Easily define and reuse complex Python objects that serialize into JSON or YAML.
Project description
kadet
Easily define and reuse complex Python objects that serialize into JSON or YAML.
Example
from kadet import BaseObj
from pprint import pprint
ships = BaseObj()
ships.root.type.container = ["panamax", "suezmax", "post-panamax"]
ships.root.type.carrier = ["conventional", "geared", "gearless"]
ships.root.type.tanker = BaseObj.from_yaml("tankers.yml")
pprint(ships.root)
# output
{'type': {'carrier': ['conventional',
'geared',
'gearless'],
'container': ['panamax',
'suezmax',
'post-panamax'],
'tanker': ['oil', 'liquified-gas', 'chemical']}}
Installation
Install using pip install kadet
.
Overview
BaseObj
BaseObj implements the basic object that serializes into JSON or YAML.
Setting keys in self.root
means they will be serialized. Keys can be set as an hierarchy of attributes.
The self.body()
method is reserved for setting self.root on instantiation.
The example below:
class MyApp(BaseObj):
def body(self):
self.root.name = "myapp"
self.root.inner.foo = "bar"
self.root.list = [1, 2, 3]
yaml.dump(MyApp().dump())
serializes into:
---
name: myapp
inner:
foo: bar
list:
- 1
- 2
- 3
The self.new()
method can be used to define a basic constructor.
self.need()
checks if a key is set and errors if it isn't (with an optional custom error message).
self.optional()
sets a key as optional. Use default
keyword to set default value when not set.
Both self.new()
and self.body()
method accept the istype
keyword to validate value type on runtime.
Supports typing
types.
kwargs
that are passed onto a new instance of BaseObj are always accessible via self.kwargs
self.new_with()
is an utility method to call super().new()
while passing kwargs to the super class.
In this example, MyApp needs name
and foo
to be passed as kwargs.
class MyApp(BaseObj):
def new(self):
self.need("name")
self.need("foo", msg="please provide a value for foo")
self.optional("baz")
def body(self):
self.root.name = self.kwargs.name
self.root.inner.foo = self.kwargs.foo
self.root.list = [1, 2, 3]
obj = MyApp(name="myapp", foo="bar")
Setting a skeleton
Defining a large body with Python can be quite hard and repetitive to read and write.
The self.root_file()
method allows importing a YAML/JSON file to set self.root
.
MyApp's skeleton can be set instead like this:
#skel.yml
---
name: myapp
inner:
foo: bar
list:
- 1
- 2
- 3
class MyApp(BaseObj):
def new(self):
self.need("name")
self.need("foo", msg="please provide a value for foo")
self.root_file("path/to/skel.yml")
Extending a MyApp's skeleton is possible just by implementing self.body()
:
class MyApp(BaseObj):
def new(self):
self.need("name")
self.need("foo", msg="please provide a value for foo")
self.root_file("path/to/skel.yml")
def body(self):
self.set_replicas()
self.root.metadata.labels = {"app": "mylabel"}
def set_replicas(self):
self.root.spec.replicas = 5
Inheritance
Python inheritance will work as expected:
class MyOtherApp(MyApp):
def new(self):
super().new() # MyApp's new()
self.need("size")
def body(self):
super().body() # we want to extend MyApp's body
self.root.size = self.kwargs.size
del self.root.list # get rid of "list"
obj = MyOtherApp(name="otherapp1", foo="bar2", size=3)
yaml.dump(obj.dump())
serializes to:
---
name: otherapp1
inner:
foo: bar2
replicas: 5
size: 3
BaseModel
BaseModel integrates Kadet semantics with Pydantic's BaseModel together with powerful data validation and type hinting features.
Just like in BaseObj, keys in self.root
will be serialized, but kwargs is no longer necessary as BaseModel's parameters are set as attributes in self
.
The self.body()
method is reserved for setting self.root on instantiation.
The example below:
class Boat(BaseModel):
name: str # Required
length: int # Required
description: str = "I am a boat" # Default description
def body(self):
self.root.name = self.name
self.root.details.length = self.length
self.root.details.description = self.description
print(yaml.dump(Boat(name="Boaty", length=600).dump()))
---
details:
description: I am a boat
length: 600
name: Boaty
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