pyiron_workflow_to_universal.ipynb

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   "execution_count": 1,
   "id": "4655322e-5755-455e-aff7-30067a999b7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyiron_workflow import Workflow"
   ]
  },
  {
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   "execution_count": 2,
   "id": "fa69f50a-797a-41ba-af2f-8693a1d6596e",
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   "outputs": [],
   "source": [
    "@Workflow.wrap.as_function_node(\"x\", \"y\", \"z\")\n",
    "def add_x_and_y(x, y):\n",
    "    z = x + y\n",
    "    return x, y, z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f484294c-bddf-4544-adef-0ee8b5e18517",
   "metadata": {},
   "outputs": [],
   "source": [
    "@Workflow.wrap.as_function_node()\n",
    "def add_x_and_y_and_z(x, y, z):\n",
    "    w = x + y + z\n",
    "    return w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f8d54b05-0444-4d7e-b3fb-0edec9c56f16",
   "metadata": {},
   "outputs": [],
   "source": [
    "wf = Workflow(\"my_workflow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fdab5129-bcd3-4e08-a12d-5997e990c597",
   "metadata": {},
   "outputs": [],
   "source": [
    "wf.x = 1\n",
    "wf.y = 2\n",
    "wf.data = add_x_and_y(x=wf.x, y=wf.y)\n",
    "wf.w = add_x_and_y_and_z(x=wf.data.outputs.x, y=wf.data.outputs.y, z=wf.data.outputs.z)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "id": "ef0b91de-9461-4658-8c2b-954328f143c5",
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   "outputs": [
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     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wf.draw(size=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5b7bc764-5b3d-43b4-b2da-04b295e254e1",
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "wf.run()"
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  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "12dd2927-82a9-4b34-838f-60fc0f4695e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_linked_nodes(graph_dict):\n",
    "    nodes_dict = {}\n",
    "    node_mapping_dict = {}\n",
    "    input_dict = {}\n",
    "    for i, [k, v] in enumerate(wf.graph_as_dict[\"nodes\"].items()):\n",
    "        nodes_dict[i] = v.node_function\n",
    "        node_mapping_dict[k] = i\n",
    "        input_dict[k] = {\n",
    "            con.full_label: con.value \n",
    "            for con in v.inputs.channel_dict.to_list() \n",
    "            if len(con.connections) == 0\n",
    "        }\n",
    "    return nodes_dict, node_mapping_dict, input_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "25f274f8-8730-45c4-97ea-7349063da89e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extend_nodes_dict(nodes_dict, input_dict):\n",
    "    i = len(nodes_dict)\n",
    "    nodes_links_dict = {}\n",
    "    for val_dict in input_dict.values():\n",
    "        for k, v in val_dict.items():\n",
    "            if v not in nodes_dict.values():\n",
    "                nodes_dict[i] = v\n",
    "                nodes_links_dict[k] = i\n",
    "                i += 1\n",
    "            else:\n",
    "                nodes_links_dict[k] = {tv:tk for tk, tv in nodes_dict.items()}[v]\n",
    "    return nodes_links_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b6dcee93-6c8b-42bf-bfed-d577a4f2169e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_edges(graph_dict, node_mapping_dict, nodes_links_dict):\n",
    "    edges_lst = []\n",
    "    for link in list(graph_dict[\"edges\"][\"data\"].keys()):\n",
    "        source_combo, target_combo = link\n",
    "        target, target_handle = target_combo.split(\".\")\n",
    "        source, source_handle = source_combo.split(\".\")\n",
    "        edges_lst.append({'target': node_mapping_dict[target], 'targetHandle': target_handle, 'source': node_mapping_dict[source], 'sourceHandle': source_handle})\n",
    "\n",
    "    for k, v in nodes_links_dict.items():\n",
    "        target, target_handle = k.split(\".\")\n",
    "        edges_lst.append({'target': node_mapping_dict[target], 'targetHandle': target_handle, 'source': v, 'sourceHandle': None})\n",
    "    return edges_lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0cd7e950-d09a-4eaa-b909-9fd05abc3da7",
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes_dict, node_mapping_dict, input_dict = get_linked_nodes(graph_dict=wf.graph_as_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "773d53ee-9554-4f16-8fd8-c1cbaf278156",
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes_links_dict = extend_nodes_dict(nodes_dict=nodes_dict, input_dict=input_dict)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "daac17ab-12af-4445-a054-d0c240167b2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'target': 1, 'targetHandle': 'x', 'source': 0, 'sourceHandle': 'x'},\n",
       " {'target': 1, 'targetHandle': 'y', 'source': 0, 'sourceHandle': 'y'},\n",
       " {'target': 1, 'targetHandle': 'z', 'source': 0, 'sourceHandle': 'z'},\n",
       " {'target': 0, 'targetHandle': 'x', 'source': 2, 'sourceHandle': None},\n",
       " {'target': 0, 'targetHandle': 'y', 'source': 3, 'sourceHandle': None}]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges_lst = get_edges(graph_dict=wf.graph_as_dict, node_mapping_dict=node_mapping_dict, nodes_links_dict=nodes_links_dict)\n",
    "edges_lst"
   ]
  },
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   "cell_type": "code",
   "execution_count": 14,
   "id": "161a9ec2-a63a-49f9-a1ff-1a2ac1951a43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 1: <function __main__.add_x_and_y_and_z(x, y, z)>,\n",
       " 2: 1,\n",
       " 3: 2}"
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     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
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   "execution_count": null,
   "id": "1516ada2-4dbb-476c-b3db-90e87990c423",
   "metadata": {},
   "outputs": [],
   "source": []
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