From 9a3350b574f1e3b906f0836e1f0779c4025e7f56 Mon Sep 17 00:00:00 2001 From: Jan Janssen Date: Thu, 24 Apr 2025 16:25:06 +0200 Subject: [PATCH] update jobflow updates --- example_workflows/arithmetic/jobflow.ipynb | 336 +------------- example_workflows/nfdi/jobflow.ipynb | 331 +------------- .../quantum_espresso/jobflow.ipynb | 421 +----------------- 3 files changed, 3 insertions(+), 1085 deletions(-) diff --git a/example_workflows/arithmetic/jobflow.ipynb b/example_workflows/arithmetic/jobflow.ipynb index 79ff624..5f1cd7a 100644 --- a/example_workflows/arithmetic/jobflow.ipynb +++ b/example_workflows/arithmetic/jobflow.ipynb @@ -1,335 +1 @@ -{ - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "name": "python", - "version": "3.12.8", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - } - }, - "nbformat_minor": 5, - "nbformat": 4, - "cells": [ - { - "id": "982a4fbe-7cf9-45dd-84ae-9854149db0b9", - "cell_type": "markdown", - "source": "# jobflow", - "metadata": {} - }, - { - "id": "e6180712-d081-45c7-ba41-fc5191f10427", - "cell_type": "markdown", - "source": "## Define workflow with jobflow", - "metadata": {} - }, - { - "id": "000bbd4a-f53c-4eea-9d85-76f0aa2ca10b", - "cell_type": "code", - "source": "from jobflow import job, Flow", - "metadata": { - "trusted": true, - "ExecuteTime": { - "end_time": "2025-04-24T10:30:16.328511Z", - "start_time": "2025-04-24T10:30:16.309562Z" - } - }, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'jobflow'", - "output_type": "error", - "traceback": [ - "\u001B[31m---------------------------------------------------------------------------\u001B[39m", - "\u001B[31mModuleNotFoundError\u001B[39m Traceback (most recent call last)", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[4]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mjobflow\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m job, Flow\n", - "\u001B[31mModuleNotFoundError\u001B[39m: No module named 'jobflow'" - ] - } - ], - "execution_count": 4 - }, - { - "id": "06c2bd9e-b2ac-4b88-9158-fa37331c3418", - "cell_type": "code", - "source": "from python_workflow_definition.jobflow import write_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 2 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-04-24T10:30:04.618439Z", - "start_time": "2025-04-24T10:30:04.598701Z" - } - }, - "cell_type": "code", - "source": [ - "from workflow import (\n", - " get_sum as _get_sum,\n", - " get_prod_and_div as _get_prod_and_div,\n", - ")" - ], - "id": "f9217ce7b093b5fc", - "outputs": [], - "execution_count": 1 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-04-24T10:30:04.751088Z", - "start_time": "2025-04-24T10:30:04.748941Z" - } - }, - "cell_type": "code", - "source": "workflow_json_filename = \"jobflow_simple.json\"", - "id": "1feba0898ee4e361", - "outputs": [], - "execution_count": 2 - }, - { - "id": "07598344-0f75-433b-8902-bea21a42088c", - "cell_type": "code", - "source": [ - "get_sum = job(_get_sum)\n", - "# Note: one could also transfer the outputs to the datastore as well: get_prod_and_div = job(_get_prod_and_div, data=[\"prod\", \"div\"])\n", - "# On the way from the general definition to the jobflow definition, we do this automatically to avoid overflow databases.\n", - "get_prod_and_div = job(_get_prod_and_div)" - ], - "metadata": { - "trusted": true, - "ExecuteTime": { - "end_time": "2025-04-24T10:30:05.169761Z", - "start_time": "2025-04-24T10:30:05.043635Z" - } - }, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'job' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[31m---------------------------------------------------------------------------\u001B[39m", - "\u001B[31mNameError\u001B[39m Traceback (most recent call last)", - "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[3]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m get_sum = \u001B[43mjob\u001B[49m(_get_sum)\n\u001B[32m 2\u001B[39m get_prod_and_div = job(_get_prod_and_div, data=[\u001B[33m\"\u001B[39m\u001B[33mprod\u001B[39m\u001B[33m\"\u001B[39m, \u001B[33m\"\u001B[39m\u001B[33mdiv\u001B[39m\u001B[33m\"\u001B[39m])\n", - "\u001B[31mNameError\u001B[39m: name 'job' is not defined" - ] - } - ], - "execution_count": 3 - }, - { - "id": "ecef1ed5-a8d3-48c3-9e01-4a40e55c1153", - "cell_type": "code", - "source": "obj = get_prod_and_div(x=1, y=2)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 6 - }, - { - "id": "2b88a30a-e26b-4802-89b7-79ca08cc0af9", - "cell_type": "code", - "source": "w = get_sum(x=obj.output.prod, y=obj.output.div)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 7 - }, - { - "id": "a5e5ca63-2906-47c9-bac6-adebf8643cba", - "cell_type": "code", - "source": "flow = Flow([obj, w])", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 8 - }, - { - "id": "e464da97-16a1-4772-9a07-0a47f152781d", - "cell_type": "code", - "source": "write_workflow_json(flow=flow, file_name=workflow_json_filename)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 9 - }, - { - "id": "bca646b2-0a9a-4271-966a-e5903a8c9031", - "cell_type": "code", - "source": "!cat {workflow_json_filename}", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "{\"nodes\": [{\"id\": 0, \"function\": \"arithmetic_workflow.get_prod_and_div\"}, {\"id\": 1, \"function\": \"arithmetic_workflow.get_sum\"}, {\"id\": 2, \"value\": 1}, {\"id\": 3, \"value\": 2}], \"edges\": [{\"target\": 0, \"targetPort\": \"x\", \"source\": 2, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"y\", \"source\": 3, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"x\", \"source\": 0, \"sourcePort\": \"prod\"}, {\"target\": 1, \"targetPort\": \"y\", \"source\": 0, \"sourcePort\": \"div\"}]}" - } - ], - "execution_count": 10 - }, - { - "id": "87a27540-c390-4d34-ae75-4739bfc4c1b7", - "cell_type": "markdown", - "source": "## Load Workflow with aiida", - "metadata": {} - }, - { - "id": "66a1b3a6-3d3b-4caa-b58f-d8bc089b1074", - "cell_type": "code", - "source": "from aiida import load_profile\n\nload_profile()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 11, - "output_type": "execute_result", - "data": { - "text/plain": "Profile" - }, - "metadata": {} - } - ], - "execution_count": 11 - }, - { - "id": "4679693b-039b-45cf-8c67-5b2b3d705a83", - "cell_type": "code", - "source": "from python_workflow_definition.aiida import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 12 - }, - { - "id": "68c41a61-d185-47e8-ba31-eeff71d8b2c6", - "cell_type": "code", - "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 13, - "output_type": "execute_result", - "data": { - "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", - "application/vnd.jupyter.widget-view+json": { - "version_major": 2, - "version_minor": 1, - "model_id": "4be70fedd20f4c3597415dc903adc743" - } - }, - "metadata": {} - } - ], - "execution_count": 13 - }, - { - "id": "05228ece-643c-420c-8df8-4ce3df379515", - "cell_type": "code", - "source": "wg.run()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": "04/23/2025 09:35:55 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div1\n04/23/2025 09:35:56 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_prod_and_div1, type: PyFunction, finished.\n04/23/2025 09:35:56 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum2\n04/23/2025 09:35:56 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_sum2, type: PyFunction, finished.\n04/23/2025 09:35:56 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/23/2025 09:35:56 AM <2073> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|finalize]: Finalize workgraph.\n" - } - ], - "execution_count": 14 - }, - { - "id": "2c942094-61b4-4e94-859a-64f87b5bec64", - "cell_type": "markdown", - "source": "## Load Workflow with pyiron_base", - "metadata": {} - }, - { - "id": "ea102341-84f7-4156-a7d1-c3ab1ea613a5", - "cell_type": "code", - "source": "from python_workflow_definition.pyiron_base import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 15 - }, - { - "id": "8f2a621d-b533-4ddd-8bcd-c22db2f922ec", - "cell_type": "code", - "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": "", - "image/svg+xml": "\n\n\n\n\ncreate_function_job_a30133cc7a07a2e64b505497250df84d\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x746386902750>\n\n\n\nx_03371e8bbb210fff8c1beb07977c6fca\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x746386a3b5f0>\n\n\n\nx_03371e8bbb210fff8c1beb07977c6fca->create_function_job_a30133cc7a07a2e64b505497250df84d\n\n\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce\n\nx=1\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->x_03371e8bbb210fff8c1beb07977c6fca\n\n\n\n\n\ny_69de87ef8d8a066b8926b02e01e9f7f8\n\ny=<pyiron_base.project.delayed.DelayedObject object at 0x7463869023f0>\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->y_69de87ef8d8a066b8926b02e01e9f7f8\n\n\n\n\n\ny_69de87ef8d8a066b8926b02e01e9f7f8->create_function_job_a30133cc7a07a2e64b505497250df84d\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6\n\ny=2\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->x_03371e8bbb210fff8c1beb07977c6fca\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->y_69de87ef8d8a066b8926b02e01e9f7f8\n\n\n\n\n" - }, - "metadata": {} - } - ], - "execution_count": 16 - }, - { - "id": "cf80267d-c2b0-4236-bf1d-a57596985fc1", - "cell_type": "code", - "source": "delayed_object_lst[-1].pull()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_prod_and_div_955f44280fa0072653e4d910a57d7b92 was saved and received the ID: 1\nThe job get_sum_55b699570ac3c74e1e8078a45b657240 was saved and received the ID: 2\n" - }, - { - "execution_count": 17, - "output_type": "execute_result", - "data": { - "text/plain": "2.5" - }, - "metadata": {} - } - ], - "execution_count": 17 - }, - { - "id": "9d819ed0-689c-46a7-9eff-0afb5ed66efc", - "cell_type": "code", - "source": "", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": null - } - ] -} +{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.12.8","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"id":"982a4fbe-7cf9-45dd-84ae-9854149db0b9","cell_type":"markdown","source":"# jobflow","metadata":{}},{"id":"e6180712-d081-45c7-ba41-fc5191f10427","cell_type":"markdown","source":"## Define workflow with jobflow","metadata":{}},{"id":"000bbd4a-f53c-4eea-9d85-76f0aa2ca10b","cell_type":"code","source":"from jobflow import job, Flow","metadata":{"ExecuteTime":{"end_time":"2025-04-24T10:30:16.328511Z","start_time":"2025-04-24T10:30:16.309562Z"},"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"cipher\": algorithms.TripleDES,\n/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"class\": algorithms.TripleDES,\n"}],"execution_count":1},{"id":"06c2bd9e-b2ac-4b88-9158-fa37331c3418","cell_type":"code","source":"from python_workflow_definition.jobflow import write_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":2},{"id":"f9217ce7b093b5fc","cell_type":"code","source":"from workflow import (\n get_sum as _get_sum,\n get_prod_and_div as _get_prod_and_div,\n)","metadata":{"ExecuteTime":{"end_time":"2025-04-24T10:30:04.618439Z","start_time":"2025-04-24T10:30:04.598701Z"},"trusted":true},"outputs":[],"execution_count":3},{"id":"1feba0898ee4e361","cell_type":"code","source":"workflow_json_filename = \"jobflow_simple.json\"","metadata":{"ExecuteTime":{"end_time":"2025-04-24T10:30:04.751088Z","start_time":"2025-04-24T10:30:04.748941Z"},"trusted":true},"outputs":[],"execution_count":4},{"id":"07598344-0f75-433b-8902-bea21a42088c","cell_type":"code","source":"get_sum = job(_get_sum)\n# Note: one could also transfer the outputs to the datastore as well: get_prod_and_div = job(_get_prod_and_div, data=[\"prod\", \"div\"])\n# On the way from the general definition to the jobflow definition, we do this automatically to avoid overflow databases.\nget_prod_and_div = job(_get_prod_and_div)","metadata":{"ExecuteTime":{"end_time":"2025-04-24T10:30:05.169761Z","start_time":"2025-04-24T10:30:05.043635Z"},"trusted":true},"outputs":[],"execution_count":5},{"id":"ecef1ed5-a8d3-48c3-9e01-4a40e55c1153","cell_type":"code","source":"obj = get_prod_and_div(x=1, y=2)","metadata":{"trusted":true},"outputs":[],"execution_count":6},{"id":"2b88a30a-e26b-4802-89b7-79ca08cc0af9","cell_type":"code","source":"w = get_sum(x=obj.output.prod, y=obj.output.div)","metadata":{"trusted":true},"outputs":[],"execution_count":7},{"id":"a5e5ca63-2906-47c9-bac6-adebf8643cba","cell_type":"code","source":"flow = Flow([obj, w])","metadata":{"trusted":true},"outputs":[],"execution_count":8},{"id":"e464da97-16a1-4772-9a07-0a47f152781d","cell_type":"code","source":"write_workflow_json(flow=flow, file_name=workflow_json_filename)","metadata":{"trusted":true},"outputs":[],"execution_count":9},{"id":"bca646b2-0a9a-4271-966a-e5903a8c9031","cell_type":"code","source":"!cat {workflow_json_filename}","metadata":{"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"{\"nodes\": [{\"id\": 0, \"function\": \"workflow.get_prod_and_div\"}, {\"id\": 1, \"function\": \"workflow.get_sum\"}, {\"id\": 2, \"value\": 1}, {\"id\": 3, \"value\": 2}], \"edges\": [{\"target\": 0, \"targetPort\": \"x\", \"source\": 2, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"y\", \"source\": 3, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"x\", \"source\": 0, \"sourcePort\": \"prod\"}, {\"target\": 1, \"targetPort\": \"y\", \"source\": 0, \"sourcePort\": \"div\"}]}"}],"execution_count":10},{"id":"87a27540-c390-4d34-ae75-4739bfc4c1b7","cell_type":"markdown","source":"## Load Workflow with aiida","metadata":{}},{"id":"66a1b3a6-3d3b-4caa-b58f-d8bc089b1074","cell_type":"code","source":"from aiida import load_profile\n\nload_profile()","metadata":{"trusted":true},"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"Profile"},"metadata":{}}],"execution_count":11},{"id":"4679693b-039b-45cf-8c67-5b2b3d705a83","cell_type":"code","source":"from python_workflow_definition.aiida import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":12},{"id":"68c41a61-d185-47e8-ba31-eeff71d8b2c6","cell_type":"code","source":"wg = load_workflow_json(file_name=workflow_json_filename)\nwg","metadata":{"trusted":true},"outputs":[{"execution_count":13,"output_type":"execute_result","data":{"text/plain":"NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":1,"model_id":"b00ad6ef4f114fc9ad7041fcec189c63"}},"metadata":{}}],"execution_count":13},{"id":"05228ece-643c-420c-8df8-4ce3df379515","cell_type":"code","source":"wg.run()","metadata":{"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"04/24/2025 02:14:49 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div1\n04/24/2025 02:14:50 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_prod_and_div1, type: PyFunction, finished.\n04/24/2025 02:14:50 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum2\n04/24/2025 02:14:51 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_sum2, type: PyFunction, finished.\n04/24/2025 02:14:51 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/24/2025 02:14:51 PM <99> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|finalize]: Finalize workgraph.\n"}],"execution_count":14},{"id":"2c942094-61b4-4e94-859a-64f87b5bec64","cell_type":"markdown","source":"## Load Workflow with pyiron_base","metadata":{}},{"id":"ea102341-84f7-4156-a7d1-c3ab1ea613a5","cell_type":"code","source":"from python_workflow_definition.pyiron_base import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":15},{"id":"8f2a621d-b533-4ddd-8bcd-c22db2f922ec","cell_type":"code","source":"delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()","metadata":{"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"","image/svg+xml":"\n\n\n\n\ncreate_function_job_194937dd057d87e4d087e0b4d40dcb77\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x76e7034fb9e0>\n\n\n\nx_c5597700ea3ed4abd84c6f8aaa161e23\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x76e7034fb3e0>\n\n\n\nx_c5597700ea3ed4abd84c6f8aaa161e23->create_function_job_194937dd057d87e4d087e0b4d40dcb77\n\n\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce\n\nx=1\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->x_c5597700ea3ed4abd84c6f8aaa161e23\n\n\n\n\n\ny_c6dbeb0df82287b0f91729cabadc251c\n\ny=<pyiron_base.project.delayed.DelayedObject object at 0x76e7034fb6e0>\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->y_c6dbeb0df82287b0f91729cabadc251c\n\n\n\n\n\ny_c6dbeb0df82287b0f91729cabadc251c->create_function_job_194937dd057d87e4d087e0b4d40dcb77\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6\n\ny=2\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->x_c5597700ea3ed4abd84c6f8aaa161e23\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->y_c6dbeb0df82287b0f91729cabadc251c\n\n\n\n\n"},"metadata":{}}],"execution_count":16},{"id":"cf80267d-c2b0-4236-bf1d-a57596985fc1","cell_type":"code","source":"delayed_object_lst[-1].pull()","metadata":{"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"The job get_prod_and_div_00cf2c787390eacfbc4a51e9a0c38ec7 was saved and received the ID: 1\nThe job get_sum_4b5b9d16b259a13b6a32798ce2779af8 was saved and received the ID: 2\n"},{"execution_count":17,"output_type":"execute_result","data":{"text/plain":"2.5"},"metadata":{}}],"execution_count":17},{"id":"9d819ed0-689c-46a7-9eff-0afb5ed66efc","cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]} \ No newline at end of file diff --git a/example_workflows/nfdi/jobflow.ipynb b/example_workflows/nfdi/jobflow.ipynb index d75635b..5346083 100644 --- a/example_workflows/nfdi/jobflow.ipynb +++ b/example_workflows/nfdi/jobflow.ipynb @@ -1,330 +1 @@ -{ - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "name": "python", - "version": "3.12.8", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - } - }, - "nbformat_minor": 5, - "nbformat": 4, - "cells": [ - { - "id": "048b53d1-db08-44ff-84cc-a4ff50032944", - "cell_type": "markdown", - "source": "# jobflow", - "metadata": {} - }, - { - "id": "106ded66-d202-46ac-82b0-2755ca309bdd", - "cell_type": "markdown", - "source": "https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements", - "metadata": {} - }, - { - "id": "856b2ba2-93d5-4516-93e1-a1eac49c48f2", - "cell_type": "markdown", - "source": "## Define workflow with jobflow", - "metadata": {} - }, - { - "id": "89c02460-b543-442c-a27e-f1757dc2262e", - "cell_type": "code", - "source": "from jobflow import job, Flow\n\nfrom python_workflow_definition.jobflow import write_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": "/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"cipher\": algorithms.TripleDES,\n/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"class\": algorithms.TripleDES,\n" - } - ], - "execution_count": 1 - }, - { - "metadata": {}, - "cell_type": "code", - "outputs": [], - "execution_count": null, - "source": [ - "from workflow import (\n", - " generate_mesh as _generate_mesh, \n", - " convert_to_xdmf as _convert_to_xdmf,\n", - " poisson as _poisson,\n", - " plot_over_line as _plot_over_line,\n", - " substitute_macros as _substitute_macros,\n", - " compile_paper as _compile_paper,\n", - ")" - ], - "id": "864f048d78ea3f08" - }, - { - "metadata": {}, - "cell_type": "code", - "outputs": [], - "execution_count": null, - "source": [ - "generate_mesh = job(_generate_mesh)\n", - "convert_to_xdmf = job(_convert_to_xdmf)\n", - "poisson = job(_poisson)\n", - "plot_over_line = job(_plot_over_line)\n", - "substitute_macros = job(_substitute_macros)\n", - "compile_paper = job(_compile_paper)" - ], - "id": "147b81b7b494ceda" - }, - { - "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", - "cell_type": "code", - "source": "domain_size = 2.0", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 4 - }, - { - "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", - "cell_type": "code", - "source": "gmsh_output_file = generate_mesh(\n domain_size=domain_size,\n)", - "metadata": { - "tags": [], - "trusted": true - }, - "outputs": [], - "execution_count": 5 - }, - { - "id": "1d0d9804-f250-48b3-a5d0-a546d520f79b", - "cell_type": "code", - "source": "meshio_output_dict = convert_to_xdmf(\n gmsh_output_file=gmsh_output_file.output,\n)", - "metadata": { - "tags": [], - "trusted": true - }, - "outputs": [], - "execution_count": 6 - }, - { - "id": "7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590", - "cell_type": "code", - "source": "poisson_dict = poisson(\n meshio_output_xdmf=meshio_output_dict.output.xdmf_file, \n meshio_output_h5=meshio_output_dict.output.h5_file,\n)", - "metadata": { - "tags": [], - "trusted": true - }, - "outputs": [], - "execution_count": 7 - }, - { - "id": "3c4a29b0-eb1e-490a-8be0-e03cfff15e0a", - "cell_type": "code", - "source": "pvbatch_output_file = plot_over_line(\n poisson_output_pvd_file=poisson_dict.output.pvd_file, \n poisson_output_vtu_file=poisson_dict.output.vtu_file,\n)", - "metadata": { - "tags": [], - "trusted": true - }, - "outputs": [], - "execution_count": 8 - }, - { - "id": "a0a4c233-322d-4723-9627-62ca2487bfa9", - "cell_type": "code", - "source": "macros_tex_file = substitute_macros( \n pvbatch_output_file=pvbatch_output_file.output, \n ndofs=poisson_dict.output.numdofs, \n domain_size=domain_size,\n)", - "metadata": { - "tags": [], - "trusted": true - }, - "outputs": [], - "execution_count": 9 - }, - { - "id": "c281408f-e63d-4380-a7e6-c595d49fbb8f", - "cell_type": "code", - "source": "paper_output = compile_paper(\n macros_tex=macros_tex_file.output, \n plot_file=pvbatch_output_file.output,\n)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 10 - }, - { - "id": "a384d70a-8ef5-4fdd-880c-56ac7eaf87b9", - "cell_type": "code", - "source": "flow = Flow([gmsh_output_file, meshio_output_dict, poisson_dict, pvbatch_output_file, macros_tex_file, paper_output])", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 11 - }, - { - "id": "fb23ad9c-76fd-4c0b-b546-e305d6c49796", - "cell_type": "code", - "source": "workflow_json_filename = \"jobflow_nfdi.json\"", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 12 - }, - { - "id": "4139547a-9717-4708-b1a5-8202a0382d77", - "cell_type": "code", - "source": "write_workflow_json(flow=flow, file_name=workflow_json_filename)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 13 - }, - { - "id": "11a829e2-face-469f-b343-2c95763b1f13", - "cell_type": "markdown", - "source": "## Load Workflow with aiida", - "metadata": {} - }, - { - "id": "4f3acabe-55df-479a-af4d-a23a80c4660d", - "cell_type": "code", - "source": "from aiida import load_profile\n\nload_profile()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 14, - "output_type": "execute_result", - "data": { - "text/plain": "Profile" - }, - "metadata": {} - } - ], - "execution_count": 14 - }, - { - "id": "b6ba9444-a2c8-451b-b74c-19b0f69ba369", - "cell_type": "code", - "source": "from python_workflow_definition.aiida import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 15 - }, - { - "id": "c3528d55-6bf7-47ed-a110-65c47446ba92", - "cell_type": "code", - "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 16, - "output_type": "execute_result", - "data": { - "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", - "application/vnd.jupyter.widget-view+json": { - "version_major": 2, - "version_minor": 1, - "model_id": "b702a754434d41848a5b074dc7a35118" - } - }, - "metadata": {} - } - ], - "execution_count": 16 - }, - { - "id": "5ef48778-4209-425f-8c6b-85a4cd2f92ec", - "cell_type": "code", - "source": "wg.run()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": "04/23/2025 09:36:34 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh1\n04/23/2025 09:36:36 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: generate_mesh1, type: PyFunction, finished.\n04/23/2025 09:36:36 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf2\n04/23/2025 09:36:38 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf2, type: PyFunction, finished.\n04/23/2025 09:36:38 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson3\n04/23/2025 09:36:41 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: poisson3, type: PyFunction, finished.\n04/23/2025 09:36:41 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line4\n04/23/2025 09:36:44 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: plot_over_line4, type: PyFunction, finished.\n04/23/2025 09:36:44 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros5\n04/23/2025 09:36:45 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: substitute_macros5, type: PyFunction, finished.\n04/23/2025 09:36:45 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper6\n04/23/2025 09:36:48 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: compile_paper6, type: PyFunction, finished.\n04/23/2025 09:36:48 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/23/2025 09:36:48 AM <2295> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|finalize]: Finalize workgraph.\n" - } - ], - "execution_count": 17 - }, - { - "id": "397b16a2-e1ec-4eec-8562-1c84f585c347", - "cell_type": "markdown", - "source": "## Load Workflow with pyiron_base", - "metadata": {} - }, - { - "id": "be4d5d93-e9f6-4072-a6be-0ee5dc93590f", - "cell_type": "code", - "source": "from python_workflow_definition.pyiron_base import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 18 - }, - { - "id": "4452a648-d4c3-4f5f-8678-ffb54bef17dc", - "cell_type": "code", - "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": "", - "image/svg+xml": "\n\n\n\n\ncreate_function_job_69b38eef29d5c9aba4c6de512da1bb24\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151abb90>\n\n\n\nmacros_tex_c5f640fc7b11414962941f82a40a8b04\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab920>\n\n\n\nmacros_tex_c5f640fc7b11414962941f82a40a8b04->create_function_job_69b38eef29d5c9aba4c6de512da1bb24\n\n\n\n\n\npvbatch_output_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab5f0>\n\n\n\npvbatch_output_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78->macros_tex_c5f640fc7b11414962941f82a40a8b04\n\n\n\n\n\npoisson_output_pvd_file_08c5d21e2c998fd513709b7a059c6649\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab290>\n\n\n\npoisson_output_pvd_file_08c5d21e2c998fd513709b7a059c6649->pvbatch_output_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\n\n\n\n\nplot_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab5f0>\n\n\n\npoisson_output_pvd_file_08c5d21e2c998fd513709b7a059c6649->plot_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\n\n\n\n\nplot_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78->create_function_job_69b38eef29d5c9aba4c6de512da1bb24\n\n\n\n\n\nmeshio_output_xdmf_fc75e768124c1b73ca0efc70a5765dea\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151aaf60>\n\n\n\nmeshio_output_xdmf_fc75e768124c1b73ca0efc70a5765dea->poisson_output_pvd_file_08c5d21e2c998fd513709b7a059c6649\n\n\n\n\n\npoisson_output_vtu_file_62144723b416cb6b52989d18b3dec55b\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab260>\n\n\n\nmeshio_output_xdmf_fc75e768124c1b73ca0efc70a5765dea->poisson_output_vtu_file_62144723b416cb6b52989d18b3dec55b\n\n\n\n\n\nndofs_c3811e53ce75b5460d97029d314439b5\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151ab680>\n\n\n\nmeshio_output_xdmf_fc75e768124c1b73ca0efc70a5765dea->ndofs_c3811e53ce75b5460d97029d314439b5\n\n\n\n\n\npoisson_output_vtu_file_62144723b416cb6b52989d18b3dec55b->pvbatch_output_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\n\n\n\n\npoisson_output_vtu_file_62144723b416cb6b52989d18b3dec55b->plot_file_5f8f87a5c4f1bd1a4b6cca85a1fc2b78\n\n\n\n\n\nndofs_c3811e53ce75b5460d97029d314439b5->macros_tex_c5f640fc7b11414962941f82a40a8b04\n\n\n\n\n\ngmsh_output_file_950b49ac6562a70cf11f14756f9831ea\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151aad20>\n\n\n\ngmsh_output_file_950b49ac6562a70cf11f14756f9831ea->meshio_output_xdmf_fc75e768124c1b73ca0efc70a5765dea\n\n\n\n\n\nmeshio_output_h5_efe999f964b5fb7603bd642abcd8905d\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x79d1151aaf30>\n\n\n\ngmsh_output_file_950b49ac6562a70cf11f14756f9831ea->meshio_output_h5_efe999f964b5fb7603bd642abcd8905d\n\n\n\n\n\nmeshio_output_h5_efe999f964b5fb7603bd642abcd8905d->poisson_output_pvd_file_08c5d21e2c998fd513709b7a059c6649\n\n\n\n\n\nmeshio_output_h5_efe999f964b5fb7603bd642abcd8905d->poisson_output_vtu_file_62144723b416cb6b52989d18b3dec55b\n\n\n\n\n\nmeshio_output_h5_efe999f964b5fb7603bd642abcd8905d->ndofs_c3811e53ce75b5460d97029d314439b5\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_c5f640fc7b11414962941f82a40a8b04\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_950b49ac6562a70cf11f14756f9831ea\n\n\n\n\n" - }, - "metadata": {} - } - ], - "execution_count": 19 - }, - { - "id": "1c2760b6-96b4-4f44-ac49-a229d4a0cf67", - "cell_type": "code", - "source": "delayed_object_lst[-1].pull()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "The job generate_mesh_0b48cf5155cd6802c17d20bb58104132 was saved and received the ID: 1\nThe job convert_to_xdmf_29ad6ec6927268429dc9aef8166fde43 was saved and received the ID: 2\nThe job poisson_a0224b23ceb2119d105a5d98ef37f93e was saved and received the ID: 3\nThe job plot_over_line_82b37a42e0747f11d9a7f6318f63ac6b was saved and received the ID: 4\nThe job substitute_macros_874fc185ecec04b4cb9537c58b7efb7b was saved and received the ID: 5\nThe job compile_paper_3cee534ffe692833d37faf1fd2170cb6 was saved and received the ID: 6\n" - }, - { - "execution_count": 20, - "output_type": "execute_result", - "data": { - "text/plain": "'/home/jovyan/postprocessing/paper.pdf'" - }, - "metadata": {} - } - ], - "execution_count": 20 - } - ] -} +{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.12.8","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"id":"048b53d1-db08-44ff-84cc-a4ff50032944","cell_type":"markdown","source":"# jobflow","metadata":{}},{"id":"106ded66-d202-46ac-82b0-2755ca309bdd","cell_type":"markdown","source":"https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements","metadata":{}},{"id":"856b2ba2-93d5-4516-93e1-a1eac49c48f2","cell_type":"markdown","source":"## Define workflow with jobflow","metadata":{}},{"id":"89c02460-b543-442c-a27e-f1757dc2262e","cell_type":"code","source":"from jobflow import job, Flow\n\nfrom python_workflow_definition.jobflow import write_workflow_json","metadata":{"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"cipher\": algorithms.TripleDES,\n/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"class\": algorithms.TripleDES,\n"}],"execution_count":1},{"id":"864f048d78ea3f08","cell_type":"code","source":"from workflow import (\n generate_mesh as _generate_mesh, \n convert_to_xdmf as _convert_to_xdmf,\n poisson as _poisson,\n plot_over_line as _plot_over_line,\n substitute_macros as _substitute_macros,\n compile_paper as _compile_paper,\n)","metadata":{"trusted":true},"outputs":[],"execution_count":2},{"id":"147b81b7b494ceda","cell_type":"code","source":"generate_mesh = job(_generate_mesh)\nconvert_to_xdmf = job(_convert_to_xdmf)\npoisson = job(_poisson)\nplot_over_line = job(_plot_over_line)\nsubstitute_macros = job(_substitute_macros)\ncompile_paper = job(_compile_paper)","metadata":{"trusted":true},"outputs":[],"execution_count":3},{"id":"8d911f98-3b80-457f-a0f4-3cb37ebf1691","cell_type":"code","source":"domain_size = 2.0","metadata":{"trusted":true},"outputs":[],"execution_count":4},{"id":"71d411b6-cbec-489e-99e3-ba71680bcb5b","cell_type":"code","source":"gmsh_output_file = generate_mesh(\n domain_size=domain_size,\n)","metadata":{"tags":[],"trusted":true},"outputs":[],"execution_count":5},{"id":"1d0d9804-f250-48b3-a5d0-a546d520f79b","cell_type":"code","source":"meshio_output_dict = convert_to_xdmf(\n gmsh_output_file=gmsh_output_file.output,\n)","metadata":{"tags":[],"trusted":true},"outputs":[],"execution_count":6},{"id":"7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590","cell_type":"code","source":"poisson_dict = poisson(\n meshio_output_xdmf=meshio_output_dict.output.xdmf_file, \n meshio_output_h5=meshio_output_dict.output.h5_file,\n)","metadata":{"tags":[],"trusted":true},"outputs":[],"execution_count":7},{"id":"3c4a29b0-eb1e-490a-8be0-e03cfff15e0a","cell_type":"code","source":"pvbatch_output_file = plot_over_line(\n poisson_output_pvd_file=poisson_dict.output.pvd_file, \n poisson_output_vtu_file=poisson_dict.output.vtu_file,\n)","metadata":{"tags":[],"trusted":true},"outputs":[],"execution_count":8},{"id":"a0a4c233-322d-4723-9627-62ca2487bfa9","cell_type":"code","source":"macros_tex_file = substitute_macros( \n pvbatch_output_file=pvbatch_output_file.output, \n ndofs=poisson_dict.output.numdofs, \n domain_size=domain_size,\n)","metadata":{"tags":[],"trusted":true},"outputs":[],"execution_count":9},{"id":"c281408f-e63d-4380-a7e6-c595d49fbb8f","cell_type":"code","source":"paper_output = compile_paper(\n macros_tex=macros_tex_file.output, \n plot_file=pvbatch_output_file.output,\n)","metadata":{"trusted":true},"outputs":[],"execution_count":10},{"id":"a384d70a-8ef5-4fdd-880c-56ac7eaf87b9","cell_type":"code","source":"flow = Flow([gmsh_output_file, meshio_output_dict, poisson_dict, pvbatch_output_file, macros_tex_file, paper_output])","metadata":{"trusted":true},"outputs":[],"execution_count":11},{"id":"fb23ad9c-76fd-4c0b-b546-e305d6c49796","cell_type":"code","source":"workflow_json_filename = \"jobflow_nfdi.json\"","metadata":{"trusted":true},"outputs":[],"execution_count":12},{"id":"4139547a-9717-4708-b1a5-8202a0382d77","cell_type":"code","source":"write_workflow_json(flow=flow, file_name=workflow_json_filename)","metadata":{"trusted":true},"outputs":[],"execution_count":13},{"id":"11a829e2-face-469f-b343-2c95763b1f13","cell_type":"markdown","source":"## Load Workflow with aiida","metadata":{}},{"id":"4f3acabe-55df-479a-af4d-a23a80c4660d","cell_type":"code","source":"from aiida import load_profile\n\nload_profile()","metadata":{"trusted":true},"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"Profile"},"metadata":{}}],"execution_count":14},{"id":"b6ba9444-a2c8-451b-b74c-19b0f69ba369","cell_type":"code","source":"from python_workflow_definition.aiida import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":15},{"id":"c3528d55-6bf7-47ed-a110-65c47446ba92","cell_type":"code","source":"wg = load_workflow_json(file_name=workflow_json_filename)\nwg","metadata":{"trusted":true},"outputs":[{"execution_count":16,"output_type":"execute_result","data":{"text/plain":"NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":1,"model_id":"2639a5a7e617406f8d238d7022110ad2"}},"metadata":{}}],"execution_count":16},{"id":"5ef48778-4209-425f-8c6b-85a4cd2f92ec","cell_type":"code","source":"wg.run()","metadata":{"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"04/24/2025 02:15:53 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh1\n04/24/2025 02:15:55 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: generate_mesh1, type: PyFunction, finished.\n04/24/2025 02:15:55 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf2\n04/24/2025 02:15:57 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf2, type: PyFunction, finished.\n04/24/2025 02:15:57 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson3\n04/24/2025 02:16:06 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: poisson3, type: PyFunction, finished.\n04/24/2025 02:16:06 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line4\n04/24/2025 02:16:09 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: plot_over_line4, type: PyFunction, finished.\n04/24/2025 02:16:09 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros5\n04/24/2025 02:16:10 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: substitute_macros5, type: PyFunction, finished.\n04/24/2025 02:16:10 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper6\n04/24/2025 02:17:18 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|update_task_state]: Task: compile_paper6, type: PyFunction, finished.\n04/24/2025 02:17:18 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/24/2025 02:17:18 PM <316> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [14|WorkGraphEngine|finalize]: Finalize workgraph.\n"}],"execution_count":17},{"id":"397b16a2-e1ec-4eec-8562-1c84f585c347","cell_type":"markdown","source":"## Load Workflow with pyiron_base","metadata":{}},{"id":"be4d5d93-e9f6-4072-a6be-0ee5dc93590f","cell_type":"code","source":"from python_workflow_definition.pyiron_base import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":18},{"id":"4452a648-d4c3-4f5f-8678-ffb54bef17dc","cell_type":"code","source":"delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()","metadata":{"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"","image/svg+xml":"\n\n\n\n\ncreate_function_job_540f87366e9d2012847fc7cd300d7387\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5fef0>\n\n\n\nmacros_tex_7e50dc06332e1809c8fe30ee1d48fd5a\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5fd10>\n\n\n\nmacros_tex_7e50dc06332e1809c8fe30ee1d48fd5a->create_function_job_540f87366e9d2012847fc7cd300d7387\n\n\n\n\n\npvbatch_output_file_10790f77479ebcaaa52a128a418bbaf9\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5fa70>\n\n\n\npvbatch_output_file_10790f77479ebcaaa52a128a418bbaf9->macros_tex_7e50dc06332e1809c8fe30ee1d48fd5a\n\n\n\n\n\npoisson_output_pvd_file_833dadabb722663d51a4450bb5493e8d\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5f710>\n\n\n\npoisson_output_pvd_file_833dadabb722663d51a4450bb5493e8d->pvbatch_output_file_10790f77479ebcaaa52a128a418bbaf9\n\n\n\n\n\nplot_file_10790f77479ebcaaa52a128a418bbaf9\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5fa70>\n\n\n\npoisson_output_pvd_file_833dadabb722663d51a4450bb5493e8d->plot_file_10790f77479ebcaaa52a128a418bbaf9\n\n\n\n\n\nplot_file_10790f77479ebcaaa52a128a418bbaf9->create_function_job_540f87366e9d2012847fc7cd300d7387\n\n\n\n\n\nmeshio_output_xdmf_98f79427fb4d7ccf8291df7fc1ac6838\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5f3b0>\n\n\n\nmeshio_output_xdmf_98f79427fb4d7ccf8291df7fc1ac6838->poisson_output_pvd_file_833dadabb722663d51a4450bb5493e8d\n\n\n\n\n\npoisson_output_vtu_file_a9608d2bb2030c145ddffeb990e126ac\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5f6e0>\n\n\n\nmeshio_output_xdmf_98f79427fb4d7ccf8291df7fc1ac6838->poisson_output_vtu_file_a9608d2bb2030c145ddffeb990e126ac\n\n\n\n\n\nndofs_87378fae3980624a699f18e869088c97\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5fb00>\n\n\n\nmeshio_output_xdmf_98f79427fb4d7ccf8291df7fc1ac6838->ndofs_87378fae3980624a699f18e869088c97\n\n\n\n\n\npoisson_output_vtu_file_a9608d2bb2030c145ddffeb990e126ac->pvbatch_output_file_10790f77479ebcaaa52a128a418bbaf9\n\n\n\n\n\npoisson_output_vtu_file_a9608d2bb2030c145ddffeb990e126ac->plot_file_10790f77479ebcaaa52a128a418bbaf9\n\n\n\n\n\nndofs_87378fae3980624a699f18e869088c97->macros_tex_7e50dc06332e1809c8fe30ee1d48fd5a\n\n\n\n\n\ngmsh_output_file_b3f6074f84f86309b317934247a8ae12\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5f170>\n\n\n\ngmsh_output_file_b3f6074f84f86309b317934247a8ae12->meshio_output_xdmf_98f79427fb4d7ccf8291df7fc1ac6838\n\n\n\n\n\nmeshio_output_h5_f8b981e1a2ec68db7cdb678f7f634c18\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x784df5d5f380>\n\n\n\ngmsh_output_file_b3f6074f84f86309b317934247a8ae12->meshio_output_h5_f8b981e1a2ec68db7cdb678f7f634c18\n\n\n\n\n\nmeshio_output_h5_f8b981e1a2ec68db7cdb678f7f634c18->poisson_output_pvd_file_833dadabb722663d51a4450bb5493e8d\n\n\n\n\n\nmeshio_output_h5_f8b981e1a2ec68db7cdb678f7f634c18->poisson_output_vtu_file_a9608d2bb2030c145ddffeb990e126ac\n\n\n\n\n\nmeshio_output_h5_f8b981e1a2ec68db7cdb678f7f634c18->ndofs_87378fae3980624a699f18e869088c97\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_7e50dc06332e1809c8fe30ee1d48fd5a\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_b3f6074f84f86309b317934247a8ae12\n\n\n\n\n"},"metadata":{}}],"execution_count":19},{"id":"1c2760b6-96b4-4f44-ac49-a229d4a0cf67","cell_type":"code","source":"delayed_object_lst[-1].pull()","metadata":{"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"The job generate_mesh_33d3e231d4f5badd161639211a4df9ff was saved and received the ID: 1\nThe job convert_to_xdmf_d6a46eb9a4ec352aa996e783ec3c785f was saved and received the ID: 2\nThe job poisson_757ce07607bbfc1ac00c0f2ed9fff133 was saved and received the ID: 3\nThe job plot_over_line_78c9de5c91dd3550b1cc113d2523f1e8 was saved and received the ID: 4\nThe job substitute_macros_06cc93df70c8a343d15e56040b1a651d was saved and received the ID: 5\nThe job compile_paper_e8bba68a92b18c0a5be4abe502340394 was saved and received the ID: 6\n"},{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'"},"metadata":{}}],"execution_count":20}]} \ No newline at end of file diff --git a/example_workflows/quantum_espresso/jobflow.ipynb b/example_workflows/quantum_espresso/jobflow.ipynb index aee8f40..2565859 100644 --- a/example_workflows/quantum_espresso/jobflow.ipynb +++ b/example_workflows/quantum_espresso/jobflow.ipynb @@ -1,420 +1 @@ -{ - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.8" - } - }, - "nbformat_minor": 4, - "nbformat": 4, - "cells": [ - { - "cell_type": "markdown", - "source": "# jobflow", - "metadata": {} - }, - { - "cell_type": "markdown", - "source": "## Define workflow with jobflow", - "metadata": {} - }, - { - "cell_type": "code", - "source": "import numpy as np", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 1 - }, - { - "cell_type": "code", - "source": "from jobflow import job, Flow", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": "/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"cipher\": algorithms.TripleDES,\n/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"class\": algorithms.TripleDES,\n" - } - ], - "execution_count": 2 - }, - { - "cell_type": "code", - "source": "from python_workflow_definition.jobflow import write_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 3 - }, - { - "metadata": {}, - "cell_type": "code", - "outputs": [], - "execution_count": null, - "source": [ - "from workflow import (\n", - " calculate_qe as _calculate_qe, \n", - " generate_structures as _generate_structures, \n", - " get_bulk_structure as _get_bulk_structure, \n", - " plot_energy_volume_curve as _plot_energy_volume_curve,\n", - ")" - ] - }, - { - "metadata": {}, - "cell_type": "code", - "outputs": [], - "execution_count": null, - "source": "workflow_json_filename = \"jobflow_qe.json\"" - }, - { - "cell_type": "code", - "source": [ - "calculate_qe = job(_calculate_qe)\n", - "generate_structures = job(_generate_structures)\n", - "plot_energy_volume_curve = job(_plot_energy_volume_curve)\n", - "get_bulk_structure = job(_get_bulk_structure)" - ], - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 6 - }, - { - "cell_type": "code", - "source": "pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 7 - }, - { - "cell_type": "code", - "source": "structure = get_bulk_structure(\n element=\"Al\",\n a=4.04,\n cubic=True,\n)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 8 - }, - { - "cell_type": "code", - "source": "calc_mini = calculate_qe(\n working_directory=\"mini\",\n input_dict={\n \"structure\": structure.output,\n \"pseudopotentials\": pseudopotentials,\n \"kpts\": (3, 3, 3),\n \"calculation\": \"vc-relax\",\n \"smearing\": 0.02,\n },\n)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 9 - }, - { - "cell_type": "code", - "source": "number_of_strains = 5\nstructure_lst = generate_structures(\n structure=calc_mini.output.structure,\n strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 10 - }, - { - "cell_type": "code", - "source": "job_strain_lst = []\nfor i in range(number_of_strains):\n calc_strain = calculate_qe(\n working_directory=\"strain_\" + str(i),\n input_dict={\n \"structure\": getattr(structure_lst.output, f\"s_{i}\"),\n \"pseudopotentials\": pseudopotentials,\n \"kpts\": (3, 3, 3),\n \"calculation\": \"scf\",\n \"smearing\": 0.02,\n },\n )\n job_strain_lst.append(calc_strain)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 11 - }, - { - "cell_type": "code", - "source": "plot = plot_energy_volume_curve(\n volume_lst=[job.output.volume for job in job_strain_lst],\n energy_lst=[job.output.energy for job in job_strain_lst],\n)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 12 - }, - { - "cell_type": "code", - "source": "flow = Flow([structure, calc_mini, structure_lst] + job_strain_lst + [plot])", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 13 - }, - { - "cell_type": "code", - "source": "write_workflow_json(flow=flow, file_name=workflow_json_filename)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 14 - }, - { - "cell_type": "code", - "source": "!cat {workflow_json_filename}", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "{\"nodes\": [{\"id\": 0, \"function\": \"quantum_espresso_workflow.get_bulk_structure\"}, {\"id\": 1, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 2, \"function\": \"quantum_espresso_workflow.generate_structures\"}, {\"id\": 3, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 4, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 5, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 6, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 7, \"function\": \"quantum_espresso_workflow.calculate_qe\"}, {\"id\": 8, \"function\": \"quantum_espresso_workflow.plot_energy_volume_curve\"}, {\"id\": 9, \"value\": \"Al\"}, {\"id\": 10, \"value\": 4.04}, {\"id\": 11, \"value\": true}, {\"id\": 12, \"value\": \"mini\"}, {\"id\": 13, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 14, \"value\": {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}}, {\"id\": 15, \"value\": [3, 3, 3]}, {\"id\": 16, \"value\": \"vc-relax\"}, {\"id\": 17, \"value\": 0.02}, {\"id\": 18, \"value\": [0.9, 0.9500000000000001, 1.0, 1.05, 1.1]}, {\"id\": 19, \"value\": \"strain_0\"}, {\"id\": 20, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 21, \"value\": \"scf\"}, {\"id\": 22, \"value\": \"strain_1\"}, {\"id\": 23, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 24, \"value\": \"strain_2\"}, {\"id\": 25, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 26, \"value\": \"strain_3\"}, {\"id\": 27, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 28, \"value\": \"strain_4\"}, {\"id\": 29, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 30, \"function\": \"python_workflow_definition.shared.get_list\"}, {\"id\": 31, \"function\": \"python_workflow_definition.shared.get_list\"}], \"edges\": [{\"target\": 0, \"targetPort\": \"element\", \"source\": 9, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"a\", \"source\": 10, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"cubic\", \"source\": 11, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"working_directory\", \"source\": 12, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"structure\", \"source\": 0, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"calculation\", \"source\": 16, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"input_dict\", \"source\": 13, \"sourcePort\": null}, {\"target\": 2, \"targetPort\": \"structure\", \"source\": 1, \"sourcePort\": \"structure\"}, {\"target\": 2, \"targetPort\": \"strain_lst\", \"source\": 18, \"sourcePort\": null}, {\"target\": 3, \"targetPort\": \"working_directory\", \"source\": 19, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_0\"}, {\"target\": 20, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 3, \"targetPort\": \"input_dict\", \"source\": 20, \"sourcePort\": null}, {\"target\": 4, \"targetPort\": \"working_directory\", \"source\": 22, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_1\"}, {\"target\": 23, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 4, \"targetPort\": \"input_dict\", \"source\": 23, \"sourcePort\": null}, {\"target\": 5, \"targetPort\": \"working_directory\", \"source\": 24, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_2\"}, {\"target\": 25, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 5, \"targetPort\": \"input_dict\", \"source\": 25, \"sourcePort\": null}, {\"target\": 6, \"targetPort\": \"working_directory\", \"source\": 26, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_3\"}, {\"target\": 27, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 6, \"targetPort\": \"input_dict\", \"source\": 27, \"sourcePort\": null}, {\"target\": 7, \"targetPort\": \"working_directory\", \"source\": 28, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_4\"}, {\"target\": 29, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 7, \"targetPort\": \"input_dict\", \"source\": 29, \"sourcePort\": null}, {\"target\": 30, \"targetPort\": \"0\", \"source\": 3, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"1\", \"source\": 4, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"2\", \"source\": 5, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"3\", \"source\": 6, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"4\", \"source\": 7, \"sourcePort\": \"volume\"}, {\"target\": 8, \"targetPort\": \"volume_lst\", \"source\": 30, \"sourcePort\": null}, {\"target\": 31, \"targetPort\": \"0\", \"source\": 3, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"1\", \"source\": 4, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"2\", \"source\": 5, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"3\", \"source\": 6, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"4\", \"source\": 7, \"sourcePort\": \"energy\"}, {\"target\": 8, \"targetPort\": \"energy_lst\", \"source\": 31, \"sourcePort\": null}]}" - } - ], - "execution_count": 15 - }, - { - "cell_type": "markdown", - "source": "## Load Workflow with aiida", - "metadata": {} - }, - { - "cell_type": "code", - "source": "from aiida import orm, load_profile\n\nload_profile()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 16, - "output_type": "execute_result", - "data": { - "text/plain": "Profile" - }, - "metadata": {} - } - ], - "execution_count": 16 - }, - { - "cell_type": "code", - "source": "from python_workflow_definition.aiida import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 17 - }, - { - "cell_type": "code", - "source": "wg = load_workflow_json(workflow_json_filename)", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 18 - }, - { - "cell_type": "code", - "source": "wg.nodes.get_bulk_structure1.inputs.a.value = orm.Float(4.05)", - "metadata": { - "scrolled": true, - "trusted": true - }, - "outputs": [], - "execution_count": 19 - }, - { - "cell_type": "code", - "source": "wg", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "execution_count": 20, - "output_type": "execute_result", - "data": { - "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", - "application/vnd.jupyter.widget-view+json": { - "version_major": 2, - "version_minor": 1, - "model_id": "5181550fd32b489581df9e1b0d490087" - } - }, - "metadata": {} - } - ], - "execution_count": 20 - }, - { - "cell_type": "code", - "source": "wg.run()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": "04/23/2025 09:37:37 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure1\n04/23/2025 09:37:38 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_bulk_structure1, type: PyFunction, finished.\n04/23/2025 09:37:38 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict10\n04/23/2025 09:37:39 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict10, type: PyFunction, finished.\n04/23/2025 09:37:39 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe2\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03734] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:38:33 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n04/23/2025 09:38:33 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe2, type: PyFunction, finished.\n04/23/2025 09:38:33 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures3\n04/23/2025 09:38:35 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: generate_structures3, type: PyFunction, finished.\n04/23/2025 09:38:35 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict11,get_dict12,get_dict13,get_dict14,get_dict15\n04/23/2025 09:38:36 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict11, type: PyFunction, finished.\n04/23/2025 09:38:36 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe4,get_dict12,get_dict13,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03752] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:38:47 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/23/2025 09:38:47 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe4, type: PyFunction, finished.\n04/23/2025 09:38:47 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict12,get_dict13,get_dict14,get_dict15\n04/23/2025 09:38:48 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict12, type: PyFunction, finished.\n04/23/2025 09:38:48 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe5,get_dict13,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03763] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:39:00 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/23/2025 09:39:00 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe5, type: PyFunction, finished.\n04/23/2025 09:39:00 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict13,get_dict14,get_dict15\n04/23/2025 09:39:01 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict13, type: PyFunction, finished.\n04/23/2025 09:39:01 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03775] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:39:14 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/23/2025 09:39:14 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n04/23/2025 09:39:14 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict14,get_dict15\n04/23/2025 09:39:15 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict14, type: PyFunction, finished.\n04/23/2025 09:39:15 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe7,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03786] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:39:30 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/23/2025 09:39:30 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe7, type: PyFunction, finished.\n04/23/2025 09:39:30 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict15\n04/23/2025 09:39:31 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict15, type: PyFunction, finished.\n04/23/2025 09:39:31 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe8\n[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03802] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/23/2025 09:39:49 AM <3661> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/23/2025 09:39:49 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe8, type: PyFunction, finished.\n04/23/2025 09:39:49 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list16,get_list17\n04/23/2025 09:39:50 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_list16, type: PyFunction, finished.\n04/23/2025 09:39:50 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list17\n04/23/2025 09:39:51 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_list17, type: PyFunction, finished.\n04/23/2025 09:39:51 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve9\n04/23/2025 09:39:52 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve9, type: PyFunction, finished.\n04/23/2025 09:39:52 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/23/2025 09:39:52 AM <3661> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|finalize]: Finalize workgraph.\n" - }, - { - "output_type": "display_data", - "data": { - "text/plain": "
", - "image/png": 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- }, - "metadata": {} - } - ], - "execution_count": 21 - }, - { - "cell_type": "markdown", - "source": "## Load Workflow with pyiron_base", - "metadata": {} - }, - { - "cell_type": "code", - "source": "from python_workflow_definition.pyiron_base import load_workflow_json", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 22 - }, - { - "cell_type": "code", - "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": "", - "image/svg+xml": "\n\n\n\n\ncreate_function_job_32ef32f9566b9201becfbb5fe459cf95\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7e89563a4620>\n\n\n\nvolume_lst_1de093461d597c9482af1b1162abe220\n\nvolume_lst=<pyiron_base.project.delayed.DelayedObject object at 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0x7e8956571e50>\n\n\n\nstructure_455912e219ba7dc19b4b63accdb089e8->input_dict_4b2508b7156463722cb2882e1ced8fd9\n\n\n\n\n\nworking_directory_a17ade9a563d8dcadb655fb2e1c743a7\n\nworking_directory=mini\n\n\n\nworking_directory_a17ade9a563d8dcadb655fb2e1c743a7->structure_bb0e80218d6fb6d1f539fecce43c6da5\n\n\n\n\n\ninput_dict_9588611272d06d8efced69e7f4a609b7\n\ninput_dict=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956571010>\n\n\n\ninput_dict_9588611272d06d8efced69e7f4a609b7->structure_bb0e80218d6fb6d1f539fecce43c6da5\n\n\n\n\n\nstructure_8a946279df78421b8c6c2efb8df18e00\n\nstructure=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956571220>\n\n\n\nstructure_8a946279df78421b8c6c2efb8df18e00->input_dict_9588611272d06d8efced69e7f4a609b7\n\n\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0\n\nelement=Al\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0->structure_8a946279df78421b8c6c2efb8df18e00\n\n\n\n\n\na_457b6d376c6fce696df148a385afa46d\n\na=4.04\n\n\n\na_457b6d376c6fce696df148a385afa46d->structure_8a946279df78421b8c6c2efb8df18e00\n\n\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a\n\ncubic=True\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a->structure_8a946279df78421b8c6c2efb8df18e00\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10\n\npseudopotentials={'Al': 'Al.pbe-n-kjpaw_psl.1.0.0.UPF'}\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_d4fd21664755878ddd70933cce962f18\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_9588611272d06d8efced69e7f4a609b7\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_220c96253f8aedd354ad8343c2016667\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_2e602a54c4d91fa9f13bf1817873386b\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_9d35ebdf31269fb6831eaba54d8f87bd\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_4b2508b7156463722cb2882e1ced8fd9\n\n\n\n\n\n1_16a57ad80c618ed046701f9d6bea507d\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956573da0>\n\n\n\ninput_dict_220c96253f8aedd354ad8343c2016667->1_16a57ad80c618ed046701f9d6bea507d\n\n\n\n\n\n1_b3dca6b1e782f19126f68f1450166e4c\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956573770>\n\n\n\ninput_dict_220c96253f8aedd354ad8343c2016667->1_b3dca6b1e782f19126f68f1450166e4c\n\n\n\n\n\n2_d396dc02378656e5149b50dbea2c6849\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956573bc0>\n\n\n\ninput_dict_2e602a54c4d91fa9f13bf1817873386b->2_d396dc02378656e5149b50dbea2c6849\n\n\n\n\n\n2_774a8fdeb27a17082a2eef733fa8f89a\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x7e89565732c0>\n\n\n\ninput_dict_2e602a54c4d91fa9f13bf1817873386b->2_774a8fdeb27a17082a2eef733fa8f89a\n\n\n\n\n\n3_877d87905334b912a295e5804e3fd1c2\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x7e8956573ef0>\n\n\n\ninput_dict_9d35ebdf31269fb6831eaba54d8f87bd->3_877d87905334b912a295e5804e3fd1c2\n\n\n\n\n\n3_6e96371d1e2c31701a9bf3e866b183ca\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x7e89565738c0>\n\n\n\ninput_dict_9d35ebdf31269fb6831eaba54d8f87bd->3_6e96371d1e2c31701a9bf3e866b183ca\n\n\n\n\n\n4_26ec0cf277f9f46050b75f68dd6eb03e\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x7e89563a4050>\n\n\n\ninput_dict_4b2508b7156463722cb2882e1ced8fd9->4_26ec0cf277f9f46050b75f68dd6eb03e\n\n\n\n\n\n4_df9dceb6d52a2c322ae1cba07c03d9f3\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x7e89565739b0>\n\n\n\ninput_dict_4b2508b7156463722cb2882e1ced8fd9->4_df9dceb6d52a2c322ae1cba07c03d9f3\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa\n\nkpts=[3, 3, 3]\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_d4fd21664755878ddd70933cce962f18\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_9588611272d06d8efced69e7f4a609b7\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_220c96253f8aedd354ad8343c2016667\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_2e602a54c4d91fa9f13bf1817873386b\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_9d35ebdf31269fb6831eaba54d8f87bd\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_4b2508b7156463722cb2882e1ced8fd9\n\n\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34\n\ncalculation=vc-relax\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34->input_dict_9588611272d06d8efced69e7f4a609b7\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9\n\nsmearing=0.02\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_d4fd21664755878ddd70933cce962f18\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_9588611272d06d8efced69e7f4a609b7\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_220c96253f8aedd354ad8343c2016667\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_2e602a54c4d91fa9f13bf1817873386b\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_9d35ebdf31269fb6831eaba54d8f87bd\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_4b2508b7156463722cb2882e1ced8fd9\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86\n\nstrain_lst=[0.9, 0.9500000000000001, 1.0, 1.05, 1.1]\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_8892d31d306c467640f6211152645923\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_3d5c86c809bb793502a724d190fc0992\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_73859cd8cf8266c2c8fca0036718a3ca\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_90f5c8bcaba951371c7a0fca07a3a1c6\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_455912e219ba7dc19b4b63accdb089e8\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83\n\ncalculation=scf\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_d4fd21664755878ddd70933cce962f18\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_220c96253f8aedd354ad8343c2016667\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_2e602a54c4d91fa9f13bf1817873386b\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_9d35ebdf31269fb6831eaba54d8f87bd\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_4b2508b7156463722cb2882e1ced8fd9\n\n\n\n\n\n1_16a57ad80c618ed046701f9d6bea507d->volume_lst_1de093461d597c9482af1b1162abe220\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd\n\nworking_directory=strain_1\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_16a57ad80c618ed046701f9d6bea507d\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_b3dca6b1e782f19126f68f1450166e4c\n\n\n\n\n\n1_b3dca6b1e782f19126f68f1450166e4c->energy_lst_7c0b4a6176947c3cfc7e3ede184ac4cb\n\n\n\n\n\n2_d396dc02378656e5149b50dbea2c6849->volume_lst_1de093461d597c9482af1b1162abe220\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992\n\nworking_directory=strain_2\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_d396dc02378656e5149b50dbea2c6849\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_774a8fdeb27a17082a2eef733fa8f89a\n\n\n\n\n\n2_774a8fdeb27a17082a2eef733fa8f89a->energy_lst_7c0b4a6176947c3cfc7e3ede184ac4cb\n\n\n\n\n\n3_877d87905334b912a295e5804e3fd1c2->volume_lst_1de093461d597c9482af1b1162abe220\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f\n\nworking_directory=strain_3\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_877d87905334b912a295e5804e3fd1c2\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_6e96371d1e2c31701a9bf3e866b183ca\n\n\n\n\n\n3_6e96371d1e2c31701a9bf3e866b183ca->energy_lst_7c0b4a6176947c3cfc7e3ede184ac4cb\n\n\n\n\n\n4_26ec0cf277f9f46050b75f68dd6eb03e->volume_lst_1de093461d597c9482af1b1162abe220\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7\n\nworking_directory=strain_4\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_26ec0cf277f9f46050b75f68dd6eb03e\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_df9dceb6d52a2c322ae1cba07c03d9f3\n\n\n\n\n\n4_df9dceb6d52a2c322ae1cba07c03d9f3->energy_lst_7c0b4a6176947c3cfc7e3ede184ac4cb\n\n\n\n\n\nenergy_lst_7c0b4a6176947c3cfc7e3ede184ac4cb->create_function_job_32ef32f9566b9201becfbb5fe459cf95\n\n\n\n\n" - }, - "metadata": {} - } - ], - "execution_count": 23 - }, - { - "cell_type": "code", - "source": "delayed_object_lst[0].input['a'] = 4.05", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": 24 - }, - { - "cell_type": "code", - "source": "delayed_object_lst[-1].pull()", - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_bulk_structure_f1e730ed97e30e5439e855d2ac41396f was saved and received the ID: 1\nThe job get_dict_1e47509b88d63a21fd421686554c8f4a was saved and received the ID: 2\nThe job calculate_qe_e3c0bf43f7edf24d215901bf93271e87 was saved and received the ID: 3\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03835] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job generate_structures_89c98f83a15c7e4629b528fb8c259dc0 was saved and received the ID: 4\nThe job get_dict_4460300f595bfcc30ce17af0b31c8142 was saved and received the ID: 5\nThe job calculate_qe_ce57e1390b2d70b601bd0b6372b75743 was saved and received the ID: 6\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03850] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_dict_b928c97580ae9dba3e4f7f776dd64ff2 was saved and received the ID: 7\nThe job calculate_qe_199c2f21d205b83b19eb452135f485f4 was saved and received the ID: 8\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03860] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_dict_c07eddc6adee32971572cbe8e5875ddf was saved and received the ID: 9\nThe job calculate_qe_c9beb3d48a3c6888a35ec8b706f0a333 was saved and received the ID: 10\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03870] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_dict_67d13c2b6722a40b6c41623343ace5eb was saved and received the ID: 11\nThe job calculate_qe_0c4bf53901c3453824c0261fbd4a4f7e was saved and received the ID: 12\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03884] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_dict_b70792626f9cb4bfe8bc34627f103fd4 was saved and received the ID: 13\nThe job calculate_qe_86a733fa48f90c657f29f907e2283590 was saved and received the ID: 14\n" - }, - { - "name": "stderr", - "output_type": "stream", - "text": "[jupyter-pyiron-dev-pyth-flow-definition-5x990k36:03894] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" - }, - { - "name": "stdout", - "output_type": "stream", - "text": "The job get_list_cca1d5d7a794bd0ac3693b2b5eca8bc2 was saved and received the ID: 15\nThe job get_list_1acf1cb5d3c716bd2b7eb2614b745c39 was saved and received the ID: 16\nThe job plot_energy_volume_curve_8671230cc853d6cabc56f6f722bbd04e was saved and received the ID: 17\n" - }, - { - "output_type": "display_data", - "data": { - "text/plain": "
", - "image/png": 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" - }, - "metadata": {} - } - ], - "execution_count": 25 - }, - { - "cell_type": "code", - "source": "", - "metadata": { - "trusted": true - }, - "outputs": [], - "execution_count": null - } - ] -} +{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.12.8"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# jobflow","metadata":{}},{"cell_type":"markdown","source":"## Define workflow with jobflow","metadata":{}},{"cell_type":"code","source":"import numpy as np","metadata":{"trusted":true},"outputs":[],"execution_count":1},{"cell_type":"code","source":"from jobflow import job, Flow","metadata":{"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/pkey.py:82: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"cipher\": algorithms.TripleDES,\n/srv/conda/envs/notebook/lib/python3.12/site-packages/paramiko/transport.py:253: CryptographyDeprecationWarning: TripleDES has been moved to cryptography.hazmat.decrepit.ciphers.algorithms.TripleDES and will be removed from cryptography.hazmat.primitives.ciphers.algorithms in 48.0.0.\n \"class\": algorithms.TripleDES,\n"}],"execution_count":2},{"cell_type":"code","source":"from python_workflow_definition.jobflow import write_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":3},{"cell_type":"code","source":"from workflow import (\n calculate_qe as _calculate_qe, \n generate_structures as _generate_structures, \n get_bulk_structure as _get_bulk_structure, \n plot_energy_volume_curve as _plot_energy_volume_curve,\n)","metadata":{"trusted":true},"outputs":[],"execution_count":4},{"cell_type":"code","source":"workflow_json_filename = \"jobflow_qe.json\"","metadata":{"trusted":true},"outputs":[],"execution_count":5},{"cell_type":"code","source":"calculate_qe = job(_calculate_qe)\ngenerate_structures = job(_generate_structures)\nplot_energy_volume_curve = job(_plot_energy_volume_curve)\nget_bulk_structure = job(_get_bulk_structure)","metadata":{"trusted":true},"outputs":[],"execution_count":6},{"cell_type":"code","source":"pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}","metadata":{"trusted":true},"outputs":[],"execution_count":7},{"cell_type":"code","source":"structure = get_bulk_structure(\n element=\"Al\",\n a=4.04,\n cubic=True,\n)","metadata":{"trusted":true},"outputs":[],"execution_count":8},{"cell_type":"code","source":"calc_mini = calculate_qe(\n working_directory=\"mini\",\n input_dict={\n \"structure\": structure.output,\n \"pseudopotentials\": pseudopotentials,\n \"kpts\": (3, 3, 3),\n \"calculation\": \"vc-relax\",\n \"smearing\": 0.02,\n },\n)","metadata":{"trusted":true},"outputs":[],"execution_count":9},{"cell_type":"code","source":"number_of_strains = 5\nstructure_lst = generate_structures(\n structure=calc_mini.output.structure,\n strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n)","metadata":{"trusted":true},"outputs":[],"execution_count":10},{"cell_type":"code","source":"job_strain_lst = []\nfor i in range(number_of_strains):\n calc_strain = calculate_qe(\n working_directory=\"strain_\" + str(i),\n input_dict={\n \"structure\": getattr(structure_lst.output, f\"s_{i}\"),\n \"pseudopotentials\": pseudopotentials,\n \"kpts\": (3, 3, 3),\n \"calculation\": \"scf\",\n \"smearing\": 0.02,\n },\n )\n job_strain_lst.append(calc_strain)","metadata":{"trusted":true},"outputs":[],"execution_count":11},{"cell_type":"code","source":"plot = plot_energy_volume_curve(\n volume_lst=[job.output.volume for job in job_strain_lst],\n energy_lst=[job.output.energy for job in job_strain_lst],\n)","metadata":{"trusted":true},"outputs":[],"execution_count":12},{"cell_type":"code","source":"flow = Flow([structure, calc_mini, structure_lst] + job_strain_lst + [plot])","metadata":{"trusted":true},"outputs":[],"execution_count":13},{"cell_type":"code","source":"write_workflow_json(flow=flow, file_name=workflow_json_filename)","metadata":{"trusted":true},"outputs":[],"execution_count":14},{"cell_type":"code","source":"!cat {workflow_json_filename}","metadata":{"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"{\"nodes\": [{\"id\": 0, \"function\": \"workflow.get_bulk_structure\"}, {\"id\": 1, \"function\": \"workflow.calculate_qe\"}, {\"id\": 2, \"function\": \"workflow.generate_structures\"}, {\"id\": 3, \"function\": \"workflow.calculate_qe\"}, {\"id\": 4, \"function\": \"workflow.calculate_qe\"}, {\"id\": 5, \"function\": \"workflow.calculate_qe\"}, {\"id\": 6, \"function\": \"workflow.calculate_qe\"}, {\"id\": 7, \"function\": \"workflow.calculate_qe\"}, {\"id\": 8, \"function\": \"workflow.plot_energy_volume_curve\"}, {\"id\": 9, \"value\": \"Al\"}, {\"id\": 10, \"value\": 4.04}, {\"id\": 11, \"value\": true}, {\"id\": 12, \"value\": \"mini\"}, {\"id\": 13, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 14, \"value\": {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}}, {\"id\": 15, \"value\": [3, 3, 3]}, {\"id\": 16, \"value\": \"vc-relax\"}, {\"id\": 17, \"value\": 0.02}, {\"id\": 18, \"value\": [0.9, 0.9500000000000001, 1.0, 1.05, 1.1]}, {\"id\": 19, \"value\": \"strain_0\"}, {\"id\": 20, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 21, \"value\": \"scf\"}, {\"id\": 22, \"value\": \"strain_1\"}, {\"id\": 23, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 24, \"value\": \"strain_2\"}, {\"id\": 25, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 26, \"value\": \"strain_3\"}, {\"id\": 27, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 28, \"value\": \"strain_4\"}, {\"id\": 29, \"function\": \"python_workflow_definition.shared.get_dict\"}, {\"id\": 30, \"function\": \"python_workflow_definition.shared.get_list\"}, {\"id\": 31, \"function\": \"python_workflow_definition.shared.get_list\"}], \"edges\": [{\"target\": 0, \"targetPort\": \"element\", \"source\": 9, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"a\", \"source\": 10, \"sourcePort\": null}, {\"target\": 0, \"targetPort\": \"cubic\", \"source\": 11, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"working_directory\", \"source\": 12, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"structure\", \"source\": 0, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"calculation\", \"source\": 16, \"sourcePort\": null}, {\"target\": 13, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 1, \"targetPort\": \"input_dict\", \"source\": 13, \"sourcePort\": null}, {\"target\": 2, \"targetPort\": \"structure\", \"source\": 1, \"sourcePort\": \"structure\"}, {\"target\": 2, \"targetPort\": \"strain_lst\", \"source\": 18, \"sourcePort\": null}, {\"target\": 3, \"targetPort\": \"working_directory\", \"source\": 19, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_0\"}, {\"target\": 20, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 20, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 3, \"targetPort\": \"input_dict\", \"source\": 20, \"sourcePort\": null}, {\"target\": 4, \"targetPort\": \"working_directory\", \"source\": 22, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_1\"}, {\"target\": 23, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 23, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 4, \"targetPort\": \"input_dict\", \"source\": 23, \"sourcePort\": null}, {\"target\": 5, \"targetPort\": \"working_directory\", \"source\": 24, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_2\"}, {\"target\": 25, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 25, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 5, \"targetPort\": \"input_dict\", \"source\": 25, \"sourcePort\": null}, {\"target\": 6, \"targetPort\": \"working_directory\", \"source\": 26, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_3\"}, {\"target\": 27, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 27, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 6, \"targetPort\": \"input_dict\", \"source\": 27, \"sourcePort\": null}, {\"target\": 7, \"targetPort\": \"working_directory\", \"source\": 28, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"structure\", \"source\": 2, \"sourcePort\": \"s_4\"}, {\"target\": 29, \"targetPort\": \"pseudopotentials\", \"source\": 14, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"kpts\", \"source\": 15, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"calculation\", \"source\": 21, \"sourcePort\": null}, {\"target\": 29, \"targetPort\": \"smearing\", \"source\": 17, \"sourcePort\": null}, {\"target\": 7, \"targetPort\": \"input_dict\", \"source\": 29, \"sourcePort\": null}, {\"target\": 30, \"targetPort\": \"0\", \"source\": 3, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"1\", \"source\": 4, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"2\", \"source\": 5, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"3\", \"source\": 6, \"sourcePort\": \"volume\"}, {\"target\": 30, \"targetPort\": \"4\", \"source\": 7, \"sourcePort\": \"volume\"}, {\"target\": 8, \"targetPort\": \"volume_lst\", \"source\": 30, \"sourcePort\": null}, {\"target\": 31, \"targetPort\": \"0\", \"source\": 3, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"1\", \"source\": 4, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"2\", \"source\": 5, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"3\", \"source\": 6, \"sourcePort\": \"energy\"}, {\"target\": 31, \"targetPort\": \"4\", \"source\": 7, \"sourcePort\": \"energy\"}, {\"target\": 8, \"targetPort\": \"energy_lst\", \"source\": 31, \"sourcePort\": null}]}"}],"execution_count":15},{"cell_type":"markdown","source":"## Load Workflow with aiida","metadata":{}},{"cell_type":"code","source":"from aiida import orm, load_profile\n\nload_profile()","metadata":{"trusted":true},"outputs":[{"execution_count":16,"output_type":"execute_result","data":{"text/plain":"Profile"},"metadata":{}}],"execution_count":16},{"cell_type":"code","source":"from python_workflow_definition.aiida import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":17},{"cell_type":"code","source":"wg = load_workflow_json(workflow_json_filename)","metadata":{"trusted":true},"outputs":[],"execution_count":18},{"cell_type":"code","source":"wg.nodes.get_bulk_structure1.inputs.a.value = orm.Float(4.05)","metadata":{"scrolled":true,"trusted":true},"outputs":[],"execution_count":19},{"cell_type":"code","source":"wg","metadata":{"trusted":true},"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":1,"model_id":"adc64841c31f40c68e2f9cdd4652e3ab"}},"metadata":{}}],"execution_count":20},{"cell_type":"code","source":"wg.run()","metadata":{"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":"04/24/2025 02:18:49 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure1\n04/24/2025 02:18:49 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_bulk_structure1, type: PyFunction, finished.\n04/24/2025 02:18:49 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict10\n04/24/2025 02:18:50 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict10, type: PyFunction, finished.\n04/24/2025 02:18:50 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe2\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01816] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:19:40 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n04/24/2025 02:19:40 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe2, type: PyFunction, finished.\n04/24/2025 02:19:40 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures3\n04/24/2025 02:19:41 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: generate_structures3, type: PyFunction, finished.\n04/24/2025 02:19:42 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict11,get_dict12,get_dict13,get_dict14,get_dict15\n04/24/2025 02:19:42 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict11, type: PyFunction, finished.\n04/24/2025 02:19:42 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe4,get_dict12,get_dict13,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01832] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:19:53 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/24/2025 02:19:53 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe4, type: PyFunction, finished.\n04/24/2025 02:19:53 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict12,get_dict13,get_dict14,get_dict15\n04/24/2025 02:19:54 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict12, type: PyFunction, finished.\n04/24/2025 02:19:54 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe5,get_dict13,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01842] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:20:05 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/24/2025 02:20:06 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe5, type: PyFunction, finished.\n04/24/2025 02:20:06 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict13,get_dict14,get_dict15\n04/24/2025 02:20:07 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict13, type: PyFunction, finished.\n04/24/2025 02:20:07 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6,get_dict14,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01852] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:20:19 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/24/2025 02:20:19 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n04/24/2025 02:20:19 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict14,get_dict15\n04/24/2025 02:20:20 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict14, type: PyFunction, finished.\n04/24/2025 02:20:20 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe7,get_dict15\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01862] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:20:34 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/24/2025 02:20:34 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe7, type: PyFunction, finished.\n04/24/2025 02:20:35 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict15\n04/24/2025 02:20:35 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_dict15, type: PyFunction, finished.\n04/24/2025 02:20:35 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe8\n[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01876] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n04/24/2025 02:20:51 PM <1741> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n04/24/2025 02:20:51 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: calculate_qe8, type: PyFunction, finished.\n04/24/2025 02:20:51 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list16,get_list17\n04/24/2025 02:20:52 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_list16, type: PyFunction, finished.\n04/24/2025 02:20:52 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list17\n04/24/2025 02:20:52 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: get_list17, type: PyFunction, finished.\n04/24/2025 02:20:52 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve9\n04/24/2025 02:20:53 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve9, type: PyFunction, finished.\n04/24/2025 02:20:53 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n04/24/2025 02:20:54 PM <1741> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [58|WorkGraphEngine|finalize]: Finalize workgraph.\n"},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"execution_count":21},{"cell_type":"markdown","source":"## Load Workflow with pyiron_base","metadata":{}},{"cell_type":"code","source":"from python_workflow_definition.pyiron_base import load_workflow_json","metadata":{"trusted":true},"outputs":[],"execution_count":22},{"cell_type":"code","source":"delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()","metadata":{"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"","image/svg+xml":"\n\n\n\n\ncreate_function_job_4d3ed4e7c563ae330e22f930d0400ed1\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a2ab0>\n\n\n\nvolume_lst_8f481a1c2032fb2664763537b0da7fe5\n\nvolume_lst=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a2840>\n\n\n\nvolume_lst_8f481a1c2032fb2664763537b0da7fe5->create_function_job_4d3ed4e7c563ae330e22f930d0400ed1\n\n\n\n\n\n0_ef19beb41624e4e0008e53d9d5b9d119\n\n0=<pyiron_base.project.delayed.DelayedObject object at 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0x75fb83973620>\n\n\n\ninput_dict_6788a3e86aac081f9530a587e4e014f1->structure_f8bc49b8d2c99821a1af955c22172dc5\n\n\n\n\n\nstructure_e9df848813fc62a9f6779fd8d4b62535\n\nstructure=<pyiron_base.project.delayed.DelayedObject object at 0x75fb83973830>\n\n\n\nstructure_e9df848813fc62a9f6779fd8d4b62535->input_dict_6788a3e86aac081f9530a587e4e014f1\n\n\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0\n\nelement=Al\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0->structure_e9df848813fc62a9f6779fd8d4b62535\n\n\n\n\n\na_457b6d376c6fce696df148a385afa46d\n\na=4.04\n\n\n\na_457b6d376c6fce696df148a385afa46d->structure_e9df848813fc62a9f6779fd8d4b62535\n\n\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a\n\ncubic=True\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a->structure_e9df848813fc62a9f6779fd8d4b62535\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10\n\npseudopotentials={'Al': 'Al.pbe-n-kjpaw_psl.1.0.0.UPF'}\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_adcb8214845c6f8ca7a9f217ca605d92\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_6788a3e86aac081f9530a587e4e014f1\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_52e847aed32e0c3b8d5cce4046119fea\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_484844f6c9f4804aeb0ebb63b8fa3096\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_a8652fe185a1b8add35aa55273a41532\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_e6ce1da5514cd71e266fc2718ca86f14\n\n\n\n\n\n1_51d5b1ef225b81dcb707362e767ddf31\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a2270>\n\n\n\ninput_dict_52e847aed32e0c3b8d5cce4046119fea->1_51d5b1ef225b81dcb707362e767ddf31\n\n\n\n\n\n1_e84622c341e50289fd3d7396cf64aaa9\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a1c40>\n\n\n\ninput_dict_52e847aed32e0c3b8d5cce4046119fea->1_e84622c341e50289fd3d7396cf64aaa9\n\n\n\n\n\n2_7a05249df5ced08ddddf5c3d6bf864a3\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a2090>\n\n\n\ninput_dict_484844f6c9f4804aeb0ebb63b8fa3096->2_7a05249df5ced08ddddf5c3d6bf864a3\n\n\n\n\n\n2_f81d5b2784ff607e4830e3fcae0a7566\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a1850>\n\n\n\ninput_dict_484844f6c9f4804aeb0ebb63b8fa3096->2_f81d5b2784ff607e4830e3fcae0a7566\n\n\n\n\n\n3_eeed557abcafc052c1b7626ab00a4b2b\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a23f0>\n\n\n\ninput_dict_a8652fe185a1b8add35aa55273a41532->3_eeed557abcafc052c1b7626ab00a4b2b\n\n\n\n\n\n3_7f66b5d1a8afda658d25152ca5ce852c\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a1dc0>\n\n\n\ninput_dict_a8652fe185a1b8add35aa55273a41532->3_7f66b5d1a8afda658d25152ca5ce852c\n\n\n\n\n\n4_12b2d8e6d7e2e61d2a5708f6ba633ae1\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a24b0>\n\n\n\ninput_dict_e6ce1da5514cd71e266fc2718ca86f14->4_12b2d8e6d7e2e61d2a5708f6ba633ae1\n\n\n\n\n\n4_2dc46d83cd73aa36387c694fededf8d1\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x75fb837a1e80>\n\n\n\ninput_dict_e6ce1da5514cd71e266fc2718ca86f14->4_2dc46d83cd73aa36387c694fededf8d1\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa\n\nkpts=[3, 3, 3]\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_adcb8214845c6f8ca7a9f217ca605d92\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_6788a3e86aac081f9530a587e4e014f1\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_52e847aed32e0c3b8d5cce4046119fea\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_484844f6c9f4804aeb0ebb63b8fa3096\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_a8652fe185a1b8add35aa55273a41532\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_e6ce1da5514cd71e266fc2718ca86f14\n\n\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34\n\ncalculation=vc-relax\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34->input_dict_6788a3e86aac081f9530a587e4e014f1\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9\n\nsmearing=0.02\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_adcb8214845c6f8ca7a9f217ca605d92\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_6788a3e86aac081f9530a587e4e014f1\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_52e847aed32e0c3b8d5cce4046119fea\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_484844f6c9f4804aeb0ebb63b8fa3096\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_a8652fe185a1b8add35aa55273a41532\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_e6ce1da5514cd71e266fc2718ca86f14\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86\n\nstrain_lst=[0.9, 0.9500000000000001, 1.0, 1.05, 1.1]\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_6d41e0eac8dfd18f09880d77216e7f15\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_6cccbc8c9e2e8a9c676ebd7f81495653\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_b319381aa5a2e4aac9814b7285e411f2\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_707d1bdbbecf3410f0a6bbde3d033846\n\n\n\n\n\nstrain_lst_17d5bcbc7579ab5e0f98577d05347b86->structure_f09b1d6b22659890eabfbd87ea7a04c9\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83\n\ncalculation=scf\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_adcb8214845c6f8ca7a9f217ca605d92\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_52e847aed32e0c3b8d5cce4046119fea\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_484844f6c9f4804aeb0ebb63b8fa3096\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_a8652fe185a1b8add35aa55273a41532\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_e6ce1da5514cd71e266fc2718ca86f14\n\n\n\n\n\n1_51d5b1ef225b81dcb707362e767ddf31->volume_lst_8f481a1c2032fb2664763537b0da7fe5\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd\n\nworking_directory=strain_1\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_51d5b1ef225b81dcb707362e767ddf31\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_e84622c341e50289fd3d7396cf64aaa9\n\n\n\n\n\n1_e84622c341e50289fd3d7396cf64aaa9->energy_lst_291d449ffe6031374863f6c90014edea\n\n\n\n\n\n2_7a05249df5ced08ddddf5c3d6bf864a3->volume_lst_8f481a1c2032fb2664763537b0da7fe5\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992\n\nworking_directory=strain_2\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_7a05249df5ced08ddddf5c3d6bf864a3\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_f81d5b2784ff607e4830e3fcae0a7566\n\n\n\n\n\n2_f81d5b2784ff607e4830e3fcae0a7566->energy_lst_291d449ffe6031374863f6c90014edea\n\n\n\n\n\n3_eeed557abcafc052c1b7626ab00a4b2b->volume_lst_8f481a1c2032fb2664763537b0da7fe5\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f\n\nworking_directory=strain_3\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_eeed557abcafc052c1b7626ab00a4b2b\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_7f66b5d1a8afda658d25152ca5ce852c\n\n\n\n\n\n3_7f66b5d1a8afda658d25152ca5ce852c->energy_lst_291d449ffe6031374863f6c90014edea\n\n\n\n\n\n4_12b2d8e6d7e2e61d2a5708f6ba633ae1->volume_lst_8f481a1c2032fb2664763537b0da7fe5\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7\n\nworking_directory=strain_4\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_12b2d8e6d7e2e61d2a5708f6ba633ae1\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_2dc46d83cd73aa36387c694fededf8d1\n\n\n\n\n\n4_2dc46d83cd73aa36387c694fededf8d1->energy_lst_291d449ffe6031374863f6c90014edea\n\n\n\n\n\nenergy_lst_291d449ffe6031374863f6c90014edea->create_function_job_4d3ed4e7c563ae330e22f930d0400ed1\n\n\n\n\n"},"metadata":{}}],"execution_count":23},{"cell_type":"code","source":"delayed_object_lst[0].input['a'] = 4.05","metadata":{"trusted":true},"outputs":[],"execution_count":24},{"cell_type":"code","source":"delayed_object_lst[-1].pull()","metadata":{"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"The job get_bulk_structure_2ca4aeae204ceaa28593c93054b07908 was saved and received the ID: 1\nThe job get_dict_1e47509b88d63a21fd421686554c8f4a was saved and received the ID: 2\nThe job calculate_qe_411e578f2700d09ba2df9a4c682b4582 was saved and received the ID: 3\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01906] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job generate_structures_a2be118b5bff59eaa11d83f99eaced4d was saved and received the ID: 4\nThe job get_dict_e6e21d04c5680e1114b80a92bc2e359c was saved and received the ID: 5\nThe job calculate_qe_51a232f4324d311c7fd4f7f769ddfdfe was saved and received the ID: 6\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01916] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job get_dict_437c0ffaf598d0a286c53012d3d36f25 was saved and received the ID: 7\nThe job calculate_qe_8fb25b130b8e8e933d28d21f7c44b4ca was saved and received the ID: 8\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01926] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job get_dict_d1a00c031f330c896c8f5af25db5235b was saved and received the ID: 9\nThe job calculate_qe_042e4d560dcfc093eea3a34f7e523669 was saved and received the ID: 10\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01938] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job get_dict_ea36d0f502795b1fc4b32e62fce9820d was saved and received the ID: 11\nThe job calculate_qe_b4bd2031ca3d40580969fda1aecee94a was saved and received the ID: 12\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01948] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job get_dict_d190d6b6e585cababdcd49a344547984 was saved and received the ID: 13\nThe job calculate_qe_b3927880779bfca53ff78c00360e9527 was saved and received the ID: 14\n"},{"name":"stderr","output_type":"stream","text":"[jupyter-pyiron-dev-pyth-flow-definition-kk01elen:01958] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n"},{"name":"stdout","output_type":"stream","text":"The job get_list_90f0281f335962d10db1b3572abe82df was saved and received the ID: 15\nThe job get_list_09fa36007fd192f793a1f218b70fe87b was saved and received the ID: 16\nThe job plot_energy_volume_curve_8d8f280c69be12b1969d95cc53f9411b was saved and received the ID: 17\n"},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"execution_count":25},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]} 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