Re-organize directory structure (#4971)

See discussion in #2491

Co-authored-by: Ivan Levkivskyi <ilevkivskyi@dropbox.com>

stdlib/@python2/random.pyi

@@ -0,0 +1,67 @@
+import _random
+from typing import AbstractSet, Any, Callable, Iterator, List, MutableSequence, Protocol, Sequence, TypeVar, Union, overload
+
+_T = TypeVar("_T")
+_T_co = TypeVar("_T_co", covariant=True)
+
+class _Sampleable(Protocol[_T_co]):
+    def __iter__(self) -> Iterator[_T_co]: ...
+    def __len__(self) -> int: ...
+
+class Random(_random.Random):
+    def __init__(self, x: object = ...) -> None: ...
+    def seed(self, x: object = ...) -> None: ...
+    def getstate(self) -> _random._State: ...
+    def setstate(self, state: _random._State) -> None: ...
+    def jumpahead(self, n: int) -> None: ...
+    def getrandbits(self, k: int) -> int: ...
+    @overload
+    def randrange(self, stop: int) -> int: ...
+    @overload
+    def randrange(self, start: int, stop: int, step: int = ...) -> int: ...
+    def randint(self, a: int, b: int) -> int: ...
+    def choice(self, seq: Sequence[_T]) -> _T: ...
+    def shuffle(self, x: MutableSequence[Any], random: Callable[[], None] = ...) -> None: ...
+    def sample(self, population: _Sampleable[_T], k: int) -> List[_T]: ...
+    def random(self) -> float: ...
+    def uniform(self, a: float, b: float) -> float: ...
+    def triangular(self, low: float = ..., high: float = ..., mode: float = ...) -> float: ...
+    def betavariate(self, alpha: float, beta: float) -> float: ...
+    def expovariate(self, lambd: float) -> float: ...
+    def gammavariate(self, alpha: float, beta: float) -> float: ...
+    def gauss(self, mu: float, sigma: float) -> float: ...
+    def lognormvariate(self, mu: float, sigma: float) -> float: ...
+    def normalvariate(self, mu: float, sigma: float) -> float: ...
+    def vonmisesvariate(self, mu: float, kappa: float) -> float: ...
+    def paretovariate(self, alpha: float) -> float: ...
+    def weibullvariate(self, alpha: float, beta: float) -> float: ...
+
+# SystemRandom is not implemented for all OS's; good on Windows & Linux
+class SystemRandom(Random): ...
+
+# ----- random function stubs -----
+def seed(x: object = ...) -> None: ...
+def getstate() -> object: ...
+def setstate(state: object) -> None: ...
+def jumpahead(n: int) -> None: ...
+def getrandbits(k: int) -> int: ...
+@overload
+def randrange(stop: int) -> int: ...
+@overload
+def randrange(start: int, stop: int, step: int = ...) -> int: ...
+def randint(a: int, b: int) -> int: ...
+def choice(seq: Sequence[_T]) -> _T: ...
+def shuffle(x: MutableSequence[Any], random: Callable[[], float] = ...) -> None: ...
+def sample(population: _Sampleable[_T], k: int) -> List[_T]: ...
+def random() -> float: ...
+def uniform(a: float, b: float) -> float: ...
+def triangular(low: float = ..., high: float = ..., mode: float = ...) -> float: ...
+def betavariate(alpha: float, beta: float) -> float: ...
+def expovariate(lambd: float) -> float: ...
+def gammavariate(alpha: float, beta: float) -> float: ...
+def gauss(mu: float, sigma: float) -> float: ...
+def lognormvariate(mu: float, sigma: float) -> float: ...
+def normalvariate(mu: float, sigma: float) -> float: ...
+def vonmisesvariate(mu: float, kappa: float) -> float: ...
+def paretovariate(alpha: float) -> float: ...
+def weibullvariate(alpha: float, beta: float) -> float: ...