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from typing import Sequence

def print_sequence_elements(sequence: Sequence[str]):
    for i, s in enumerate(sequence):
        print(f"item {i}: {s}")

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def foo(x: int, y: int, func: Callable[[int, int], int]) -> int:
    output = func(x, y)
    return output

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from typing import Callable

def sum_numbers(x: int, y: int) -> int:
    return x + y

def foo(x: int, y: int, func: Callable) -> int:
    output = func(x, y)
    return output

foo(1, 2, sum_numbers)

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from typing import List

NestedList = List[List[str]]
my_list: NestedList = [["tomato", "carrot"], ["melon", "apples"]]

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from typing import List

def my_dummy_function(vector: List[float]):
   return sum(vector)

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def my_dummy_function(l: list[float]):
   return sum(l)

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class Person:
    first_name: str = "John"
    last_name: str = "Does"
    age: int = 31

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a: int = 3
b: float = 2.4
c: bool = True
d: list = ["A", "B", "C"]
e: dict = {"x": "y"}
f: set = {"a", "b", "c"}
g: tuple = ("name", "age", "job")

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def add_numbers(x: type_x, y: type_y, z: type_z= 100) -> type_return:
    return x + y + z

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from spacy.matcher import Matcher

nlp = spacy.load("en_core_web_sm")
doc = nlp("You should definitely buy Bitcoin")

pattern = [
    {"LEMMA": {"IN": ["buy", "sell"]}},
    {"LOWER": {"IN": ["bitcoin", "dogecoin"]}},
]