Adding object summary

openml/datasets/dataset.py

@@ -173,6 +173,36 @@ def __init__(self, name, description, format=None,
         else:
             self.data_pickle_file = None
 
+    def __str__(self):
+        header = "OpenML Dataset"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Name": self.name,
+                  "Version": self.version,
+                  "Format": self.format,
+                  "Licence": self.licence,
+                  "Download URL": self.url,
+                  "Data file": self.data_file,
+                  "Pickle file": self.data_pickle_file,
+                  "# of features": len(self.features)}
+        if self.upload_date is not None:
+            fields["Upload Date"] = self.upload_date.replace('T', ' ')
+        if self.dataset_id is not None:
+            fields["OpenML URL"] = "{}d/{}".format(base_url, self.dataset_id)
+        if self.qualities['NumberOfInstances'] is not None:
+            fields["# of instances"] = int(self.qualities['NumberOfInstances'])
+
+        # determines the order in which the information will be printed
+        order = ["Name", "Version", "Format", "Upload Date", "Licence", "Download URL",
+                 "OpenML URL", "Data File", "Pickle File", "# of features", "# of instances"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body
+
     def _data_arff_to_pickle(self, data_file):
         data_pickle_file = data_file.replace('.arff', '.pkl.py3')
         if os.path.exists(data_pickle_file):

openml/evaluations/evaluation.py

@@ -1,3 +1,5 @@
+import openml.config
+
 
 class OpenMLEvaluation(object):
     """
@@ -47,3 +49,32 @@ def __init__(self, run_id, task_id, setup_id, flow_id, flow_name,
         self.value = value
         self.values = values
         self.array_data = array_data
+
+    def __str__(self):
+        header = "OpenML Evaluation"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Upload Date": self.upload_time,
+                  "Run ID": self.run_id,
+                  "OpenML Run URL": "{}r/{}".format(base_url, self.run_id),
+                  "Task ID": self.task_id,
+                  "OpenML Task URL": "{}t/{}".format(base_url, self.task_id),
+                  "Flow ID": self.flow_id,
+                  "OpenML Flow URL": "{}f/{}".format(base_url, self.flow_id),
+                  "Setup ID": self.setup_id,
+                  "Data ID": self.data_id,
+                  "Data Name": self.data_name,
+                  "OpenML Data URL": "{}d/{}".format(base_url, self.data_id),
+                  "Metric Used": self.function,
+                  "Result": self.value}
+
+        order = ["Uploader Date", "Run ID", "OpenML Run URL", "Task ID", "OpenML Task URL"
+                 "Flow ID", "OpenML Flow URL", "Setup ID", "Data ID", "Data Name",
+                 "OpenML Data URL", "Metric Used", "Result"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body

openml/flows/flow.py

@@ -7,6 +7,8 @@
 from ..extensions import get_extension_by_flow
 from ..utils import extract_xml_tags, _tag_entity
 
+import openml.config
+
 
 class OpenMLFlow(object):
     """OpenML Flow. Stores machine learning models.
@@ -132,6 +134,35 @@ def __init__(self, name, description, model, components, parameters,
 
         self.extension = get_extension_by_flow(self)
 
+    def __str__(self):
+        header = "OpenML Flow"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Flow Name": self.name,
+                  "Flow Description": self.description,
+                  "Dependencies": self.dependencies}
+        if self.flow_id is not None:
+            if self.version is not None:
+                fields["Flow ID"] = "{} (version {})".format(self.flow_id, self.version)
+            else:
+                fields["Flow ID"] = self.flow_id
+            fields["Flow URL"] = "{}f/{}".format(base_url, self.flow_id)
+        if self.upload_date is not None:
+            fields["Upload Date"] = self.upload_date.replace('T', ' ')
+        if self.binary_url is not None:
+            fields["Binary URL"] = self.binary_url
+
+        # determines the order in which the information will be printed
+        order = ["Flow ID", "Flow URL", "Flow Name", "Flow Description", "Binary URL",
+                 "Upload Date", "Dependencies"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body
+
     def _to_xml(self) -> str:
         """Generate xml representation of self for upload to server.
 

openml/runs/run.py

@@ -64,12 +64,40 @@ def __init__(self, task_id, flow_id, dataset_id, setup_string=None,
         self.predictions_url = predictions_url
 
     def __str__(self):
-        flow_name = self.flow_name
-        if flow_name is not None and len(flow_name) > 26:
-            # long enough to show sklearn.pipeline.Pipeline
-            flow_name = flow_name[:26] + "..."
-        return "[run id: {}, task id: {}, flow id: {}, flow name: {}]".format(
-            self.run_id, self.task_id, self.flow_id, flow_name)
+        header = "OpenML Run"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Uploader Name": self.uploader_name,
+                  "Metric": self.task_evaluation_measure,
+                  "Run ID": self.run_id,
+                  "Task ID": self.task_id,
+                  "Task Type": self.task_type,
+                  "Task URL": "{}t/{}".format(base_url, self.task_id),
+                  "Flow ID": self.flow_id,
+                  "Flow Name": self.flow_name,
+                  "Flow URL": "{}f/{}".format(base_url, self.flow_id),
+                  "Setup ID": self.setup_id,
+                  "Setup String": self.setup_string,
+                  "Dataset ID": self.dataset_id,
+                  "Dataset URL": "{}d/{}".format(base_url, self.dataset_id)}
+        if self.uploader is not None:
+            fields["Uploader Profile"] = "{}u/{}".format(base_url, self.uploader)
+        if self.run_id is not None:
+            fields["Run URL"] = "{}r/{}".format(base_url, self.run_id)
+        if self.task_evaluation_measure in self.evaluations:
+            fields["Result"] = self.evaluations[self.task_evaluation_measure]
+
+        # determines the order in which the information will be printed
+        order = ["Uploader Name", "Uploader Profile", "Metric", "Result", "Run ID", "Run URL",
+                 "Task ID", "Task Type", "Task URL", "Flow ID", "Flow Name", "Flow URL",
+                 "Setup ID", "Setup String", "Dataset ID", "Dataset URL"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body
 
     def _repr_pretty_(self, pp, cycle):
         pp.text(str(self))

openml/setups/setup.py

@@ -1,3 +1,5 @@
+import openml.config
+
 
 class OpenMLSetup(object):
     """Setup object (a.k.a. Configuration).
@@ -25,6 +27,25 @@ def __init__(self, setup_id, flow_id, parameters):
         self.flow_id = flow_id
         self.parameters = parameters
 
+    def __str__(self):
+        header = "OpenML Setup"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Setup ID": self.setup_id,
+                  "Flow ID": self.flow_id,
+                  "Flow URL": "{}f/{}".format(base_url, self.flow_id),
+                  "# of Parameters": len(self.parameters)}
+
+        # determines the order in which the information will be printed
+        order = ["Setup ID", "Flow ID", "Flow URL", "# of Parameters"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body
+
 
 class OpenMLParameter(object):
     """Parameter object (used in setup).
@@ -60,3 +81,34 @@ def __init__(self, input_id, flow_id, flow_name, full_name, parameter_name,
         self.data_type = data_type
         self.default_value = default_value
         self.value = value
+
+    def __str__(self):
+        header = "OpenML Parameter"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"ID": self.id,
+                  "Flow ID": self.flow_id,
+                  # "Flow Name": self.flow_name,
+                  "Flow Name": self.full_name,
+                  "Flow URL": "{}f/{}".format(base_url, self.flow_id),
+                  "Parameter Name": self.parameter_name}
+        # indented prints for parameter attributes
+        # indention = 2 spaces + 1 | + 2 underscores
+        indent = "{}|{}".format(" " * 2, "_" * 2)
+        parameter_data_type = "{}Data Type".format(indent)
+        fields[parameter_data_type] = self.data_type
+        parameter_default = "{}Default".format(indent)
+        fields[parameter_default] = self.default_value
+        parameter_value = "{}Value".format(indent)
+        fields[parameter_value] = self.value
+
+        # determines the order in which the information will be printed
+        order = ["ID", "Flow ID", "Flow Name", "Flow URL", "Parameter Name",
+                 parameter_data_type, parameter_default, parameter_value]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body

openml/study/study.py

@@ -89,6 +89,39 @@ def __init__(
         self.runs = runs
         pass
 
+    def __str__(self):
+        # header is provided by the sub classes
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Name": self.name,
+                  "Status": self.status,
+                  "Main Entity Type": self.main_entity_type}
+        if self.id is not None:
+            fields["ID"] = self.id
+            fields["Study URL"] = "{}s/{}".format(base_url, self.id)
+        if self.creator is not None:
+            fields["Creator"] = "{}u/{}".format(base_url, self.creator)
+        if self.creation_date is not None:
+            fields["Upload Time"] = self.creation_date.replace('T', ' ')
+        if self.data is not None:
+            fields["# of Data"] = len(self.data)
+        if self.tasks is not None:
+            fields["# of Tasks"] = len(self.tasks)
+        if self.flows is not None:
+            fields["# of Flows"] = len(self.flows)
+        if self.runs is not None:
+            fields["# of Runs"] = len(self.runs)
+
+        # determines the order in which the information will be printed
+        order = ["ID", "Name", "Status", "Main Entity Type", "Study URL",
+                 "# of Data", "# of Tasks", "# of Flows", "# of Runs",
+                 "Creator", "Upload Time"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return body
+
     def publish(self) -> int:
         """
         Publish the study on the OpenML server.
@@ -233,6 +266,12 @@ def __init__(
             setups=setups,
         )
 
+    def __str__(self):
+        header = "OpenML Study"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+        body = super(OpenMLStudy, self).__str__()
+        return header + body
+
 
 class OpenMLBenchmarkSuite(BaseStudy):
 
@@ -302,3 +341,9 @@ def __init__(
             runs=None,
             setups=None,
         )
+
+    def __str__(self):
+        header = "OpenML Benchmark Suite"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+        body = super(OpenMLBenchmarkSuite, self).__str__()
+        return header + body

openml/tasks/task.py

@@ -42,6 +42,36 @@ def __init__(
         self.estimation_procedure_id = estimation_procedure_id
         self.split = None  # type: Optional[OpenMLSplit]
 
+    def __str__(self):
+        header = "OpenML Task"
+        header = '{}\n{}\n'.format(header, '=' * len(header))
+
+        base_url = "{}".format(openml.config.server[:-len('api/v1/xml')])
+        fields = {"Task Type": self.task_type}
+        if self.task_id is not None:
+            fields["Task ID"] = self.task_id
+            fields["Task URL"] = "{}t/{}".format(base_url, self.task_id)
+        if self.evaluation_measure is not None:
+            fields["Evaluation Measure"] = self.evaluation_measure
+        if self.estimation_procedure is not None:
+            fields["Estimation Procedure"] = self.estimation_procedure['type']
+        if self.target_name is not None:
+            fields["Target Feature"] = self.target_name
+            if hasattr(self, 'class_labels'):
+                fields["# of Classes"] = len(self.class_labels)
+            if hasattr(self, 'cost_matrix'):
+                fields["Cost Matrix"] = "Available"
+
+        # determines the order in which the information will be printed
+        order = ["Task Type", "Task ID", "Task URL", "Estimation Procedure", "Evaluation Measure",
+                 "Target Feature", "# of Classes", "Cost Matrix"]
+        fields = [(key, fields[key]) for key in order if key in fields]
+
+        longest_field_name_length = max(len(name) for name, value in fields)
+        field_line_format = "{{:.<{}}}: {{}}".format(longest_field_name_length)
+        body = '\n'.join(field_line_format.format(name, value) for name, value in fields)
+        return header + body
+
     def get_dataset(self) -> datasets.OpenMLDataset:
         """Download dataset associated with task"""
         return datasets.get_dataset(self.dataset_id)