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48
content/blog/copydecorator.md
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48
content/blog/copydecorator.md
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---
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title: "Quick Python: Copy Decorator"
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date: 2020-04-08T18:49:54-04:00
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draft: false
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tags: ["python"]
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---
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If you want to guarantee that your function doesn't modify any of the references and don't mind paying a price in memory consumption, here is a decorator you can easily add to your functions.
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```python
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from copy import deepcopy
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def copy_arguments(func):
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def wrapper(*args, **kwargs):
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new_args = deepcopy(args)
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new_kwargs = deepcopy(kwargs)
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return func(*new_args, **new_kwargs)
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return wrapper
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```
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Example usage:
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```python
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@copy_arguments
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def modify1(xs):
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for i, _ in enumerate(xs):
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xs[i] *= 2
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```
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Comparison:
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```python
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def modify2(xs):
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for i, _ in enumerate(xs):
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xs[i] *= 2
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a = [1, 2, 3, 4, 5]
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b = [1, 2, 3, 4, 5]
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modify1(a)
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modify2(a)
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print(a)
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print(b)
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```
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```
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[1, 2, 3, 4, 5]
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[2, 4, 6, 8, 10]
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```
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29
content/blog/pydataclass.md
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content/blog/pydataclass.md
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---
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title: "Quick Python: Dataclasses"
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date: 2020-04-08T18:59:48-04:00
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draft: false
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tags: ["python"]
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---
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Python 3.7 and above have a feature called dataclasses. This allows us to reduce boilerplate code by removing the need to create a whole constructor and providing a sensible `__repr__` function.
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```python
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from dataclasses import dataclass
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@dataclass
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class Person:
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name: str
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age: int
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```
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Usage:
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```python
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p = Person("Bob", 30)
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print(p)
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```
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```
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Person(name='Bob', age=20)
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```
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53
content/blog/pygetset.md
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content/blog/pygetset.md
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---
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title: "Quick Python: Getters and Setters"
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date: 2020-04-08T18:15:21-04:00
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draft: false
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tags: ["python"]
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---
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One of the hidden gems in Python classes are seamless getters and setters. I discovered this through the book [Effective Python by Brett Slatkin](https://effectivepython.com/). Though the example I'll use is different and shorter than the one he uses in his book.
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Let's create a class representing a person. The only information we're going to store is their age and we'll make it optional to provide it.
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```python
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class Person:
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def __init__(self, age=None):
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self._age = None
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@property
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def age(self):
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if self._age is None:
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raise ValueError("age must be set before accessing it.")
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return self._age
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@age.setter
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def age(self, age):
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if age < 0:
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raise ValueError("age must be at least zero.")
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self._age = age
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```
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The second function in the class decorated by `@property` will be the getter function for the attribute `_age`. The name of the function will be what we expect the user to access it as. The setter is then decorated with `age.setter` where `age` is the name of the attribute. As such the name chosen in the getter function name, setter function name, and decorator must all match.
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Now let's try using it
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```python
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bobby = Person()
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bobby.age
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```
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```
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Traceback (most recent call last):
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File "<stdin>", line 1, in <module>
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File "/home/user/test.py", line 7, in age
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raise ValueError("age must first be set before accessing it")
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ValueError: age must first be set before accessing it
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```
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```python
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bobby.age = 5
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bobby.age
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```
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```
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5
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```
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