.8', 'flat', '0', 'normal', 'negative'], ['58', 'female', 'typ_angina', '150', '283', 't', 'left_vent_hyper', '162', 'no', '1', 'up', '0', 'normal', 'negative'], ['50', 'female', 'non_anginal', '120', '219', 'f', 'normal', '158', 'no', '1.6', 'flat', '0', 'normal', 'negative'], ['58', 'female', 'non_anginal', '120', '340', 'f', 'normal', '172', 'no', '0', 'up', '0', 'normal', 'negative'], ['66', 'female', 'typ_angina', '150', '226', 'f', 'normal', '114', 'no', '2.6', 'down', '0', 'normal', 'negative'], ['43', 'male', 'asympt', '150', '247', 'f', 'normal', '171', 'no', '1.5', 'up', '0', 'normal', 'negative'], ['69', 'female', 'typ_angina', '140', '239', 'f', 'normal', '151', 'no', '1.8', 'up', '2', 'normal', 'negative'], ['59', 'male', 'asympt', '135', '234', 'f', 'normal', '161', 'no', '0.5', 'flat', '0', 'reversable_defect', 'negative'], ['44', 'male', 'non_anginal', '130', '233', 'f', 'normal', '179', 'yes', '0.4', 'up', '0', 'normal', 'negative'], ['42', 'male', 'asympt', '140', '226', 'f', 'normal', '178', 'no', '0', 'up', '0', 'normal', 'negative'], ['61', 'male', 'non_anginal', '150', '243', 't', 'normal', '137', 'yes', '1', 'flat', '0', 'normal', 'negative'], ['40', 'male', 'typ_angina', '140', '199', 'f', 'normal', '178', 'yes', '1.4', 'up', '0', 'reversable_defect', 'negative'], ['71', 'female', 'atyp_angina', '160', '302', 'f', 'normal', '162', 'no', '0.4', 'up', '2', 'normal', 'negative'], ['59', 'male', 'non_anginal', '150', '212', 't', 'normal', '157', 'no', '1.6', 'up', '0', 'normal', 'negative'], ['51', 'male', 'non_anginal', '110', '175', 'f', 'normal', '123', 'no', '0.6', 'up', '0', 'normal', 'negative'], ['65', 'female', 'non_anginal', '140', '417', 't', 'left_vent_hyper', '157', 'no', '0.8', 'up', '1', 'normal', 'negative'], ['53', 'male', 'non_anginal', '130', '197', 't', 'left_vent_hyper', '152', 'no', '1.2', 'down', '0', 'normal', 'negative']]

你知道我怎样才能得到像下面这样由 arff 库(来自 Weka)创建的输出吗？

Answer 1

你说“没有外部库”，但你至少可以剪切并粘贴到你自己的代码中吗？你可能会发现 the source code to the arff module很有用(200 行，大约 5.6 KB)。

编辑:

您可能会发现此格式引用很有用:http://weka.wikispaces.com/ARFF+%28stable+version%29

编辑2:

为了好玩，我编写了自己的 .arrf 解析器；它几乎与 WEKA 代码一样长，但应该更具可读性——只有六个函数、一个调度表和一个非常模块化的类。您可以遍历类实例以将每个数据行作为命名元组获取。

看看你的想法:

from collections import namedtuple
from keyword import iskeyword
import re

def NotDone(msg):
    raise NotImplemented(msg)

def nominal(spec):
    """
    Create an ARFF nominal (enumerated) data type
    """
    spec = spec.lstrip("{ \t").rstrip("} \t")
    good_values = set(val.strip() for val in spec.split(","))

    def fn(s):
        s = s.strip()
        if s in good_values:
            return s
        else:
            raise ValueError("'{}' is not a recognized value".format(s))

    # patch docstring
    fn.__name__ = "nominal"
    fn.__doc__ = """
    ARFF nominal (enumerated) data type

    Legal values are {}
    """.format(sorted(good_values))
    return fn

def numeric(s):
    """
    Convert string to int or float
    """
    try:
        return int(s)
    except ValueError:
        return float(s)

field_maker = {
    "date":       (lambda spec: NotDone("date data type not implemented")),
    "integer":    (lambda spec: int),
    "nominal":    (lambda spec: nominal(spec)),
    "numeric":    (lambda spec: numeric),
    "string":     (lambda spec: str),
    "real":       (lambda spec: float),
    "relational": (lambda spec: NotDone("relational data type not implemented")),
}

def file_lines(fname):
    # lazy file reader; ensures file is closed when done,
    # returns lines without trailing spaces or newline
    with open(fname) as inf:
        for line in inf:
            yield line.rstrip()

def no_data_yet(*items):
    raise ValueError("AarfRow not fully defined (haven't seen a @data directive yet)")

def make_field_name(s):
    """
    Mangle string to make it a valid Python identifier
    """
    s = s.lower()                               # force to lowercase
    s = "_".join(re.findall("[a-z0-9]+", s))    # strip all invalid chars; join what's left with "_"
    if iskeyword(s) or re.match("[0-9]", s):    # if the result is a keyword or starts with a digit
        s = "f_"+s                              #   make it a safe field name
    return s  

class ArffReader:
    line_types = ["blank", "comment", "relation", "attribute", "data"]

    def __init__(self, fname):
        # get input file
        self.fname = fname
        self.lines = file_lines(fname)

        # prepare to read file header
        self.relation = '(not specified)'
        self.data_names = []
        self.data_types = []
        self.dtype = no_data_yet

        # read file header
        line_tests = [
            (getattr(self, "line_is_{}".format(item)), getattr(self, "line_do_{}".format(item)))
            for item in self.__class__.line_types
        ]
        for line in self.lines:
            for is_, do in line_tests:
                if is_(line):
                    done = do(line)
                    break
            if done:
                break

        # use header fields to build data type (and make it print as requested)
        class ArffRow(namedtuple('ArffRow', self.data_names)):
            __slots__ = ()
            def __str__(self):
                items = (getattr(self, field) for field in self._fields)
                return "({})".format(", ".join(repr(it) for it in items))
        self.dtype = ArffRow

    #
    # figure out input-line type
    #

    def line_is_blank(self, line):
        return not line

    def line_is_comment(self, line):
        return line.lower().startswith('%')

    def line_is_relation(self, line):
        return line.lower().startswith('@relation')

    def line_is_attribute(self, line):
        return line.lower().startswith('@attribute')

    def line_is_data(self, line):
        return line.lower().startswith('@data')

    #    
    # handle input-line type
    #    

    def line_do_blank(self, line):
        pass

    def line_do_comment(self, line):
        pass

    def line_do_relation(self, line):
        self.relation = line[10:].strip()

    def line_do_attribute(self, line):
        m = re.match(
            "^@attribute"           #   line starts with '@attribute'
            "\s+"                   #
            "("                     # name is one of:
                "(?:'[^']+')"       #   ' string in single-quotes '
                "|(?:\"[^\"]+\")"   #   " string in double-quotes "
                "|(?:[^ \t'\"]+)"   #   single_word_string (no spaces)
            ")"                     #
            "\s+"                   #
            "("                     # type is one of:
                "(?:{[^}]+})"       #   { set, of, nominal, values }
                "|(?:\w+)"          #   datatype
            ")"                     #
            "\s*"                   #
            "("                     # spec string
                ".*"                #   anything to end of line
            ")$",                   #
            line, flags=re.I)       #   case-insensitive
        if m:
            name, type_, spec = m.groups()
            self.data_names.append(make_field_name(name))
            if type_[0] == '{':
                type_, spec = 'nominal', type_
            self.data_types.append(field_maker[type_](spec))
        else:
            raise ValueError("failed parsing attribute line '{}'".format(line))

    def line_do_data(self, line):
        return True  # flag end of header

    #
    # make the class iterable
    #

    def __iter__(self):
        return self

    def next(self):
        """
        Return one data row at a time
        """
        data = next(self.lines).split(',')
        return self.dtype(*(fn(dat) for fn,dat in zip(self.data_types, data)))

它可以用作

for row in ArffReader('mydata.arff'):
    print(row)

结果

(63.0, 'male', 'typ_angina', 145.0, 233.0, 't', 'left_vent_hyper', 150.0, 'no', 2.3, 'down', 0.0, 'fixed_defect', 'negative')
(37.0, 'male', 'non_anginal', 130.0, 250.0, 'f', 'normal', 187.0, 'no', 3.5, 'down', 0.0, 'normal', 'negative')
(41.0, 'female', 'atyp_angina', 130.0, 204.0, 'f', 'left_vent_hyper', 172.0, 'no', 1.4, 'up', 0.0, 'normal', 'negative')
(56.0, 'male', 'atyp_angina', 120.0, 236.0, 'f', 'normal', 178.0, 'no', 0.8, 'up', 0.0, 'normal', 'negative')
(57.0, 'female', 'asympt', 120.0, 354.0, 'f', 'normal', 163.0, 'yes', 0.6, 'up', 0.0, 'normal', 'negative')
(57.0, 'male', 'asympt', 140.0, 192.0, 'f', 'normal', 148.0, 'no', 0.4, 'flat', 0.0, 'fixed_defect', 'negative')
(56.0, 'female', 'atyp_angina', 140.0, 294.0, 'f', 'left_vent_hyper', 153.0, 'no', 1.3, 'flat', 0.0, 'normal', 'negative')
(44.0, 'male', 'atyp_angina', 120.0, 263.0, 'f', 'normal', 173.0, 'no', 0.0, 'up', 0.0, 'reversable_defect', 'negative')
(52.0, 'male', 'non_anginal', 172.0, 199.0, 't', 'normal', 162.0, 'no', 0.5, 'up', 0.0, 'reversable_defect', 'negative')

字段也可以通过名称寻址，即

for patient in ArffReader('mydata.arff'):
    print("{} year old {}".format(patient.age, patient.sex))

给出

63.0 year old male
37.0 year old male
41.0 year old female
56.0 year old male
57.0 year old female
57.0 year old male
56.0 year old female
44.0 year old male
52.0 year old male

你可以看到文件名

>>> print(repr(patient))
ArffRow(age=63.0, sex='male', cp='typ_angina', trestbps=145.0, chol=233.0, fbs='t', restecg='left_vent_hyper', thalach=150.0, exang='no', oldpeak=2.3, slope='down', ca=0.0, thal='fixed_defect', f_class='negative')

字段名称按照 ARFF header ，强制小写(并且在 'class' 的情况下以 'f_' 为前缀，因为 class 是 Python 关键字，因此不能用作字段名称)。