# 6. Dragon ADR Init Position¶

• ADR - Architecture Design Records

## 6.1. Problem¶

• Set Dragon's initial position to x=50, y=120

## 6.2. Option 1¶

>>> dragon = Dragon('Wawelski', 50, 120)


Pros and Cons:

• Good: easy to use

• Bad: requires knowledge of API to answer what are those numbers

• Bad: It does suggest, that x and y are some parameters to texture (for example width and height of a texture image, or gold and hit points)

• Decision: rejected, not explicit

Problems:

>>> dragon = Dragon('Wawelski', 0, 0)
>>> dragon = Dragon('Wawelski', 'img/dragon/alive.png', 0, 0)

>>> pt = CartesianAxisPoint(1, 2)        # ok
>>> pt = GPSPoint(1, 2)                  # maybe

>>> knn = KNearestNeighbors(3)           # ok
>>> knn = KNearestNeighbors(3, [1,2,3])  # bad


## 6.3. Option 2¶

>>> dragon = Dragon('Wawelski', x=50, y=120)


Pros and Cons:

• Good: easy to use

• Good: short argument names

• Good: verbose in this example

• Good: you can assign None by default to set default point

• Good: extensible, easy to add z with default value 0

• Bad: It does suggest, that x and y are some parameters to texture (for example width and height of a texture image)

• Decision: rejected, not explicit enough

Problem:

>>> dragon = Dragon('Wawelski', x=0, y=0)
>>> dragon = Dragon('Wawelski', texture='img/dragon/alive.png', x=0, y=0)

>>> pt = CartesianAxisPoint(x=1, y=2)           # ok
>>> pt = GPSPoint(...)                          # both longitude and latitude starts with letter "l"

>>> knn = KNearestNeighbors(k=3)                # ok
>>> knn = KNearestNeighbors(k=3, w=[1,2,3])     # bad


## 6.4. Option 3¶

>>> dragon = Dragon('Wawelski', posx=50, posy=120)
>>> dragon = Dragon('Wawelski', posX=50, posY=120)


Pros and Cons:

• Good: simple, easy to use

• Good: you can assign None by default to set default point

• Good: extensible, easy to add posZ with default value 0

• Decision: rejected, not explicit enough

Example:

>>> dragon = Dragon('Wawelski', posx=0, posy=0)    # maybe, bad


Problem:

>>> pt = CartesianAxisPoint(xax=1, yax=2)          # bad, misleading
>>> pt = GPSPoint(lon=1, lat=2)                    # ok

>>> knn = KNearestNeighbors(k=3, wgt=[1,2,3])      # bad


## 6.5. Option 4¶

>>> dragon = Dragon('Wawelski', positionx=50, positiony=120)
>>> dragon = Dragon('Wawelski', positionX=50, positionY=120)


Pros and Cons:

• Good: simple, easy to use

• Good: you can assign None by default to set default point

• Good: extensible, easy to add positionZ with default value 0

• Decision: candidate, but names could be better

Example:

>>> current = CartesianAxisPoint(xaxis=1, yaxis=2)   # bad, too verbose
>>> current = GPSPoint(longitude=1, latitude=2)      # ok

>>> knn = KNearestNeighbors(k=3, weights=[1,2,3])    # ok


Problem:

>>> df.plot(kind='line', subplots=True, color='grey', sharey=True)  # bad


## 6.6. Option 5¶

>>> dragon = Dragon('Wawelski', position_x=50, position_y=120)


Pros and Cons:

• Good: simple, easy to use

• Good: you can assign None by default to set initial point

• Good: extensible, easy to add position_z with default value 0

• Good: backward compatible

• Decision: candidate

Example:

>>> df.plot(kind='line', sub_plots=True, color='grey', share_y=True)      # ok
>>> df.plot(kind='line', sub_plots=True, color='grey', share_y_axis=True) # ok
>>> df.plot(kind='line', sub_plots=True, color='grey', share_axis_y=True) # ok


## 6.7. Option 6¶

>>> dragon = Dragon('Wawelski', (50, 120))
>>> dragon = Dragon('Wawelski', position=(50, 120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple, easy to use

• Good: you can assign None to set default pos

• Good: can set only one axis to None

• Good: always has to pass both x and y coordinates together

• Bad: always has to pass both x and y coordinates together

• Bad: you have to know that first is x and second is y

• Bad: order is important, you cannot change it

• Bad: not extensible, pos will always be 2D

• Bad: could be refactored to 3D using regexp: pattern = r'[$$$(\s*?:\d+|None\s*)\s*,\s*(\s*?:\d+|None\s*)[$$$]'

• Decision: rejected, not extensible

Problem:

>>> dragon = Dragon('Wawelski', (0, 0))             # bad
>>> dragon = Dragon('Wawelski', position=(0, 0))    # ok


Use Case:

>>> np.random.randint(0,10, (3,3))
>>> np.random.randint(0,10, size=(3,3))


Example:

>>> pt = (50, 120)
>>>
>>> pt
50
>>> pt
120
>>>
>>> pt, pt
(50, 120)


## 6.8. Option 7¶

>>> dragon = Dragon('Wawelski', {'x':50, 'y':120})
>>> dragon = Dragon('Wawelski', position={'x':50, 'y':120})


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: you can assign None by default to set default point

• Good: order is not important

• Good: always has to pass both x and y

• Good: possible to extend to 3D with refactoring

• Good: easier to refactor than tuple - pattern = r'\{\s*"x"\s*:\s*(?:\d+|None)\s*,\s*"y"\s*:\s*(?:\d+|None)\s*\}'

• Bad: always has to pass both x and y

• Bad: not extensible, position will always be 2D

• Decision: rejected, not extensible

Example:

>>> pt = {'x':50, 'y':120}
>>>
>>> pt['x']
50
>>> pt['y']
120


## 6.9. Option 8¶

>>> from collections import namedtuple
>>>
>>> Position = namedtuple('Point', ['x', 'y'])
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple, easy to use

• Good: always has to pass both x and y

• Good: possible to extend to 3D (Python will crash if z not found)

• Good: keyword argument is not required, class name is verbose enough

• Good: lightweight, in the end this is a tuple

• Bad: always has to pass both x and y

• Bad: not extensible, position will always be 2D

• Decision: rejected, could be done better

Example:

>>> pt = Point(x=50, y=120)
>>>
>>> pt, pt
(50, 120)
>>>
>>> pt.x, pt.y
(50, 120)


## 6.10. Option 9¶

>>> from typing import NamedTuple
>>>
>>> class Position(NamedTuple):
...     x: int
...     y: int
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple, easy to use

• Good: verbose

• Good: you can assign None by default to set default position

• Good: very easy to extend to 3D

• Good: keyword argument is not required, class name is verbose enough

• Good: lightweight, in the end this is a tuple

• Decision: candidate

Example:

>>> pt = Point(x=50, y=120)
>>>
>>> pt, pt
(50, 120)
>>>
>>> pt.x, pt.y
(50, 120)


## 6.11. Option 10¶

>>> from typing import TypedDict
>>>
>>> class Position(TypedDict):
...     x: int
...     y: int
>>>
>>>
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position={'x': 50, 'y': 120})


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple

• Good: you can assign position=None by default to set default position

• Good: relatively easy to extend to 3D

• Good: keyword argument is not required, class name is verbose enough

• Bad: TypeDict does not support default values

• Decision: rejected, better than dict, does not support default values

Example:

>>> pt = Point(x=50, y=120)
>>>
>>> pt['x']
50
>>> pt['y']
120


## 6.12. Option 11¶

>>> from typing import TypedDict, Required, NotRequired
>>>
>>> class Position(TypedDict):
...     x: Required[int]
...     y: Required[int]
...     z: NotRequired[int]
>>>
>>>
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position={'x': 50, 'y': 120})

• Good: data is stored together (x and y coordinates)

• Good: simple

• Good: you can assign position=None by default to set default position

• Good: relatively easy to extend to 3D

• Good: keyword argument is not required, class name is verbose enough

• Bad: TypeDict does not support default values

• Decision: rejected, does not support default values

Example:

>>> pt = Point(x=50, y=120)
>>>
>>> pt['x']
50
>>> pt['y']
120


## 6.13. Option 12¶

>>> class Position:
...     x: int
...     y: int
...
...     def __init__(self, x: int = 0, y: int = 0) -> None:
...         self.x = x
...         self.y = y
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: very common pattern

• Good: easy to use

• Good: faster than dataclasses

• Good: more explicit than dataclass

• Good: easy to extend to 3D

• Good: can set default values

• Good: keyword argument is not required, class name is verbose enough

• Bad: allows creation of not existing attributes

• Bad: allows for attribute mutation

• Decision: maybe, has some limitation

Example:

>>> pt = Point(x=1, y=2)
>>>
>>> pt.x, pt.y
(1, 2)
>>>
>>> pt.x = 10            # ok
>>> pt.y = 20            # ok
>>> pt.notexisting = 30  # ok


## 6.14. Option 13¶

>>> class Position:
...     __slots__ = ('x', 'y')
...     x: int
...     y: int
...
...     def __init__(self, x: int = 0, y: int = 0) -> None:
...         self.x = x
...         self.y = y
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: common pattern

• Good: easy to use

• Good: more explicit than dataclass

• Good: easy to extend to 3D

• Good: can set default values

• Good: keyword argument is not required, class name is verbose enough

• Bad: too complex for now

• Bad: allows for attribute mutation

• Decision: maybe, too complex for now

Example:

>>> pt = Point(x=1, y=2)
>>>
>>> pt.x, pt.y
(1, 2)
>>>
>>> pt.x = 10             # ok
>>> pt.y = 20             # ok
>>> pt.notexisting = 30   # error


## 6.15. Option 14¶

>>> from dataclasses import dataclass
>>>
>>> @dataclass
... class Position:
...     x: int
...     y: int
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple, easy to use

• Good: verbose

• Good: you can assign None to set default position

• Good: very easy to extend to 3D

• Good: keyword argument is not required, class name is verbose enough

• Bad: allows creation of not existing attributes

• Bad: allows for attribute mutation

• Decision: maybe, has some limitation

Example:

>>> pt = Point(x=1, y=2)
>>>
>>> pt.x, pt.y
(1, 2)
>>>
>>> pt.x = 10             # ok
>>> pt.y = 20             # ok
>>> pt.notexisting = 30   # ok


## 6.16. Option 15¶

>>> from dataclasses import dataclass
>>>
>>> @dataclass(frozen=True, slots=True)
... class Position:
...     x: int = 0
...     y: int = 0
>>>
>>>
>>> dragon = Dragon('Wawelski', Position(50, 120))
>>> dragon = Dragon('Wawelski', Position(x=50, y=120))
>>> dragon = Dragon('Wawelski', position=Position(50, 120))
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))


Pros and Cons:

• Good: data is stored together (x and y coordinates)

• Good: simple, easy to use

• Good: verbose

• Good: you can assign None by default to set default position

• Good: very easy to extend to 3D

• Good: keyword argument is not required, class name is verbose enough

• Good: is faster and leaner than simple dataclass

• Good: does not allow for attribute mutation

• Good: does not allow for attribute creation

• Bad: more complicated than mutable dataclasses

• Decision: candidate

Example:

>>> pt = Point(x=1, y=2)
>>>
>>> pt.x, pt.y
(1, 2)
>>>
>>> pt.x = 10             # error
>>> pt.y = 20             # error
>>> pt.notexisting = 30   # error


## 6.17. Decision¶

>>> class Dragon:
...     def __init__(name: str, /,
...                  *, position_x: int, position_y: int,
...                  ) -> None: ...
>>>
>>>
>>> dragon = Dragon('Wawelski', position_x=50, position_y=120)


Pros and Cons:

• Good: simple

• Good: explicit

• Good: verbose

• Good: extensible

Re-evaluate in future:

>>> class Dragon:
...     def __init__(name: str, /, *, position: Position) -> None: ...
>>>
>>>
>>> dragon = Dragon('Wawelski', position=Position(x=50, y=120))

• Choices: NameTuple, dataclass(frozen=True, slots=True)

• Good: explicit

• Good: verbose

• Good: extensible

• Bad: to complicated for now