diff --git a/recipes/recipes_emscripten/numpy/build.sh b/recipes/recipes_emscripten/numpy/build.sh
index d1068f99132..4a10cb35d18 100644
--- a/recipes/recipes_emscripten/numpy/build.sh
+++ b/recipes/recipes_emscripten/numpy/build.sh
@@ -6,7 +6,9 @@ rm -r -f branding
 
 export CFLAGS="$CFLAGS -Wno-return-type -Wno-implicit-function-declaration"
 export MESON_CROSS_FILE=$RECIPE_DIR/emscripten.meson.cross
-export LDFLAGS="$LDFLAGS -sWASM_BIGINT"
+export LDFLAGS="$LDFLAGS -sWASM_BIGINT -sEXPORTED_FUNCTIONS=['_init_numpy'] -sDEFAULT_LIBRARY_FUNCS_TO_INCLUDE=['sin','cos','exp','log']"
+
+
 
 cp $RECIPE_DIR/config/config.h.in  numpy/_core/config.h.in
 # 
diff --git a/recipes/recipes_emscripten/numpy/recipe.yaml b/recipes/recipes_emscripten/numpy/recipe.yaml
index 17e700ef797..90613100672 100644
--- a/recipes/recipes_emscripten/numpy/recipe.yaml
+++ b/recipes/recipes_emscripten/numpy/recipe.yaml
@@ -11,7 +11,7 @@ source:
   url: https://github.com/numpy/numpy/releases/download/v${{ version }}/numpy-${{ version }}.tar.gz
   sha256: e0486a11ec30cdecb53f184d496d1c6a20786c81e55e41640270130056f8ee48
 build:
-  number: 0
+  number: 1
 
 requirements:
   build:
diff --git a/recipes/recipes_emscripten/numpy/test_numpy.py b/recipes/recipes_emscripten/numpy/test_numpy.py
index 839ca268a61..ee36d7f6871 100644
--- a/recipes/recipes_emscripten/numpy/test_numpy.py
+++ b/recipes/recipes_emscripten/numpy/test_numpy.py
@@ -1,5 +1,31 @@
 def test_numpy():
-    import numpy
+    import numpy as np
 
-    ones = numpy.ones(shape=[2,3])
-    assert ones.shape == (2,3)
\ No newline at end of file
+    ones = np.ones(shape=[2,3])
+    assert ones.shape == (2,3)
+    
+        
+
+    # 1. Array creation & dtype
+    a = np.arange(6).reshape(2, 3)
+    print("Array a:\n", a, "dtype:", a.dtype)
+
+    # 2. Elementwise ops & broadcasting
+    b = np.ones((2, 1))
+    print("a + b (broadcasted):\n", a + b)
+
+    # 3. Reduction
+    print("Sum of a:", np.sum(a))
+
+    # 4. Matrix multiplication (BLAS check)
+    c = np.array([[1, 2], [3, 4]])
+    d = np.array([[5, 6], [7, 8]])
+    print("Matrix product c @ d:\n", c @ d)
+
+    # 5. Linear algebra (LAPACK check)
+    eigvals, eigvecs = np.linalg.eig(c)
+    print("Eigenvalues of c:", eigvals)
+
+    # 6. Random numbers
+    rng = np.random.default_rng(42)
+    print("Random sample:", rng.random(3))