prettyformatter 1.7.4

Pretty formatter enables pretty formatting using hanging indents, dataclasses, ellipses, and simple customizability by registering formatters.

prettyformatter

Pretty formatter enables pretty formatting using aligned and hanging indents for JSON, dataclasses, named tuples, and any custom formatted object such as Numpy arrays.

For the full documentation, see here.

Installation

Windows:

py -m pip install prettyformatter

Unix/MacOS:

python3 -m pip install prettyformatter

Imports

from prettyformatter import PrettyClass, PrettyDataclass
from prettyformatter import pprint, pformat, register

JSON Data

prettyformatter works with JSON data.

batters = [
    {"id": "1001", "type": "Regular"},
    {"id": "1002", "type": "Chocolate"},
    {"id": "1003", "type": "Blueberry"},
    {"id": "1004", "type": "Devil's Food"},
]

toppings = [
    {"id": "5001", "type": None},
    {"id": "5002", "type": "Glazed"},
    {"id": "5005", "type": "Sugar"},
    {"id": "5007", "type": "Powdered Sugar"},
    {"id": "5006", "type": "Chocolate with Sprinkles"},
    {"id": "5003", "type": "Chocolate"},
    {"id": "5004", "type": "Maple"},
]

data = {"id": "0001", "type": "donut", "name": "Cake", "ppu": 0.55, "batters": batters, "topping": toppings}

pprint:

prettyformatter attempts to compromise between alignment, readability, and horizontal/vertical compactness.

Support for JSON data is also as easy as pprint(json=True).

from prettyformatter import pprint

pprint(data, json=True)
"""
{
    "id"    : "0001",
    "type"  : "donut",
    "name"  : "Cake",
    "ppu"   : 0.55,
    "batters":
        [
            {"id": "1001", "type": "Regular"},
            {"id": "1002", "type": "Chocolate"},
            {"id": "1003", "type": "Blueberry"},
            {"id": "1004", "type": "Devil's Food"}
        ],
    "topping":
        [
            {"id": "5001", "type": None},
            {"id": "5002", "type": "Glazed"},
            {"id": "5005", "type": "Sugar"},
            {"id": "5007", "type": "Powdered Sugar"},
            {"id": "5006", "type": "Chocolate with Sprinkles"},
            {"id": "5003", "type": "Chocolate"},
            {"id": "5004", "type": "Maple"}
        ]
}
"""

pprint supports the same parameters as print, meaning saving to files is as easy as file=file.

from prettyformatter import pprint

with open("cake.json", mode="w") as file:
    pprint(data, json=True, file=file)

PrettyDataclass

prettyformatter supports dataclasses easily.

@dataclass
class Person(PrettyDataclass):
    name: str
    birthday: str
    phone_number: str
    address: str


print(Person("Jane Doe", "2001-01-01", "012-345-6789", "123 Sample St."))
"""
Person(
    name=
        "Jane Doe",
    birthday=
        "2001-01-01",
    phone_number=
        "012-345-6789",
    address=
        "123 Sample St.",
)
"""

register

Custom formatters for existing classes can be registered.

import numpy as np

@register(np.ndarray)
def pformat_ndarray(obj, specifier, depth, indent, shorten, json):
    if json:
        return pformat(obj.tolist(), specifier, depth, indent, shorten, json)
    with np.printoptions(formatter=dict(all=lambda x: format(x, specifier))):
        return repr(obj).replace("\n", "\n" + " " * depth)

pprint(dict.fromkeys("ABC", np.arange(9).reshape(3, 3)))
"""
{
    "A":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
    "B":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
    "C":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
}
"""

pprint(dict.fromkeys("ABC", np.arange(9).reshape(3, 3)), json=True)
"""
{
    "A" : [[0, 1, 2], [3, 4, 5], [6, 7, 8]],
    "B" : [[0, 1, 2], [3, 4, 5], [6, 7, 8]],
    "C" : [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
}
"""