πŸ€” Python decorators

What are they? How do you use them?

🧡 Let's find out πŸ‘‡

1️⃣ Decorator is a function or a class that wraps another function or class modifying its behavior.

So how does that work?

The first thing to know is that everything in Python is an object - functions too
2️⃣ That means they can be passed to another function as an argument or returned from a function

Functions that take other functions as an argument are called higher-order functions
3️⃣ In Python, you can define a function inside other function - such functions are called inner functions
4️⃣ To create a decorator you just need to apply all of that together

log_enter_leave is a decorator.

my_function is the function.

To alter my_function's behavior we reassign it applying log_enter_leave decorator.
5️⃣ To simplify usage of decorators Python offers us syntactic sugar

A "pie-decorator" syntax using @

@decorator_name
6️⃣ The only problem here is that my_function now identify as the wrapper function

To solve that we just need to use wraps from functools
7️⃣ You can decorate classes too.

For example, you can dataclass decorator on your class to automatically generate its __init__ and __repr__ methods
8️⃣ You can also use a class as a decorator

Decorator class needs methods:
- __init__
- __call__ (it makes class callable)
9️⃣ For example, decorators are used for registering view functions to the Flask application
1️⃣0️⃣ Read more:

https://t.co/eBMh1Gv0xZ

https://t.co/2YdA2ZIQoV

https://t.co/Wb0jSjmzlc
1️⃣1️⃣ Script with all of the examples:

https://t.co/Tw1qrbN0nN

More from Machine learning

Really enjoyed digging into recent innovations in the football analytics industry.

>10 hours of interviews for this w/ a dozen or so of top firms in the game. Really grateful to everyone who gave up time & insights, even those that didnt make final cut πŸ™‡β€β™‚οΈ https://t.co/9YOSrl8TdN


For avoidance of doubt, leading tracking analytics firms are now well beyond voronoi diagrams, using more granular measures to assess control and value of space.

This @JaviOnData & @LukeBornn paper from 2018 referenced in the piece demonstrates one method
https://t.co/Hx8XTUMpJ5


Bit of this that I nerded out on the most is "ghosting" β€” technique used by @counterattack9 & co @stats_insights, among others.

Deep learning models predict how specific players β€” operating w/in specific setups β€” will move & execute actions. A paper here: https://t.co/9qrKvJ70EN


So many use-cases:
1/ Quickly & automatically spot situations where opponent's defence is abnormally vulnerable. Drill those to death in training.
2/ Swap target player B in for current player A, and simulate. How does target player strengthen/weaken team? In specific situations?
Starting a new project using #Angular? Here is a list of all the stuff i use to launch my projects the fastest i can.

A THREAD πŸ‘‡

Have you heard about Monorepo? I created one with all my Angular (and Nest) projects using
https://t.co/aY5llDtXg8.

I can share A LOT of code with it. Ex: Everytime i start a new project, i just need to import an Auth lib, that i created, and all Auth related stuff is set up.

Everyone in the Angular community knows about https://t.co/kDnunQZnxE. It's not the most beautiful component library out there, but it's good and easy to work with.

There's a bunch of state management solutions for Angular, but https://t.co/RJwpn74Qev is by far my favorite.

There's a lot of boilerplate, but you can solve this with the built-in schematics and/or with your own schematics

Are you not using custom schematics yet? Take a look at this:

https://t.co/iLrIaHVafm
https://t.co/3382Tn2k7C

You can automate all the boilerplate with hundreds of files associates with creating a new feature.

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