from tamr_unify_client.models.binning_model import BinningModel
from tamr_unify_client.models.dataset.resource import Dataset
from tamr_unify_client.models.machine_learning_model import MachineLearningModel
from tamr_unify_client.models.project.estimated_pair_counts import EstimatedPairCounts
from tamr_unify_client.models.project.resource import Project
[docs]class MasteringProject(Project):
"""A Mastering project in Unify."""
[docs] def pairs(self):
"""Record pairs generated by Unify's binning model.
Pairs are displayed on the "Pairs" page in the Unify UI.
Call :func:`~tamr_unify_client.models.dataset.resource.Dataset.refresh` from
this dataset to regenerate pairs according to the latest binning model.
:returns: The record pairs represented as a dataset.
:rtype: :class:`~tamr_unify_client.models.dataset.resource.Dataset`
"""
alias = self.api_path + "/recordPairs"
return Dataset(self.client, None, alias)
[docs] def pair_matching_model(self):
"""Machine learning model for pair-matching for this Mastering project.
Learns from verified labels and predicts categorization labels for unlabeled pairs.
Calling :func:`~tamr_unify_client.models.machine_learning_model.MachineLearningModel.predict`
from this dataset will produce new (unpublished) clusters. These clusters
are displayed on the "Clusters" page in the Unify UI.
:returns: The machine learning model for pair-matching.
:rtype: :class:`~tamr_unify_client.models.machine_learning_model.MachineLearningModel`
"""
alias = self.api_path + "/recordPairsWithPredictions/model"
return MachineLearningModel(self.client, None, alias)
[docs] def high_impact_pairs(self):
"""High-impact pairs as a dataset. Unify labels pairs as "high-impact" if
labeling these pairs would help it learn most quickly (i.e. "Active learning").
High-impact pairs are displayed with a ⚡ lightning bolt icon on the
"Pairs" page in the Unify UI.
Call :func:`~tamr_unify_client.models.dataset.resource.Dataset.refresh` from
this dataset to produce new high-impact pairs according to the latest
pair-matching model.
:returns: The high-impact pairs represented as a dataset.
:rtype: :class:`~tamr_unify_client.models.dataset.resource.Dataset`
"""
alias = self.api_path + "/highImpactPairs"
return Dataset(self.client, None, alias)
[docs] def record_clusters(self):
"""Record Clusters as a dataset. Unify clusters labeled pairs using pairs
model. These clusters populate the cluster review page and get transient
cluster ids, rather than published cluster ids (i.e., "Permanent Ids")
Call :func:`~tamr_unify_client.models.dataset.resource.Dataset.refresh` from
this dataset to generate clusters based on to the latest pair-matching model.
:returns: The record clusters represented as a dataset.
:rtype: :class:`~tamr_unify_client.models.dataset.resource.Dataset`
"""
alias = self.api_path + "/recordClusters"
return Dataset(self.client, None, alias)
[docs] def published_clusters(self):
"""Published record clusters generated by Unify's pair-matching model.
:returns: The published clusters represented as a dataset.
:rtype: :class:`~tamr_unify_client.models.dataset.resource.Dataset`
"""
unified_dataset = self.unified_dataset()
# Replace this workaround with a direct API call once API
# is fixed. APIs that need to work are: fetching the dataset and
# being able to call refresh on resulting dataset. Until then, we grab
# the dataset by constructing its name from the corresponding Unified Dataset's name
name = unified_dataset.name + "_dedup_published_clusters"
canonical = self.client.datasets.by_name(name)
resource_json = canonical._data
alias = self.api_path + "/publishedClusters"
return Dataset.from_json(self.client, resource_json, alias)
[docs] def estimate_pairs(self):
"""Returns pair estimate information for a mastering project
:return: Pairs Estimate information.
:rtype: :class:`~tamr_unify_client.models.project.estimated_pair_counts`
"""
alias = self.api_path + "/estimatedPairCounts"
estimate_json = self.client.get(alias).successful().json()
info = EstimatedPairCounts.from_json(self.client, estimate_json, api_path=alias)
return info
[docs] def record_clusters_with_data(self):
"""Project's unified dataset with associated clusters.
:returns: The record clusters with data represented as a dataset
:rtype: :class:`~tamr_unify_client.models.dataset.resource.Dataset`
"""
unified_dataset = self.unified_dataset()
# Replace this workaround with a direct API call once API
# is fixed. APIs that need to work are: fetching the dataset and
# being able to call refresh on resulting dataset. Until then, we grab
# the dataset by constructing its name from the corresponding Unified Dataset's name
name = unified_dataset.name + "_dedup_clusters_with_data"
return self.client.datasets.by_name(name)
# super.__repr__ is sufficient
[docs] def published_clusters_with_data(self):
"""Project's unified dataset with associated clusters.
:returns: The published clusters with data represented as a dataset
:rtype :class `~tamr_unify_client.models.dataset.resource.Dataset`
"""
unified_dataset = self.unified_dataset()
name = unified_dataset.name + "_dedup_published_clusters_with_data"
return self.client.datasets.by_name(name)
[docs] def binning_model(self):
"""
Binning model for this project.
:return: Binning model for this project.
:rtype: :class:`~tamr_unify_client.models.binning_model.BinningModel`
"""
alias = self.api_path + "/binningModel"
# Cannot get this resource and so we hard code
resource_json = {"relativeId": alias}
return BinningModel.from_json(self.client, resource_json, alias)