Airtable field update and add unit testing

.github/scripts/airtableops.py

@@ -141,6 +141,10 @@ def write_information(self, data: BaseInformation, readme_path=None):
         text += "* Output Type: `{0}`\n".format(", ".join(d["Output Type"]))
         text += "* Output Shape: `{0}`\n".format(d["Output Shape"])
         text += "* Interpretation: {0}\n\n".format(d["Interpretation"])
+        text += "## Baseline Performance\n\n"
+        text += "* Computational Performance For One Input: `{0}`\n".format(d["Computational Performance 1"])
+        text += "* Computational Performance For Ten Input: `{0}`\n".format(d["Computational Performance 10"])
+        text += "* Computational Performance For Hundred Input: `{0}`\n".format(d["Computational Performance 100"])
         text += "## References\n\n"
         text += "* [Publication]({0})\n".format(d["Publication"])
         text += "* [Source Code]({0})\n".format(d["Source Code"])
@@ -260,7 +264,6 @@ def insert_metadata_to_airtable(model, contributor, api_key):
         airtable_data["Source Code"] = data["Source Code"]
     ai.table.create(airtable_data)
 
-
 def update_metadata_to_airtable(user, repo, branch, api_key):
     # Works with airtable-update option
     rm = RepoMetadataFile(model_id=repo, config_json=None)

.github/workflows/tests_and_cleanup.yml

@@ -102,7 +102,7 @@ jobs:
 
       - name: Run pytest
         run: |     
-          pip install pytest pytest-benchmark pytest-asyncio rdkit-pypi nox rich fuzzywuzzy scipy
+          pip install pytest pytest-benchmark pytest-asyncio rdkit-pypi nox rich fuzzywuzzy scipy pyairtable
           pytest
 
   run-cli-test-single:

ersilia/hub/content/base_information.py

@@ -13,15 +13,19 @@
 from ...utils.exceptions_utils.base_information_exceptions import (
     BiomedicalAreaBaseInformationError,
     BothIdentifiersBaseInformationError,
+    ComputationalPerformanceHundredBaseInformationError,
+    ComputationalPerformanceOneBaseInformationError,
+    ComputationalPerformanceTenBaseInformationError,
     DescriptionBaseInformationError,
     DockerArchitectureBaseInformationError,
     DockerhubBaseInformationError,
+    EnvironmentSizeMbBaseInformationError,
     GithubBaseInformationError,
     IdentifierBaseInformationError,
+    ImageSizeMbBaseInformationError,
     InputBaseInformationError,
     InputShapeBaseInformationError,
     LicenseBaseInformationError,
-    MemoryGbBaseInformationError,
     ModeBaseInformationError,
     OutputBaseInformationError,
     OutputConsistencyBaseInformationError,
@@ -56,7 +60,90 @@ class BaseInformation(ErsiliaBase):
         Configuration data in JSON format.
     """
 
-    def __init__(self, config_json):
+    def __init__(self, config_json=None):
+        """
+        Initialize the base information object with a provided configuration.
+
+        Parameters
+        ----------
+        config_json : dict
+            A JSON-compatible dictionary containing configuration data.
+
+        Attributes
+        ----------
+        _github : None
+            Placeholder for GitHub URL of the model.
+        _identifier : None
+            Placeholder for a unique identifier string.
+        _slug : None
+            Placeholder for a descriptive slug string.
+        _status : None
+            Placeholder for the current status of the object.
+        _title : None
+            Placeholder for the model’s title.
+        _description : None
+            Placeholder for a description of the model.
+        _mode : None
+            Placeholder for the training mode, one of 'retrained', 'pretrained', 'in-house', or 'online'.
+        _task : None
+            Placeholder for the primary task associated with the model, such as 'classification', or 'regression'.
+        _subtask : None
+            Placeholder for the subtask associated with the model, such as 'activity prediction', or 'featurization'.
+        _input : None
+            Placeholder for input data specifications, such as 'Compound'.
+        _input_shape : None
+            Placeholder for the shape of the input data.
+        _output : None
+            Placeholder for output data specifications, such as 'Probability', or 'Compound'.
+        _output_type : None
+            Placeholder for the type of output data.
+        _output_shape : None
+            Placeholder for the shape of the output data.
+        _output_dimension : None
+            Placeholder for dimensional notes about the output.
+        _output_consistency : None
+            Placeholder for output consistency metrics, one of 'fixed', or 'variable'.
+        _interpretation : None
+            Placeholder for interpretation details of the model's output.
+        _tag : None
+            Placeholder for tags associated with the model.
+        _biomedical_area : None
+            Placeholder for the biomedical area associated with the model, such as 'ADMET'.
+        _target_organism : None
+            Placeholder for the target organism associated with the model.
+        _publication_type : None
+            Placeholder for the type of publication associated with the model, one of Preprint or Peer reviewed.
+        _publication_year : None
+            Placeholder for the year of publication.
+        _publication : None
+            Placeholder for publication references.
+        _source_code : None
+            Placeholder for source code metadata.
+        _license : None
+            Placeholder for license information.
+        _contributor : None
+            Placeholder for contributor information.
+        _dockerhub : None
+            Placeholder for Docker Hub repository details.
+        _docker_architecture : None
+            Placeholder for Docker image architecture details.
+        _s3 : None
+            Placeholder for related AWS S3 information.
+        _source : None
+            Placeholder for the source of the model, one of 'Local', or 'Online'
+        _source_type: None
+            Placeholder for the type of source of the model, one of 'Internal', 'External', or 'Replicated'.
+        _environment_size_mb : None
+            Placeholder for environment size in megabytes.
+        _image_size_mb : None
+            Placeholder for Docker image size in megabytes.
+        _computational_performance_one : None
+            Placeholder for single-run computational performance.
+        _computational_performance_ten : None
+            Placeholder for ten-run computational performance.
+        _computational_performance_hund : None
+            Placeholder for hundred-run computational performance.
+        """
         ErsiliaBase.__init__(self, config_json=config_json, credentials_json=None)
         self._github = None
         self._identifier = None
@@ -66,6 +153,7 @@ def __init__(self, config_json):
         self._description = None
         self._mode = None
         self._task = None
+        self._subtask = None
         self._input = None
         self._input_shape = None
         self._output = None
@@ -75,14 +163,24 @@ def __init__(self, config_json):
         self._output_consistency = None
         self._interpretation = None
         self._tag = None
+        self._biomedical_area = None
+        self._target_organism = None
+        self._publication_type = None
+        self._publication_year = None
         self._publication = None
         self._source_code = None
         self._license = None
         self._contributor = None
         self._dockerhub = None
         self._docker_architecture = None
         self._s3 = None
-        self._memory_gb = None
+        self._source = None
+        self._source_type = None
+        self._environment_size_mb = None
+        self._image_size_mb = None
+        self._computational_performance_one = None
+        self._computational_performance_ten = None
+        self._computational_performance_hund = None
 
     def _is_valid_url(self, url_string: str) -> bool:
         result = validators.url(url_string)
@@ -1141,35 +1239,151 @@ def both_identifiers(self):
         return self._both_identifiers
 
     @property
-    def memory_gb(self):
+    def environment_size(self):
+        """
+        Get the model evironment Size in Mb.
+
+        Returns
+        -------
+        int
+            The model evironment Size in Mb.
+        """
+        return self._environment_size_mb
+
+    @environment_size.setter
+    def environment_size(self, new_environment_size):
+        """
+        Set the environment size in MB.
+
+        Parameters
+        ----------
+        new_environment_size : int
+            The new environment size in MB.
+
+        Raises
+        ------
+        EnvironmentSizeMbBaseInformationError
+            If the environment size value is not valid.
         """
-        Get the model memory in GB.
+        if not isinstance(new_environment_size, (int, float)):
+            raise EnvironmentSizeMbBaseInformationError
+        self._environment_size_mb = new_environment_size
+
+    @property
+    def image_size_mb(self):
+        """Get the image size in megabytes.
 
         Returns
         -------
         int
-            The model memory in GB.
+            The size of the image in MB.
+        """
+        return self._image_size_mb
+
+    @image_size_mb.setter
+    def image_size_mb(self, new_image_size_mb):
+        """Set the image size in megabytes.
+
+        Parameters
+        ----------
+        new_image_size_mb : int
+            The new image size in MB.
+
+        Raises
+        ------
+        ImageSizeMbBaseInformationError
+            If `new_image_size_mb` is not an integer.
+        """
+        if not isinstance(new_image_size_mb, (int, float)):
+            raise ImageSizeMbBaseInformationError
+        self._image_size_mb = new_image_size_mb
+
+    @property
+    def computational_performance_one(self):
+        """Get the computational performance at level one.
+
+        Returns
+        -------
+        int or float
+            The computational performance metric at level one.
+        """
+        return self._computational_performance_one
+
+    @computational_performance_one.setter
+    def computational_performance_one(self, new_value):
+        """Set the computational performance at level one.
+
+        Parameters
+        ----------
+        new_value : int or float
+            The new computational performance value.
+
+        Raises
+        ------
+        ComputationalPerformanceOneBaseInformationError
+            If `new_value` is not an int or float.
+        """
+        if not isinstance(new_value, (int, float)):
+            raise ComputationalPerformanceOneBaseInformationError
+        self._computational_performance_one = new_value
+
+    @property
+    def computational_performance_ten(self):
+        """Get the computational performance at level ten.
+
+        Returns
+        -------
+        int or float
+            The computational performance metric at level ten.
+        """
+        return self._computational_performance_ten
+
+    @computational_performance_ten.setter
+    def computational_performance_ten(self, new_value):
+        """Set the computational performance at level ten.
+
+        Parameters
+        ----------
+        new_value : int or float
+            The new computational performance value.
+
+        Raises
+        ------
+        ComputationalPerformanceTenBaseInformationError
+            If `new_value` is not an int or float.
         """
-        return self._memory_gb
+        if not isinstance(new_value, (int, float)):
+            raise ComputationalPerformanceTenBaseInformationError
+        self._computational_performance_ten = new_value
+
+    @property
+    def computational_performance_hund(self):
+        """Get the computational performance at level hundred.
 
-    @memory_gb.setter
-    def memory_gb(self, new_memory_gb):
+        Returns
+        -------
+        int or float
+            The computational performance metric at level hundred.
         """
-        Set the model memory in GB.
+        return self._computational_performance_hund
+
+    @computational_performance_hund.setter
+    def computational_performance_hund(self, new_value):
+        """Set the computational performance at level hundred.
 
         Parameters
         ----------
-        new_memory_gb : int
-            The new model memory in GB.
+        new_value : int or float
+            The new computational performance value.
 
         Raises
         ------
-        MemoryGbBaseInformationError
-            If the memory value is not valid.
+        ComputationalPerformanceHundredBaseInformationError
+            If `new_value` is not an int or float.
         """
-        if type(new_memory_gb) != int:
-            raise MemoryGbBaseInformationError
-        self._memory_gb = new_memory_gb
+        if not isinstance(new_value, (int, float)):
+            raise ComputationalPerformanceHundredBaseInformationError
+        self._computational_performance_hund = new_value
 
     def as_dict(self):
         """
@@ -1211,7 +1425,11 @@ def as_dict(self):
             "DockerHub": self.dockerhub,
             "Docker Architecture": self.docker_architecture,
             "S3": self.s3,
-            "Memory Gb": self.memory_gb,
+            "Environment Size": self.environment_size,
+            "Image Size": self.image_size_mb,
+            "Computational Performance 1": self.computational_performance_one,
+            "Computational Performance 10": self.computational_performance_ten,
+            "Computational Performance 100": self.computational_performance_hund,
         }
         data = dict((k, v) for k, v in data.items() if v is not None)
         return data
@@ -1258,4 +1476,14 @@ def from_dict(self, data):
         self._assign("dockerhub", "DockerHub", data)
         self._assign("docker_architecture", "Docker Architecture", data)
         self._assign("s3", "S3", data)
-        self._assign("memory_gb", "Memory Gb", data)
+        self._assign("environment_size", "Environment Size", data)
+        self._assign("image_size_mb", "Image Size", data)
+        self._assign(
+            "computational_performance_one", "Computational Performance 1", data
+        )
+        self._assign(
+            "computational_performance_ten", "Computational Performance 10", data
+        )
+        self._assign(
+            "computational_performance_hund", "Computational Performance 100", data
+        )