New example: Lossy zip of iterators

Resolves https://github.com/satwikkansal/wtfpython/issues/121
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Satwik Kansal 2019-06-09 19:45:13 +05:30 committed by Satwik
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README.md vendored
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@ -1253,6 +1253,55 @@ I've lost faith in truth!
---
### ▶ Lossy zip of iterators
```py
>>> numbers = list(range(7))
>>> numbers
[0, 1, 2, 3, 4, 5, 6]
>>> first_three, remaining = numbers[:3], numbers[3:]
>>> first_three, remaining
([0, 1, 2], [3, 4, 5, 6])
>>> numbers_iter = iter(numbers)
>>> list(zip(numbers_iter, first_three))
[(0, 0), (1, 1), (2, 2)]
# so far so good, let's zip the remaining
>>> list(zip(numbers_iter, remaining))
[(4, 3), (5, 4), (6, 5)]
```
Where did element `3` go from the `numbers` list?
#### 💡 Explanation:
- From Python [docs](https://docs.python.org/3.3/library/functions.html#zip), here's an approximate implementation of zip function,
```py
def zip(*iterables):
sentinel = object()
iterators = [iter(it) for it in iterables]
while iterators:
result = []
for it in iterators:
elem = next(it, sentinel)
if elem is sentinel:
return
result.append(elem)
yield tuple(result)
```
- So the function takes in arbitrary number of itreable objects, adds each of their items to the `result` list by calling the `next` function on them, and stops whenever any of the iterable is exhausted.
- The caveat here is when any iterable is exhausted, the existing elements in the `result` list are discarded. That's what happened with `3` in the `numbers_iter`.
- The correct way to do the above using `zip` would be,
```py
>>> numbers = list(range(7))
>>> numbers_iter = iter(numbers)
>>> list(zip(first_three, numbers_iter))
[(0, 0), (1, 1), (2, 2)]
>>> list(zip(remaining, numbers_iter))
[(3, 3), (4, 4), (5, 5), (6, 6)]
```
The first argument of zip should be the one with fewest elements.
---
### ▶ From filled to None in one instruction...
```py