adding commentmixin to remaining entities (#416)

* adding commentmixin to remaining entities
* additional tests
* type hints
* additional entities
* additional tests
* additional tests
* projects cleanup

rubicon_ml/client/artifact.py

@@ -9,15 +9,15 @@
 import fsspec
 
 from rubicon_ml.client.base import Base
-from rubicon_ml.client.mixin import TagMixin
+from rubicon_ml.client.mixin import CommentMixin, TagMixin
 from rubicon_ml.client.utils.exception_handling import failsafe
 
 if TYPE_CHECKING:
     from rubicon_ml.client import Project
     from rubicon_ml.domain import Artifact as ArtifactDomain
 
 
-class Artifact(Base, TagMixin):
+class Artifact(Base, TagMixin, CommentMixin):
     """A client artifact.
 
     An `artifact` is a catch-all for any other type of

rubicon_ml/client/dataframe.py

@@ -2,7 +2,7 @@
 
 from typing import TYPE_CHECKING, Callable, Literal, Optional, Union
 
-from rubicon_ml.client import Base, TagMixin
+from rubicon_ml.client import Base, CommentMixin, TagMixin
 from rubicon_ml.client.utils.exception_handling import failsafe
 from rubicon_ml.exceptions import RubiconException
 
@@ -11,7 +11,7 @@
     from rubicon_ml.domain import Dataframe as DataframeDomain
 
 
-class Dataframe(Base, TagMixin):
+class Dataframe(Base, TagMixin, CommentMixin):
     """A client dataframe.
 
     A `dataframe` is a two-dimensional, tabular dataset with

rubicon_ml/client/experiment.py

@@ -56,7 +56,15 @@ def _get_identifiers(self):
         return self.project.name, self.id
 
     @failsafe
-    def log_metric(self, name, value, directionality="score", description=None, tags=[]):
+    def log_metric(
+        self,
+        name: str,
+        value: float,
+        directionality: str = "score",
+        description: str = None,
+        tags: list[str] = [],
+        comments: list[str] = [],
+    ) -> Metric:
         """Create a metric under the experiment.
 
         Parameters
@@ -76,6 +84,9 @@ def log_metric(self, name, value, directionality="score", description=None, tags
         tags : list of str, optional
             Values to tag the experiment with. Use tags to organize and
             filter your metrics.
+        comments : list of str, optional
+            Values to comment the experiment with. Use comments to organize and
+            filter your metrics.
 
         Returns
         -------
@@ -85,8 +96,18 @@ def log_metric(self, name, value, directionality="score", description=None, tags
         if not isinstance(tags, list) or not all([isinstance(tag, str) for tag in tags]):
             raise ValueError("`tags` must be `list` of type `str`")
 
+        if not isinstance(comments, list) or not all(
+            [isinstance(comment, str) for comment in comments]
+        ):
+            raise ValueError("`comments` must be `list` of type `str`")
+
         metric = domain.Metric(
-            name, value, directionality=directionality, description=description, tags=tags
+            name,
+            value,
+            directionality=directionality,
+            description=description,
+            tags=tags,
+            comments=comments,
         )
         for repo in self.repositories:
             repo.create_metric(metric, self.project.name, self.id)
@@ -161,7 +182,14 @@ def metric(self, name=None, id=None):
             return [m for m in self.metrics() if m.id == id][0]
 
     @failsafe
-    def log_feature(self, name, description=None, importance=None, tags=[]):
+    def log_feature(
+        self,
+        name: str,
+        description: str = None,
+        importance: float = None,
+        tags: list[str] = [],
+        comments: list[str] = [],
+    ) -> Feature:
         """Create a feature under the experiment.
 
         Parameters
@@ -176,6 +204,9 @@ def log_feature(self, name, description=None, importance=None, tags=[]):
         tags : list of str, optional
             Values to tag the experiment with. Use tags to organize and
             filter your features.
+        comments : list of str, optional
+            Values to comment the experiment with. Use comments to organize and
+            filter your features.
 
         Returns
         -------
@@ -185,7 +216,14 @@ def log_feature(self, name, description=None, importance=None, tags=[]):
         if not isinstance(tags, list) or not all([isinstance(tag, str) for tag in tags]):
             raise ValueError("`tags` must be `list` of type `str`")
 
-        feature = domain.Feature(name, description=description, importance=importance, tags=tags)
+        if not isinstance(comments, list) or not all(
+            [isinstance(comment, str) for comment in comments]
+        ):
+            raise ValueError("`comments` must be `list` of type `str`")
+
+        feature = domain.Feature(
+            name, description=description, importance=importance, tags=tags, comments=comments
+        )
 
         for repo in self.repositories:
             repo.create_feature(feature, self.project.name, self.id)
@@ -260,7 +298,14 @@ def feature(self, name=None, id=None):
             return [f for f in self.features() if f.id == id][0]
 
     @failsafe
-    def log_parameter(self, name, value=None, description=None, tags=[]):
+    def log_parameter(
+        self,
+        name: str,
+        value: object = None,
+        description: str = None,
+        tags: list[str] = [],
+        comments: list[str] = [],
+    ) -> Parameter:
         """Create a parameter under the experiment.
 
         Parameters
@@ -277,6 +322,9 @@ def log_parameter(self, name, value=None, description=None, tags=[]):
         tags : list of str, optional
             Values to tag the parameter with. Use tags to organize and
             filter your parameters.
+        comments : list of str, optional
+            Values to comment the experiment with. Use comments to organize and
+            filter your features.
 
         Returns
         -------
@@ -286,7 +334,14 @@ def log_parameter(self, name, value=None, description=None, tags=[]):
         if not isinstance(tags, list) or not all([isinstance(tag, str) for tag in tags]):
             raise ValueError("`tags` must be `list` of type `str`")
 
-        parameter = domain.Parameter(name, value=value, description=description, tags=tags)
+        if not isinstance(comments, list) or not all(
+            [isinstance(comment, str) for comment in comments]
+        ):
+            raise ValueError("`comments` must be `list` of type `str`")
+
+        parameter = domain.Parameter(
+            name, value=value, description=description, tags=tags, comments=comments
+        )
 
         for repo in self.repositories:
             repo.create_parameter(parameter, self.project.name, self.id)

rubicon_ml/client/feature.py

@@ -3,14 +3,14 @@
 from datetime import datetime
 from typing import TYPE_CHECKING, Optional
 
-from rubicon_ml.client import Base, TagMixin
+from rubicon_ml.client import Base, CommentMixin, TagMixin
 
 if TYPE_CHECKING:
     from rubicon_ml.client import Experiment
     from rubicon_ml.domain import Feature as FeatureDomain
 
 
-class Feature(Base, TagMixin):
+class Feature(Base, TagMixin, CommentMixin):
     """A client feature.
 
     A `feature` is an input to an `experiment` (model run)

rubicon_ml/client/metric.py

@@ -3,14 +3,14 @@
 from datetime import datetime
 from typing import TYPE_CHECKING, Optional
 
-from rubicon_ml.client import Base, TagMixin
+from rubicon_ml.client import Base, CommentMixin, TagMixin
 
 if TYPE_CHECKING:
     from rubicon_ml.client import Experiment
     from rubicon_ml.domain import Metric as MetricDomain
 
 
-class Metric(Base, TagMixin):
+class Metric(Base, TagMixin, CommentMixin):
     """A client metric.
 
     A `metric` is a single-value output of an `experiment` that

rubicon_ml/client/mixin.py

@@ -69,6 +69,7 @@ def log_artifact(
         name: Optional[str] = None,
         description: Optional[str] = None,
         tags: Optional[List[str]] = None,
+        comments: Optional[List[str]] = None,
     ) -> Artifact:
         """Log an artifact to this client object.
 
@@ -93,6 +94,9 @@ def log_artifact(
         tags : list of str, optional
             Values to tag the experiment with. Use tags to organize and
             filter your artifacts.
+        comments : list of str, optional
+            Values to comment the experiment with. Use comments to organize and
+            filter your artifacts.
 
         Notes
         -----
@@ -128,13 +132,21 @@ def log_artifact(
         if not isinstance(tags, list) or not all([isinstance(tag, str) for tag in tags]):
             raise ValueError("`tags` must be `list` of type `str`")
 
+        if comments is None:
+            comments = []
+        if not isinstance(comments, list) or not all(
+            [isinstance(comment, str) for comment in comments]
+        ):
+            raise ValueError("`comments` must be `list` of type `str`")
+
         data_bytes, name = self._validate_data(data_bytes, data_file, data_object, data_path, name)
 
         artifact = domain.Artifact(
             name=name,
             description=description,
             parent_id=self._domain.id,
             tags=tags,
+            comments=comments,
         )
 
         project_name, experiment_id = self._get_identifiers()
@@ -413,6 +425,7 @@ def log_dataframe(
         description: Optional[str] = None,
         name: Optional[str] = None,
         tags: Optional[List[str]] = None,
+        comments: Optional[List[str]] = None,
     ) -> Dataframe:
         """Log a dataframe to this client object.
 
@@ -425,6 +438,8 @@ def log_dataframe(
             additional context.
         tags : list of str
             The values to tag the dataframe with.
+        comments: list of str
+            The values to comment the dataframe with.
 
         Returns
         -------
@@ -436,11 +451,19 @@ def log_dataframe(
         if not isinstance(tags, list) or not all([isinstance(tag, str) for tag in tags]):
             raise ValueError("`tags` must be `list` of type `str`")
 
+        if comments is None:
+            comments = []
+        if not isinstance(comments, list) or not all(
+            [isinstance(comment, str) for comment in comments]
+        ):
+            raise ValueError("`comments` must be `list` of type `str`")
+
         dataframe = domain.Dataframe(
             parent_id=self._domain.id,
             description=description,
             name=name,
             tags=tags,
+            comments=comments,
         )
 
         project_name, experiment_id = self._get_identifiers()

rubicon_ml/client/parameter.py

@@ -3,14 +3,14 @@
 from datetime import datetime
 from typing import TYPE_CHECKING, Optional, Union
 
-from rubicon_ml.client import Base, TagMixin
+from rubicon_ml.client import Base, CommentMixin, TagMixin
 
 if TYPE_CHECKING:
     from rubicon_ml.client import Experiment
     from rubicon_ml.domain import Parameter as ParameterDomain
 
 
-class Parameter(Base, TagMixin):
+class Parameter(Base, TagMixin, CommentMixin):
     """A client parameter.
 
     A `parameter` is an input to an `experiment` (model run)

rubicon_ml/domain/artifact.py

@@ -4,17 +4,18 @@
 from datetime import datetime
 from typing import List, Optional
 
-from rubicon_ml.domain.mixin import TagMixin
+from rubicon_ml.domain.mixin import CommentMixin, TagMixin
 from rubicon_ml.domain.utils import uuid
 
 
 @dataclass
-class Artifact(TagMixin):
+class Artifact(TagMixin, CommentMixin):
     name: str
 
     id: str = field(default_factory=uuid.uuid4)
     description: Optional[str] = None
     created_at: datetime = field(default_factory=datetime.utcnow)
     tags: List[str] = field(default_factory=list)
+    comments: List[str] = field(default_factory=list)
 
     parent_id: Optional[str] = None

rubicon_ml/domain/dataframe.py

@@ -4,16 +4,17 @@
 from datetime import datetime
 from typing import List, Optional
 
-from rubicon_ml.domain.mixin import TagMixin
+from rubicon_ml.domain.mixin import CommentMixin, TagMixin
 from rubicon_ml.domain.utils import uuid
 
 
 @dataclass
-class Dataframe(TagMixin):
+class Dataframe(TagMixin, CommentMixin):
     id: str = field(default_factory=uuid.uuid4)
     name: Optional[str] = None
     description: Optional[str] = None
     tags: List[str] = field(default_factory=list)
+    comments: List[str] = field(default_factory=list)
     created_at: datetime = field(default_factory=datetime.utcnow)
 
     parent_id: Optional[str] = None

rubicon_ml/domain/feature.py

@@ -2,16 +2,17 @@
 from datetime import datetime
 from typing import List, Optional
 
-from rubicon_ml.domain.mixin import TagMixin
+from rubicon_ml.domain.mixin import CommentMixin, TagMixin
 from rubicon_ml.domain.utils import uuid
 
 
 @dataclass
-class Feature(TagMixin):
+class Feature(TagMixin, CommentMixin):
     name: str
 
     id: str = field(default_factory=uuid.uuid4)
     description: Optional[str] = None
     importance: Optional[float] = None
     tags: List[str] = field(default_factory=list)
+    comments: List[str] = field(default_factory=list)
     created_at: datetime = field(default_factory=datetime.utcnow)

rubicon_ml/domain/metric.py

@@ -2,14 +2,14 @@
 from datetime import datetime
 from typing import List, Optional
 
-from rubicon_ml.domain.mixin import TagMixin
+from rubicon_ml.domain.mixin import CommentMixin, TagMixin
 from rubicon_ml.domain.utils import uuid
 
 DIRECTIONALITY_VALUES = ["score", "loss"]
 
 
 @dataclass
-class Metric(TagMixin):
+class Metric(TagMixin, CommentMixin):
     name: str
     value: float
 
@@ -18,6 +18,7 @@ class Metric(TagMixin):
     directionality: str = "score"
     created_at: datetime = field(default_factory=datetime.utcnow)
     tags: List[str] = field(default_factory=list)
+    comments: List[str] = field(default_factory=list)
 
     def __post_init__(self):
         if self.directionality not in DIRECTIONALITY_VALUES: