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Jan Giacomelli
@jangiacomelli 5 years, 9 months ago 1288 views

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🤔 Python generators

What are they? How to use them?

#Python

🧵Let's find out 👇

1️⃣ Python generators are lazy iterators delivering the next value when their .next() is called.

They are created by using the yield keyword

next() can be called explicitly or implicitly inside for loop

They can be finite or infinite

2️⃣ yield - where a value is sent back to the caller, but the function doesn’t exit afterward as with the return statement

The state of function is remembered.

For example, the number is incremented and sent back from yield at the consecutive call next()

3️⃣ Generator stores only the current state of the function - it generates next element on next() call and forgets the previous one -> it saves memory

For example, we don't need to store 1mio elements in memory to do something with each element

4️⃣ When you call a generator function generator object is returned - it's not executed yet

It executes only when next() is called

For example, that's why Exception is raised only on the next() call

5️⃣ When the generator goes out of elements it raises StopIteration exception

6️⃣ You can also create a class that behaves like a generator - it needs implemented methods:

- __iter__ -> to enable iteration
- __next__ -> to enable next element access

7️⃣ You can also create a generator with one-liner expression similar to list comprehension

8️⃣ You can read more:

https://t.co/mXp7L8l2Ai

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@PrasoonPratham

Are you planning to learn Python for machine learning this year?

Here's everything you need to get started.
🧵👇

In this thread, we'll look at all the concepts in Python you need to know for machine learning along with free resources to help you out.

All of this is based on my experience of successfully teaching 300+ students how to code using Python.

(2 / 19

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This makes Python a no-brainer to learn for machine learning as a beginner.

(3 / 19)

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