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Rename simple to arithmetic (#70)
* Rename simple to arithmetic * fix * another fix * rename file
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.github/workflows/pipeline.yml

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@@ -67,7 +67,7 @@ jobs:
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papermill pyiron_base_qe.ipynb pyiron_base_qe_out.ipynb -k "python3"
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papermill universal_workflow_qe.ipynb universal_workflow_qe_out.ipynb -k "python3"
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simple:
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arithmetic:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Tests
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shell: bash -l {0}
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run: |
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papermill aiida_simple.ipynb aiida_simple_out.ipynb -k "python3"
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papermill jobflow_simple.ipynb jobflow_simple_out.ipynb -k "python3"
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papermill pyiron_base_simple.ipynb pyiron_base_simple_out.ipynb -k "python3"
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papermill universal_workflow_simple.ipynb universal_workflow_simple_out.ipynb -k "python3"
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papermill aiida_arithmetic.ipynb aiida_arithmetic_out.ipynb -k "python3"
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papermill jobflow_arithmetic.ipynb jobflow_arithmetic_out.ipynb -k "python3"
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papermill pyiron_base_arithmetic.ipynb pyiron_base_arithmetic_out.ipynb -k "python3"
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papermill universal_workflow_arithmetic.ipynb universal_workflow_arithmetic_out.ipynb -k "python3"
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book:
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runs-on: ubuntu-latest

README.md

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@@ -27,8 +27,8 @@ These two Python functions are combined in the following example workflow:
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tmp_dict = get_prod_and_div(x=1, y=2)
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result = get_sum(x=tmp_dict["prod"], y=tmp_dict["div"])
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```
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For the workflow representation of these Python functions the Python functions are stored in the [simple_workflow.py](simple_workflow.py)
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Python module. The connection of the Python functions are stored in the [workflow_simple.json](workflow_simple.json)
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For the workflow representation of these Python functions the Python functions are stored in the [arithmetic_workflow.py](arithmetic_workflow.py)
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Python module. The connection of the Python functions are stored in the [workflow_arithmetic.json](workflow_arithmetic.json)
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JSON file:
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```
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{
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The corresponding Jupyter notebooks demonstrate this functionality:
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| Example | Explanation |
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|--------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
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| [aiida_simple.ipynb](aiida_simple.ipynb) | Define Workflow with aiida and execute it with jobflow and pyiron_base. |
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| [jobflow_simple.ipynb](jobflow_simple.ipynb) | Define Workflow with jobflow and execute it with aiida and pyiron_base. |
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| [pyiron_base_simple.ipynb](pyiron_base_simple.ipynb) | Define Workflow with pyiron_base and execute it with aiida and jobflow. |
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| [universal_workflow_simple.ipynb](universal_workflow_simple.ipynb) | Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python. |
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| Example | Explanation |
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|----------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
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| [aiida_arithmetic.ipynb](aiida_arithmetic.ipynb) | Define Workflow with aiida and execute it with jobflow and pyiron_base. |
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| [jobflow_arithmetic.ipynb](jobflow_arithmetic.ipynb) | Define Workflow with jobflow and execute it with aiida and pyiron_base. |
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| [pyiron_base_arithmetic.ipynb](pyiron_base_arithmetic.ipynb) | Define Workflow with pyiron_base and execute it with aiida and jobflow. |
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| [universal_workflow_arithmetic.ipynb](universal_workflow_arithmetic.ipynb) | Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python. |
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### Quantum Espresso Workflow
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The second workflow example is the calculation of an energy volume curve with Quantum Espresso. In the first step the
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{
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"cell_type": "code",
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"source": [
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"from simple_workflow import (\n",
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"from arithmetic_workflow import (\n",
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" get_sum as _get_sum,\n",
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" get_prod_and_div as _get_prod_and_div,\n",
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")"
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},
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{
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"cell_type": "code",
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"source": "wg = WorkGraph(\"wg-simple\")",
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"source": "wg = WorkGraph(\"arithmetic\")",
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"metadata": {
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"trusted": true
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},

book/_toc.yml

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root: README
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chapters:
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- file: intro.md
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- file: simple.md
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- file: arithmetic.md
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sections:
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- file: aiida_simple.ipynb
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- file: jobflow_simple.ipynb
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- file: pyiron_base_simple.ipynb
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- file: aiida_arithmetic.ipynb
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- file: jobflow_arithmetic.ipynb
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- file: pyiron_base_arithmetic.ipynb
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- file: evcurve.md
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sections:
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- file: aiida_qe.ipynb

book/simple.md renamed to book/arithmetic.md

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# Simple Workflow
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# Arithmetic Workflow
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As a first example we define two Python functions which add multiple inputs:
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```python
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def get_sum(x, y):
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tmp_dict = get_prod_and_div(x=1, y=2)
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result = get_sum(x=tmp_dict["prod"], y=tmp_dict["div"])
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```
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For the workflow representation of these Python functions the Python functions are stored in the [simple_workflow.py](simple_workflow.py)
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Python module. The connection of the Python functions are stored in the [workflow_simple.json](workflow_simple.json)
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For the workflow representation of these Python functions the Python functions are stored in the [arithmetic_workflow.py](arithmetic_workflow.py)
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Python module. The connection of the Python functions are stored in the [workflow_arithmetic.json](workflow_arithmetic.json)
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JSON file:
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```
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{
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"nodes": [
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{"id": 0, "function": "simple_workflow.get_prod_and_div"},
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{"id": 1, "function": "simple_workflow.get_sum"},
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{"id": 0, "function": "arithmetic_workflow.get_prod_and_div"},
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{"id": 1, "function": "arithmetic_workflow.get_sum"},
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{"id": 2, "value": 1},
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{"id": 3, "value": 2}
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],
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"id": "fb847d49-7bf9-4839-9b99-c116d1b0e9ee",
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"cell_type": "code",
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"source": [
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"from simple_workflow import (\n",
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"from arithmetic_workflow import (\n",
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" get_sum as _get_sum,\n",
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" get_prod_and_div as _get_prod_and_div,\n",
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")"
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"id": "fb847d49-7bf9-4839-9b99-c116d1b0e9ee",
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"cell_type": "code",
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"source": [
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"from simple_workflow import (\n",
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"from arithmetic_workflow import (\n",
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" get_sum as _get_sum,\n",
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" get_prod_and_div as _get_prod_and_div,\n",
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")"
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{
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"id": "8f95244e",
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"cell_type": "code",
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"source": "workflow_json_filename = \"pyiron_base_simple.json\"",
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"source": "workflow_json_filename = \"pyiron_arithmetic.json\"",
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"metadata": {
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"trusted": true
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},
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},
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{
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"cell_type": "code",
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"source": "plot(file_name='workflow_simple.json')",
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"source": "plot(file_name='workflow_arithmetic.json')",
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"metadata": {
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"trusted": true
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},
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},
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{
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"cell_type": "code",
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"source": "workgraph = load_workflow_json(file_name='workflow_simple.json')",
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"source": "workgraph = load_workflow_json(file_name='workflow_arithmetic.json')",
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"metadata": {
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"trusted": true
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},
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},
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{
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"cell_type": "code",
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"source": "with SingleNodeExecutor(max_workers=1) as exe:\n result = load_workflow_json(file_name=\"workflow_simple.json\", exe=exe).result()",
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"source": "with SingleNodeExecutor(max_workers=1) as exe:\n result = load_workflow_json(file_name=\"workflow_arithmetic.json\", exe=exe).result()",
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"metadata": {
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"trusted": true
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},
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},
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{
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"cell_type": "code",
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"source": "flow = load_workflow_json(file_name=\"workflow_simple.json\")",
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"source": "flow = load_workflow_json(file_name=\"workflow_arithmetic.json\")",
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"metadata": {
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"trusted": true
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},
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{
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"cell_type": "code",
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"source": [
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"delayed_object_lst = load_workflow_json(file_name=\"workflow_simple.json\")\n",
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"delayed_object_lst = load_workflow_json(file_name=\"workflow_arithmetic.json\")\n",
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"delayed_object_lst[-1].draw()"
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],
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"metadata": {
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},
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{
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"cell_type": "code",
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"source": "load_workflow_json(file_name=\"workflow_simple.json\")",
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"source": "load_workflow_json(file_name=\"workflow_arithmetic.json\")",
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"metadata": {
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"trusted": true
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},
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{
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"nodes": [
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{"id": 0, "function": "simple_workflow.get_prod_and_div"},
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{"id": 1, "function": "simple_workflow.get_sum"},
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{"id": 0, "function": "arithmetic_workflow.get_prod_and_div"},
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{"id": 1, "function": "arithmetic_workflow.get_sum"},
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{"id": 2, "value": 1},
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{"id": 3, "value": 2}
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],

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