added first iteration of easy_publish

.readthedocs.yml

@@ -4,7 +4,7 @@ formats:
   - pdf
 
 python:
-  version: 3.6
+  version: 3.8
   install:
      - method: pip
        path: .

dlhub_sdk/client.py

@@ -2,7 +2,7 @@
 import json
 import os
 from tempfile import mkstemp
-from typing import Union, Any, Optional, Tuple, Dict
+from typing import Sequence, Union, Any, Optional, Tuple, Dict, List
 import requests
 import globus_sdk
 
@@ -14,6 +14,13 @@
 from funcx.sdk.client import FuncXClient
 from globus_sdk.scopes import AuthScopes, SearchScopes
 
+from dlhub_sdk.models.servables.keras import KerasModel
+from dlhub_sdk.models.servables.pytorch import TorchModel
+from dlhub_sdk.models.servables.python import PythonClassMethodModel
+from dlhub_sdk.models.servables.python import PythonStaticMethodModel
+from dlhub_sdk.models.servables.tensorflow import TensorFlowModel
+from dlhub_sdk.models.servables.sklearn import ScikitLearnModel
+
 from dlhub_sdk.config import DLHUB_SERVICE_ADDRESS, CLIENT_ID
 from dlhub_sdk.utils.futures import DLHubFuture
 from dlhub_sdk.utils.schemas import validate_against_dlhub_schema
@@ -26,6 +33,10 @@
 logger = logging.getLogger(__name__)
 
 
+class HelpMessage(Exception):
+    """Raised from another error to provide the user an additional message"""
+
+
 class DLHubClient(BaseClient):
     """Main class for interacting with the DLHub service
 
@@ -343,6 +354,70 @@ def get_result(self, task_id, verbose=False):
             result = result[0]
         return result
 
+    def easy_publish(self, title: str, creators: Union[str, List[str]], short_name: str, servable_type: str, serv_options: Dict[str, Any],
+                     affiliations: List[Sequence[str]] = None, paper_doi: str = None):
+        """Simplified publishing method for servables
+
+        Args:
+            title (string): title for the servable
+            creators (string | list): either the creator's name (FamilyName, GivenName) or a list of the creators' names
+            short_name (string): shorthand name for the servable
+            servable_type (string): the type of the servable, must be a member of ("static_method",
+                                                                                   "class_method",
+                                                                                   "keras",
+                                                                                   "pytorch",
+                                                                                   "tensorflow",
+                                                                                   "sklearn") more information on servable types can be found here:
+                                                                                   https://dlhub-sdk.readthedocs.io/en/latest/servable-types.html
+            serv_options (dict): the servable_type specific arguments that are necessary for publishing
+            affiliations (list): list of affiliations for each author
+            paper_doi (str): DOI of a paper that describes the servable
+        Returns:
+            (string): task id of this submission, can be used to check for success
+        Raises:
+            ValueError: If the given servable_type is not in the list of acceptable types
+            Exception: If the serv_options are incomplete or the request to publish results in an error
+        """
+        # conversion table for model string names to classes
+        models = {"static_method": PythonStaticMethodModel,
+                  "class_method": PythonClassMethodModel,
+                  "keras": KerasModel,
+                  "pytorch": TorchModel,
+                  "tensorflow": TensorFlowModel,
+                  "sklearn": ScikitLearnModel}
+
+        # raise an error if the provided servable_type is invalid
+        model = models.get(servable_type)
+        if model is None:
+            raise ValueError(f"dl.easy_publish given invalid servable type: {servable_type}, please refer to the docstring")
+
+        # attempt to construct the model and raise a helpful error if needed
+        try:
+            # if the servable is a python function, set the parameter to attempt to auto-generate the inputs/outputs
+            if servable_type in {"static_method", "class_method"}:
+                serv_options["auto_inspect"] = True
+
+            model_info = model.create_model(**serv_options)
+        except Exception as e:
+            help_err = HelpMessage(f"Help can be found here:\nhttps://dlhub-sdk.readthedocs.io/en/latest/source/dlhub_sdk.models.servables.html#"
+                                   f"{model.__module__}.{model.__name__}.create_model")
+            raise help_err from e
+
+        # set the required datacite fields
+        model_info.set_title(title)
+        creators = [creators] if isinstance(creators, str) else creators  # handle the case where creators is a string
+        model_info.set_creators(creators, affiliations or [])  # affiliations if provided, else empty list
+        model_info.set_name(short_name)
+
+        if paper_doi is not None:
+            model_info.add_related_resource(paper_doi, "DOI", "IsDescribedBy")
+
+        # perform the publish
+        task_id = self.publish_servable(model_info)
+
+        # return the id of the publish task
+        return task_id
+
     def publish_servable(self, model):
         """Submit a servable to DLHub
 

dlhub_sdk/models/datacite.py

@@ -182,8 +182,9 @@ class DataciteRelationType(Enum):
 class DataciteRelatedIdentifier(BaseModel):
     """Identifier of a related resource. Use this property to indicate subsets of properties, as appropriate."""
     relatedIdentifier: str
-    relatedIdentifierType: DataciteRelatedIdentifierType
-    relatedMetadataScheme: str
+    relatedIdentifierType: Union[str, DataciteRelatedIdentifierType]
+    relationType: Union[str, DataciteRelationType]
+    relatedMetadataScheme: Optional[str]
     schemeURI: Optional[AnyUrl] = None
 
 

dlhub_sdk/models/servables/python.py

@@ -1,8 +1,11 @@
 """Tools to annotate generic operations (e.g., class method calls) in Python"""
 import pickle as pkl
+import importlib
+from inspect import Signature
 
 from dlhub_sdk.models.servables import BaseServableModel, ArgumentTypeMetadata
 from dlhub_sdk.utils.types import compose_argument_block
+from dlhub_sdk.utils.inspect import signature_to_input, signature_to_output
 
 
 class BasePythonServableModel(BaseServableModel):
@@ -113,14 +116,15 @@ class PythonClassMethodModel(BasePythonServableModel):
     any arguments of the class that should be set as defaults."""
 
     @classmethod
-    def create_model(cls, path, method, function_kwargs=None) -> 'PythonClassMethodModel':
+    def create_model(cls, path, method, function_kwargs=None, *, auto_inspect=False) -> 'PythonClassMethodModel':
         """Initialize a model for a python object
 
         Args:
             path (string): Path to a pickled Python file
             method (string): Name of the method for this class
             function_kwargs (dict): Names and values of any other argument of the function to set
                 the values must be JSON serializable.
+            auto_inspect (boolean): Whether or not to attempt to automatically extract inputs from the function
         """
         output = super(PythonClassMethodModel, cls).create_model(method, function_kwargs)
 
@@ -135,6 +139,11 @@ def create_model(cls, path, method, function_kwargs=None) -> 'PythonClassMethodM
             'class_name': class_name
         })
 
+        if auto_inspect:
+            func = getattr(obj, method)
+
+            output = add_extracted_metadata(func, output)
+
         return output
 
     def _get_handler(self):
@@ -153,8 +162,8 @@ class PythonStaticMethodModel(BasePythonServableModel):
     """
 
     @classmethod
-    def create_model(cls, module, method, autobatch=False, function_kwargs=None):
-        """Initialize the method
+    def create_model(cls, module=None, method=None, autobatch=False, function_kwargs=None, *, f=None, auto_inspect=False):
+        """Initialize the method based on the provided arguments
 
         Args:
             module (string): Name of the module holding the function
@@ -163,28 +172,61 @@ def create_model(cls, module, method, autobatch=False, function_kwargs=None):
                 Calls :code:`map(f, list)`
             function_kwargs (dict): Names and values of any other argument of the function to set
                 the values must be JSON serializable.
+            f (object): function pointer to the desired python function
+            auto_inspect (boolean): Whether or not to attempt to automatically extract inputs from the function
+        Raises:
+            TypeError: If there is no valid way to process the given arguments
         """
+        # if a pointer is provided, get the module and method
+        if f is not None:
+            module, method = f.__module__, f.__name__
+            func = f
+        # if it is not, ensure both the module and method are provided and get the function pointer
+        elif module is not None and method is not None:
+            module_obj = importlib.import_module(module)
+            func = getattr(module_obj, method)
+        else:
+            raise TypeError("PythonStaticMethodModel.create_model was not provided valid arguments. Please provide either a funtion pointer"
+                            " or the module and name of the desired static function")
+
         output = super(PythonStaticMethodModel, cls).create_model(method, function_kwargs)
 
         output.servable.methods["run"].method_details.update({
             'module': module,
             'autobatch': autobatch
         })
+
+        if auto_inspect:
+            output = add_extracted_metadata(func, output)
+
         return output
 
     @classmethod
     def from_function_pointer(cls, f, autobatch=False, function_kwargs=None):
         """Construct the module given a function pointer
-
         Args:
-            f (object): A function pointer
+            f (object): Function pointer to the Python function to be published
             autobatch (bool): Whether to run function on an iterable of entries
             function_kwargs (dict): Any default options for this function
         """
-        return cls.create_model(f.__module__, f.__name__, autobatch, function_kwargs)
+        return cls.create_model(f=f, autobatch=autobatch, function_kwargs=function_kwargs)
 
     def _get_handler(self):
         return 'python.PythonStaticMethodServable'
 
     def _get_type(self):
         return 'Python static method'
+
+
+def add_extracted_metadata(func, model: BasePythonServableModel) -> BasePythonServableModel:
+    """Helper function for adding generated input/output metadata to a model object
+    Args:
+        func: a pointer to the function whose data is to be extracted
+        model (BasePythonServableModel): the model who needs its data to be updated
+    Returns:
+        (BasePythonServableModel): the model that was given after it is updated
+    """
+    sig = Signature.from_callable(func)
+    model = model.set_inputs(**signature_to_input(sig))
+    model = model.set_outputs(**signature_to_output(sig))
+    return model

dlhub_sdk/tests/test_dlhub_client.py

@@ -1,9 +1,12 @@
 import os
+import pickle as pkl
+from typing import Dict
 
 import mdf_toolbox
 from pytest import fixture, raises, mark
+from pytest_mock import mocker  # noqa: F401 (flake8 cannot detect usage)
 
-from dlhub_sdk.models.servables.python import PythonStaticMethodModel
+from dlhub_sdk.models.servables.python import PythonClassMethodModel, PythonStaticMethodModel
 from dlhub_sdk.utils.futures import DLHubFuture
 from dlhub_sdk.client import DLHubClient
 
@@ -13,6 +16,16 @@
 client_secret = os.getenv('CLIENT_SECRET')
 fx_scope = "https://auth.globus.org/scopes/facd7ccc-c5f4-42aa-916b-a0e270e2c2a9/all"
 is_gha = os.getenv('GITHUB_ACTIONS')
+_pickle_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "pickle.pkl"))
+
+
+# make dummy reply for mocker patch to return
+class DummyReply:
+    def __init__(self) -> None:
+        self.status_code = 200
+
+    def json(self) -> Dict[str, str]:
+        return {"task_id": "bf06d72e-0478-11ed-97f9-4b1381555b22"}  # valid task id, status is known to be FAILED
 
 
 @fixture()
@@ -53,7 +66,7 @@ def test_get_servables(dl):
 
 def test_run(dl):
     user = "aristana_uchicago"
-    name = "noop_v10"
+    name = "noop_v11"  # published 2/22/2022
     data = True  # accepts anything as input, but listed as Boolean in DLHub
 
     # Test a synchronous request
@@ -73,9 +86,7 @@ def test_run(dl):
     assert res.result(timeout=60) == 'Hello world!'
 
 
-@mark.skipif(not is_gha, reason='Avoid running this test except on larger-scale tests of the system')
-@mark.skip
-def test_submit(dl):
+def test_submit(dl, mocker):  # noqa: F811 (flake8 does not understand usage)
     # Make an example function
     model = PythonStaticMethodModel.create_model('numpy.linalg', 'norm')
     model.dlhub.test = True
@@ -84,8 +95,35 @@ def test_submit(dl):
     model.set_inputs('ndarray', 'Array to be normed', shape=[None])
     model.set_outputs('number', 'Norm of the array')
 
+    # patch requests.post
+    mocker.patch("requests.post", return_value=DummyReply())
+
     # Submit the model
-    dl.publish_servable(model)
+    task_id = dl.publish_servable(model)
+    assert task_id == "bf06d72e-0478-11ed-97f9-4b1381555b22"
+
+    # pickle class method to test
+    with open(_pickle_path, 'wb') as fp:
+        pkl.dump(DummyReply(), fp)
+
+    # test auto_inspect for class methods
+    model = PythonClassMethodModel.create_model(_pickle_path, "json", auto_inspect=True)
+    model.dlhub.test = True
+    model.set_name("dummy_json")
+    model.set_title("Dummy JSON")
+
+    # Submit the model
+    task_id = dl.publish_servable(model)
+    assert task_id == "bf06d72e-0478-11ed-97f9-4b1381555b22"
+
+    # make sure invalid call raises proper error
+    with raises(TypeError):
+        model = PythonStaticMethodModel.create_model("dlhub_sdk.utils.validation")
+
+    # Submit the model using easy publish
+    task_id = dl.easy_publish("Validate dl.run Calls", "Darling, Isaac", "validate_run", "static_method",
+                              {"module": "dlhub_sdk.utils.validation", "method": "validate"}, [["University of Chicago"]], "not-a-real-doi")
+    assert task_id == "bf06d72e-0478-11ed-97f9-4b1381555b22"
 
 
 def test_describe_model(dl):
@@ -220,6 +258,6 @@ def test_namespace(dl):
 
 
 def test_status(dl):
-    future = dl.run('aristana_uchicago/noop_v10', True, asynchronous=True)
+    future = dl.run('aristana_uchicago/noop_v11', True, asynchronous=True)
     # Need spec for Fx status returns
     assert isinstance(dl.get_task_status(future.task_id), dict)