Pythonのラムダ式とは？map/filter/sortedで使う実例集

# 基本: 引数xを2倍にする匿名関数
double = lambda x: x * 2
print(double(5))  # 10

# 引数を複数取る例
add = lambda a, b: a + b
print(add(3, 4))  # 7

# すぐに呼び出す(即時実行)
result = (lambda s: s.upper())("hello")
print(result)  # "HELLO"

# mapと組み合わせる
nums = [1, 2, 3]
squared = list(map(lambda n: n * n, nums))  # [1, 4, 9]
print(squared)

# OK: 条件演算子は「式」
label = lambda x: "even" if x % 2 == 0 else "odd"
print(label(3))  # "odd"

# NG例(コメントのみ、実際に実行するとSyntaxError):
# bad = lambda x: y = x + 1  # 代入文は不可
# bad2 = lambda x: for i in range(x): print(i)  # 文は不可

# 代わりにdefで書く
def verbose(x):
    y = x + 1
    print(y)
    return y

# 期待: 0,1,2 と表示したい
funcs_bad = [lambda: i for i in range(3)]
print([f() for f in funcs_bad])  # すべて最後のi=2を参照してしまう -> [2, 2, 2]

# 回避1: デフォルト引数で値を束縛
funcs_ok1 = [lambda i=i: i for i in range(3)]
print([f() for f in funcs_ok1])  # [0, 1, 2]

# 回避2: 引数を取る関数にして即時呼び出し
funcs_ok2 = [(lambda x: (lambda: x))(i) for i in range(3)]
print([f() for f in funcs_ok2])  # [0, 1, 2]

from typing import Callable, TypeAlias

# 関数の受け渡し側でCallableを使う
def apply(f: Callable[[int], int], x: int) -> int:
    return f(x)

# ラムダに直接注釈は付けられないが、受け手で担保できる
print(apply(lambda n: n + 1, 10))  # 11

# 型エイリアスで表現する
IntToInt: TypeAlias = Callable[[int], int]
inc: IntToInt = lambda n: n + 1
print(inc(5))

nums = [1, 2, 3, 4]
squared_iter = map(lambda x: x * x, nums)  # まだイテレータ
squared_list = list(squared_iter)          # list化して使う
print(squared_list)

a = [1, 2, 3]
b = [10, 20, 30, 40]
summed = list(map(lambda x, y: x + y, a, b))  # 3要素で止まる
print(summed)

nums = [1, 2, 3]
m = map(lambda x: x * 2, nums)
print(list(m))  # ここで消費される
print(list(m))  # もう空

nums = list(range(10))
evens = list(filter(lambda x: x % 2 == 0, nums))
print(evens)

nums = list(range(20))
# 5の倍数かつ10未満
picked = list(filter(lambda x: (x % 5 == 0) and (x < 10), nums))
print(picked)

words = ["apple", "Banana", "apricot", "berry"]
# 先頭がa(大文字小文字無視)
starts_with_a = list(filter(lambda w: w.lower().startswith("a"), words))
print(starts_with_a)

users = [
    {"name": "Alice", "age": 19},
    {"name": "Bob", "age": 25},
    {"name": "Carol", "age": 17},
]
# 20歳以上のユーザーだけ
adults = list(filter(lambda u: u["age"] >= 20, users))
print([u["name"] for u in adults])

names = ["bob", "Alice", "carol"]
# 大文字小文字を無視してソート
sorted_names = sorted(names, key=lambda s: s.lower())
print(sorted_names)

people = [
    {"name": "Bob", "age": 25},
    {"name": "Alice", "age": 20},
    {"name": "Carol", "age": 25},
]
by_age = sorted(people, key=lambda p: p["age"])
print([(p["name"], p["age"]) for p in by_age])

people = [
    {"name": "Bob", "age": 25},
    {"name": "Alice", "age": 25},
    {"name": "Carol", "age": 20},
]
# 年齢(昇順) → 名前(昇順)
sorted_people = sorted(people, key=lambda p: (p["age"], p["name"]))
print([(p["name"], p["age"]) for p in sorted_people])

records = [
    ("A", 2),
    ("B", 1),
    ("C", 2),
    ("D", 1),
]
# 2段階: まず第2要素で昇順、次にレーベルを降順(安定性により同順位の中だけ反映)
tmp = sorted(records, key=lambda r: r[1])                  # 第2要素昇順
final = sorted(tmp, key=lambda r: r[0], reverse=True)      # ラベル降順
print(final)

# 1回でやるならtupleキー + reverseの工夫
once = sorted(records, key=lambda r: (-r[1], r[0]))  # 第2要素を負にして実質降順
print(once)

words = ["aaa", "b", "cc"]
shortest = min(words, key=lambda w: len(w))
longest = max(words, key=lambda w: len(w))
print(shortest, longest)

data = [("alice", 3), ("bob", 1), ("carol", 2)]
data.sort(key=lambda t: t[1])  # インプレースで並べ替え
print(data)