最近女朋友在背单词，被我推荐了下 macOX 下自带的 New Oxford American Dictionary ，表示十分受用， 我就想着是否可以把词典内容，按需求取出，比如语源出处，或者派生词，这样更好去归纳记忆。
首先去查了 API ，通过官方的提供的文档来看只有 DCSCopyTextDefinition 可以或得到无标记的纯文本内容，通过文本解析来说定然没那么简单方便准确，所以找了下其他的方法。
#! /usr/bin/env xcrun swift
import Foundation
import CoreServices
func getDefinition(_ textString : String) -> String? {
let range : CFRange = CFRangeMake(0, textString.characters.count)
if let definition = DCSCopyTextDefinition(nil, textString, range) {
return definition.takeRetainedValue() as String
}
return nil
}
func main() {
if Process.arguments.count != 2{
print("Usage: madicly [word]")
} else {
let word = Process.arguments[1]
if let definition = getDefinition(word) {
print(definition)
} else {
print("No definition found in Dictionary.")
}
}
}
main()其实直觉上，直接解析词典包会比较容易，尝试再三后发现有诸多问题，在此略过，最终尝试找到可以通过私有 API DCSCopyRecordsForSearchString 来获得词典应用展示的 HTML 内容。 并没有找到如何用 Swift 调用私有 API 的方法，下面换了 objc。
#import <Foundation/Foundation.h>
NSArray *DCSCopyAvailableDictionaries();
NSArray *DCSCopyRecordsForSearchString(DCSDictionaryRef dictionary, CFStringRef string, void *, void *);
NSArray *DCSRecordCopyData(CFTypeRef record);
NSString *DCSDictionaryGetName(DCSDictionaryRef dictID);
NSString * const DictZh = @"牛津英汉汉英词典";
NSString * const DictEn = @"New Oxford American Dictionary";
NSString * const DictJa = @"ウィズダム英和辞典 / ウィズダム和英辞典";
NSString * const DictKo = @"뉴에이스 영한사전 / 뉴에이스 한영사전";
int main(int argc, char * argv[])
{
@autoreleasepool {
if(argc < 2)
{
printf("Usage: %s [word]\n", argv[0]);
return -1;
}
NSString *dictname = DictEn;
int c;
while( (c = getopt(argc, argv, "zejk")) != -1) {
switch(c) {
case 'z':
dictname = DictZh;
break;
case 'e':
dictname = DictEn;
break;
case 'j':
dictname = DictJa;
break;
case 'k':
dictname = DictKo;
break;
case '?':
printf("Unknown flag: %c", optopt);
break;
}
}
CFTypeRef dictionary = NULL;
NSArray *dicts = DCSCopyAvailableDictionaries();
for (NSObject *aDict in dicts) {
NSString *aShortName = DCSDictionaryGetName((DCSDictionaryRef)aDict);
if ([aShortName isEqualToString:dictname])
dictionary = (DCSDictionaryRef)aDict;
}
NSString * word = [NSString stringWithCString: argv[2] encoding: NSUTF8StringEncoding];
NSArray *records = DCSCopyRecordsForSearchString(dictionary, (CFStringRef)word, 0, 0);
for (id record in records) {
printf("%s", [(NSString*)DCSRecordCopyData(record) UTF8String]);
}
}
return 0;
}实际上去得到的内容还包含了 CSS 样式， 下面是去掉样式后的样子。
<html>
<body>
<d:entry id="m_en_us1225918" d:title="benefactor" class="entry">
<span class="hg"><span d:dhw="1" role="text" syllabified="ben·e·fac·tor" class="hw">benefactor<span class="gp tg_hw"> </span></span><span class="pr"> |<span d:pr="US_IPA" soundFile="benefactor#_us_2" media="online" geo="us" class="ph">ˈbɛnəˌfæktər</span>| </span><span class="gp tg_hg"> </span></span><span class="sg"><span class="se1"><span class="gp tg_se1">▶</span><span role="text" class="posg"><span d:ps="1" class="pos"><span class="gp tg_pos">noun</span></span><span class="gp tg_posg"> </span></span><span d:abs="1" id="m_en_us1225918.001" class="msDict t_core"><span role="text" class="df">a person who gives money or other help to a person or cause<span class="gp tg_df">.</span></span></span></span><span class="gp tg_sg"> </span></span>
<span role="text" class="etym">
<span class="gp ty_label tg_etym">ORIGIN </span><span class="dg"><span class="date">late Middle English</span></span>: from <span class="la">Latin</span>
<html>
<body>
<d:entry id="m_en_us1225918" d:title="benefactor" class="entry"><span class="hg"><span d:dhw="1" role="text" syllabified="ben·e·fac·tor" class="hw">benefactor<span class="gp tg_hw"> </span></span><span class="pr"> |<span d:pr="US_IPA" soundFile="benefactor#_us_2" media="online" geo="us" class="ph">ˈbɛnəˌfæktər</span>| </span><span class="gp tg_hg"> </span></span><span class="sg"><span class="se1"><span class="gp tg_se1">▶</span><span role="text" class="posg"><span d:ps="1" class="pos"><span class="gp tg_pos">noun</span></span><span class="gp tg_posg"> </span></span><span d:abs="1" id="m_en_us1225918.001" class="msDict t_core"><span role="text" class="df">a person who gives money or other help to a person or cause<span class="gp tg_df">.</span></span></span></span><span class="gp tg_sg"> </span></span><span role="text" class="etym"><span class="gp ty_label tg_etym">ORIGIN </span><span class="dg"><span class="date">late Middle English</span></span>: from <span class="la">Latin</span>, from <span class="ff"> bene facere </span><span class="trans"><span class="gp tg_tr">‘</span>do good (to)<span class="gp tg_tr">’ </span></span><span class="xrg"> (see <span class="xr"><a href="x-dictionary:r:m_en_us1225916:com.apple.dictionary.NOAD">benefaction</a></span>) </span><span class="gp tg_etym">.</span></span></d:entry>
</body>
</html>
from <span class="ff"> bene facere </span><span class="trans"><span class="gp tg_tr">‘</span>do good (to)<span class="gp tg_tr">’ </span></span><span class="xrg"> (see <span class="xr"><a href="x-dictionary:r:m_en_us1225916:com.apple.dictionary.NOAD">benefaction</a></span>) </span><span class="gp tg_etym">.</span>
</span>
</d:entry>
</body>
</html>简易的用 BeautifulSoup 解析了下写了个类，封装了下单词诸如音标，解释，语源等信息。
#! /usr/bin/env python
import sys
from bs4 import BeautifulSoup
import subprocess
class Mdict:
def __init__(self, word):
self.word = word
p = subprocess.Popen(['bin/dicttool', '-e', word],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
out, err = p.communicate()
self._soup = BeautifulSoup(out, "lxml")
p_zh = subprocess.Popen(['bin/dicttool', '-z', word],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
out_zh, err_zh = p_zh.communicate()
self._soup_zh = BeautifulSoup(out_zh, "lxml")
@property
def IPAs(self):
return [item.text.strip() for item in self._soup.find("span", "hg").findAll("span", {"d:pr": "US_IPA"})]
@property
def etym(self):
res = self._soup.find("span", "etym")
return(res.text if res else None)
@property
def derivatives(self):
return [item.find("span", "l").text.strip() for item in self._soup.findAll("span", "subEntry")]
@property
def roots(self):
return [item.text.strip() for item in self._soup.findAll("span", "ff")]
@property
def origin(self):
return [item.text.strip() for item in self._soup.find("span", "etym").findAll("span", "la")]
@property
def definitions_zh(self):
return [item.find("span", "trans").text.strip() for item in self._soup_zh.findAll("span", "trg")]
def printword(w):
print(w.word, " ")
print("|{}|".format(','.join(w.IPAs)))
for i, k in enumerate(w.definitions_zh):
print(i+1, ".", k)
print("\n{}\n".format(w.etym))
if __name__ == '__main__':
word = sys.argv[1]
q = Mdict(word)
printword(q)在 IPython 实验一下效果如下
In [1]: from mdict import Mdict
In [2]: Mdict('benefactor')
Out[2]: <mdict.mod.Mdict instance at 0x10b86fab8>
In [3]: word = Mdict('benefactor')
In [4]: word.definitions_zh
Out[4]:
[u'\u8d5e\u52a9\u4eba',
u'\u4e0d\u77e5\u540d\u7684/\u533f\u540d\u7684\u6350\u52a9\u8005']
In [5]: word.etym
Out[5]: u'ORIGIN late Middle English: from Latin, from bene facere \u2018do good (to)\u2019 (see benefaction) .'
In [6]: word.IPAs
Out[6]: [u'\u02c8b\u025bn\u0259\u02ccf\xe6kt\u0259r']
In [7]: word.origin
Out[7]: [u'Latin']到此，大概能满足我用 Python 批量的取得单词中的某项内容的需求， 遂把经过写下来供以后有需要的人参考。 抛砖引玉，简易的代码在 Github ，如果有兴趣请点赞支持或者完善代码。