edtf 4.0.1

python edtf

在python中edtf格式的一种实现，以及用于解析自然语言日期文本和将edtf日期转换为相关python对象的实用函数。

有关当前规范草案，请参见http://www.loc.gov/standards/datetime/" rel="nofollow">http://www.loc.gov/standards/datetime/。

安装

pip install edtf

使用

>>> from edtf import parse_edtf
# Parse an EDTF string to an EDTFObject
>>> e = parse_edtf("1979-08~") # approx August 1979
>>> e
UncertainOrApproximate: '1979-08~'
# normalised string representation (some different EDTF strings have identical meanings)
>>> unicode(e)
u'1979-08~'

# Derive Python date objects
# lower and upper bounds that strictly adhere to the given range
>>> e.lower_strict()[:3], e.upper_strict()[:3]
((1979, 8, 1), (1979, 8, 31))
# lower and upper bounds that are padded if there's indicated uncertainty
>>> e.lower_fuzzy()[:3], e.upper_fuzzy()[:3]
((1979, 7, 1), (1979, 9, 30))

# Date intervals
>>> interval = parse_edtf("1979-08~/open")
>>> interval
Level1Interval: '1979-08~/open'
# Intervals have lower and upper EDTF objects.
>>> interval.lower, interval.upper
(UncertainOrApproximate: '1979-08~', UncertainOrApproximate: 'open')
>>> interval.lower.upper_strict()[:3]
(1979, 8, 31)
>>> interval.upper.lower_strict() # 'open' is interpreted to mean 'still happening'.
[Today's date]

# Date collections
>>> coll = parse_edtf('{1667,1668, 1670..1672}')
>>> coll
MultipleDates: '{1667, 1668, 1670..1672}'
>>> coll.objects
(Date: '1667', Date: '1668', Consecutives: '1670..1672')

parse_edtf（）返回的对象是一个edtf.parser.parser_classes.edtf object子类的实例，具体取决于分析的日期类型。这些类是：

# Level 0
Date
DateAndTime
Interval

# Level 1
UncertainOrApproximate
Unspecified
Level1Interval
LongYear
Season

# Level 2
PartialUncertainOrApproximate
PartialUnspecified
OneOfASet
MultipleDates
MaskedPrecision
Level2Interval
ExponentialYear

所有这些都实现了upper/lower_strict/fuzzy（）方法来派生pythondate对象。

*interval实例具有upper和lower属性，这些属性本身就是edtfobject实例。

oneofset和multipledates实例有一个对象属性，该属性是集合或列表中分析的所有EDTF日期的列表。

EDTF规范包含

该库包括edtf规范的0、1和2级的实现。

测试覆盖范围包括功能规格表中给出的每个示例。

0级ISO 8601功能

• 日期：

  >>> parse_edtf('1979-08') # August 1979
  Date: '1979-08'
  

• 日期和时间：

  >>> parse_edtf('2004-01-01T10:10:10+05:00')
  DateAndTime: '2004-01-01T10:10:10+05:00'
  

• 间隔（开始/结束）：

  >>> parse_edtf('1979-08-28/1979-09-25') # From August 28 to September 25 1979
  Interval: '1979-08-28/1979-09-25'
  

一级扩展

• 不确定/大概日期：

  >>> parse_edtf('1979-08-28~') # Approximately August 28th 1979
  UncertainOrApproximate: '1979-08-28~'
  

• 未指定日期：

  >>> parse_edtf('1979-08-uu') # An unknown day in August 1979
  Unspecified: '1979-08-uu'
  >>> parse_edtf('1979-uu') # Some month in 1979
  Unspecified: '1979-uu'
  

• 延长间隔：

  >>> parse_edtf('1984-06-02?/2004-08-08~')
  Level1Interval: '1984-06-02?/2004-08-08~'
  

• 超过四位数的年份：

  pip install edtf
  

  0

• 季节：

  pip install edtf
  

  1

2级扩展

• 部分不确定/近似：

  pip install edtf
  

  2

• 部分未指定：

  pip install edtf
  

  3

• 一组：

  pip install edtf
  

  4

• 多个日期：

  pip install edtf
  

  5

• 掩蔽精度：

  pip install edtf
  

  6

• 2级延长间隔：

  pip install edtf
  

  7

• 需要超过4位数的年份-指数形式：

  pip install edtf
  

  8

自然语言表示法

该库包括一个基本的英语自然语言解析器（它还不够智能，无法处理诸如"复活节"或其他语言的场合）：

pip install edtf

注意，结果是一个字符串，而不是一个etdfobject

解析器可以解析如下字符串：

>>> from edtf import parse_edtf
# Parse an EDTF string to an EDTFObject
>>> e = parse_edtf("1979-08~") # approx August 1979
>>> e
UncertainOrApproximate: '1979-08~'
# normalised string representation (some different EDTF strings have identical meanings)
>>> unicode(e)
u'1979-08~'

# Derive Python date objects
# lower and upper bounds that strictly adhere to the given range
>>> e.lower_strict()[:3], e.upper_strict()[:3]
((1979, 8, 1), (1979, 8, 31))
# lower and upper bounds that are padded if there's indicated uncertainty
>>> e.lower_fuzzy()[:3], e.upper_fuzzy()[:3]
((1979, 7, 1), (1979, 9, 30))

# Date intervals
>>> interval = parse_edtf("1979-08~/open")
>>> interval
Level1Interval: '1979-08~/open'
# Intervals have lower and upper EDTF objects.
>>> interval.lower, interval.upper
(UncertainOrApproximate: '1979-08~', UncertainOrApproximate: 'open')
>>> interval.lower.upper_strict()[:3]
(1979, 8, 31)
>>> interval.upper.lower_strict() # 'open' is interpreted to mean 'still happening'.
[Today's date]

# Date collections
>>> coll = parse_edtf('{1667,1668, 1670..1672}')
>>> coll
MultipleDates: '{1667, 1668, 1670..1672}'
>>> coll.objects
(Date: '1667', Date: '1668', Consecutives: '1670..1672')

从edtf表示生成自然文本是未来的目标。

当解释一个不明确的日期时，自然文本解析器做了什么假设？

• "1800年代"模糊地说是一个世纪或十年。如果给定日期不确定或近似，则使用十年解释。如果日期确定且准确，则使用世纪解释。

• 如果未指定世纪（edtf（natural_text="The'70s"），则如果年份大于当前年份，则表示世纪为"19"，否则表示世纪为当前世纪。

• 默认情况下，使用自然语言假定美国订购日期（mm/dd/yyyy）。若要更改此设置，请在"设置"中将"天"设置为"真"。

• 如果一个自然语言组的日期是一个"/"，它被解释为"或"而不是"和"。生成的edtf文本是一个由[]（"其中一个日期"）括起的列表，而不是{}（所有这些日期）。

转换到python日期和从python日期转换到python日期

由于edtf日期通常是区域性的，而且常常不精确，因此我们需要根据具体情况使用一些不同的python日期。通常，python日期用于排序和筛选，不直接显示给用户。

结构时间日期表示法

因为python的datetime模块不支持超出1ad到9999ad范围的日期，所以我们返回日期a默认情况下是stime.struct\u time对象，而不是您可能期望的datetime.date或datetime.datetime对象。

struct_time表示更难使用，但可以按主要用例进行排序，并且可以相对容易地转换为date或date time对象（前提是年份在公元1到9999年内）或更灵活的库中的最新对象，例如astropy.time对于外部年份这些界限。

如果确定使用的日期在python的date time模块支持的范围内，则可以使用edtf.struct\u time to\u date和edtf.struct\u time to\u datetime函数获得这些更方便的对象。

注意：在切换到struct-time之前，默认情况下，此库确实从方法返回了date和datetime对象。见票据https://github.com/ixc/python edtf/issues/26

低严格和高严格

这些日期表示日期范围内严格的最早和最晚日期，忽略不确定性或近似性。思考这个问题的一种方法是"如果你必须选择一个单独的日期来排序，那会是什么？"

在升序排序（最近的最后一次）中，按lower_strict排序以获得自然排序顺序。在降序排序（最新排序）中，按upper_strict排序：

>>> from edtf import parse_edtf
# Parse an EDTF string to an EDTFObject
>>> e = parse_edtf("1979-08~") # approx August 1979
>>> e
UncertainOrApproximate: '1979-08~'
# normalised string representation (some different EDTF strings have identical meanings)
>>> unicode(e)
u'1979-08~'

# Derive Python date objects
# lower and upper bounds that strictly adhere to the given range
>>> e.lower_strict()[:3], e.upper_strict()[:3]
((1979, 8, 1), (1979, 8, 31))
# lower and upper bounds that are padded if there's indicated uncertainty
>>> e.lower_fuzzy()[:3], e.upper_fuzzy()[:3]
((1979, 7, 1), (1979, 9, 30))

# Date intervals
>>> interval = parse_edtf("1979-08~/open")
>>> interval
Level1Interval: '1979-08~/open'
# Intervals have lower and upper EDTF objects.
>>> interval.lower, interval.upper
(UncertainOrApproximate: '1979-08~', UncertainOrApproximate: 'open')
>>> interval.lower.upper_strict()[:3]
(1979, 8, 31)
>>> interval.upper.lower_strict() # 'open' is interpreted to mean 'still happening'.
[Today's date]

# Date collections
>>> coll = parse_edtf('{1667,1668, 1670..1672}')
>>> coll
MultipleDates: '{1667, 1668, 1670..1672}'
>>> coll.objects
(Date: '1667', Date: '1668', Consecutives: '1670..1672')

>>> from edtf import parse_edtf
# Parse an EDTF string to an EDTFObject
>>> e = parse_edtf("1979-08~") # approx August 1979
>>> e
UncertainOrApproximate: '1979-08~'
# normalised string representation (some different EDTF strings have identical meanings)
>>> unicode(e)
u'1979-08~'

# Derive Python date objects
# lower and upper bounds that strictly adhere to the given range
>>> e.lower_strict()[:3], e.upper_strict()[:3]
((1979, 8, 1), (1979, 8, 31))
# lower and upper bounds that are padded if there's indicated uncertainty
>>> e.lower_fuzzy()[:3], e.upper_fuzzy()[:3]
((1979, 7, 1), (1979, 9, 30))

# Date intervals
>>> interval = parse_edtf("1979-08~/open")
>>> interval
Level1Interval: '1979-08~/open'
# Intervals have lower and upper EDTF objects.
>>> interval.lower, interval.upper
(UncertainOrApproximate: '1979-08~', UncertainOrApproximate: 'open')
>>> interval.lower.upper_strict()[:3]
(1979, 8, 31)
>>> interval.upper.lower_strict() # 'open' is interpreted to mean 'still happening'.
[Today's date]

# Date collections
>>> coll = parse_edtf('{1667,1668, 1670..1672}')
>>> coll
MultipleDates: '{1667, 1668, 1670..1672}'
>>> coll.objects
(Date: '1667', Date: '1668', Consecutives: '1670..1672')

>>> from edtf import parse_edtf
# Parse an EDTF string to an EDTFObject
>>> e = parse_edtf("1979-08~") # approx August 1979
>>> e
UncertainOrApproximate: '1979-08~'
# normalised string representation (some different EDTF strings have identical meanings)
>>> unicode(e)
u'1979-08~'

# Derive Python date objects
# lower and upper bounds that strictly adhere to the given range
>>> e.lower_strict()[:3], e.upper_strict()[:3]
((1979, 8, 1), (1979, 8, 31))
# lower and upper bounds that are padded if there's indicated uncertainty
>>> e.lower_fuzzy()[:3], e.upper_fuzzy()[:3]
((1979, 7, 1), (1979, 9, 30))

# Date intervals
>>> interval = parse_edtf("1979-08~/open")
>>> interval
Level1Interval: '1979-08~/open'
# Intervals have lower and upper EDTF objects.
>>> interval.lower, interval.upper
(UncertainOrApproximate: '1979-08~', UncertainOrApproximate: 'open')
>>> interval.lower.upper_strict()[:3]
(1979, 8, 31)
>>> interval.upper.lower_strict() # 'open' is interpreted to mean 'still happening'.
[Today's date]

# Date collections
>>> coll = parse_edtf('{1667,1668, 1670..1672}')
>>> coll
MultipleDates: '{1667, 1668, 1670..1672}'
>>> coll.objects
(Date: '1667', Date: '1668', Consecutives: '1670..1672')