GitLocker: The Coding Marketplace

Description:

jsonbourne 0.29.0

jsonbourne

Install: pip install jsonbourne

Python json lib/pkg that makes json feel like the JSON module in javascript/typescript:

from jsonbourne import JSON; JSON.parse(JSON.stringify({"key": "value"}))
Automatically uses best json-lib-backend available (orjson/python-rapidjson) ~ can be configured

Hybrid dict/class object (jsonbourne.JsonObj):

Dot-notation getting/setting (featuring protected attributes!)
All your favorite python dictionary methods (items, keys, update, values) and more!
Works with pydantic and attrs

FastAPI:

JSONBOURNEResponse ~ auto use the best

No hard dependencies ~ works with python-stdlib-json as well as orjson and python-rapidjson
jsonbourne.JsonObj uses list/dict comprehensions (some are recursive) everywhere because 'why not?' and it is a bit faster

Usage:
JSON ~ from jsonbourne import JSON
Importing:
# Importing JSON:
from jsonbourne import JSON

# or
import JSON

# Importing jsonbourne:
import jsonbourne
import david_webb # jsonbourne's `True` identity

JSON basics:
import JSON # Module included with jsonbourne

string_stringify = JSON.stringify(
{"a": 1, "b": 2, "c": 3}
) # '{"a": 1, "b": 2, "c": 3}'
string_dumps = JSON.dumps({"a": 1, "b": 2, "c": 3}) # '{"a": 1, "b": 2, "c": 3}'
string_dumps

'{"a":1,"b":2,"c":3}'

JSON option kwargs ~ pretty & sort_keys
pretty:
string_dumps = JSON.stringify(
{"b": 2, "a": 1, "c": 3}, pretty=True
) # '{"a": 1, "b": 2, "c": 3}'
print(string_dumps)

{
"b": 2,
"a": 1,
"c": 3
}

sort_keys:
string_dumps = JSON.stringify(
{"b": 2, "a": 1, "c": 3}, pretty=True, sort_keys=True
) # '{"a": 1, "b": 2, "c": 3}'
print(string_dumps)

{
"a": 1,
"b": 2,
"c": 3
}

JsonObj & JSON

Python dictionary/object with dot access
Protections against setting class/obj attributes
Is as javascript-y as possible (keys have to be strings -- ints/floats will be converted to strings)
Create a jsonbourne.JsonObj with jsonbourne.JSON
Recursive jsonification
Allows for kwarging (**json_obj)
Works with pydantic and attrs

Make an empty JsonObj
The following 3 examples all produce the same thing
from jsonbourne import JSON
j = JSON() # j => JsonObj(**{})
# OR
import JSON
j = JSON() # j => JsonObj(**{})
# OR
from jsonbourne import JsonObj
j = JsonObj() # j => JsonObj(**{})

From a dictionary o data
import datetime

data = {
"key": "value",
"list": [1, 2, 3, 4, 5],
"dt": datetime.datetime(1970, 1, 1, 0, 0, 0, 1),
"sub": {
"b": 3,
"key": "val",
"a": 1,
},
"timedelta": datetime.timedelta(days=2),
}

JSON(data)

JsonObj(**{
'dt': datetime.datetime(1970, 1, 1, 0, 0, 0, 1),
'key': 'value',
'list': [1, 2, 3, 4, 5],
'sub': {'a': 1, 'b': 3, 'key': 'val'},
'timedelta': datetime.timedelta(days=2)
})
Dot access
JSON(data).sub.b

3

stringified_data = JSON(data).stringify(pretty=True)
print(stringified_data)

{
"key": "value",
"list": [
1,
2,
3,
4,
5
],
"dt": "1970-01-01T00:00:00.000001",
"sub": {
"b": 3,
"key": "val",
"a": 1
},
"timedelta": 172800.0
}

parsed_data = JSON(stringified_data)
parsed_data

JsonObj(**{
'dt': '1970-01-01T00:00:00.000001',
'key': 'value',
'list': [1, 2, 3, 4, 5],
'sub': {'a': 1, 'b': 3, 'key': 'val'},
'timedelta': 172800.0
})
list(parsed_data.keys())

['key', 'list', 'dt', 'sub', 'timedelta']

list(parsed_data.items())

[('key', 'value'),
('list', [1, 2, 3, 4, 5]),
('dt', '1970-01-01T00:00:00.000001'),
('sub', JsonObj(**{'b': 3, 'key': 'val', 'a': 1})),
('timedelta', 172800.0)]

list(parsed_data.dot_keys())

[('key',),
('list',),
('dt',),
('sub', 'b'),
('sub', 'key'),
('sub', 'a'),
('timedelta',)]

list(parsed_data.dot_items())

[(('key',), 'value'),
(('list',), [1, 2, 3, 4, 5]),
(('dt',), '1970-01-01T00:00:00.000001'),
(('sub', 'b'), 3),
(('sub', 'key'), 'val'),
(('sub', 'a'), 1),
(('timedelta',), 172800.0)]

parsed_data[("sub", "key")]

'val'

parsed_data.dot_lookup("sub.key")

'val'

{**parsed_data}

{'key': 'value',
'list': [1, 2, 3, 4, 5],
'dt': '1970-01-01T00:00:00.000001',
'sub': JsonObj(**{'b': 3, 'key': 'val', 'a': 1}),
'timedelta': 172800.0}

# fully eject
parsed_data.eject()

{'key': 'value',
'list': [1, 2, 3, 4, 5],
'dt': '1970-01-01T00:00:00.000001',
'sub': {'b': 3, 'key': 'val', 'a': 1},
'timedelta': 172800.0}

Protected keys
jsonbourne.JsonObj protects against setting attributes like 'items' through dot-notation.
from jsonbourne import JSON

j = JSON()
j.key = "value"
try: # CANNOT set 'items' using dot-access
j.items = [1, 2, 3, 4]
except ValueError:
pass
# CAN set 'items' through key/item access
j["items"] = [1, 2, 3, 4]
print(j.__dict__)
print(j)
j_items = j.items
print("items", j_items)
# Getting 'items' through dot-access returns the `items()` method
assert j.items != [1, 2, 3, 4]
# Getting 'items' with key-access returns the stored value
assert j["items"] == [1, 2, 3, 4]

{'_data': {'key': 'value', 'items': [1, 2, 3, 4]}}
JsonObj(**{
'items': [1, 2, 3, 4], 'key': 'value'
})
items <bound method JsonObj.items of JsonObj(**{'key': 'value', 'items': [1, 2, 3, 4]})>

pydantic & jsonbourne

from jsonbourne.pydantic import JsonBaseModel
Allows for aliases when getting/setting attribute(s)
Supports __post_init__ (like dataclasses)

Basic usage:
from jsonbourne import JsonObj
from jsonbourne.pydantic import JsonBaseModel

class JsonSubObj(JsonBaseModel):
herm: int

def to_dict(self):
return self.dict()

def to_json(self, *args, **kwargs):
return self.json()

@classmethod
def from_json(cls, json_string: str):
return JsonSubObj(json.loads(json_string))

class JsonObjModel(JsonBaseModel):
a: int
b: int
c: str
d: JsonObj
e: JsonSubObj

#
@property
def a_property(self) -> str:
return "prop_value"

def to_json(self, *args, **kwargs):
return self.json()

@classmethod
def from_json(cls, json_string: str):
return cls(**json.loads(json_string))

obj = JsonObjModel(
**{"a": 1, "b": 2, "c": "herm", "d": {"nested": "nestedval"}, "e": {"herm": 2}}
)
obj

JsonObjModel(**{
'a': 1,
'b': 2,
'c': 'herm',
'd': JsonObj(**{'nested': 'nestedval'}),
'e': {'herm': 2}
})
# respects properties (which I don't think pydantic does(currently))
obj.a_property

'prop_value'

JSON backend/lib
jsonbourne finds the best json-lib (python-rapidjson/orjson) it can! On import jsonbourne gets to
work spying on your python env. jsonbourne, the most highly qualified json-CIA-agent, will import the best
python-json library it can find; if jsonbourne's cover is blown (meaning: the
only json library found is the python stdlib json), jsonbourne will fallback
to
the python stdlib json.
jsonbourne will look for the following json-packages in the following order:

rapidjson
orjson

Custom lib preferences
from jsonbourne import import_json

json = import_json(("rapidjson", "orjson")) # prefer rapidjson over orjson
string = json.dumps({"a": 1, "b": 2, "c": 3})
print(json)
print(string)

<class 'jsonbourne.jsonlib.RAPIDJSON'>
{"a":1,"b":2,"c":3}

Installing better JSON lib:
orjson

pip install orjson [pip]

rapidjson/python-rapidjson

pip install python-rapidjson [pip]
conda install -c anaconda python-rapidjson [conda anaconda/defaults]
conda install -c conda-forge python-rapidjson [conda-forge]