Data formatting and parsing

Self-formatting objects using PrettyObject

PrettyObject - A self-formatting object to be used with print()

Ever been looking for an easy way to print an object and see it’s internal state? Look no further!

from qtils import PrettyObject


class MyPrettyObject(PrettyObject):

    __pretty_fields__ = ['foo', 'bar']

    def __init__(self, foo):
        self.foo = foo

    @property
    def bar(self):
        return self.foo*2


obj = MyPrettyObject('hello')
print( obj )

You can customize the format of the class and the individual fields too:

from qtils import PrettyObject


class MyPrettyObject(PrettyObject):

    __pretty_fields__ = ['foo', 'bar']

    def __init__(self, foo):
        self.foo = foo

    @property
    def bar(self):
        return foo*2


obj1 = MyPrettyObject('hello')
print( obj1 )

Creating table-like formatting

Creating table-like formatting using tab \\t as field separator and fixed width fields.

>>> from qtils import PrettyObject, PRETTY_FORMAT

>>> class MathConstant(PrettyObject):
...     __pretty_format__ = PRETTY_FORMAT.MINIMAL
...     __pretty_field_separator__ = "    " # should be a tab but it fails in doctest
...     __pretty_fields__ = [
...         "name!r:<23",
...         "symbol!s:<5",
...         "value:>10.6f",
...     ]
...     def __init__(self, name, symbol, value):
...         self.name = name
...         self.symbol = symbol
...         self.value = value
...
>>> math_constants = [
...     MathConstant("Archimedes constant", "π", 3.1415926535),
...     MathConstant("Euler's number", "e", 2.7182818284),
...     MathConstant("Pythagoras constant", "√2", 1.414213562373095),
... ]
>>> for mc in math_constants:
...     print(mc)
<MathConstant name='Archimedes constant'      symbol=π        value=  3.141593>
<MathConstant name="Euler's number"           symbol=e        value=  2.718282>
<MathConstant name='Pythagoras constant'      symbol=√2       value=  1.414214>

tabs:

Formatting and parsing file sizes using DataSize

Integer object representing data size with two-way conversion ability.

It stores the data size in bytes as int. It can display the value in different units. By default it uses the most suitable unit automatically. This behaviour can be changed by calling the DataSize.format() directly, or by changing the default unit in the DEFAULT_UNIT class attribute.

This class supports different systems of units. It supports the BINARY system in which a magnitude is 2**10=1024 bytes, and the METRIC system in which a magnitude is 10**3=1000 bytes. By default it uses the METRIC system. Read more about the topic in the Units of information Wikipedia article.

Pretty printing data size values with automatic unit and precision detection:

>>> from qtils import DataSize

>>> print(DataSize(123000))
123 k
>>> print(DataSize(123456000))
123.5 M
>>> print(DataSize(23*10**8))
2.30 G
>>> print(DataSize(1000**8))
1.00 Y

Parsing data sizes from strings using the METRIC unit system (default behaviour):

>>> DataSize('256')
256
>>> DataSize('1.45 megabytes')
1450000
>>> DataSize('23.3G')
23300000000
>>> DataSize('1 T')
1000000000000
>>> DataSize('1,123,456.789 MB')
1123456789000

Parsing data sizes using the BINARY unit system:

>>> from qtils import DATA_UNIT_SYSTEM

>>> DataSize('1.45 mebibytes')
1520435
>>> DataSize('23.3gib')
25018184499
>>> DataSize('1 T', system=DATA_UNIT_SYSTEM.BINARY)
1099511627776
>>> DataSize('1,123,456.789 MB', system=0)
1178029825982

Comparison of the BINARY and the METRIC unit systems:

>>> binary_1k = DataSize("1 KiB")
>>> metric_1k = DataSize("1 kB")
>>> binary_1k
1024
>>> metric_1k
1000
>>> binary_1k.format(system=DATA_UNIT_SYSTEM.BINARY)
'1 K'
>>> metric_1k.format(system=DATA_UNIT_SYSTEM.BINARY)
'1000 b'

DataSize works as a regular int:

>>> size = DataSize('1 M') + DataSize('500k')
>>> size
1500000
>>> print(size)
1.5 M
>>> size * 2.5
3750000
>>> print(size * 2.5)
3.8 M
>>> size / 3
500000
>>> print(size - 500000)
1.0 M

Throws ValueError exception if data can not be parsed:

>>> DataSize('invalid size data')
Traceback (most recent call last):
...
ValueError: Invalid data size literal: 'invalid size data'

Working with “Not Available” values

A value to represent not available: NA

What happens if None is actually a meaningful value, but you need to model a situation when even None wasn’t supplied? I know what you think… why would anybody end up in a situation like that? I agree, but unfortunately not every API is under the control of sane people, so we just need to cope with it.

>>> from qtils import NA
>>>
>>> value = None
>>> value is NA
False
>>> value == True
False
>>> value == False
False
>>> value = NA
>>> value is None
False
>>> value == NA
True
>>> value is NA
True
>>> value == True
False
>>> value == False
False