Data pipeline

Chainable transformations with |.

functional OOP pipeline

Implement `class Pipeline` with:
- `__init__(data)` — wraps iterable
- `__or__(fn)` — applies fn to each element; returns new Pipeline
- `collect() -> list` — materialise results

Constraints

Functions are unary transformations.

Example

result = Pipeline([1,2,3,4,5]) | (lambda x: x*2) | (lambda x: x+1)
result.collect()  # [3,5,7,9,11]

40 points ~35 min

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Hints

__or__ returns Pipeline(map(fn, self._data)).

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