diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py
index f062ee56..93274ec5 100644
--- a/GPy/kern/__init__.py
+++ b/GPy/kern/__init__.py
@@ -2,5 +2,9 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 
-from constructors import rbf, Matern32, Matern52, exponential, linear, white, bias, finite_dimensional, spline, Brownian, rbf_sympy, sympykern, periodic_exponential, periodic_Matern32, periodic_Matern52, prod, prod_orthogonal, symmetric, coregionalise, rational_quadratic, fixed, rbfcos
+from constructors import rbf, Matern32, Matern52, exponential, linear, white, bias, finite_dimensional, spline, Brownian, periodic_exponential, periodic_Matern32, periodic_Matern52, prod, prod_orthogonal, symmetric, coregionalise, rational_quadratic, fixed, rbfcos
+try:
+    from constructors import rbf_sympy, sympykern # these depend on sympy
+except:
+    pass
 from kern import kern
diff --git a/GPy/kern/constructors.py b/GPy/kern/constructors.py
index 6a968da4..e5743f47 100644
--- a/GPy/kern/constructors.py
+++ b/GPy/kern/constructors.py
@@ -165,34 +165,40 @@ def Brownian(D,variance=1.):
     part = Brownianpart(D,variance)
     return kern(D, [part])
 
-import sympy as sp
-from sympykern import spkern
-from sympy.parsing.sympy_parser import parse_expr
+try:
+    import sympy as sp
+    from sympykern import spkern
+    from sympy.parsing.sympy_parser import parse_expr
+    sympy_available = True
+except ImportError:
+    sympy_available = False
 
-def rbf_sympy(D,ARD=False,variance=1., lengthscale=1.):
-    """
-    Radial Basis Function covariance.
-    """
-    X = [sp.var('x%i'%i) for i in range(D)]
-    Z = [sp.var('z%i'%i) for i in range(D)]
-    rbf_variance = sp.var('rbf_variance',positive=True)
-    if ARD:
-        rbf_lengthscales = [sp.var('rbf_lengthscale_%i'%i,positive=True) for i in range(D)]
-        dist_string = ' + '.join(['(x%i-z%i)**2/rbf_lengthscale_%i**2'%(i,i,i) for i in range(D)])
-        dist = parse_expr(dist_string)
-        f =  rbf_variance*sp.exp(-dist/2.)
-    else:
-        rbf_lengthscale = sp.var('rbf_lengthscale',positive=True)
-        dist_string = ' + '.join(['(x%i-z%i)**2'%(i,i) for i in range(D)])
-        dist = parse_expr(dist_string)
-        f =  rbf_variance*sp.exp(-dist/(2*rbf_lengthscale**2))
-    return kern(D,[spkern(D,f)])
+if sympy_available:
+    def rbf_sympy(D,ARD=False,variance=1., lengthscale=1.):
+        """
+        Radial Basis Function covariance.
+        """
+        X = [sp.var('x%i'%i) for i in range(D)]
+        Z = [sp.var('z%i'%i) for i in range(D)]
+        rbf_variance = sp.var('rbf_variance',positive=True)
+        if ARD:
+            rbf_lengthscales = [sp.var('rbf_lengthscale_%i'%i,positive=True) for i in range(D)]
+            dist_string = ' + '.join(['(x%i-z%i)**2/rbf_lengthscale_%i**2'%(i,i,i) for i in range(D)])
+            dist = parse_expr(dist_string)
+            f =  rbf_variance*sp.exp(-dist/2.)
+        else:
+            rbf_lengthscale = sp.var('rbf_lengthscale',positive=True)
+            dist_string = ' + '.join(['(x%i-z%i)**2'%(i,i) for i in range(D)])
+            dist = parse_expr(dist_string)
+            f =  rbf_variance*sp.exp(-dist/(2*rbf_lengthscale**2))
+        return kern(D,[spkern(D,f)])
 
-def sympykern(D,k):
-    """
-    A kernel from a symbolic sympy representation
-    """
-    return kern(D,[spkern(D,k)])
+    def sympykern(D,k):
+        """
+        A kernel from a symbolic sympy representation
+        """
+        return kern(D,[spkern(D,k)])
+del sympy_available
 
 def periodic_exponential(D=1,variance=1., lengthscale=None, period=2*np.pi,n_freq=10,lower=0.,upper=4*np.pi):
     """