pycallnumber 0.2.0
A Python library for parsing call numbers.
License: BSD
Keywords: python,callnumber,callnumbers,call number,call numbers

# pycallnumber

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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](#Installation)
* [What can you do with pycallnumber?](#what-can-you-do-with-pycallnumber)
* [Configurable settings](#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#### Warning: Outdated Python Versions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](https://docs.python-guide.org/en/latest/dev/virtualenvs/) using pip is recommended.

```sh
$ 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.:

```sh
git clone https://github.com/[your-github-user]/pycallnumber.git pycallnumber
```
or (SSH)
```sh
git clone git@github.com:[your-github-user]/pycallnumber.git pycallnumber
```

Then use pip to do an editable install of the package with the `dev` extras (which installs pytest).

```sh
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](http://doc.pytest.org/) to run tests in your current Python environment.
```sh
pytest
```

##### Tox

You can use [tox](https://tox.wiki/en/latest/) to run tests against multiple Python versions, provided you have them available on the `PATH`. An excellent tool for this is [pyenv](https://github.com/pyenv/pyenv) with [pyenv-virtualenv](https://github.com/pyenv/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.

```sh
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.
```

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## What can you do with pycallnumber?

#### Parse

You can parse call number strings, like Library of Congress call numbers ...

```pycon
>>> 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 ...

```pycon
>>> 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 ...

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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&mdash;even partial dates&mdash;if recognized, are parsed into a year, month, and day.

```pycon
>>> 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 ...

```pycon
>>> 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 ...

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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](https://docs.python.org/2/library/stdtypes.html#set).

E.g., given the following ranges:

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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&mdash;i.e., the set of things in one or the other but not both.

```pycon
>>> 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:

```python
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
```
```pycon
>>> 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:

```python
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}]
)
```
```pycon
>>> 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.
```

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## 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&mdash;`pycallnumber.callnumber`, `pycallnumber.cnrange`, `pycallnumber.cnset`&mdash;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:

```python
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.

1. **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.

2. **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.

1. 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.

    ```pycon
    >>> pycallnumber.units.Cutter.sort_case = 'upper'
    >>> pycallnumber.units.Cutter('c35').for_sort()
    u'C!35'
    ```

2. 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).

    ```pycon
    >>> pycallnumber.units.Cutter('c35', sort_case='upper').for_sort()
    u'C!35'
    ```

3. 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.

    ```pycon
    >>> myopts = {'sort_case': 'upper'}
    >>> mytypes = [pycallnumber.units.Cutter]
    >>> pycallnumber.callnumber('c35',
    ...                         unittypes=mytypes,
    ...                         useropts=myopts).for_sort()
    u'C!35'
    ```

4. 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.

    ```pycon
    >>> 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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