diff --git a/examples/fortran/ipython-integration-demo.ipynb b/examples/fortran/ipython-integration-demo.ipynb
index 1b0a9df8d18da1947171eadf744cb3db2ea312da..8fe25780b3a3909b1b8b07b0df847348d27c103d 100644
--- a/examples/fortran/ipython-integration-demo.ipynb
+++ b/examples/fortran/ipython-integration-demo.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,9 +25,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/kaushikggg/pack/loopy_kc_env/src/loopy/loopy/frontend/fortran/translator.py:807: LoopyWarning: 'lang_version' was not passed to make_function(). To avoid this warning, pass lang_version=(2018, 2) in this invocation. (Or say 'from loopy.version import LOOPY_USE_LANGUAGE_VERSION_2018_2' in the global scope of the calling frame.)\n",
+      "  seq_dependencies=seq_dependencies,\n"
+     ]
+    }
+   ],
    "source": [
     "%%fortran_kernel\n",
     "\n",
@@ -45,11 +54,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---------------------------------------------------------------------------\n",
+      "KERNEL: fill\n",
+      "---------------------------------------------------------------------------\n",
+      "ARGUMENTS:\n",
+      "a: ValueArg, type: np:dtype('float64')\n",
+      "n: ValueArg, type: np:dtype('int32')\n",
+      "out: type: np:dtype('float64'), shape: (n), dim_tags: (N0:stride:1) aspace: global\n",
+      "---------------------------------------------------------------------------\n",
+      "DOMAINS:\n",
+      "[n] -> { [i] : 0 <= i < n }\n",
+      "---------------------------------------------------------------------------\n",
+      "INAME IMPLEMENTATION TAGS:\n",
+      "i: None\n",
+      "---------------------------------------------------------------------------\n",
+      "INSTRUCTIONS:\n",
+      "for i\n",
+      "  \u001b[36mout[i]\u001b[0m = \u001b[35ma\u001b[0m  {id=\u001b[32minsn0\u001b[0m}\n",
+      "end i\n",
+      "---------------------------------------------------------------------------\n"
+     ]
+    }
+   ],
    "source": [
-    "print(fill)"
+    "print(prog)"
    ]
   },
   {
@@ -61,7 +96,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -70,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -92,19 +127,53 @@
     "! tr_fill = lp.parse_fortran(SOURCE)\n",
     "! tr_fill = lp.split_iname(tr_fill, \"i\", split_amount,\n",
     "!     outer_tag=\"g.0\", inner_tag=\"l.0\")\n",
-    "! RESULT = [tr_fill]\n",
+    "! RESULT = tr_fill\n",
     "!\n",
     "!$loopy end"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---------------------------------------------------------------------------\n",
+      "KERNEL: tr_fill\n",
+      "---------------------------------------------------------------------------\n",
+      "ARGUMENTS:\n",
+      "a: ValueArg, type: np:dtype('float64')\n",
+      "n: ValueArg, type: np:dtype('int32')\n",
+      "out: type: np:dtype('float64'), shape: (n), dim_tags: (N0:stride:1) aspace: global\n",
+      "---------------------------------------------------------------------------\n",
+      "DOMAINS:\n",
+      "[n] -> { [i_outer, i_inner] : i_inner >= 0 and -128i_outer <= i_inner <= 127 and i_inner < n - 128i_outer }\n",
+      "---------------------------------------------------------------------------\n",
+      "INAME IMPLEMENTATION TAGS:\n",
+      "i_inner: l.0\n",
+      "i_outer: g.0\n",
+      "---------------------------------------------------------------------------\n",
+      "INSTRUCTIONS:\n",
+      "for i_inner, i_outer\n",
+      "    \u001b[36mout[i_inner + i_outer*128]\u001b[0m = \u001b[35ma\u001b[0m  {id=\u001b[32minsn0\u001b[0m}\n",
+      "end i_inner, i_outer\n",
+      "---------------------------------------------------------------------------\n"
+     ]
+    }
+   ],
    "source": [
-    "print(tr_fill)"
+    "print(prog)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/loopy/ipython_ext.py b/loopy/ipython_ext.py
index e44b183ed3a08726d66019f8900fc273d432d613..c0c74913b60fadb669d58cfd6153a4679947a595 100644
--- a/loopy/ipython_ext.py
+++ b/loopy/ipython_ext.py
@@ -9,10 +9,8 @@ import loopy as lp
 class LoopyMagics(Magics):
     @cell_magic
     def fortran_kernel(self, line, cell):
-        result = lp.parse_fortran(cell, return_list_of_knls=True)
-
-        for knl in result:
-            self.shell.user_ns[knl.name] = knl
+        result = lp.parse_fortran(cell)
+        self.shell.user_ns['prog'] = result
 
     @cell_magic
     def transformed_fortran_kernel(self, line, cell):
@@ -20,8 +18,7 @@ class LoopyMagics(Magics):
                 cell,
                 transform_code_context=self.shell.user_ns)
 
-        for knl in result:
-            self.shell.user_ns[knl.name] = knl
+        self.shell.user_ns['prog'] = result
 
 
 def load_ipython_extension(ip):
diff --git a/loopy/program.py b/loopy/program.py
index 5c79edec7515fc222cd1dd118a702b2f063905ae..76568cafa70da2b8ef5a67484fb053f146ea4114 100644
--- a/loopy/program.py
+++ b/loopy/program.py
@@ -311,10 +311,6 @@ class Program(ImmutableRecord):
 
         return self.copy(callables_table=callables_table)
 
-    def __iter__(self):
-        #FIXME: Document
-        return six.iterkeys(self.callables_table.resolved_functions)
-
     def __getitem__(self, name):
         result = self.callables_table[name]
         if isinstance(result, CallableKernel):