diff --git a/.gitignore b/.gitignore
index 01c1e46..ed2d84e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,3 +6,6 @@ venv
 .idea
 *~
 **~
+
+# MacOS
+.DS_Store
diff --git a/numpy-stubs/__init__.pyi b/numpy-stubs/__init__.pyi
index 49a085a..c51f3a6 100644
--- a/numpy-stubs/__init__.pyi
+++ b/numpy-stubs/__init__.pyi
@@ -35,6 +35,11 @@ if sys.version_info[0] < 3:
 else:
     from typing import SupportsBytes
 
+if sys.version_info >= (3, 8):
+    from typing import Literal
+else:
+    from typing_extensions import Literal
+
 # TODO: remove when the full numpy namespace is defined
 def __getattr__(name: str) -> Any: ...
 
@@ -792,3 +797,123 @@ class AxisError(ValueError, IndexError):
     def __init__(
         self, axis: int, ndim: Optional[int] = ..., msg_prefix: Optional[str] = ...
     ) -> None: ...
+
+# Functions from np.core.fromnumeric
+_Mode = Literal["raise", "wrap", "clip"]
+_Order = Literal["C", "F", "A"]
+_PartitionKind = Literal["introselect"]
+_SortKind = Literal["quicksort", "mergesort", "heapsort", "stable"]
+
+# Various annotations for scalars
+
+# While dt.datetime and dt.timedelta are not technically part of NumPy,
+# they are one of the rare few builtin scalars which serve as valid return types.
+# See https://github.com/numpy/numpy-stubs/pull/67#discussion_r412604113.
+_ScalarNumpy = Union[generic, dt.datetime, dt.timedelta]
+_ScalarBuiltin = Union[str, bytes, dt.date, dt.timedelta, bool, int, float, complex]
+_Scalar = Union[_ScalarBuiltin, _ScalarNumpy]
+
+_ScalarGeneric = TypeVar(
+    "_ScalarGeneric", bound=Union[dt.datetime, dt.timedelta, generic]
+)
+
+# An array-like object consisting of integers
+_Int = Union[int, integer]
+_ArrayLikeIntNested = Any  # TODO: wait for support for recursive types
+_ArrayLikeInt = Union[_Int, ndarray, Sequence[_Int], Sequence[_ArrayLikeIntNested]]
+
+# The signature of take() follows a common theme with its overloads:
+# 1. A generic comes in; the same generic comes out
+# 2. A scalar comes in; a generic comes out
+# 3. An array-like object comes in; some keyword ensures that a generic comes out
+# 4. An array-like object comes in; an ndarray or generic comes out
+@overload
+def take(
+    a: _ScalarGeneric,
+    indices: int,
+    axis: Optional[int] = ...,
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> _ScalarGeneric: ...
+@overload
+def take(
+    a: _Scalar,
+    indices: int,
+    axis: Optional[int] = ...,
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> _ScalarNumpy: ...
+@overload
+def take(
+    a: _ArrayLike,
+    indices: int,
+    axis: Optional[int] = ...,
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> _ScalarNumpy: ...
+@overload
+def take(
+    a: _ArrayLike,
+    indices: _ArrayLikeInt,
+    axis: Optional[int] = ...,
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> Union[_ScalarNumpy, ndarray]: ...
+def reshape(a: _ArrayLike, newshape: _ShapeLike, order: _Order = ...) -> ndarray: ...
+@overload
+def choose(
+    a: _ScalarGeneric,
+    choices: Union[Sequence[_ArrayLike], ndarray],
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> _ScalarGeneric: ...
+@overload
+def choose(
+    a: _Scalar,
+    choices: Union[Sequence[_ArrayLike], ndarray],
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> _ScalarNumpy: ...
+@overload
+def choose(
+    a: _ArrayLike,
+    choices: Union[Sequence[_ArrayLike], ndarray],
+    out: Optional[ndarray] = ...,
+    mode: _Mode = ...,
+) -> ndarray: ...
+def repeat(
+    a: _ArrayLike, repeats: _ArrayLikeInt, axis: Optional[int] = ...
+) -> ndarray: ...
+def put(a: ndarray, ind: _ArrayLikeInt, v: _ArrayLike, mode: _Mode = ...) -> None: ...
+def swapaxes(
+    a: Union[Sequence[_ArrayLike], ndarray], axis1: int, axis2: int
+) -> ndarray: ...
+def transpose(
+    a: _ArrayLike, axes: Union[None, Sequence[int], ndarray] = ...
+) -> ndarray: ...
+def partition(
+    a: _ArrayLike,
+    kth: _ArrayLikeInt,
+    axis: Optional[int] = ...,
+    kind: _PartitionKind = ...,
+    order: Union[None, str, Sequence[str]] = ...,
+) -> ndarray: ...
+def argpartition(
+    a: _ArrayLike,
+    kth: _ArrayLikeInt,
+    axis: Optional[int] = ...,
+    kind: _PartitionKind = ...,
+    order: Union[None, str, Sequence[str]] = ...,
+) -> ndarray: ...
+def sort(
+    a: Union[Sequence[_ArrayLike], ndarray],
+    axis: Optional[int] = ...,
+    kind: Optional[_SortKind] = ...,
+    order: Union[None, str, Sequence[str]] = ...,
+) -> ndarray: ...
+def argsort(
+    a: Union[Sequence[_ArrayLike], ndarray],
+    axis: Optional[int] = ...,
+    kind: Optional[_SortKind] = ...,
+    order: Union[None, str, Sequence[str]] = ...,
+) -> ndarray: ...
diff --git a/tests/fail/fromnumeric.py b/tests/fail/fromnumeric.py
new file mode 100644
index 0000000..9d01f21
--- /dev/null
+++ b/tests/fail/fromnumeric.py
@@ -0,0 +1,62 @@
+"""Tests for :mod:`numpy.core.fromnumeric`."""
+
+import numpy as np
+
+A = np.array(True, ndmin=2, dtype=bool)
+A.setflags(write=False)
+
+a = np.bool_(True)
+
+np.take(a, None)  # E: No overload variant of "take" matches argument types
+np.take(a, axis=1.0)  # E: No overload variant of "take" matches argument types
+np.take(A, out=1)  # E: No overload variant of "take" matches argument types
+np.take(A, mode="bob")  # E: No overload variant of "take" matches argument types
+
+np.reshape(a, None)  # E: Argument 2 to "reshape" has incompatible type
+np.reshape(A, 1, order="bob")  # E: Argument "order" to "reshape" has incompatible type
+
+np.choose(a, None)  # E: No overload variant of "choose" matches argument types
+np.choose(a, out=1.0)  # E: No overload variant of "choose" matches argument types
+np.choose(A, mode="bob")  # E: No overload variant of "choose" matches argument types
+
+np.repeat(a, None)  # E: Argument 2 to "repeat" has incompatible type
+np.repeat(A, 1, axis=1.0)  # E: Argument "axis" to "repeat" has incompatible type
+
+np.swapaxes(a, 0, 0)  # E: Argument 1 to "swapaxes" has incompatible type
+np.swapaxes(A, None, 1)  # E: Argument 2 to "swapaxes" has incompatible type
+np.swapaxes(A, 1, [0])  # E: Argument 3 to "swapaxes" has incompatible type
+
+np.transpose(a, axes=1)  # E: Argument "axes" to "transpose" has incompatible type
+np.transpose(A, axes=1.0)  # E: Argument "axes" to "transpose" has incompatible type
+
+np.partition(a, None)  # E: Argument 2 to "partition" has incompatible type
+np.partition(
+    a, 0, axis="bob"  # E: Argument "axis" to "partition" has incompatible type
+)
+np.partition(
+    A, 0, kind="bob"  # E: Argument "kind" to "partition" has incompatible type
+)
+np.partition(
+    A, 0, order=range(5)  # E: Argument "order" to "partition" has incompatible type
+)
+
+np.argpartition(a, None)  # E: Argument 2 to "argpartition" has incompatible type
+np.argpartition(
+    a, 0, axis="bob"  # E: Argument "axis" to "argpartition" has incompatible type
+)
+np.argpartition(
+    A, 0, kind="bob"  # E: Argument "kind" to "argpartition" has incompatible type
+)
+np.argpartition(
+    A, 0, order=range(5)  # E: Argument "order" to "argpartition" has incompatible type
+)
+
+np.sort(a)  # E: Argument 1 to "sort" has incompatible type
+np.sort(A, axis="bob")  # E: Argument "axis" to "sort" has incompatible type
+np.sort(A, kind="bob")  # E: Argument "kind" to "sort" has incompatible type
+np.sort(A, order=range(5))  # E: Argument "order" to "sort" has incompatible type
+
+np.argsort(a)  # E: Argument 1 to "argsort" has incompatible type
+np.argsort(A, axis="bob")  # E: Argument "axis" to "argsort" has incompatible type
+np.argsort(A, kind="bob")  # E: Argument "kind" to "argsort" has incompatible type
+np.argsort(A, order=range(5))  # E: Argument "order" to "argsort" has incompatible type
diff --git a/tests/pass/fromnumeric.py b/tests/pass/fromnumeric.py
new file mode 100644
index 0000000..1e7ba57
--- /dev/null
+++ b/tests/pass/fromnumeric.py
@@ -0,0 +1,65 @@
+"""Tests for :mod:`numpy.core.fromnumeric`."""
+
+import numpy as np
+
+A = np.array(True, ndmin=2, dtype=bool)
+B = np.array(1.0, ndmin=2, dtype=np.float32)
+A.setflags(write=False)
+B.setflags(write=False)
+
+a = np.bool_(True)
+b = np.float32(1.0)
+c = 1.0
+
+np.take(a, 0)
+np.take(b, 0)
+np.take(c, 0)
+np.take(A, 0)
+np.take(B, 0)
+np.take(A, [0])
+np.take(B, [0])
+
+np.reshape(a, 1)
+np.reshape(b, 1)
+np.reshape(c, 1)
+np.reshape(A, 1)
+np.reshape(B, 1)
+
+np.choose(a, [True])
+np.choose(b, [1.0])
+np.choose(c, [1.0])
+np.choose(A, [True])
+np.choose(B, [1.0])
+
+np.repeat(a, 1)
+np.repeat(b, 1)
+np.repeat(c, 1)
+np.repeat(A, 1)
+np.repeat(B, 1)
+
+np.swapaxes(A, 0, 0)
+np.swapaxes(B, 0, 0)
+
+np.transpose(a)
+np.transpose(b)
+np.transpose(c)
+np.transpose(A)
+np.transpose(B)
+
+np.partition(a, 0)
+np.partition(b, 0)
+np.partition(c, 0)
+np.partition(A, 0)
+np.partition(B, 0)
+
+np.argpartition(a, 0)
+np.argpartition(b, 0)
+np.argpartition(c, 0)
+np.argpartition(A, 0)
+np.argpartition(B, 0)
+
+np.sort(A, 0)
+np.sort(B, 0)
+
+np.argsort(A, 0)
+np.argsort(B, 0)
diff --git a/tests/reveal/fromnumeric.py b/tests/reveal/fromnumeric.py
new file mode 100644
index 0000000..82450df
--- /dev/null
+++ b/tests/reveal/fromnumeric.py
@@ -0,0 +1,85 @@
+"""Tests for :mod:`numpy.core.fromnumeric`."""
+
+import numpy as np
+
+A = np.array(True, ndmin=2, dtype=bool)
+B = np.array(1.0, ndmin=2, dtype=np.float32)
+A.setflags(write=False)
+B.setflags(write=False)
+
+a = np.bool_(True)
+b = np.float32(1.0)
+c = 1.0
+
+reveal_type(np.take(a, 0))  # E: numpy.bool_
+reveal_type(np.take(b, 0))  # E: numpy.float32
+reveal_type(
+    np.take(c, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
+)
+reveal_type(
+    np.take(A, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
+)
+reveal_type(
+    np.take(B, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
+)
+reveal_type(
+    np.take(  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta, numpy.ndarray]
+        A, [0]
+    )
+)
+reveal_type(
+    np.take(  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta, numpy.ndarray]
+        B, [0]
+    )
+)
+
+reveal_type(np.reshape(a, 1))  # E: numpy.ndarray
+reveal_type(np.reshape(b, 1))  # E: numpy.ndarray
+reveal_type(np.reshape(c, 1))  # E: numpy.ndarray
+reveal_type(np.reshape(A, 1))  # E: numpy.ndarray
+reveal_type(np.reshape(B, 1))  # E: numpy.ndarray
+
+reveal_type(np.choose(a, [True]))  # E: numpy.bool_
+reveal_type(np.choose(b, [1.0]))  # E: numpy.float32
+reveal_type(
+    np.choose(  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
+        c, [1.0]
+    )
+)
+reveal_type(np.choose(A, [True]))  # E: numpy.ndarray
+reveal_type(np.choose(B, [1.0]))  # E: numpy.ndarray
+
+reveal_type(np.repeat(a, 1))  # E: numpy.ndarray
+reveal_type(np.repeat(b, 1))  # E: numpy.ndarray
+reveal_type(np.repeat(c, 1))  # E: numpy.ndarray
+reveal_type(np.repeat(A, 1))  # E: numpy.ndarray
+reveal_type(np.repeat(B, 1))  # E: numpy.ndarray
+
+# TODO: Add tests for np.put()
+
+reveal_type(np.swapaxes(A, 0, 0))  # E: numpy.ndarray
+reveal_type(np.swapaxes(B, 0, 0))  # E: numpy.ndarray
+
+reveal_type(np.transpose(a))  # E: numpy.ndarray
+reveal_type(np.transpose(b))  # E: numpy.ndarray
+reveal_type(np.transpose(c))  # E: numpy.ndarray
+reveal_type(np.transpose(A))  # E: numpy.ndarray
+reveal_type(np.transpose(B))  # E: numpy.ndarray
+
+reveal_type(np.partition(a, 0))  # E: numpy.ndarray
+reveal_type(np.partition(b, 0))  # E: numpy.ndarray
+reveal_type(np.partition(c, 0))  # E: numpy.ndarray
+reveal_type(np.partition(A, 0))  # E: numpy.ndarray
+reveal_type(np.partition(B, 0))  # E: numpy.ndarray
+
+reveal_type(np.argpartition(a, 0))  # E: numpy.ndarray
+reveal_type(np.argpartition(b, 0))  # E: numpy.ndarray
+reveal_type(np.argpartition(c, 0))  # E: numpy.ndarray
+reveal_type(np.argpartition(A, 0))  # E: numpy.ndarray
+reveal_type(np.argpartition(B, 0))  # E: numpy.ndarray
+
+reveal_type(np.sort(A, 0))  # E: numpy.ndarray
+reveal_type(np.sort(B, 0))  # E: numpy.ndarray
+
+reveal_type(np.argsort(A, 0))  # E: numpy.ndarray
+reveal_type(np.argsort(B, 0))  # E: numpy.ndarray