pycallnumber 0.2.0

Description:

pycallnumber 0.2.0

pycallnumber

Use pycallnumber in your library's Python projects to parse, model, and manipulate any type of call number string. Support for Library of Congress, Dewey Decimal, SuDocs, and local call numbers is built in, and you can extend built-in classes to customize behavior or model other types of call numbers and formatted strings.

Installation
What can you do with pycallnumber?
Configurable settings

Installation
Requirements
Tests pass on Linux and MacOS Python 2.7, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. Versions 3.4 and below may still work, but I'm unable to get these to compile any more so cannot test them.
Warning: Outdated Python Versions
Warning — The next release, v1.0.0, will drop support for Python versions older than 3.7.
Dependencies
If you're using Python >=3.8, there are no external dependencies beyond the standard library.
For Python 2.7 to 3.7, the importlib_metadata backport is used for importlib.metadata functionality (first available in Python 3.8).
For Python 2.7, the future module is used to replicate various Python 3 behaviors.
Setup
Installing to a virtualenv using pip is recommended.
$ python -m pip install pycallnumber

Development setup and testing
If you want to contribute to pycallnumber, you should fork the project and then download and install your fork from GitHub. E.g.:
git clone https://github.com/[your-github-user]/pycallnumber.git pycallnumber

or (SSH)
git clone [email protected]:[your-github-user]/pycallnumber.git pycallnumber

Then use pip to do an editable install of the package with the dev extras (which installs pytest).
cd pycallnumber
python -m pip install -e .[dev]

Running tests
(The below commands assume you've installed from GitHub as described above and are in the repository root.)
Invoke pytest to run tests in your current Python environment.
pytest

Tox
You can use tox to run tests against multiple Python versions, provided you have them available on the PATH. An excellent tool for this is pyenv with pyenv-virtualenv.
The tox configuration is in pyproject.toml (see the [tool.tox] section), which defines several test environments. You can run them all at once or target specific environments.
tox # run tests against all configured environments
tox -e py27-oldest # run tests against python 2.7 with oldest deps
tox -e py310-latest # run tests against python 3.10 with latest deps
tox -e flake8 # run flake8 linting
# etc.

Top
What can you do with pycallnumber?
Parse
You can parse call number strings, like Library of Congress call numbers ...
>>> import pycallnumber as pycn
>>> cn = pycn.callnumber('MT 1001 .C35 B40 1992 no. 1')
>>> cn
<LC 'MT 1001 .C35 B40 1992 no. 1'>
>>> cn.classification
<LcClass 'MT 1001'>
>>> cn.classification.letters
<LcClass.ClassLetters 'MT'>
>>> cn.classification.number
<LcClass.ClassNumber '1001'>
>>> cn.cutters[0]
<Cutter 'C35'>
>>> cn.cutters[1]
<Cutter 'B40'>
>>> cn.edition
<Edition '1992'>
>>> cn.item
<Item 'no. 1'>

... Dewey Decimal call numbers ...
>>> cn = pycn.callnumber('500.1 C226t bk.2')
>>> cn
<Dewey '500.1 C226t bk.2'>
>>> cn.classification
<DeweyClass '500.1'>
>>> cn.cutters[0]
<DeweyCutter 'C226t'>
>>> cn.cutters[0].workmark
<Alphabetic 't'>
>>> cn.item
<Item 'bk.2'>

... US SuDocs numbers ...
>>> cn = pycn.callnumber('HI.F 3/178-8:A 44/2013 ardocs')
>>> cn
<SuDoc 'HI.F 3/178-8:A 44/2013 ardocs'>
>>> cn.stem
<AgencyDotSeries 'HI.F 3/178-8'>
>>> cn.stem.agency
<Agency 'HI'>
>>> cn.stem.series
<Series 'F 3/178-8'>
>>> cn.stem.series.main_series
<Cutter 'F 3'>
>>> cn.stem.series.related_series
<Series.RelatedSeries '178-8'>
>>> cn.book_number
<BookNumber 'A 44/2013 ardocs'>
>>> cn.book_number.parts[0]
<BookNumber.Component 'A 44'>
>>> cn.book_number.parts[1]
<BookNumber.Component '2013 ardocs'>

... and other (i.e. local) call numbers that don't follow the above prescribed patterns.
>>> cn = pycn.callnumber('LPCD 100,025-A')
>>> cn
<Local 'LPCD 100,025-A'>
>>> cn.parts[0]
<Alphabetic 'LPCD'>
>>> cn.parts[1]
<Number '100,025'>
>>> cn.parts[2]
<Formatting '-'>
>>> cn.parts[3]
<Alphabetic 'A'>

When parsing, pycallnumber is as permissive as possible, allowing for differences in spacing, formatting, and case. As such, it's intended to be suitable for use in a real-world environment, requiring no pre-normalization of call number strings.
>>> pycn.callnumber('mt 1001 c35 1992 no. 1')
<LC 'mt 1001 c35 1992 no. 1'>
>>> pycn.callnumber('mt 1001 c35 1992 no. 1').classification
<LcClass 'mt 1001'>
>>> pycn.callnumber('Mt1001 c35 1992 no. 1').classification
<LcClass 'Mt1001'>
>>> pycn.callnumber('Mt 1001 c35 1992 no. 1').classification
<LcClass 'Mt 1001'>
>>> pycn.callnumber('Mt 1001 c35 1992 no. 1').classification.letters
<LcClass.ClassLetters 'Mt'>
>>> pycn.callnumber('Mt 1001 c35 1992 no. 1').classification.number
<LcClass.ClassNumber '1001'>
>>> pycn.callnumber('mt 1001c35 1992 no. 1').cutters[0]
<Cutter 'c35'>
>>> pycn.callnumber('mt 1001.c35 1992 no. 1').cutters[0]
<Cutter 'c35'>
>>> pycn.callnumber('mt 1001 c35 1992 no. 1').cutters[0]
<Cutter 'c35'>
>>> pycn.callnumber('mt 1001 .c35 1992 no. 1').cutters[0]
<Cutter 'c35'>
>>> pycn.callnumber('mt 1001 .c 35 1992 no. 1').cutters[0]
<Cutter 'c 35'>
>>> pycn.callnumber('mt 1001 C 35 1992 no. 1').cutters[0]
<Cutter 'C 35'>

Finally, pycallnumber attempts to interpret and parse structured bits that you might find within less structured parts of call numbers, like item-specific information (volume and copy numbers, issue dates, etc.). Numbers may or may not include a thousands separator. Dates—even partial dates—if recognized, are parsed into a year, month, and day.
>>> pycn.callnumber('LPCD 100,001') == pycn.callnumber('LPCD 100001')
True
>>> cn = pycn.callnumber('MT 1001 .C35 January 2012')
>>> cn.item
<Item 'January 2012'>
>>> cn.item.parts[0]
<DateString 'January 2012'>
>>> cn.item.parts[0].year
<Year '2012'>
>>> cn.item.parts[0].month
<Month 'January'>
>>> cn.item.parts[0].day
>>> cn = pycn.callnumber('MT 1001 .C35 01-31-2012')
>>> cn.item.parts[0].year
<Year '2012'>
>>> cn.item.parts[0].month
<Month '01'>
>>> cn.item.parts[0].day
<Day '31'>
>>>

Normalize
Any call number can be normalized for sorting ...
>>> import pycallnumber as pycn
>>> lc_cn = pycn.callnumber('MT 1001 .C35 B40 1992 no. 1')
>>> dewey_cn = pycn.callnumber('500.1 c226t bk.2')
>>> sudocs_cn = pycn.callnumber('HI.F 3/178-8:A 44/2013 ardocs')
>>> local_cn = pycn.callnumber('LPCD 100,025-A')
>>> lc_cn.for_sort()
u'mt!1001!c!35!b!40!0000001992!!0000000001'
>>> dewey_cn.for_sort()
u'500.1!c!226!t!!0000000002'
>>> sudocs_cn.for_sort()
u'hi.f!3/0000000178-0000000008!!a!0000000044/0000002013!!ardocs'
>>> local_cn.for_sort()
u'lpcd!0000100025!a'

... for left-anchored searching ...
>>> lc_cn.for_search()
u'mt1001c35b4019921'
>>> dewey_cn.for_search()
u'500.1c226t2'
>>> sudocs_cn.for_search()
u'hif31788a442013ardocs'
>>> local_cn.for_search()
u'lpcd100025a'

... and for display.
>>> lc_cn.for_print()
u'MT 1001 .C35 B40 1992 no. 1'
>>> dewey_cn.for_print()
u'500.1 c226t bk.2'
>>> sudocs_cn.for_print()
u'HI.F 3/178-8:A 44/2013 ardocs'
>>> local_cn.for_print()
u'LPCD 100,025-A'

Operate
You can compare call numbers using comparison operators, and the typical methods for sorting work as you'd expect. Comparison operators use the normalized for_sort version of the call number as the basis for comparison, so call numbers expressed with differences in spacing or formatting won't throw off comparisons and sorting, as long as the call numbers are recognizable and are parsed correctly.
>>> import pycallnumber as pycn
>>> pycn.callnumber('Mt1001 c35 1992 no. 1') == pycn.callnumber('MT 1001 .C35 1992 #1')
True
>>> cnstrings = ['MT 1001 .C35 B40 1992 no. 1',
... 'MT 1001 .C35 B40 1992 no. 2',
... 'MT 1001 .C35 B40 1990',
... 'M 120 .A20 2002 c.2',
... 'MT 100 .S23 1985',
... 'M 120 .A20 2002 copy 1',
... 'MT 1001 .C35 B100 2013',
... 'MT 1001 .C35 B40 1991',
... 'MT 1001 .C35 B40 1992 no. 2 copy 2']
>>> lccns = [pycn.callnumber(cn) for cn in cnstrings]
>>> lccns[1] > lccns[2]
True
>>> lccns[1] < lccns[2]
False
>>> for cn in sorted(lccns): print cn
...
M 120 .A20 2002 copy 1
M 120 .A20 2002 c.2
MT 100 .S23 1985
MT 1001 .C35 B100 2013
MT 1001 .C35 B40 1990
MT 1001 .C35 B40 1991
MT 1001 .C35 B40 1992 no. 1
MT 1001 .C35 B40 1992 no. 2
MT 1001 .C35 B40 1992 no. 2 copy 2

You can also work with sets of call numbers using the same operators you'd use for built-in Python sets.
E.g., given the following ranges:
>>> MT0_MT500 = pycn.cnrange('MT 0', 'MT 500')
>>> MT500_MT1000 = pycn.cnrange('MT 500', 'MT 1000')
>>> MT300_MT800 = pycn.cnrange('MT 300', 'MT 800')
>>> MT0_N0 = pycn.cnrange('MT 0', 'N 0')
>>> MT2000_N0 = pycn.cnrange('MT 2000', 'N 0')
>>> for rg in (MT0_MT500, MT500_MT1000, MT300_MT800, MT0_N0, MT2000_N0): print rg
...
<LcClass RangeSet 'MT 0' to 'MT 500'>
<LcClass RangeSet 'MT 500' to 'MT 1000'>
<LcClass RangeSet 'MT 300' to 'MT 800'>
<LcClass RangeSet 'MT 0' to 'N 0'>
<LcClass RangeSet 'MT 2000' to 'N 0'>

You can test whether a call number is in a particular range or set.
>>> pycn.callnumber('MT 500 .A0 1900').classification in MT0_MT500
False
>>> pycn.callnumber('MT 500 .A0 1900').classification in MT500_MT1000
True
>>> pycn.callnumber('MS 9999.9999 .Z99 9999').classification in MT0_MT500
False

Test how sets relate to one another.
>>> MT0_MT500 in MT500_MT1000
False
>>> MT0_MT500.issubset(MT500_MT1000)
False
>>> MT0_MT500 > MT500_MT1000
False
>>> MT0_MT500 < MT500_MT1000
False
>>> MT0_MT500.issuperset(MT500_MT1000)
False
>>> MT0_MT500.overlaps(MT500_MT1000)
False
>>> MT0_MT500.isdisjoint(MT500_MT1000)
True
>>> MT0_MT500.issequential(MT500_MT1000)
True
>>> MT0_MT500.isbefore(MT500_MT1000)
True
>>> MT0_MT500.extendslower(MT500_MT1000)
True
>>> MT0_MT500.overlaps(MT300_MT800)
True
>>> MT0_MT500.isdisjoint(MT300_MT800)
False
>>> MT0_MT500.isbefore(MT300_MT800)
False
>>> MT0_MT500.isafter(MT300_MT800)
False
>>> MT300_MT800.extendshigher(MT0_MT500)
True
>>> MT0_MT500.extendslower(MT300_MT800)
True
>>> MT0_MT500 in MT300_MT800
False
>>> MT300_MT800 in MT0_MT500
False
>>> MT0_MT500 in MT0_N0
True
>>> MT0_MT500.issubset(MT0_N0)
True
>>> MT0_MT500 < MT0_N0
True

Join two or more sets.
>>> MT0_MT500 | MT300_MT800
<LcClass RangeSet 'MT 0' to 'MT 800'>
>>> MT0_MT500 | MT2000_N0
<LcClass RangeSet 'MT 0' to 'MT 500', 'MT 2000' to 'N 0'>
>>> MT0_MT500 | MT2000_N0 | MT500_MT1000
<LcClass RangeSet 'MT 0' to 'MT 1000', 'MT 2000' to 'N 0'>
>>> MT0_MT500.union(MT500_MT1000, MT2000_N0, MT0_N0)
<LcClass RangeSet 'MT 0' to 'N 0'>

Intersect two or more sets.
>>> MT0_MT500 & MT300_MT800
<LcClass RangeSet 'MT 300' to 'MT 500'>
>>> MT0_MT500 & MT500_MT1000
<RangeSet >
>>> MT300_MT800 & MT500_MT1000 & MT0_N0
<LcClass RangeSet 'MT 500' to 'MT 800'>
>>> MT300_MT800.intersection(MT500_MT1000, MT0_N0)
<LcClass RangeSet 'MT 500' to 'MT 800'>

Get the difference of two or more sets.
>>> MT0_N0 - MT0_MT500
<LcClass RangeSet 'MT 500' to 'N 0'>
>>> MT0_N0 - MT2000_N0
<LcClass RangeSet 'MT 0' to 'MT 2000'>
>>> MT0_N0 - MT2000_N0 - MT300_MT800
<LcClass RangeSet 'MT 0' to 'MT 300', 'MT 800' to 'MT 2000'>
>>> MT0_N0.difference(MT2000_N0, MT300_MT800)
<LcClass RangeSet 'MT 0' to 'MT 300', 'MT 800' to 'MT 2000'>

Get the symmetric difference of two sets—i.e., the set of things in one or the other but not both.
>>> MT300_MT800 ^ MT0_N0
<LcClass RangeSet 'MT 0' to 'MT 300', 'MT 800' to 'N 0'>
>>> MT0_MT500 ^ MT2000_N0
<LcClass RangeSet 'MT 0' to 'MT 500', 'MT 2000' to 'N 0'>

Extend
You can subclass any of the call number Unit classes in your own projects if you need to customize their behavior.
For example, if you want your LC call numbers to be normalized a particular way for display, you can override the for_print method:
import pycallnumber as pycn

class MyLC(pycn.units.LC):
def for_print(self):
lcclass = '{}{}'.format(str(self.classification.letters).upper(),
self.classification.number)
cutters = ['{}{}'.format(str(c.letters.upper()), c.number)
for c in self.cutters]
output = '{} .{}'.format(lcclass, ' '.join(cutters))
if self.edition is not None:
output = '{} {}'.format(output, self.edition)
if self.item is not None:
output = '{} {}'.format(output, self.item)
return output

>>> MyLC('MT 100 .C35 1992').for_print()
'MT100 .C35 1992'
>>> MyLC('MT 100 c35 1992').for_print()
'MT100 .C35 1992'
>>> MyLC('mt 100 c35 1992 v. 1').for_print()
'MT100 .C35 1992 v. 1'
>>> MyLC('mt 100 c35 e20 1992 v. 1').for_print()
'MT100 .C35 E20 1992 v. 1'

Unit classes also have a derive class factory method that makes deriving new unit types simpler and less verbose. This is useful if you need to represent call numbers and other formatted strings not included in the package. For example, you could create a unit type for US dollars:
import pycallnumber as pycn

DollarSign = pycn.units.Formatting.derive(
classname='DollarSign', base_pattern=r'\$', min_length=1, max_length=1
)
DollarAmount = pycn.units.Number.derive(
classname='DollarAmount', min_decimal_places=0, max_decimal_places=2
)
UsDollars = pycn.units.NumericSymbol.derive(
classname='UsDollars', separator_type=None,
groups=[{'name': 'dollarsign', 'min': 1, 'max': 1, 'type': DollarSign},
{'name': 'amount', 'min': 1, 'max': 1, 'type': DollarAmount}]
)

>>> UsDollars('$23')
<UsDollars '$23'>
>>> UsDollars('$23.00')
<UsDollars '$23.00'>
>>> UsDollars('$23.03')
<UsDollars '$23.03'>
>>> UsDollars('$23.030')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pycallnumber/unit.py", line 143, in __init__
super(CompoundUnit, self).__init__(cnstr, name, **options)
File "pycallnumber/unit.py", line 28, in __init__
self._validate_result = type(self).validate(cnstr, self.options)
File "pycallnumber/unit.py", line 74, in validate
raise InvalidCallNumberStringError(msg)
pycallnumber.exceptions.InvalidCallNumberStringError: '$23.030' is not a valid UsDollars Unit. It should be a string with 1 ``dollarsign`` grouping and 1 ``amount`` grouping.

**** Here is what was found while attempting to parse '$23.030' ****

'$' matched the dollarsign grouping.
'23.03' matched the ``amount`` grouping.
'0' does not match any grouping.
>>>
>>> UsDollars('23.00')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pycallnumber/unit.py", line 143, in __init__
super(CompoundUnit, self).__init__(cnstr, name, **options)
File "pycallnumber/unit.py", line 28, in __init__
self._validate_result = type(self).validate(cnstr, self.options)
File "pycallnumber/unit.py", line 74, in validate
raise InvalidCallNumberStringError(msg)
pycallnumber.exceptions.InvalidCallNumberStringError: '23.00' is not a valid UsDollars Unit. It should be a string with 1 ``dollarsign`` grouping and 1 ``amount`` grouping.

**** Here is what was found while attempting to parse '23.00' ****

'23.00' does not match any grouping.

Top
Configurable settings
Pycallnumber uses a package-wide settings.py file to store various default configuration settings. With one exception, the defaults should suffice for most uses. But, since you can override certain settings, and the options aren't immediately obvious, I've documented them here.
Overriding the list of Unit types that the factory functions detect
By far the most common thing that you will want to override is the list of default Unit types that the factory functions—pycallnumber.callnumber, pycallnumber.cnrange, pycallnumber.cnset—detect automatically. (The default list is in pycallnumber.settings.DEFAULT_UNIT_TYPES.)
You can override the default list on a call-by-call basis. To do so, pass a list of the Unit classes you want to detect to one of the factory functions via the unittypes kwarg. Example:
import pycallnumber

class MyDewey(pycallnumber.units.Dewey):
# Defines local Dewey Unit type
# ...

my_unit_types = [
MyDewey,
pycallnumber.units.LC,
pycallnumber.units.SuDoc,
pycallnumber.units.Local
]
call = pycallnumber.callnumber(
'M 801.951 L544p',
unittypes=my_unit_types)
# ... rest of the script

Two important things to note.


Unit type order matters. A string may match multiple Unit types, and the factory functions will use whatever type matches first. Make sure you have them listed in order of precedence. For instance, the Local type will match just about anything and serves as a catch-all, so it's listed last. Since you can vary the list on a call-by-call basis, you could tailor that list dynamically to help increase chances of matching a particular call number to the correct type.


Your unittypes list should be a list of classes, not a list of class path strings. The settings.DEFAULT_UNIT_TYPES is a list of class path strings, but this was done to get around having circular imports in the settings module.


Overriding certain Unit options
Each Unit type has a list of options that you can pass via kwargs when you instantiate it. Children classes inherit options from their parents. Default values for each class are set via an options_defaults class attribute, and the default defaults are in settings.py. These values should work for 99% of uses, but you can override them if you need to.
Alphabetic case options
units.simple.Alphabetic, all Unit types derived from that type, and all CompoundUnit types that include a Unit derived from that type allow you to control how alphabetic case is normalized.
Value 'lower' normalizes alphabetic characters to lowercase; 'upper' normalizes to uppercase. Anything else keeps the original case.


display_case controls what case the for_print Unit method outputs. Default is a blank string, to keep the original case (settings.DEFAULT_DISPLAY_CASE).


search_case controls what case the for_search Unit method outputs. Default is 'lower' (settings.DEFAULT_SEARCH_CASE).


sort_case controls what case the for_sort Unit method outputs. Default is 'lower' (settings.DEFAULT_SORT_CASE).


Formatting 'use in' options
units.simple.Formatting, all Unit types derived from that type, and all CompoundUnit types that include a Unit derived from that type allow you to control whether or not formatting appears in normalized forms of that Unit.
Value True means the formatting characters are included in the normalized string; False means they are not.

use_formatting_in_search controls whether the for_search Unit method output includes formatting characters. Default is False (settings.DEFAULT_USE_FORMATTING_IN_SEARCH).
use_formatting_in_sort controls whether the for_sort Unit method output includes formatting characters. Default is False (settings.DEFAULT_USE_FORMATTING_IN_SORT).

How to override Unit options
There are four ways to override Unit options, listed here in order of precedence.


Setting the relevant class attribute for a Unit type will force that type to use that particular value for that option, always. This overrides absolutely everything else.
>>> pycallnumber.units.Cutter.sort_case = 'upper'
>>> pycallnumber.units.Cutter('c35').for_sort()
u'C!35'



Set the option for an individual object by passing the option via a kwarg when you initialize the object. This will override any options defaults (see 4) but not forced class attributes (see 1).
>>> pycallnumber.units.Cutter('c35', sort_case='upper').for_sort()
u'C!35'



If you're using one of the factory functions, you can pass options in using a dict via the useropts kwarg. The options get passed to the correct Unit object when it's initialized. This is equivalent to 2.
>>> myopts = {'sort_case': 'upper'}
>>> mytypes = [pycallnumber.units.Cutter]
>>> pycallnumber.callnumber('c35',
... unittypes=mytypes,
... useropts=myopts).for_sort()
u'C!35'



You can set or change the default value for an option on a particular class by setting the relevant option in the options_defaults class attribute (a dict). This changes the default for that Unit type, which is what's used if nothing else overrides it. Caveat: be careful that you create a copy of the options_defaults dict before making changes to it. Otherwise you will end up changing defaults for other Unit types.
>>> pycallnumber.units.Cutter.options_defaults =\
... pycallnumber.units.Cutter.options_defaults.copy()
>>> pycallnumber.units.Cutter.options_defaults['sort_case'] = 'upper'
>>> pycallnumber.units.Cutter('c35').for_sort()
u'C!35'
>>> pycallnumber.units.Cutter('C35', sort_case='lower').for_sort()
u'c!35'



Default settings you cannot override
Currently there is one default value that you cannot override directly. That is settings.DEFAULT_MAX_NUMERIC_ZFILL, which is 10. This means any units.simple.Numeric (or derived) class with no max_length set will, by default, fill zeros to 10 digits. If you create a new Numeric class with a valid max_length, then the zero-padding (max_numeric_zfill) will be adjusted for you automatically based on the max length.
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