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# Coroutines

Similar to generators with a few differences:

* **generators** are **data producers**
* **coroutines** are **data consumers**

**Generator blueprint:**

```python
def fib():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a+b
```

We then commonly use it in a `for` loop like this:

```python
for i in fib():
    print(i)
```

It is **fast and does not put a lot of pressure on memory because it generates the values on the fly** rather than storing them in a list.

**If we use `yield` in the above example, we get a coroutine**.

**Coroutines consume values which are sent to it**.

Example: a `grep` alternative in Python:

```python
def grep(pattern):
    print("Searching for", pattern)
    while True:
        line = (yield)
        if pattern in line:
            print(line)
```

**We have turned it into a coroutine**. `yield` does not contain any value initially, instead **we supply it values externally. We supply values by using the `.send()`method**. Example:

```python
search = grep('coroutine')
next(search)
# Output: Searching for coroutine
search.send("I love you")
search.send("Don't you love me?")
search.send("I love coroutines instead!")
# Output: I love coroutines instead!
```

**The sent values are accessed by `yield`**. 

**`next()`is required to start the coroutine**. Just like `generators`, **coroutines do not start the function immediately. Instead they run it in response to the `__next__()` and `.send()` methods**. Therefore, you have to run `next()` so that the execution advances to the `yield` expression.

Close a coroutine by calling the `.close()` method:

```python
search = grep('coroutine')
# ...
search.close()
```

## Further reading

There is a lot more to `coroutines`. I suggest you check out [this awesome presentation](http://www.dabeaz.com/coroutines/Coroutines.pdf) by David Beazley.