Metadata-Version: 2.1
Name: chinatime
Version: 1.0.4
Summary: Analysis China time in sentence
Home-page: https://github.com/playscforever/Time_NLP
Author: playSCforever
Author-email: playSCforever@gmail.com
License: MIT Licence
Keywords: time,nlp,china
Platform: any
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: regex (>=2017)
Requires-Dist: arrow (>=0.10)

## 简介
Time-NLP的python3版本   
python 版本https://github.com/sunfiyes/Time-NLPY  
Java 版本https://github.com/shinyke/Time-NLP
## 功能说明
用于句子中时间词的抽取和转换  
详情请见test.py

    res = tn.parse(target=u'过十分钟') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
    res = tn.parse(target=u'2013年二月二十八日下午四点三十分二十九秒', timeBase='2013-02-28 16:30:29') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
    res = tn.parse(target=u'我需要大概33天2分钟四秒', timeBase='2013-02-28 16:30:29') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
    res = tn.parse(target=u'今年儿童节晚上九点一刻') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
    res = tn.parse(target=u'2个小时以前') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
    res = tn.parse(target=u'晚上8点到上午10点之间') # target为待分析语句，timeBase为基准时间默认是当前时间
    print(res)
返回结果：

    {"timedelta": "0 days, 0:10:00", "type": "timedelta"}
    {"timestamp": "2013-02-28 16:30:29", "type": "timestamp"}
    {"type": "timedelta", "timedelta": {"year": 0, "month": 1, "day": 3, "hour": 0, "minute": 2, "second": 4}}
    {"timestamp": "2018-06-01 21:15:00", "type": "timestamp"}
    {"error": "no time pattern could be extracted."}
    {"type": "timespan", "timespan": ["2018-03-16 20:00:00", "2018-03-16 10:00:00"]}

## 使用方式 
demo：python3 Test.py


