diff --git a/Python/cython/Makefile b/Python/cython/Makefile
new file mode 100644
index 00000000..618641b4
--- /dev/null
+++ b/Python/cython/Makefile
@@ -0,0 +1,11 @@
+.PHONY: build clean test
+
+build:
+	python setup.py build_ext --inplace
+
+clean:
+	rm -f compute.c hpc_kernels.o compute*.so compute*.pyd
+	rm -rf build *.egg-info
+
+test: build
+	python driver.py
diff --git a/Python/cython/README.md b/Python/cython/README.md
new file mode 100644
index 00000000..d6e0d612
--- /dev/null
+++ b/Python/cython/README.md
@@ -0,0 +1,61 @@
+# Cython Shared Library - HPCTrainingExamples Kernels
+
+This example wraps **actual C computation kernels from the HPCTrainingExamples repo** into a Python-callable shared library (`.so` / `.pyd`) using Cython.
+
+## Wrapped Kernels
+
+| Function | Original Source | Description |
+|---|---|---|
+| `py_cpu_func(inp)` | `ManagedMemory/CPU_Code/cpu_code.c` | Doubles every element: `out[i] = in[i] * 2.0` |
+| `py_saxpy(a, x, y)` | `Pragma_Examples/OpenMP/C/1_saxpy` | SAXPY: `y = a*x + y` |
+| `py_vecadd(a, b)` | `Pragma_Examples/OpenMP/C/3_vecadd` | Vector addition: `c = a + b` |
+| `py_reduction(x)` | `Pragma_Examples/OpenMP/C/2_reduction` | Sum-reduction of an array |
+
+The core loops in [hpc_kernels.c](hpc_kernels.c) are extracted directly from the original repo sources (with `main()` and OpenMP timing scaffolding removed). The Cython wrapper in [compute.pyx](compute.pyx) calls into these C functions and handles NumPy array ↔ C pointer conversion.
+
+## Prerequisites
+
+```bash
+pip install cython numpy
+```
+
+## Build
+
+```bash
+# Option 1 - Makefile
+make build
+
+# Option 2 - setup.py directly
+python setup.py build_ext --inplace
+```
+
+This compiles `hpc_kernels.c` + `compute.pyx` into `compute.<platform>.so`.
+
+## Run
+
+```bash
+make test
+# or
+python driver.py
+```
+
+The driver benchmarks each Cython-wrapped kernel against its NumPy equivalent and validates correctness using the same expected values as the original C programs.
+
+## Clean
+
+```bash
+make clean
+```
+
+## File Layout
+
+```
+Python/cython/
+├── hpc_kernels.h      C declarations for the kernels
+├── hpc_kernels.c      C kernel implementations (from repo)
+├── compute.pyx        Cython wrapper module
+├── setup.py           Build script (setuptools + Cython)
+├── driver.py          Benchmark / validation driver
+├── Makefile           Build automation
+└── README.md
+```
diff --git a/Python/cython/compute.pyx b/Python/cython/compute.pyx
new file mode 100644
index 00000000..3df3a2f5
--- /dev/null
+++ b/Python/cython/compute.pyx
@@ -0,0 +1,78 @@
+# cython: boundscheck=False, wraparound=False, cdivision=True
+"""
+Cython wrappers around C kernels from HPCTrainingExamples.
+
+Wraps the following repo examples as a shared library:
+  - cpu_func     (ManagedMemory/CPU_Code/cpu_code.c)
+  - saxpy        (Pragma_Examples/OpenMP/C/1_saxpy)
+  - vecadd       (Pragma_Examples/OpenMP/C/3_vecadd)
+  - reduction    (Pragma_Examples/OpenMP/C/2_reduction)
+"""
+
+import numpy as np
+cimport numpy as np
+
+ctypedef np.float64_t DOUBLE_t
+ctypedef np.float32_t FLOAT_t
+
+
+cdef extern from "hpc_kernels.h":
+    void cpu_func(double *inp, double *out, int M)
+    void saxpy(float a, float *x, float *y, int N)
+    void vecadd(double *a, double *b, double *c, int N)
+    double reduction(double *x, int n)
+
+
+# Python wrappers around the c kernels.
+
+def py_cpu_func(np.ndarray[DOUBLE_t, ndim=1] inp):
+    """Double every element  (ManagedMemory/CPU_Code/cpu_code.c  cpu_func)."""
+    # Ensure correct dtype and contiguous memory to safely take &inp[0]
+    inp_c = np.ascontiguousarray(inp, dtype=np.float64)
+    cdef int M = inp_c.shape[0]
+    if M == 0:
+        return np.empty(0, dtype=np.float64)
+    cdef np.ndarray[DOUBLE_t, ndim=1] out = np.empty(M, dtype=np.float64)
+    cpu_func(&inp_c[0], &out[0], M)
+    return out
+
+
+def py_saxpy(float a,
+             np.ndarray[FLOAT_t, ndim=1] x,
+             np.ndarray[FLOAT_t, ndim=1] y):
+    """y = a*x + y  (Pragma_Examples/OpenMP/C/1_saxpy  saxpy)."""
+    # Coerce to float32 contiguous arrays and check lengths
+    x_c = np.ascontiguousarray(x, dtype=np.float32)
+    y_c = np.ascontiguousarray(y, dtype=np.float32)
+    cdef int N = x_c.shape[0]
+    if y_c.shape[0] != N:
+        raise ValueError("x and y must have the same length")
+    if N == 0:
+        return y_c.copy()
+    cdef np.ndarray[FLOAT_t, ndim=1] y_out = y_c.copy()
+    saxpy(a, &x_c[0], &y_out[0], N)
+    return y_out
+
+
+def py_vecadd(np.ndarray[DOUBLE_t, ndim=1] a,
+              np.ndarray[DOUBLE_t, ndim=1] b):
+    """c = a + b  (Pragma_Examples/OpenMP/C/3_vecadd  vecadd)."""
+    a_c = np.ascontiguousarray(a, dtype=np.float64)
+    b_c = np.ascontiguousarray(b, dtype=np.float64)
+    cdef int N = a_c.shape[0]
+    if b_c.shape[0] != N:
+        raise ValueError("a and b must have the same length")
+    if N == 0:
+        return np.empty(0, dtype=np.float64)
+    cdef np.ndarray[DOUBLE_t, ndim=1] c = np.empty(N, dtype=np.float64)
+    vecadd(&a_c[0], &b_c[0], &c[0], N)
+    return c
+
+
+def py_reduction(np.ndarray[DOUBLE_t, ndim=1] x):
+    """Sum all elements  (Pragma_Examples/OpenMP/C/2_reduction  reduction)."""
+    x_c = np.ascontiguousarray(x, dtype=np.float64)
+    cdef int n = x_c.shape[0]
+    if n == 0:
+        return 0.0
+    return reduction(&x_c[0], n)
diff --git a/Python/cython/driver.py b/Python/cython/driver.py
new file mode 100644
index 00000000..207b4d8f
--- /dev/null
+++ b/Python/cython/driver.py
@@ -0,0 +1,111 @@
+#!/usr/bin/env python3
+"""
+Driver for the Cython-wrapped HPC Training Examples kernels.
+
+Exercises every kernel from the shared library and validates
+results against NumPy equivalents, matching the behaviour of
+the original C programs in the repo.
+"""
+
+import time
+import numpy as np
+
+try:
+    import compute
+except ImportError:
+    raise ImportError(
+        "Could not import the 'compute' shared library.\n"
+        "Build it first:  python setup.py build_ext --inplace"
+    )
+
+
+def bench(label, func, *args, repeats=50):
+    """Time a function and return its result."""
+    result = func(*args)  # warm-up
+    t0 = time.perf_counter()
+    for _ in range(repeats):
+        func(*args)
+    elapsed = (time.perf_counter() - t0) / repeats
+    print(f"  {label:40s}  {elapsed*1e6:10.1f} us")
+    return result
+
+
+def test_cpu_func():
+    """ManagedMemory/CPU_Code/cpu_code.c — doubles every element."""
+    M = 100_000
+    inp = np.ones(M, dtype=np.float64)
+
+    out = bench("Cython  cpu_func", compute.py_cpu_func, inp)
+
+    # The original C program expects sum(out) == 200000
+    assert np.allclose(out, inp * 2.0), "cpu_func mismatch!"
+    total = out.sum()
+    print(f"  Result is {total:.6f}  (expected {M * 2.0:.6f})")
+
+
+def test_saxpy():
+    """Pragma_Examples/OpenMP/C/1_saxpy — y = a*x + y."""
+    N = 1_000_000
+    a = np.float32(2.0)
+    x = np.ones(N, dtype=np.float32)
+    y = np.full(N, 2.0, dtype=np.float32)
+
+    y_out = bench("Cython  saxpy", compute.py_saxpy, a, x, y)
+    y_ref = bench("NumPy   a*x + y", lambda: a * x + y)
+
+    # Original program expects y[0] == 4.0, y[N-1] == 4.0
+    assert np.allclose(y_out, a * x + y), "saxpy mismatch!"
+    print(f"  y[0] {y_out[0]:.6f}  y[N-1] {y_out[-1]:.6f}  (expected 4.0)")
+
+
+def test_vecadd():
+    """Pragma_Examples/OpenMP/C/3_vecadd — c = a + b."""
+    N = 100_000
+    a = np.array([np.sin(i+1)**2 for i in range(N)], dtype=np.float64)
+    b = np.array([np.cos(i+1)**2 for i in range(N)], dtype=np.float64)
+
+    c_cy = bench("Cython  vecadd", compute.py_vecadd, a, b)
+    c_np = bench("NumPy   a + b", np.add, a, b)
+
+    assert np.allclose(c_cy, c_np), "vecadd mismatch!"
+    # Original expects mean(c) ≈ 1.0 (sin²+cos²=1)
+    avg = c_cy.mean()
+    print(f"  Final result: {avg:.6f}  (expected ≈1.0)")
+
+
+def test_reduction():
+    """Pragma_Examples/OpenMP/C/2_reduction — sum of array."""
+    n = 100_000
+    x = np.full(n, 2.0, dtype=np.float64)
+
+    s_cy = bench("Cython  reduction", compute.py_reduction, x)
+    s_np = bench("NumPy   np.sum", np.sum, x)
+
+    # Original expects sum == 200000
+    assert abs(s_cy - s_np) < 1e-6, "reduction mismatch!"
+    print(f"  Sum={s_cy:.6f}  (expected {n * 2.0:.6f})")
+
+
+def main():
+    print("=" * 62)
+    print("HPCTrainingExamples — Cython Shared Library Tests")
+    print("=" * 62)
+
+    print(f"\n--- cpu_func (ManagedMemory/CPU_Code) ---")
+    test_cpu_func()
+
+    print(f"\n--- saxpy (Pragma_Examples/OpenMP/C/1_saxpy) ---")
+    test_saxpy()
+
+    print(f"\n--- vecadd (Pragma_Examples/OpenMP/C/3_vecadd) ---")
+    test_vecadd()
+
+    print(f"\n--- reduction (Pragma_Examples/OpenMP/C/2_reduction) ---")
+    test_reduction()
+
+    print(f"\n{'=' * 62}")
+    print("All tests passed.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Python/cython/hpc_kernels.c b/Python/cython/hpc_kernels.c
new file mode 100644
index 00000000..0a5bd376
--- /dev/null
+++ b/Python/cython/hpc_kernels.c
@@ -0,0 +1,43 @@
+/*
+ * hpc_kernels.c
+ *
+ * CPU computation kernels extracted from HPCTrainingExamples.
+ * Each function mirrors the core loop from the original source
+ * (with the main() and OpenMP/timing scaffolding stripped out so
+ * the pure kernel can be called from Python via Cython).
+ *
+ * Original sources:
+ *   cpu_func  - ManagedMemory/CPU_Code/cpu_code.c
+ *   saxpy     - Pragma_Examples/OpenMP/C/1_saxpy/0_saxpy_portyourself/saxpy.c
+ *   vecadd    - Pragma_Examples/OpenMP/C/3_vecadd/0_vecadd_portyourself/vecadd.c
+ *   reduction - Pragma_Examples/OpenMP/C/2_reduction/0_reduction_portyourself/reduction.c
+ */
+
+#include "hpc_kernels.h"
+
+/* cpu_func (ManagedMemory/CPU_Code/cpu_code.c) */
+void cpu_func(double *in, double *out, int M) {
+    for (int i = 0; i < M; i++) {
+        out[i] = in[i] * 2.0;
+    }
+}
+
+void saxpy(float a, float *x, float *y, int N) {
+    for (int i = 0; i < N; i++) {
+        y[i] = a * x[i] + y[i];
+    }
+}
+
+void vecadd(double *a, double *b, double *c, int N) {
+    for (int i = 0; i < N; i++) {
+        c[i] = a[i] + b[i];
+    }
+}
+
+double reduction(double *x, int n) {
+    double sum = 0.0;
+    for (int i = 0; i < n; i++) {
+        sum = sum + x[i];
+    }
+    return sum;
+}
diff --git a/Python/cython/hpc_kernels.h b/Python/cython/hpc_kernels.h
new file mode 100644
index 00000000..c7859514
--- /dev/null
+++ b/Python/cython/hpc_kernels.h
@@ -0,0 +1,28 @@
+/*
+ * hpc_kernels.h
+ *
+ * Declarations for CPU computation kernels extracted from
+ * HPCTrainingExamples so they can be compiled into a shared
+ * library via Cython.
+ *
+ * Sources:
+ *   cpu_func  – ManagedMemory/CPU_Code/cpu_code.c
+ *   saxpy     – Pragma_Examples/OpenMP/C/1_saxpy/0_saxpy_portyourself/saxpy.c
+ *   vecadd    – Pragma_Examples/OpenMP/C/3_vecadd/0_vecadd_portyourself/vecadd.c
+ *   reduction – Pragma_Examples/OpenMP/C/2_reduction/0_reduction_portyourself/reduction.c
+ */
+
+#ifndef HPC_KERNELS_H
+#define HPC_KERNELS_H
+
+/* Double every element: out[i] = in[i] * 2.0 */
+void cpu_func(double *in, double *out, int M);
+
+/* SAXPY: y[i] = a * x[i] + y[i] */
+void saxpy(float a, float *x, float *y, int N);
+
+void vecadd(double *a, double *b, double *c, int N);
+
+double reduction(double *x, int n);
+
+#endif /* HPC_KERNELS_H */
diff --git a/Python/cython/setup.py b/Python/cython/setup.py
new file mode 100644
index 00000000..c7abdf84
--- /dev/null
+++ b/Python/cython/setup.py
@@ -0,0 +1,16 @@
+from setuptools import setup, Extension
+from Cython.Build import cythonize
+import numpy as np
+
+extensions = [
+    Extension(
+        "compute",
+        sources=["compute.pyx", "hpc_kernels.c"],
+        include_dirs=[np.get_include(), "."],
+    )
+]
+
+setup(
+    name="hpc-cython-kernels",
+    ext_modules=cythonize(extensions, compiler_directives={"language_level": "3"}),
+)