diff --git a/.github/workflows/check.yml b/.github/workflows/check.yml
new file mode 100644
index 0000000..0d2f11a
--- /dev/null
+++ b/.github/workflows/check.yml
@@ -0,0 +1,53 @@
+name: check
+
+on:
+  workflow_dispatch:
+  pull_request:
+  push:
+    branches:
+    - main
+
+jobs:
+
+  standard:
+
+    strategy:
+      fail-fast: false
+      matrix:
+        runs-on: [ubuntu-latest, macos-latest, windows-latest]
+
+    defaults:
+      run:
+        shell: bash -l {0}
+
+    name: ${{ matrix.runs-on }} • x64 ${{ matrix.args }}
+    runs-on: ${{ matrix.runs-on }}
+
+    steps:
+
+    - name: Basic GitHub action setup
+      uses: actions/checkout@v3
+
+    - name: Set conda environment
+      uses: mamba-org/provision-with-micromamba@main
+      with:
+        environment-file: environment-dev.yml
+        environment-name: myenv
+        cache-env: true
+        extra-specs: |
+          prettytable
+          setuptools_scm
+          scikit-build
+          xsimd
+
+    - name: Set dummy version
+      run: echo "SETUPTOOLS_SCM_PRETEND_VERSION=0.0" >> $GITHUB_ENV
+
+    - name: Build and install Python module
+      working-directory: python-module
+      run: |
+        SKBUILD_CONFIGURE_OPTIONS="-DUSE_XSIMD=1" python -m pip install . -v
+
+    - name: Run Python tests
+      working-directory: python-module
+      run: python -m unittest discover tests
diff --git a/.github/workflows/profile.yml b/.github/workflows/profile.yml
new file mode 100644
index 0000000..f838a48
--- /dev/null
+++ b/.github/workflows/profile.yml
@@ -0,0 +1,53 @@
+name: profile
+
+on:
+  workflow_dispatch:
+  pull_request:
+  push:
+    branches:
+    - main
+
+jobs:
+
+  standard:
+
+    strategy:
+      fail-fast: false
+      matrix:
+        runs-on: [ubuntu-latest, macos-latest, windows-latest]
+
+    defaults:
+      run:
+        shell: bash -l {0}
+
+    name: ${{ matrix.runs-on }} • x64 ${{ matrix.args }}
+    runs-on: ${{ matrix.runs-on }}
+
+    steps:
+
+    - name: Basic GitHub action setup
+      uses: actions/checkout@v3
+
+    - name: Set conda environment
+      uses: mamba-org/provision-with-micromamba@main
+      with:
+        environment-file: environment-dev.yml
+        environment-name: myenv
+        cache-env: true
+        extra-specs: |
+          prettytable
+          setuptools_scm
+          scikit-build
+          xsimd
+
+    - name: Set dummy version
+      run: echo "SETUPTOOLS_SCM_PRETEND_VERSION=0.0" >> $GITHUB_ENV
+
+    - name: Build and install Python module
+      working-directory: python-module
+      run: |
+        SKBUILD_CONFIGURE_OPTIONS="-DUSE_XSIMD=1" python -m pip install . -v
+
+    - name: Run Python profiling
+      working-directory: python-module
+      run: python -m unittest discover profiling
diff --git a/.gitignore b/.gitignore
index 9413a44..72c0e07 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,5 @@
+_skbuild
+
 # Prerequisites
 *.d
 
diff --git a/environment-dev.yml b/environment-dev.yml
index 6dff19f..2386b82 100644
--- a/environment-dev.yml
+++ b/environment-dev.yml
@@ -5,9 +5,9 @@ dependencies:
   # Build dependencies
   - cmake
   # Host dependencies
-  - xtensor=0.24.0
+  - xtensor >=0.24.0
   - numpy
-  - pybind11=2.4.3
+  - pybind11 >=2.4.3
   # Test dependencies
   - pytest
 
diff --git a/python-module/CMakeLists.txt b/python-module/CMakeLists.txt
new file mode 100644
index 0000000..44391a6
--- /dev/null
+++ b/python-module/CMakeLists.txt
@@ -0,0 +1,63 @@
+cmake_minimum_required(VERSION 3.18..3.21)
+
+project(xt)
+
+# The C++ functions are build to a library with name "_${PROJECT_NAME}"
+# The Python library simply loads all functions
+set(PYPROJECT_NAME "_${PROJECT_NAME}")
+
+option(USE_WARNINGS "${PROJECT_NAME}: Build with runtime warnings" ON)
+option(USE_XSIMD "${PROJECT_NAME}: Build with hardware optimization" OFF)
+
+if (DEFINED ENV{SETUPTOOLS_SCM_PRETEND_VERSION})
+    set(PROJECT_VERSION $ENV{SETUPTOOLS_SCM_PRETEND_VERSION})
+    message(STATUS "Building ${PROJECT_NAME} ${PROJECT_VERSION} (read from SETUPTOOLS_SCM_PRETEND_VERSION)")
+else()
+    execute_process(
+        COMMAND python -c "from setuptools_scm import get_version; print(get_version(root='..'))"
+        WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
+        OUTPUT_VARIABLE PROJECT_VERSION
+        OUTPUT_STRIP_TRAILING_WHITESPACE)
+
+    message(STATUS "Building ${PROJECT_NAME} ${PROJECT_VERSION}")
+endif()
+
+if(NOT CMAKE_BUILD_TYPE)
+    set(CMAKE_BUILD_TYPE Release)
+endif()
+
+find_package(xtensor REQUIRED)
+find_package(pybind11 REQUIRED CONFIG)
+
+if (SKBUILD)
+    find_package(NumPy REQUIRED)
+else()
+    find_package(Python REQUIRED COMPONENTS Interpreter Development NumPy)
+endif()
+
+pybind11_add_module(${PYPROJECT_NAME} module/main.cpp)
+
+target_compile_definitions(${PYPROJECT_NAME} PUBLIC VERSION_INFO=${PROJECT_VERSION})
+target_link_libraries(${PYPROJECT_NAME} PUBLIC xtensor)
+target_include_directories(${PYPROJECT_NAME} PUBLIC "../include")
+
+if (SKBUILD)
+    target_include_directories(${PYPROJECT_NAME} PUBLIC ${NumPy_INCLUDE_DIRS})
+else()
+    target_link_libraries(${PYPROJECT_NAME} PUBLIC pybind11::module Python::NumPy)
+endif()
+
+if (USE_SIMD)
+    find_package(xsimd REQUIRED)
+    target_link_libraries(${PYPROJECT_NAME} PUBLIC xtensor::optimize xtensor::use_xsimd)
+    message(STATUS "Compiling ${PROJECT_NAME}-Python with hardware optimization")
+endif()
+
+if (SKBUILD)
+    if(APPLE)
+        set_target_properties(${PYPROJECT_NAME} PROPERTIES INSTALL_RPATH "@loader_path/${CMAKE_INSTALL_LIBDIR}")
+    else()
+        set_target_properties(${PYPROJECT_NAME} PROPERTIES INSTALL_RPATH "$ORIGIN/${CMAKE_INSTALL_LIBDIR}")
+    endif()
+    install(TARGETS ${PYPROJECT_NAME} DESTINATION .)
+endif()
diff --git a/python-module/module/main.cpp b/python-module/module/main.cpp
new file mode 100644
index 0000000..4a6e89a
--- /dev/null
+++ b/python-module/module/main.cpp
@@ -0,0 +1,60 @@
+/**
+ * @file
+ * @copyright Copyright 2020. Tom de Geus. All rights reserved.
+ * @license This project is released under the GNU Public License (MIT).
+ */
+
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+
+#define FORCE_IMPORT_ARRAY
+#include <xtensor-python/pyarray.hpp>
+#include <xtensor-python/pytensor.hpp>
+#include <xtensor.hpp>
+
+namespace py = pybind11;
+
+/**
+ * Overrides the `__name__` of a module.
+ * Classes defined by pybind11 use the `__name__` of the module as of the time they are defined,
+ * which affects the `__repr__` of the class type objects.
+ */
+class ScopedModuleNameOverride {
+public:
+    explicit ScopedModuleNameOverride(py::module m, std::string name) : module_(std::move(m))
+    {
+        original_name_ = module_.attr("__name__");
+        module_.attr("__name__") = name;
+    }
+    ~ScopedModuleNameOverride()
+    {
+        module_.attr("__name__") = original_name_;
+    }
+
+private:
+    py::module module_;
+    py::object original_name_;
+};
+
+PYBIND11_MODULE(_xt, m)
+{
+    // Ensure members to display as `xt.X` (not `xt._xt.X`)
+    ScopedModuleNameOverride name_override(m, "xt");
+
+    xt::import_numpy();
+
+    m.doc() = "Python bindings of xtensor";
+
+    m.def("mean", [](const xt::pyarray<double>& a) -> xt::pyarray<double> { return xt::mean(a); });
+    m.def("average", [](const xt::pyarray<double>& a, const xt::pyarray<double>& w) -> xt::pyarray<double> { return xt::average(a, w); });
+    m.def("average", [](const xt::pyarray<double>& a, const xt::pyarray<double>& w, const std::vector<ptrdiff_t>& axes) -> xt::pyarray<double> { return xt::average(a, w, axes); });
+
+    m.def("flip", [](const xt::pyarray<double>& a, ptrdiff_t axis) -> xt::pyarray<double> { return xt::flip(a, axis); });
+
+    m.def("cos", [](const xt::pyarray<double>& a) -> xt::pyarray<double> { return xt::cos(a); });
+
+    m.def("isin", [](const xt::pyarray<int>& a, const xt::pyarray<int>& b) -> xt::pyarray<bool> { return xt::isin(a, b); });
+    m.def("in1d", [](const xt::pyarray<int>& a, const xt::pyarray<int>& b) -> xt::pyarray<bool> { return xt::in1d(a, b); });
+
+
+}
diff --git a/python-module/module/xt/__init__.py b/python-module/module/xt/__init__.py
new file mode 100644
index 0000000..eadaf1c
--- /dev/null
+++ b/python-module/module/xt/__init__.py
@@ -0,0 +1 @@
+from ._xt import *  # noqa: F401, F403
diff --git a/python-module/profiling/test_a.py b/python-module/profiling/test_a.py
new file mode 100644
index 0000000..a35957d
--- /dev/null
+++ b/python-module/profiling/test_a.py
@@ -0,0 +1,79 @@
+import unittest
+import timeit
+import warnings
+from prettytable import PrettyTable
+
+import xt
+import numpy as np
+
+
+class test_a(unittest.TestCase):
+    """
+    ??
+    """
+
+    @classmethod
+    def setUpClass(self):
+
+        self.a = np.random.random([103, 102, 101])
+        self.axis = int(np.random.randint(0, high=3))
+        self.data = []
+
+    @classmethod
+    def tearDownClass(self):
+
+        self.data = sorted(self.data, key=lambda x: x[1])
+
+        table = PrettyTable(["function", "xtensor / numpy"])
+
+        for row in self.data:
+            table.add_row(row)
+
+        print("")
+        print(table)
+        print("")
+
+        # code = table.get_html_string()
+        # with open('profile.html', 'w') as file:
+        #     file.write(code)
+
+    def test_mean(self):
+
+        n = timeit.timeit(lambda: np.mean(self.a), number=10)
+        x = timeit.timeit(lambda: xt.mean(self.a), number=10)
+        self.data.append(("mean", x / n))
+
+    def test_flip(self):
+
+        n = timeit.timeit(lambda: np.flip(self.a, self.axis), number=10)
+        x = timeit.timeit(lambda: xt.flip(self.a, self.axis), number=10)
+        self.data.append(("flip", x / n))
+
+    def test_cos(self):
+
+        n = timeit.timeit(lambda: np.cos(self.a), number=10)
+        x = timeit.timeit(lambda: xt.cos(self.a), number=10)
+        self.data.append(("cos", x / n))
+
+    def test_isin(self):
+
+        a = (np.random.random([103, 102]) * 1000).astype(np.intc)
+        b = (np.random.random([103, 102]) * 1000).astype(np.intc)
+
+        n = timeit.timeit(lambda: np.isin(a, b), number=10)
+        x = timeit.timeit(lambda: xt.isin(a, b), number=10)
+        self.data.append(("isin", x / n))
+
+    def test_in1d(self):
+
+        a = (np.random.random([1003]) * 1000).astype(np.intc)
+        b = (np.random.random([1003]) * 1000).astype(np.intc)
+
+        n = timeit.timeit(lambda: np.in1d(a, b), number=10)
+        x = timeit.timeit(lambda: xt.in1d(a, b), number=10)
+        self.data.append(("in1d", x / n))
+
+
+if __name__ == "__main__":
+
+    unittest.main()
diff --git a/python-module/setup.py b/python-module/setup.py
new file mode 100644
index 0000000..a8e9f26
--- /dev/null
+++ b/python-module/setup.py
@@ -0,0 +1,24 @@
+from pathlib import Path
+
+from setuptools_scm import get_version
+from skbuild import setup
+
+project_name = "xt"
+
+this_directory = Path(__file__).parent
+long_description = (this_directory / ".." / "README.md").read_text()
+license = (this_directory / ".." / "LICENSE").read_text()
+
+setup(
+    name=project_name,
+    description="xt - Python bindings of xtensor",
+    long_description=long_description,
+    version=get_version(root="..", relative_to=__file__),
+    license=license,
+    author="Tom de Geus",
+    url=f"ttps://github.com/xtensor-stack/{project_name}",
+    packages=[f"{project_name}"],
+    package_dir={"": "module"},
+    cmake_install_dir=f"module/{project_name}",
+    cmake_minimum_required_version="3.13",
+)
diff --git a/python-module/tests/__init__.py b/python-module/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/python-module/tests/test_a.py b/python-module/tests/test_a.py
new file mode 100644
index 0000000..98d18eb
--- /dev/null
+++ b/python-module/tests/test_a.py
@@ -0,0 +1,59 @@
+import unittest
+
+import xt
+import numpy as np
+
+
+class test_a(unittest.TestCase):
+    """
+    ??
+    """
+
+    def test_mean(self):
+
+        a = np.random.random([103, 102, 101])
+        n = np.mean(a)
+        x = xt.mean(a)
+
+        self.assertTrue(np.allclose(n, x))
+
+    def test_average(self):
+
+        a = np.random.random([103, 102, 101])
+        w = np.random.random([103, 102, 101])
+        n = np.average(a, weights=w)
+        x = xt.average(a, w)
+
+        self.assertTrue(np.allclose(n, x))
+
+    def test_average_axes(self):
+
+        a = np.random.random([103, 102, 101])
+        w = np.random.random([103, 102, 101])
+        axis = int(np.random.randint(0, high=3))
+        n = np.average(a, weights=w, axis=(axis,))
+        x = xt.average(a, w, [axis])
+
+        self.assertTrue(np.allclose(n, x))
+
+    def test_flip(self):
+
+        axis = int(np.random.randint(0, high=3))
+        a = np.random.random([103, 102, 101])
+        n = np.flip(a, axis)
+        x = xt.flip(a, axis)
+
+        self.assertTrue(np.allclose(n, x))
+
+    def test_cos(self):
+
+        a = np.random.random([103, 102, 101])
+        n = np.cos(a)
+        x = xt.cos(a)
+
+        self.assertTrue(np.allclose(n, x))
+
+
+if __name__ == "__main__":
+
+    unittest.main()