Latest file versions. Should we use nbstripout?

Author: GeigerJ2

.gitignore

@@ -187,4 +187,16 @@ strain_1/
 strain_2/
 strain_3/
 strain_4/
+aiida_to_pyiron_base_qe.json
+pyiron_base_to_aiida_qe.json
+jobflow_to_pyiron_base_simple.json
+aiida_to_pyiron_base_simple.json
+jobflow_to_aiida_simple.json
+pyiron_base_to_jobflow_simple.json
+aiida_to_jobflow_simple.json
+jobflow_to_pyiron_base_qe.json
+jobflow_to_aiida_qe.json
+aiida_to_jobflow_qe.json
+pyiron_base_to_aiida_simple.json
+pyiron_base_to_jobflow_qe.json
 

jobflow_to_aiida_qe.ipynb

@@ -85,7 +85,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -218,7 +218,7 @@
      "output_type": "stream",
      "text": [
       "\u001b[38;5;238m───────┬────────────────────────────────────────────────────────────────────────\u001b[0m\n",
-      "       \u001b[38;5;238m│ \u001b[0mFile: \u001b[1mworkflow_qe_jobflow.json\u001b[0m\n",
+      "       \u001b[38;5;238m│ \u001b[0mFile: \u001b[1mjobflow_to_aiida_qe.json\u001b[0m\n",
       "\u001b[38;5;238m───────┼────────────────────────────────────────────────────────────────────────\u001b[0m\n",
       "\u001b[38;5;238m   1\u001b[0m   \u001b[38;5;238m│\u001b[0m \u001b[38;5;231m{\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;208mnodes\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;231m:\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;231m{\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;208m0\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;231m:\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;186m\"\u001b[0m\u001b[38;5;186mquantum_espresso_workflow.get_bulk_structure\u001b[0m\u001b[38;5;186m\"\u001b[0m\u001b[38;5;231m,\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;208m1\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;231m:\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;186m\"\u001b[0m\u001b[38;5;186mq\u001b[0m\n",
       "\u001b[38;5;238m    \u001b[0m   \u001b[38;5;238m│\u001b[0m \u001b[38;5;186muantum_espresso_workflow.calculate_qe\u001b[0m\u001b[38;5;186m\"\u001b[0m\u001b[38;5;231m,\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;208m2\u001b[0m\u001b[38;5;208m\"\u001b[0m\u001b[38;5;231m:\u001b[0m\u001b[38;5;231m \u001b[0m\u001b[38;5;186m\"\u001b[0m\u001b[38;5;186mquantum_espresso_workflow\u001b[0m\n",

jobflow_to_pyiron_base_qe.ipynb

@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "80fb0d34",
    "metadata": {},
    "outputs": [],

pyiron_base_to_aiida_qe.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 14,
    "id": "28d69730-d8cb-4174-ae3f-aa70da8a8108",
    "metadata": {
     "trusted": true
@@ -14,30 +14,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 15,
    "id": "cacaa0a8-27c8-44de-9e37-69cd3d13408b",
    "metadata": {
     "trusted": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/geiger_j/.aiida_venvs/adis/lib/python3.10/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from this module in 48.0.0.\n",
-      "  \"cipher\": algorithms.TripleDES,\n",
-      "/home/geiger_j/.aiida_venvs/adis/lib/python3.10/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from this module in 48.0.0.\n",
-      "  \"class\": algorithms.TripleDES,\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from jobflow.managers.local import run_locally"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 16,
    "id": "14d87342-706e-4120-99e6-b5363f724601",
    "metadata": {
     "trusted": true
@@ -49,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 17,
    "id": "a2ed2608-9e1b-4a81-81cb-5079573ea2d1",
    "metadata": {
     "trusted": true
@@ -61,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 18,
    "id": "444347b0-d5ba-4903-b8d4-a9d7fc35d268",
    "metadata": {
     "trusted": true
@@ -73,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 19,
    "id": "b75c2530-9b89-4185-838f-a17e517fa68f",
    "metadata": {
     "trusted": true
@@ -90,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "07a950ca",
    "metadata": {},
    "outputs": [],
@@ -100,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 21,
    "id": "208ddfb8-dfda-4227-aa1f-3dc29e34ea82",
    "metadata": {
     "trusted": true
@@ -115,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 22,
    "id": "5071d3a0-7c1f-44c5-85e0-dede1566c10c",
    "metadata": {
     "trusted": true
@@ -127,7 +116,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 23,
    "id": "13debfcd-362d-4fd0-a91f-5ab33632fceb",
    "metadata": {
     "trusted": true
@@ -136,7 +125,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ca214d411c864d6c846aca7e1449701a",
+       "model_id": "0c30d907e2cc45ecb5447f75b42fb69d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -155,7 +144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 24,
    "id": "1f1cb12f-4001-478d-8ea0-b369f4f2981a",
    "metadata": {
     "trusted": true
@@ -172,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 25,
    "id": "4140f07b-af54-41ef-be22-df6b5b53bf95",
    "metadata": {
     "trusted": true
@@ -194,7 +183,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 26,
    "id": "3c4dae11-8750-42d5-807c-cd19f2b65706",
    "metadata": {
     "trusted": true
@@ -212,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 27,
    "id": "fdf3b62d-6cce-4312-8a5b-057224e36aca",
    "metadata": {
     "trusted": true
@@ -237,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 28,
    "id": "b2823306-0a8a-4ae6-bb1f-104e90e2fe41",
    "metadata": {
     "trusted": true
@@ -253,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 29,
    "id": "52646121-335f-48e6-bd5e-a1d69d00e8bc",
    "metadata": {
     "trusted": true

pyiron_base_to_jobflow_qe.ipynb

@@ -18,13 +18,11 @@ def load_workflow_json(file_name):
     task_name_mapping = {}
 
     for id, identifier in data["nodes"].items():
-        # if isinstance(identifier, str) and identifier in func_mapping:
         if isinstance(identifier, str) and "." in identifier:
             p, m = identifier.rsplit(".", 1)
             mod = import_module(p)
             _func = getattr(mod, m)
             func = task.pythonjob()(_func)
-            # func = func_mapping[identifier]
             # I use the register_pickle_by_value, because the function is defined in a local file
             wg.add_task(func, register_pickle_by_value=True)
 
@@ -44,9 +42,11 @@ def load_workflow_json(file_name):
             # because we are not define the outputs explicitly during the pythonjob creation
             # we add it here, and assume the output exit
             if link["sourceHandle"] not in from_task.outputs:
+            # if str(link["sourceHandle"]) not in from_task.outputs:
                 from_socket = from_task.add_output(
                     "workgraph.any",
                     name=link["sourceHandle"],
+                    # name=str(link["sourceHandle"]),
                     metadata={"is_function_output": True},
                 )
             else:

python_workflow_definition/src/python_workflow_definition/aiida.py

@@ -207,9 +207,17 @@ def load_workflow_json(project, file_name):
 def write_workflow_json(delayed_object, file_name="workflow.json"):
     nodes_dict, edges_lst = delayed_object.get_graph()
     nodes_dict, edges_lst = _remove_server_obj(nodes_dict=nodes_dict, edges_lst=edges_lst)
+
+    # import ipdb; ipdb.set_trace()
     delayed_object_updated_dict, match_dict = _get_unique_objects(nodes_dict=nodes_dict)
+
+    # import ipdb; ipdb.set_trace()
     connection_dict, lookup_dict = _get_connection_dict(delayed_object_updated_dict=delayed_object_updated_dict, match_dict=match_dict)
+
+    # import ipdb; ipdb.set_trace()
     nodes_new_dict = _get_nodes(connection_dict=connection_dict, delayed_object_updated_dict=delayed_object_updated_dict)
+
+    # import ipdb; ipdb.set_trace()
     edges_new_lst = _get_edges_dict(edges_lst=edges_lst, nodes_dict=nodes_dict, connection_dict=connection_dict, lookup_dict=lookup_dict)
 
     nodes_store_dict = {}
@@ -223,6 +231,8 @@ def write_workflow_json(delayed_object, file_name="workflow.json"):
             nodes_store_dict[k] = v.tolist()
         else:
             nodes_store_dict[k] = v
+    
+    # import ipdb; ipdb.set_trace()
 
     with open(file_name, "w") as f:
         json.dump({"nodes": nodes_store_dict, "edges": edges_new_lst}, f)