Issue with finding the dependencies among the sub-tasks of a primary calculation using pymatgen API. #3884

hongyi-zhao · 2024-06-17T00:41:26Z

hongyi-zhao
Jun 17, 2024

Dear pymatgen Development Team,

I want to retrieve task dependencies and their corresponding directories using the pymatgen API. However, I am encountering an issue where the dir_name field is not being returned in the TaskDoc documents, despite explicitly requesting it.

Here is a snippet of the code I am using:

from mp_api.client import MPRester

material_id = "mp-1183063"

# Get all task IDs related to the given material ID
with MPRester() as mpr:
    tasks = mpr.materials.search(material_ids=[material_id], fields=["task_ids"])

# Print all task IDs
print("All related task IDs:")
task_ids = tasks[0].task_ids
for task_id in task_ids:
    print(task_id)

# Analyze the dependencies between different task IDs
print("\nDependencies between task IDs:")
path_to_mp_id = {}
for task_id in task_ids:
    with MPRester() as mpr:
        selected_task = mpr.materials.tasks.search(task_ids=[task_id], fields=["task_id", "calcs_reversed"])

    if selected_task:
        task = selected_task[0]
        calcs_reversed = getattr(task, "calcs_reversed", [])
        if calcs_reversed:
            print(f"\nTask ID {task_id} reverse dependencies:")
            for calc in calcs_reversed:
                reverse_task_dir = calc["dir_name"] if "dir_name" in calc else "dir_name field not found"
                print(f"  - {reverse_task_dir}")
                path_to_mp_id[reverse_task_dir] = None  # Initialize dictionary

        else:
            print(f"\nTask ID {task_id} has no reverse dependencies.")
    else:
        print(f"\nNo data found for task_id: {task_id}")

# Get detailed information for all related tasks
all_task_details = []
with MPRester() as mpr:
    for task_id in task_ids:
        task_details = mpr.materials.tasks.search(task_ids=[task_id], fields=["*"])
        all_task_details.extend(task_details)

# Print detailed information for all tasks
print("\nDetailed information for all tasks:")
for task_detail in all_task_details:
    print(task_detail)  # Directly print MPDataDoc object

# Find the mp-id corresponding to each path
print("\nFinding mp-id for each path:")
for path in path_to_mp_id.keys():
    found = False
    for task_detail in all_task_details:
        if hasattr(task_detail, "dir_name") and task_detail.dir_name == path:
            path_to_mp_id[path] = task_detail.task_id
            found = True
            break
    if not found:
        print(f"Path not found: {path}")

# Print the mapping from path to mp-id
print("\nMapping from path to mp-id:")
for path, mp_id in path_to_mp_id.items():
    print(f"Path: {path} -> mp-id: {mp_id}")

The output I receive indicates that the dir_name field is not found:

Retrieving MaterialsDoc documents: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 10131.17it/s]
All related task IDs:
mp-2091866
mp-1183063
mp-1957696
mp-1383698
mp-1933559
mp-2309155
mp-1757249
mp-1951473
mp-1626915

Dependencies between task IDs:
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12052.60it/s]

Task ID mp-2091866 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11366.68it/s]

Task ID mp-1183063 reverse dependencies:
  - dir_name field not found
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12264.05it/s]

Task ID mp-1957696 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11522.81it/s]

Task ID mp-1383698 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11781.75it/s]

Task ID mp-1933559 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11949.58it/s]

Task ID mp-2309155 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11949.58it/s]

Task ID mp-1757249 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11748.75it/s]

Task ID mp-1951473 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11586.48it/s]

Task ID mp-1626915 reverse dependencies:
  - dir_name field not found
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11491.24it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11915.64it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12633.45it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12087.33it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11881.88it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12122.27it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11949.58it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11748.75it/s]
Retrieving TaskDoc documents: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11949.58it/s]

Detailed information for all tasks:
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']
MPDataDoc<TaskDoc>


Fields not requested:
['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated']

Finding mp-id for each path:
Path not found: dir_name field not found

Mapping from path to mp-id:
Path: dir_name field not found -> mp-id: None

Could you please help me understand why the dir_name field is not being returned and how I can successfully retrieve it?

Thank you for your time and assistance.

Best regards,
Zhao

Answered by QuantumChemist

Jun 17, 2024

hmm.... you basically produced the same result.

At this point, I'm not quite sure if you can extract the sequential order of the jobs using the MP API.

The entries of the MPIDs are according to "last_updated":

tasks = mpr.materials.search(material_ids=[material_id])
for task in tasks:
    for mpid, dft_type in task.calc_types.items():
        print(mpid, dft_type, mpr.materials.tasks.search(task_ids=[mpid])[0].last_updated)

with the output:

Retrieving MaterialsDoc documents: 100%|██████████| 1/1 [00:00<00:00, 34379.54it/s]
mp-1183063 GGA Structure Optimization 2019-01-11 11:43:27.830000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 32768.00it/s]
Retrieving TaskDoc docum…

View full answer

QuantumChemist · 2024-06-17T09:01:51Z

QuantumChemist
Jun 17, 2024

Dear @hongyi-zhao ,

when you print the dir_name of the task_detail like this

for task_detail in all_task_details:
    print(task_detail.dir_name)

You will get None as output, so dir_name does exist, returning None because you first have to run a calculation (e.g., VASP) for the field to be updated.

Alternatively, you can also print all the entries:

for task_detail in all_task_details:
    for item in task_detail:
        print(item)

which will get you

('builder_meta', None)
('nsites', None)
('elements', None)
('nelements', None)
('composition', None)
('composition_reduced', None)
('formula_pretty', None)
('formula_anonymous', None)
('chemsys', None)
('volume', None)
('density', None)
('density_atomic', None)
('symmetry', None)
('tags', None)
('dir_name', None)
('state', None)
('calcs_reversed', None)
('structure', None)
('task_type', None)
('task_id', None)
('orig_inputs', None)
('input', None)
('output', None)
('included_objects', None)
('vasp_objects', None)
('entry', None)
('task_label', None)
('author', None)
('icsd_id', None)
('transformations', None)
('additional_json', None)
('custodian', None)
('analysis', None)
('last_updated', None)
('fields_not_requested', ['builder_meta', 'nsites', 'elements', 'nelements', 'composition', 'composition_reduced', 'formula_pretty', 'formula_anonymous', 'chemsys', 'volume', 'density', 'density_atomic', 'symmetry', 'tags', 'dir_name', 'state', 'calcs_reversed', 'structure', 'task_type', 'task_id', 'orig_inputs', 'input', 'output', 'included_objects', 'vasp_objects', 'entry', 'task_label', 'author', 'icsd_id', 'transformations', 'additional_json', 'custodian', 'analysis', 'last_updated'])

Again, every entry is None because you just initialized the TaskDoc and have to run a calculation for the entries to be updated.

13 replies

QuantumChemist Jun 17, 2024

if you look closer, you'll see that the GGA Structure Optimization (I think the DFT lvl is PBE), R2SCAN Structure Optimization and the PBEsol Structure Optimization are the ones showing no dependencies, so the structural optimization was most likely started from the experimental data (e.g. ICSD data) or so in each case. Therefore they don't depend on the other calculations. (At least that's what I think)

For the case of multiple dependencies: When comparing the IDs and the calculation types they belong to, it appears to me that the order of the IDs in the list has been the sequence of the calculation executions, but honestly I wouldn't know why one would do a R2SCAN structure optimization before a PBEsol structure optimization...

QuantumChemist Jun 17, 2024

Or in other words, this

Calculation Types:
Task ID: mp-1183063, Calculation Type: GGA Structure Optimization
Task ID: mp-1383698, Calculation Type: GGA Static
Task ID: mp-1757249, Calculation Type: GGA NSCF Uniform
Task ID: mp-1933559, Calculation Type: GGA Static
Task ID: mp-1626915, Calculation Type: GGA NSCF Uniform
Task ID: mp-1957696, Calculation Type: R2SCAN Structure Optimization
Task ID: mp-1951473, Calculation Type: PBESol Structure Optimization
Task ID: mp-2091866, Calculation Type: GGA NSCF Uniform
Task ID: mp-2309155, Calculation Type: GGA NSCF Uniform

has been the sequence of the calculation. But I'm not 100% sure.

hongyi-zhao Jun 17, 2024
Author

Now, I construct a dependency graph and then use topological sorting to ensure the dependencies are in the correct order, as shown below:

from mp_api.client import MPRester
from collections import defaultdict, deque

def standardize_task_type(task_type):
    """Standardize the task type string"""
    return str(task_type).replace('_', ' ').title()

def analyze_dependencies(item):
    task_types = item.task_types
    calc_types = item.calc_types
    run_types = item.run_types  # Assuming run_types is available in the item

    # Print task types, calculation types, and run types for debugging
    print("\nTask Types:")
    for task_id, task_type in task_types.items():
        print(f"Task ID: {task_id}, Task Type: {task_type}")

    print("\nCalculation Types:")
    for task_id, calc_type in calc_types.items():
        print(f"Task ID: {task_id}, Calculation Type: {calc_type}")

    print("\nRun Types:")
    for task_id, run_type in run_types.items():
        print(f"Task ID: {task_id}, Run Type: {run_type}")

    dependencies = defaultdict(list)
    for task_id, task_type in task_types.items():
        dependencies[task_id] = []

    # Determine dependencies based on task type, calculation type, and run type
    task_ids = list(task_types.keys())
    for i in range(len(task_ids)):
        current_task_id = task_ids[i]
        current_task_type = standardize_task_type(task_types[current_task_id])
        current_calc_type = calc_types.get(current_task_id, None)
        current_run_type = run_types.get(current_task_id, None)

        for j in range(i):
            previous_task_id = task_ids[j]
            previous_task_type = standardize_task_type(task_types[previous_task_id])
            previous_calc_type = calc_types.get(previous_task_id, None)
            previous_run_type = run_types.get(previous_task_id, None)

            # Determine dependencies based on task type, calculation type, and run type
            if current_task_type in ['Nscf Line', 'Nscf Uniform'] and previous_task_type in ['Structure Optimization', 'Static']:
                dependencies[current_task_id].append(previous_task_id)
            elif current_task_type == 'Static' and previous_task_type == 'Structure Optimization':
                dependencies[current_task_id].append(previous_task_id)

    # Function to perform topological sort
    def topological_sort(dependencies):
        in_degree = {u: 0 for u in dependencies}  # Initialize in-degree of each node to 0
        for u in dependencies:
            for v in dependencies[u]:
                in_degree[v] += 1  # Calculate in-degree of each node

        queue = deque([u for u in dependencies if in_degree[u] == 0])  # Nodes with in-degree 0
        topo_order = []

        while queue:
            u = queue.popleft()
            topo_order.append(u)
            for v in dependencies[u]:
                in_degree[v] -= 1
                if in_degree[v] == 0:
                    queue.append(v)

        return topo_order

    # Perform topological sort to get the correct order
    sorted_tasks = topological_sort(dependencies)

    # Print dependencies in topologically sorted order
    print("\nDependencies:")
    for task_id in sorted_tasks:
        print(f"Task ID: {task_id}")
        print(f"  Depends on: {dependencies[task_id]}")

material_id = "mp-1183063"

with MPRester() as mpr:
    tasks = mpr.materials.search(material_ids=[material_id])
    for item in tasks:
        analyze_dependencies(item)

The result is as follows:

Retrieving MaterialsDoc documents: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 10810.06it/s]

Task Types:
Task ID: mp-1183063, Task Type: Structure Optimization
Task ID: mp-1383698, Task Type: Static
Task ID: mp-1757249, Task Type: NSCF Uniform
Task ID: mp-1933559, Task Type: Static
Task ID: mp-1626915, Task Type: NSCF Line
Task ID: mp-1957696, Task Type: Structure Optimization
Task ID: mp-1951473, Task Type: Structure Optimization
Task ID: mp-2091866, Task Type: NSCF Line
Task ID: mp-2309155, Task Type: NSCF Line

Calculation Types:
Task ID: mp-1183063, Calculation Type: GGA Structure Optimization
Task ID: mp-1383698, Calculation Type: GGA Static
Task ID: mp-1757249, Calculation Type: GGA NSCF Uniform
Task ID: mp-1933559, Calculation Type: GGA Static
Task ID: mp-1626915, Calculation Type: GGA NSCF Uniform
Task ID: mp-1957696, Calculation Type: R2SCAN Structure Optimization
Task ID: mp-1951473, Calculation Type: PBESol Structure Optimization
Task ID: mp-2091866, Calculation Type: GGA NSCF Uniform
Task ID: mp-2309155, Calculation Type: GGA NSCF Uniform

Run Types:
Task ID: mp-1183063, Run Type: GGA
Task ID: mp-1383698, Run Type: GGA
Task ID: mp-1757249, Run Type: GGA
Task ID: mp-1933559, Run Type: GGA
Task ID: mp-1626915, Run Type: GGA
Task ID: mp-1957696, Run Type: R2SCAN
Task ID: mp-1951473, Run Type: PBESol
Task ID: mp-2091866, Run Type: GGA
Task ID: mp-2309155, Run Type: GGA

Dependencies:
Task ID: mp-1757249
  Depends on: ['mp-1183063', 'mp-1383698']
Task ID: mp-1626915
  Depends on: ['mp-1183063', 'mp-1383698', 'mp-1933559']
Task ID: mp-2091866
  Depends on: ['mp-1183063', 'mp-1383698', 'mp-1933559', 'mp-1957696', 'mp-1951473']
Task ID: mp-2309155
  Depends on: ['mp-1183063', 'mp-1383698', 'mp-1933559', 'mp-1957696', 'mp-1951473']
Task ID: mp-1383698
  Depends on: ['mp-1183063']
Task ID: mp-1933559
  Depends on: ['mp-1183063']
Task ID: mp-1957696
  Depends on: []
Task ID: mp-1951473
  Depends on: []
Task ID: mp-1183063
  Depends on: []

What do you think of the above result?

QuantumChemist Jun 17, 2024

hmm.... you basically produced the same result.

At this point, I'm not quite sure if you can extract the sequential order of the jobs using the MP API.

The entries of the MPIDs are according to "last_updated":

tasks = mpr.materials.search(material_ids=[material_id])
for task in tasks:
    for mpid, dft_type in task.calc_types.items():
        print(mpid, dft_type, mpr.materials.tasks.search(task_ids=[mpid])[0].last_updated)

with the output:

Retrieving MaterialsDoc documents: 100%|██████████| 1/1 [00:00<00:00, 34379.54it/s]
mp-1183063 GGA Structure Optimization 2019-01-11 11:43:27.830000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 32768.00it/s]
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 38130.04it/s]
mp-1383698 GGA Static 2020-05-03 14:53:11.108000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 36472.21it/s]
mp-1757249 GGA NSCF Uniform 2020-07-23 03:44:17.290000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 41527.76it/s]
mp-1933559 GGA Static 2021-02-10 02:16:44.369000
mp-1626915 GGA NSCF Uniform 2021-02-22 08:53:53.912000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 43690.67it/s]
mp-1957696 R2SCAN Structure Optimization 2021-03-05 06:35:44.432000
Retrieving TaskDoc documents: 100%|██████████| 1/1 [00:00<00:00, 45590.26it/s]
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mp-1951473 PBESol Structure Optimization 2021-03-05 13:40:42.669000
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mp-2091866 GGA NSCF Uniform 2021-07-13 01:05:36.311000
mp-2309155 GGA NSCF Uniform 2022-06-10 11:43:35.117000
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But regarding the correct sequence of DFT calculations, why don't you rely on the atomate2 VASP workflows, e.g. the BandStructureMaker?

Answer selected by hongyi-zhao

hongyi-zhao Jun 18, 2024
Author

But regarding the correct sequence of DFT calculations, why don't you rely on the atomate2 VASP workflows,

I have a question: Are the MP website databases built via atomate2?

Another question: Should I use atomate or atomate2?

e.g. the BandStructureMaker?

RelaxBandStructureMaker will do a one-shot calculation for this type of job.

hongyi-zhao Jul 1, 2024
Author

I have a question: Are the MP website databases built via atomate2?

See JaGeo/TutorialAtomate2Forcefields#4 (comment) for the related comments.

Another question: Should I use atomate or atomate2?

See https://matsci.org/t/using-atomate-and-atomate2-in-the-same-virtual-environment/56000 for the related comments.

Also, see below for the related discussions:

hongyi-zhao Nov 15, 2024
Author

#3884 (reply in thread)
The entries of the MPIDs are according to "last_updated":

tasks = mpr.materials.search(material_ids=[material_id])
for task in tasks:
    for mpid, dft_type in task.calc_types.items():
        print(mpid, dft_type, mpr.materials.tasks.search(task_ids=[mpid])[0].last_updated)

The following is the current API call method:

In [2]: from mp_api.client import MPRester
   ...: 
   ...: with MPRester() as mpr:
   ...:     material = mpr.materials.search(material_ids=["mp-126"])[0]
   ...:     task_ids = list(material.calc_types.keys())
   ...:     tasks = mpr.materials.tasks.search(task_ids=task_ids)
   ...: 
   ...:     for task in tasks:
   ...:         calc_type = task.run_type
   ...:         task_type = task.task_type  # 直接使用task_type属性
   ...: 
   ...:         print(f"Task ID: {task.task_id}")
   ...:         print(f"Functional Type: {calc_type}")
   ...:         print(f"Task Type: {task_type}")
   ...:         print(f"Last Updated: {task.last_updated}")
   ...:         print("-" * 50)
   ...: 
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Retrieving TaskDoc documents: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 34/34 [00:00<00:00, 288676.79it/s]
Task ID: mp-1055992
Functional Type: GGA
Task Type: Structure Optimization
Last Updated: 2018-03-20 03:35:16
--------------------------------------------------
Task ID: mp-1055993
Functional Type: GGA
Task Type: Static
Last Updated: 2018-03-20 03:35:53
--------------------------------------------------
Task ID: mp-1056001
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2018-03-20 03:37:36
--------------------------------------------------
Task ID: mp-1056247
Functional Type: GGA
Task Type: Structure Optimization
Last Updated: 2018-03-20 04:23:37
--------------------------------------------------
Task ID: mp-126
Functional Type: GGA
Task Type: Structure Optimization
Last Updated: 2011-05-12 17:09:50
--------------------------------------------------
Task ID: mp-907907
Functional Type: GGA
Task Type: Static
Last Updated: 2014-12-22 15:57:14
--------------------------------------------------
Task ID: mp-922432
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2015-01-27 17:16:41
--------------------------------------------------
Task ID: mp-923216
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2015-01-28 08:25:22
--------------------------------------------------
Task ID: mp-2294633
Functional Type: GGA
Task Type: Static
Last Updated: 2022-06-08 22:26:23.408000
--------------------------------------------------
Task ID: mp-2340601
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2022-06-11 11:52:38.076000
--------------------------------------------------
Task ID: mp-2383760
Functional Type: GGA
Task Type: Structure Optimization
Last Updated: 2023-03-11 00:09:28.715000
--------------------------------------------------
Task ID: mp-2383769
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 08:19:37.028000
--------------------------------------------------
Task ID: mp-2383896
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 07:23:14.019000
--------------------------------------------------
Task ID: mp-2383941
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 07:46:20.077000
--------------------------------------------------
Task ID: mp-2448899
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2022-06-15 10:05:40.847000
--------------------------------------------------
Task ID: mp-2625813
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 08:01:44.102000
--------------------------------------------------
Task ID: mp-2383742
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 09:02:16.022000
--------------------------------------------------
Task ID: mp-2383776
Functional Type: GGA
Task Type: Deformation
Last Updated: 2023-10-07 08:22:20.700000
--------------------------------------------------
Task ID: mp-1055997
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-03-07 11:35:21.245000
--------------------------------------------------
Task ID: mp-1056265
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-03-07 14:33:33.125000
--------------------------------------------------
Task ID: mp-1538277
Functional Type: SCAN
Task Type: Structure Optimization
Last Updated: 2021-05-21 22:33:23.744000
--------------------------------------------------
Task ID: mp-1945969
Functional Type: r2SCAN
Task Type: Structure Optimization
Last Updated: 2021-03-05 15:26:23.081000
--------------------------------------------------
Task ID: mp-2190020
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-07-22 19:13:05.897000
--------------------------------------------------
Task ID: mp-2192388
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-07-23 17:50:24.270000
--------------------------------------------------
Task ID: mp-2290358
Functional Type: HSE06
Task Type: Static
Last Updated: 2022-06-08 22:11:50.428000
--------------------------------------------------
Task ID: mp-2298003
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2022-06-08 01:33:55.432000
--------------------------------------------------
Task ID: mp-1056257
Functional Type: GGA
Task Type: Static
Last Updated: 2018-03-20 04:25:12
--------------------------------------------------
Task ID: mp-1056272
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2018-03-20 04:26:54
--------------------------------------------------
Task ID: mp-1440668
Functional Type: GGA
Task Type: Static
Last Updated: 2020-05-02 13:41:55.114000
--------------------------------------------------
Task ID: mp-1587354
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-02-23 14:48:51.684000
--------------------------------------------------
Task ID: mp-1596926
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2021-02-23 14:25:12.455000
--------------------------------------------------
Task ID: mp-1671102
Functional Type: GGA
Task Type: NSCF Uniform
Last Updated: 2020-07-15 00:56:55.828000
--------------------------------------------------
Task ID: mp-1791299
Functional Type: GGA
Task Type: Static
Last Updated: 2020-11-10 21:02:58.812000
--------------------------------------------------
Task ID: mp-1950487
Functional Type: PBEsol
Task Type: Structure Optimization
Last Updated: 2021-03-04 23:49:32.208000
--------------------------------------------------

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Issue with finding the dependencies among the sub-tasks of a primary calculation using pymatgen API. #3884

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Issue with finding the dependencies among the sub-tasks of a primary calculation using pymatgen API. #3884

hongyi-zhao Jun 17, 2024

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