Developer Interface¶

Authentication¶

class tamr_unify_client.auth.UsernamePasswordAuth(username, password)[source]¶

Provides username/password authentication for Tamr. Specifically, sets the Authorization HTTP header with Tamr’s custom BasicCreds format.

Parameters

username (str) –
password (str) –

Usage:

>>> from tamr_unify_client.auth import UsernamePasswordAuth
>>> auth = UsernamePasswordAuth('my username', 'my password')
>>> import tamr_unify_client as api
>>> unify = api.Client(auth)

Client¶

class tamr_unify_client.Client(auth, host='localhost', protocol='http', port=9100, base_path='/api/versioned/v1/', session=None)[source]¶

Python Client for Tamr API.

Each client is specific to a specific origin (protocol, host, port).

Parameters

auth (AuthBase) –
Tamr-compatible Authentication provider.

Recommended: use one of the classes described in Authentication
host (str) – Host address of remote Tamr instance (e.g. '10.0.10.0')
protocol (str) – Either 'http' or 'https'
port (int) – Tamr instance main port
base_path (str) – Base API path. Requests made by this client will be relative to this path.
session (Optional[Session]) – Session to use for API calls. If none is provided, will use a new requests.Session.

Example

>>> from tamr_unify_client import Client
>>> from tamr_unify_client.auth import UsernamePasswordAuth
>>> auth = UsernamePasswordAuth('my username', 'my password')
>>> tamr_local = Client(auth) # on http://localhost:9100
>>> tamr_remote = Client(auth, protocol='https', host='10.0.10.0') # on https://10.0.10.0:9100

property origin¶

HTTP origin i.e. <protocol>://<host>[:<port>].

For additional information, see MDN web docs .

Return type: str

request(method, endpoint, **kwargs)[source]¶

Sends a request to Tamr.

The URL for the request will be <origin>/<base_path>/<endpoint>. The request is authenticated via Client.auth.

Parameters

method (str) – The HTTP method to use (e.g. ‘GET’ or ‘POST’)
endpoint (str) – API endpoint to call (relative to the Base API path for this client).

Return type

Response

Returns

HTTP response from the Tamr server

get(endpoint, **kwargs)[source]¶: Calls request() with the "GET" method.

post(endpoint, **kwargs)[source]¶: Calls request() with the "POST" method.

put(endpoint, **kwargs)[source]¶: Calls request() with the "PUT" method.

delete(endpoint, **kwargs)[source]¶: Calls request() with the "DELETE" method.

property projects¶

Collection of all projects on this Tamr instance.

Return type: ProjectCollection
Returns: Collection of all projects.

property datasets¶

Collection of all datasets on this Tamr instance.

Return type: DatasetCollection
Returns: Collection of all datasets.

Attributes¶

Attribute¶

class tamr_unify_client.attribute.resource.Attribute(client, data, alias=None)[source]¶

A Tamr Attribute.

See https://docs.tamr.com/reference#attribute-types

property relative_id¶

Type: str

property name¶

Type: str

property description¶

Type: str

property type¶

Type: AttributeType

property is_nullable¶

Type: bool

spec()[source]¶

Returns a spec representation of this attribute.

Returns: The attribute spec.
Return type: AttributeSpec

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

Attribute Spec¶

class tamr_unify_client.attribute.resource.AttributeSpec(client, data, api_path)[source]¶

A representation of the server view of an attribute

static of(resource)[source]¶

Creates an attribute spec from an attribute.

Parameters: resource (Attribute) – The existing attribute.
Returns: The corresponding attribute spec.
Return type: AttributeSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new attribute.

Returns: The empty spec.
Return type: AttributeSpec

from_data(data)[source]¶

Creates a spec with the same client and API path as this one, but new data.

Parameters: data (dict) – The data for the new spec.
Returns: The new spec.
Return type: AttributeSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_name(new_name)[source]¶

Creates a new spec with the same properties, updating name.

Parameters: new_name (str) – The new name.
Returns: The new spec.
Return type: AttributeSpec

with_description(new_description)[source]¶

Creates a new spec with the same properties, updating description.

Parameters: new_description (str) – The new description.
Returns: The new spec.
Return type: AttributeSpec

with_type(new_type)[source]¶

Creates a new spec with the same properties, updating type.

Parameters: new_type (AttributeTypeSpec) – The spec of the new type.
Returns: The new spec.
Return type: AttributeSpec

with_is_nullable(new_is_nullable)[source]¶

Creates a new spec with the same properties, updating is nullable.

Parameters: new_is_nullable (bool) – The new is nullable.
Returns: The new spec.
Return type: AttributeSpec

put()[source]¶

Commits the changes and updates the attribute in Tamr.

Returns: The updated attribute.
Return type: Attribute

Attribute Collection¶

class tamr_unify_client.attribute.collection.AttributeCollection(client, api_path)[source]¶

Collection of Attribute s.

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection. E.g. "datasets/1/attributes".

by_resource_id(resource_id)[source]¶

Retrieve an attribute by resource ID.

Parameters: resource_id (str) – The resource ID. E.g. "AttributeName"
Returns: The specified attribute.
Return type: Attribute

by_relative_id(relative_id)[source]¶

Retrieve an attribute by relative ID.

Parameters: relative_id (str) – The resource ID. E.g. "datasets/1/attributes/AttributeName"
Returns: The specified attribute.
Return type: Attribute

by_external_id(external_id)[source]¶

Retrieve an attribute by external ID.

Since attributes do not have external IDs, this method is not supported and will raise a NotImplementedError .

Parameters

external_id (str) – The external ID.

Returns

The specified attribute, if found.

Return type

Attribute

Raises

KeyError – If no attribute with the specified external_id is found
LookupError – If multiple attributes with the specified external_id are found

stream()[source]¶

Stream attributes in this collection. Implicitly called when iterating over this collection.

Returns: Stream of attributes.
Return type: Python generator yielding Attribute

Usage:

>>> for attribute in collection.stream(): # explicit
>>>     do_stuff(attribute)
>>> for attribute in collection: # implicit
>>>     do_stuff(attribute)

by_name(attribute_name)[source]¶

Lookup a specific attribute in this collection by exact-match on name.

Parameters: attribute_name (str) – Name of the desired attribute.
Returns: Attribute with matching name in this collection.
Return type: Attribute

create(creation_spec)[source]¶

Create an Attribute in this collection

Parameters: creation_spec (dict[str, str]) – Attribute creation specification should be formatted as specified in the Public Docs for adding an Attribute.
Returns: The created Attribute
Return type: Attribute

delete_by_resource_id(resource_id)¶

Deletes a resource from this collection by resource ID.

Parameters: resource_id (str) – The resource ID of the resource that will be deleted.
Returns: HTTP response from the server.
Return type: requests.Response

Attribute Type¶

class tamr_unify_client.attribute.type.AttributeType(data)[source]¶

The type of an Attribute or SubAttribute.

See https://docs.tamr.com/reference#attribute-types

Parameters: data (dict) – JSON data representing this type

property base_type¶

Type: str

property inner_type¶

Type: AttributeType

property attributes¶

Type: list[SubAttribute]

spec()[source]¶

Returns a spec representation of this attribute type.

Returns: The attribute type spec.
Return type: AttributeTypeSpec

Attribute Type Spec¶

class tamr_unify_client.attribute.type.AttributeTypeSpec(data)[source]¶

static of(resource)[source]¶

Creates an attribute type spec from an attribute type.

Parameters: resource (AttributeType) – The existing attribute type.
Returns: The corresponding attribute type spec.
Return type: AttributeTypeSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new attribute type.

Returns: The empty spec.
Return type: AttributeTypeSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_base_type(new_base_type)[source]¶

Creates a new spec with the same properties, updating the base type.

Parameters: new_base_type (str) – The new base type.
Returns: The new spec.
Return type: AttributeTypeSpec

with_inner_type(new_inner_type)[source]¶

Creates a new spec with the same properties, updating the inner type.

Parameters: new_inner_type (AttributeTypeSpec) – The spec of the new inner type.
Returns: The new spec.
Return type: AttributeTypeSpec

with_attributes(new_attributes)[source]¶

Creates a new spec with the same properties, updating attributes.

Parameters: new_attributes (list[AttributeSpec]) – The specs of the new attributes.
Returns: The new spec.
Return type: AttributeTypeSpec

SubAttribute¶

class tamr_unify_client.attribute.subattribute.SubAttribute(name, type, is_nullable, _json, description=None)[source]¶

An attribute which is itself a property of another attribute.

See https://docs.tamr.com/reference#attribute-types

Parameters

name (str) – Name of sub-attribute
description (Optional[str]) – Description of sub-attribute
type (AttributeType) – See https://docs.tamr.com/reference#attribute-types
is_nullable (bool) – If this sub-attribute can be null

static from_json(data)[source]¶

Create a SubAttribute from JSON data.

Parameters: data (Dict[str, Any]) – JSON data received from Tamr server.
Return type: SubAttribute

Categorization¶

Categorization Project¶

class tamr_unify_client.categorization.project.CategorizationProject(client, data, alias=None)[source]¶

A Categorization project in Tamr.

model()[source]¶

Machine learning model for this Categorization project. Learns from verified labels and predicts categorization labels for unlabeled records.

Returns: The machine learning model for categorization.
Return type: MachineLearningModel

create_taxonomy(creation_spec)[source]¶

Creates a Taxonomy for this project.

A taxonomy cannot already be associated with this project.

Parameters: creation_spec (dict) – The creation specification for the taxonomy, which can include name.
Returns: The new Taxonomy
Return type: Taxonomy

taxonomy()[source]¶

Retrieves the Taxonomy associated with this project. If a taxonomy is not already associated with this project, call create_taxonomy() first.

Returns: The project’s Taxonomy
Return type: Taxonomy

add_input_dataset(dataset)¶

Associate a dataset with a project in Tamr.

By default, datasets are not associated with any projects. They need to be added as input to a project before they can be used as part of that project

Parameters: dataset (Dataset) – The dataset to associate with the project.
Returns: HTTP response from the server
Return type: requests.Response

as_categorization()¶

Convert this project to a CategorizationProject

Returns: This project.
Return type: CategorizationProject
Raises: TypeError – If the type of this project is not "CATEGORIZATION"

as_mastering()¶

Convert this project to a MasteringProject

Returns: This project.
Return type: MasteringProject
Raises: TypeError – If the type of this project is not "DEDUP"

attribute_configurations()¶

Project’s attribute’s configurations.

Returns: The configurations of the attributes of a project.
Return type: AttributeConfigurationCollection

attribute_mappings()¶

Project’s attribute’s mappings.

Returns: The attribute mappings of a project.
Return type: AttributeMappingCollection

property attributes¶

Attributes of this project.

Returns: Attributes of this project.
Return type: AttributeCollection

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property description¶

Type: str

property external_id¶

Type: str

input_datasets()¶

Retrieve a collection of this project’s input datasets.

Returns: The project’s input datasets.
Return type: DatasetCollection

property name¶

Type: str

property relative_id¶

Type: str

remove_input_dataset(dataset)¶

Remove a dataset from a project.

Parameters: dataset (Dataset) – The dataset to be removed from this project.
Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

spec()¶

Returns this project’s spec.

Returns: The spec for the project.
Return type: ProjectSpec

property type¶

A Tamr project type, listed in https://docs.tamr.com/reference#create-a-project.

Type: str

unified_dataset()¶

Unified dataset for this project.

Returns: Unified dataset for this project.
Return type: Dataset

Categories¶

Category¶

class tamr_unify_client.categorization.category.resource.Category(client, data, alias=None)[source]¶

A category of a taxonomy

property name¶

Type: str

property description¶

Type: str

property path¶

Type: list[str]

parent()[source]¶

Gets the parent Category of this one, or None if it is a tier 1 category

Returns: The parent Category or None
Return type: Category

spec()[source]¶

Returns this category’s spec.

Returns: The spec for the category.
Return type: CategorySpec

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Category Spec¶

class tamr_unify_client.categorization.category.resource.CategorySpec(client, data, api_path)[source]¶

A representation of the server view of a category.

static of(resource)[source]¶

Creates a category spec from a category.

Parameters: resource (Category) – The existing category.
Returns: The corresponding category spec.
Return type: CategorySpec

static new()[source]¶

Creates a blank spec that could be used to construct a new category.

Returns: The empty spec.
Return type: CategorySpec

from_data(data)[source]¶

Creates a spec with the same client and API path as this one, but new data.

Parameters: data (dict) – The data for the new spec.
Returns: The new spec.
Return type: CategorySpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_name(new_name)[source]¶

Creates a new spec with the same properties, updating name.

Parameters: new_name (str) – The new name.
Returns: The new spec.
Return type: CategorySpec

with_description(new_description)[source]¶

Creates a new spec with the same properties, updating description.

Parameters: new_description (str) – The new description.
Returns: The new spec.
Return type: CategorySpec

with_path(new_path)[source]¶

Creates a new spec with the same properties, updating path.

Parameters: new_path (list[str]) – The new path.
Returns: The new spec.
Return type: CategorySpec

Category Collection¶

class tamr_unify_client.categorization.category.collection.CategoryCollection(client, api_path)[source]¶

Collection of Category s.

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection. E.g. "projects/1/taxonomy/categories".

by_resource_id(resource_id)[source]¶

Retrieve a category by resource ID.

Parameters: resource_id (str) – The resource ID. E.g. "1"
Returns: The specified category.
Return type: Category

by_relative_id(relative_id)[source]¶

Retrieve a category by relative ID.

Parameters: relative_id (str) – The relative ID. E.g. "projects/1/categories/1"
Returns: The specified category.
Return type: Category

by_external_id(external_id)[source]¶

Retrieve an attribute by external ID.

Since categories do not have external IDs, this method is not supported and will raise a NotImplementedError .

Parameters

external_id (str) – The external ID.

Returns

The specified category, if found.

Return type

Category

Raises

KeyError – If no category with the specified external_id is found
LookupError – If multiple categories with the specified external_id are found

stream()[source]¶

Stream categories in this collection. Implicitly called when iterating over this collection.

Returns: Stream of categories.
Return type: Python generator yielding Category

Usage:

>>> for category in collection.stream(): # explicit
>>>     do_stuff(category)
>>> for category in collection: # implicit
>>>     do_stuff(category)

create(creation_spec)[source]¶

Creates a new category.

Parameters: creation_spec (dict) – Category creation specification, formatted as specified in the Public Docs for Creating a Category.
Returns: The newly created category.
Return type: Category

bulk_create(creation_specs)[source]¶

Creates new categories in bulk.

Parameters: creation_specs (iterable[dict]) – A collection of creation specifications, as detailed for create.
Returns: JSON response from the server
Return type: dict

delete_by_resource_id(resource_id)¶

Deletes a resource from this collection by resource ID.

Parameters: resource_id (str) – The resource ID of the resource that will be deleted.
Returns: HTTP response from the server.
Return type: requests.Response

Taxonomy¶

class tamr_unify_client.categorization.taxonomy.Taxonomy(client, data, alias=None)[source]¶

A project’s taxonomy

property name¶

Type: str

categories()[source]¶

Retrieves the categories of this taxonomy.

Returns: A collection of the taxonomy categories.
Return type: CategoryCollection

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Datasets¶

Dataset¶

class tamr_unify_client.dataset.resource.Dataset(client, data, alias=None)[source]¶

A Tamr dataset.

property name¶

Type: str

property external_id¶

Type: str

property description¶

Type: str

property version¶

Type: str

property tags¶

Type: list[str]

property key_attribute_names¶

Type: list[str]

property attributes¶

Attributes of this dataset.

Returns: Attributes of this dataset.
Return type: AttributeCollection

upsert_records(records, primary_key_name, **json_args)[source]¶

Creates or updates the specified records.

Parameters

records (iterable[dict]) – The records to update, as dictionaries.
primary_key_name (str) – The name of the primary key for these records, which must be a key in each record dictionary.
**json_args – Arguments to pass to the JSON dumps function, as documented here. Some of these, such as indent, may not work with Tamr.

Returns

JSON response body from the server.

Return type

dict

delete_records(records, primary_key_name)[source]¶

Deletes the specified records.

Parameters

records (iterable[dict]) – The records to delete, as dictionaries.
primary_key_name (str) – The name of the primary key for these records, which must be a key in each record dictionary.

Returns

JSON response body from the server.

Return type

dict

delete_records_by_id(record_ids)[source]¶

Deletes the specified records.

Parameters: record_ids (iterable) – The IDs of the records to delete.
Returns: JSON response body from the server.
Return type: dict

delete_all_records()[source]¶

Removes all records from the dataset.

Returns: HTTP response from the server
Return type: requests.Response

refresh(**options)[source]¶

Brings dataset up-to-date if needed, taking whatever actions are required.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The refresh operation.
Return type: Operation

profile()[source]¶

Returns profile information for a dataset.

If profile information has not been generated, call create_profile() first. If the returned profile information is out-of-date, you can call refresh() on the returned object to bring it up-to-date.

Returns: Dataset Profile information.
Return type: DatasetProfile

create_profile(**options)[source]¶

Create a profile for this dataset.

If a profile already exists, the existing profile will be brought up to date.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The operation to create the profile.
Return type: Operation

records()[source]¶

Stream this dataset’s records as Python dictionaries.

Returns: Stream of records.
Return type: Python generator yielding dict

status()[source]¶

Retrieve this dataset’s streamability status.

Returns: Dataset streamability status.
Return type: DatasetStatus

usage()[source]¶

Retrieve this dataset’s usage by recipes and downstream datasets.

Returns: The dataset’s usage.
Return type: DatasetUsage

from_geo_features(features, geo_attr=None)[source]¶

Upsert this dataset from a geospatial FeatureCollection or iterable of Features.

features can be:

An object that implements __geo_interface__ as a FeatureCollection (see https://gist.github.com/sgillies/2217756)
An iterable of features, where each element is a feature dictionary or an object that implements the __geo_interface__ as a Feature
A map where the “features” key contains an iterable of features

See: geopandas.GeoDataFrame.from_features()

If geo_attr is provided, then the named Tamr attribute will be used for the geometry. If geo_attr is not provided, then the first attribute on the dataset with geometry type will be used for the geometry.

Parameters

features – geospatial features
geo_attr (str) – (optional) name of the Tamr attribute to use for the feature’s geometry

upstream_datasets()[source]¶

The Dataset’s upstream datasets.

API returns the URIs of the upstream datasets, resulting in a list of DatasetURIs, not actual Datasets.

Returns: A list of the Dataset’s upstream datasets.
Return type: list[DatasetURI]

spec()[source]¶

Returns this dataset’s spec.

Returns: The spec of this dataset.
Return type: DatasetSpec

delete(cascade=False)[source]¶

Deletes this dataset, optionally deleting all derived datasets as well.

Parameters: cascade (bool) – Whether to delete all datasets derived from this one. Optional, default is False. Do not use this option unless you are certain you need it as it can have unindended consequences.
Returns: HTTP response from the server
Return type: requests.Response

itergeofeatures(geo_attr=None)[source]¶

Returns an iterator that yields feature dictionaries that comply with __geo_interface__

See https://gist.github.com/sgillies/2217756

Parameters: geo_attr (str) – (optional) name of the Tamr attribute to use for the feature’s geometry
Returns: stream of features
Return type: Python generator yielding dict[str, object]

property relative_id¶

Type: str

property resource_id¶

Type: str

Dataset Spec¶

class tamr_unify_client.dataset.resource.DatasetSpec(client, data, api_path)[source]¶

A representation of the server view of a dataset.

static of(resource)[source]¶

Creates a dataset spec from a dataset.

Parameters: resource (Dataset) – The existing dataset.
Returns: The corresponding dataset spec.
Return type: DatasetSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new dataset.

Returns: The empty spec.
Return type: DatasetSpec

from_data(data)[source]¶

Creates a spec with the same client and API path as this one, but new data.

Parameters: data (dict) – The data for the new spec.
Returns: The new spec.
Return type: DatasetSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_name(new_name)[source]¶

Creates a new spec with the same properties, updating name.

Parameters: new_name (str) – The new name.
Returns: A new spec.
Return type: DatasetSpec

with_external_id(new_external_id)[source]¶

Creates a new spec with the same properties, updating external ID.

Parameters: new_external_id (str) – The new external ID.
Returns: A new spec.
Return type: DatasetSpec

with_description(new_description)[source]¶

Creates a new spec with the same properties, updating description.

Parameters: new_description (str) – The new description.
Returns: A new spec.
Return type: DatasetSpec

with_key_attribute_names(new_key_attribute_names)[source]¶

Creates a new spec with the same properties, updating key attribute names.

Parameters: new_key_attribute_names (list[str]) – The new key attribute names.
Returns: A new spec.
Return type: DatasetSpec

with_tags(new_tags)[source]¶

Creates a new spec with the same properties, updating tags.

Parameters: new_tags (list[str]) – The new tags.
Returns: A new spec.
Return type: DatasetSpec

put()[source]¶

Updates the dataset on the server.

Returns: The modified dataset.
Return type: Dataset

Dataset Collection¶

class tamr_unify_client.dataset.collection.DatasetCollection(client, api_path='datasets')[source]¶

Collection of Dataset s.

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection. E.g. "projects/1/inputDatasets". Default: "datasets".

by_resource_id(resource_id)[source]¶

Retrieve a dataset by resource ID.

Parameters: resource_id (str) – The resource ID. E.g. "1"
Returns: The specified dataset.
Return type: Dataset

by_relative_id(relative_id)[source]¶

Retrieve a dataset by relative ID.

Parameters: relative_id (str) – The resource ID. E.g. "datasets/1"
Returns: The specified dataset.
Return type: Dataset

by_external_id(external_id)[source]¶

Retrieve a dataset by external ID.

Parameters

external_id (str) – The external ID.

Returns

The specified dataset, if found.

Return type

Dataset

Raises

KeyError – If no dataset with the specified external_id is found
LookupError – If multiple datasets with the specified external_id are found

stream()[source]¶

Stream datasets in this collection. Implicitly called when iterating over this collection.

Returns: Stream of datasets.
Return type: Python generator yielding Dataset

Usage:

>>> for dataset in collection.stream(): # explicit
>>>     do_stuff(dataset)
>>> for dataset in collection: # implicit
>>>     do_stuff(dataset)

by_name(dataset_name)[source]¶

Lookup a specific dataset in this collection by exact-match on name.

Parameters: dataset_name (str) – Name of the desired dataset.
Returns: Dataset with matching name in this collection.
Return type: Dataset
Raises: KeyError – If no dataset with specified name was found.

delete_by_resource_id(resource_id, cascade=False)[source]¶

Deletes a dataset from this collection by resource_id. Optionally deletes all derived datasets as well.

Parameters

resource_id (str) – The resource id of the dataset in this collection to delete.
cascade (bool) – Whether to delete all datasets derived from the deleted one. Optional, default is False. Do not use this option unless you are certain you need it as it can have unindended consequences.

Returns

HTTP response from the server.

Return type

requests.Response

create(creation_spec)[source]¶

Create a Dataset in Tamr

Parameters: creation_spec (dict[str, str]) – Dataset creation specification should be formatted as specified in the Public Docs for Creating a Dataset.
Returns: The created Dataset
Return type: Dataset

create_from_dataframe(df, primary_key_name, dataset_name, ignore_nan=True)[source]¶

Creates a dataset in this collection with the given name, creates an attribute for each column in the df (with primary_key_name as the key attribute), and upserts a record for each row of df.

Each attribute has the default type ARRAY[STRING], besides the key attribute, which will have type STRING.

This function attempts to ensure atomicity, but it is not guaranteed. If an error occurs while creating attributes or records, an attempt will be made to delete the dataset that was created. However, if this request errors, it will not try again.

Parameters

df (pandas.DataFrame) – The data to create the dataset with.
primary_key_name (str) – The name of the primary key of the dataset. Must be a column of df.
dataset_name (str) – What to name the dataset in Tamr. There cannot already be a dataset with this name.
ignore_nan (bool) – Whether to convert NaN values to null before upserting records to Tamr. If False and NaN is in df, this function will fail. Optional, default is True.

Returns

The newly created dataset.

Return type

Dataset

Raises

KeyError – If primary_key_name is not a column in df.
CreationError – If a step in creating the dataset fails.

class tamr_unify_client.dataset.collection.CreationError(error_message)[source]¶

An error from create_from_dataframe()

with_traceback()¶: Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

Dataset Profile¶

class tamr_unify_client.dataset.profile.DatasetProfile(client, data, alias=None)[source]¶

Profile info of a Tamr dataset.

property dataset_name¶

The name of the associated dataset.

Type: str
Return type: str

property relative_dataset_id¶

The relative dataset ID of the associated dataset.

Type: str
Return type: str

property is_up_to_date¶

Whether the associated dataset is up to date.

Type: bool
Return type: bool

property profiled_data_version¶

The profiled data version.

Type: str
Return type: str

property profiled_at¶

Info about when profile info was generated.

Type: dict
Return type: dict

property simple_metrics¶

Simple metrics for profiled dataset.

Type: list
Return type: list

property attribute_profiles¶

Simple metrics for profiled dataset.

Type: list
Return type: list

refresh(**options)[source]¶

Updates the dataset profile if needed.

The dataset profile is updated on the server; you will need to call profile() to retrieve the updated profile.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The refresh operation.
Return type: Operation

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Dataset Status¶

class tamr_unify_client.dataset.status.DatasetStatus(client, data, alias=None)[source]¶

Streamability status of a Tamr dataset.

property dataset_name¶

The name of the associated dataset.

Type: str
Return type: str

property relative_dataset_id¶

The relative dataset ID of the associated dataset.

Type: str
Return type: str

property is_streamable¶

Whether the associated dataset is available to be streamed.

Type: bool
Return type: bool

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Dataset URI¶

class tamr_unify_client.dataset.uri.DatasetURI(client, uri)[source]¶

Indentifier of a dataset.

Parameters

client (Client) – Queried dataset’s client.
uri (str) – Queried dataset’s dataset ID.

property resource_id¶

Type: str

property relative_id¶

Type: str

property uri¶

Type: str

dataset()[source]¶

Fetch the dataset that this identifier points to.

Returns

A Tamr dataset.

Return type

class: ~tamr_unify_client.dataset.resource.Dataset

Dataset Usage¶

class tamr_unify_client.dataset.usage.DatasetUsage(client, data, alias=None)[source]¶

The usage of a dataset and its downstream dependencies.

See https://docs.tamr.com/reference#retrieve-downstream-dataset-usage

property relative_id¶

Type: str

property usage¶

Type: DatasetUse

property dependencies¶

Type: list[DatasetUse]

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

Dataset Use¶

class tamr_unify_client.dataset.use.DatasetUse(client, data)[source]¶

The use of a dataset in project steps. This is not a BaseResource because it has no API path and cannot be directly retrieved or modified.

See https://docs.tamr.com/reference#retrieve-downstream-dataset-usage

Parameters

client (Client) – Delegate underlying API calls to this client.
data (dict) – The JSON body containing usage information.

property dataset_id¶

Type: str

property dataset_name¶

Type: str

property input_to_project_steps¶

Type: list[ProjectStep]

property output_from_project_steps¶

Type: list[ProjectStep]

dataset()[source]¶

Retrieves the Dataset this use represents.

Returns: The dataset being used.
Return type: Dataset

Machine Learning Model¶

class tamr_unify_client.base_model.MachineLearningModel(client, data, alias=None)[source]¶

A Tamr Machine Learning model.

train(**options)[source]¶

Learn from verified labels.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The resultant operation.
Return type: Operation

predict(**options)[source]¶

Suggest labels for unverified records.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The resultant operation.
Return type: Operation

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Mastering¶

Binning Model¶

class tamr_unify_client.mastering.binning_model.BinningModel(client, data, alias=None)[source]¶

A binning model object.

records()[source]¶

Stream this object’s records as Python dictionaries.

Returns: Stream of records.
Return type: Python generator yielding dict

update_records(records)[source]¶

Send a batch of record creations/updates/deletions to this dataset.

Parameters: records (iterable[dict]) – Each record should be formatted as specified in the Public Docs for Dataset updates.
Returns: JSON response body from server.
Return type: dict

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Estimated Pair Counts¶

class tamr_unify_client.mastering.estimated_pair_counts.EstimatedPairCounts(client, data, alias=None)[source]¶

Estimated Pair Counts info for Mastering Project

property is_up_to_date¶

Whether an estimate pairs job has been run since the last edit to the binning model.

Return type: bool

property total_estimate¶

The total number of estimated candidate pairs and generated pairs for the model across all clauses.

Returns

A dictionary containing candidate pairs and estimated pairs mapped to their corresponding estimated counts. For example:

{

“candidatePairCount”: “54321”,

”generatedPairCount”: “12345”

}

Return type

dict[str, str]

property clause_estimates¶

The estimated candidate pair count and generated pair count for each clause in the model.

Returns

A dictionary containing each clause name mapped to a dictionary containing the corresponding estimated candidate and generated pair counts. For example:

{

“Clause1”: {

“candidatePairCount”: “321”,

”generatedPairCount”: “123”

},

”Clause2”: {

“candidatePairCount”: “654”,

”generatedPairCount”: “456”

}

}

Return type

dict[str, dict[str, str]]

refresh(**options)[source]¶

Updates the estimated pair counts if needed.

The pair count estimates are updated on the server; you will need to call estimate_pairs() to retrieve the updated estimate.

Parameters: **options – Options passed to underlying Operation . See apply_options() .
Returns: The refresh operation.
Return type: Operation

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Mastering Project¶

class tamr_unify_client.mastering.project.MasteringProject(client, data, alias=None)[source]¶

A Mastering project in Tamr.

pairs()[source]¶

Record pairs generated by Tamr’s binning model. Pairs are displayed on the “Pairs” page in the Tamr UI.

Call refresh() from this dataset to regenerate pairs according to the latest binning model.

Returns: The record pairs represented as a dataset.
Return type: Dataset

pair_matching_model()[source]¶

Machine learning model for pair-matching for this Mastering project. Learns from verified labels and predicts categorization labels for unlabeled pairs.

Calling predict() from this dataset will produce new (unpublished) clusters. These clusters are displayed on the “Clusters” page in the Tamr UI.

Returns: The machine learning model for pair-matching.
Return type: MachineLearningModel

high_impact_pairs()[source]¶

High-impact pairs as a dataset. Tamr 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 Tamr UI.

Call 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.
Return type: Dataset

record_clusters()[source]¶

Record Clusters as a dataset. Tamr 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 refresh() from this dataset to generate clusters based on to the latest pair-matching model.

Returns: The record clusters represented as a dataset.
Return type: Dataset

published_clusters()[source]¶

Published record clusters generated by Tamr’s pair-matching model.

Returns: The published clusters represented as a dataset.
Return type: Dataset

published_clusters_configuration()[source]¶

Retrieves published clusters configuration for this project.

Returns: The published clusters configuration
Return type: PublishedClustersConfiguration

published_cluster_ids()[source]¶

Retrieves published cluster IDs for this project.

Returns: The published cluster ID dataset.
Return type: Dataset

published_cluster_stats()[source]¶

Retrieves published cluster stats for this project.

Returns: The published cluster stats dataset.
Return type: Dataset

published_cluster_versions(cluster_ids)[source]¶

Retrieves version information for the specified published clusters. See https://docs.tamr.com/reference#retrieve-published-clusters-given-cluster-ids.

Parameters: cluster_ids (iterable[str]) – The persistent IDs of the clusters to get version information for.
Returns: A stream of the published clusters.
Return type: Python generator yielding PublishedCluster

record_published_cluster_versions(record_ids)[source]¶

Retrieves version information for the published clusters of the given records. See https://docs.tamr.com/reference#retrieve-published-clusters-given-record-ids.

Parameters: record_ids (iterable[str]) – The Tamr IDs of the records to get cluster version information for.
Returns: A stream of the relevant published clusters.
Return type: Python generator yielding RecordPublishedCluster

estimate_pairs()[source]¶

Returns pair estimate information for a mastering project

Returns: Pairs Estimate information.
Return type: EstimatedPairCounts

record_clusters_with_data()[source]¶

Project’s unified dataset with associated clusters.

Returns: The record clusters with data represented as a dataset
Return type: Dataset

published_clusters_with_data()[source]¶

Project’s unified dataset with associated clusters.

Returns: The published clusters with data represented as a dataset
Return type: Dataset

binning_model()[source]¶

Binning model for this project.

Returns: Binning model for this project.
Return type: BinningModel

add_input_dataset(dataset)¶

Associate a dataset with a project in Tamr.

By default, datasets are not associated with any projects. They need to be added as input to a project before they can be used as part of that project

Parameters: dataset (Dataset) – The dataset to associate with the project.
Returns: HTTP response from the server
Return type: requests.Response

as_categorization()¶

Convert this project to a CategorizationProject

Returns: This project.
Return type: CategorizationProject
Raises: TypeError – If the type of this project is not "CATEGORIZATION"

as_mastering()¶

Convert this project to a MasteringProject

Returns: This project.
Return type: MasteringProject
Raises: TypeError – If the type of this project is not "DEDUP"

attribute_configurations()¶

Project’s attribute’s configurations.

Returns: The configurations of the attributes of a project.
Return type: AttributeConfigurationCollection

attribute_mappings()¶

Project’s attribute’s mappings.

Returns: The attribute mappings of a project.
Return type: AttributeMappingCollection

property attributes¶

Attributes of this project.

Returns: Attributes of this project.
Return type: AttributeCollection

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property description¶

Type: str

property external_id¶

Type: str

input_datasets()¶

Retrieve a collection of this project’s input datasets.

Returns: The project’s input datasets.
Return type: DatasetCollection

property name¶

Type: str

property relative_id¶

Type: str

remove_input_dataset(dataset)¶

Remove a dataset from a project.

Parameters: dataset (Dataset) – The dataset to be removed from this project.
Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

spec()¶

Returns this project’s spec.

Returns: The spec for the project.
Return type: ProjectSpec

property type¶

A Tamr project type, listed in https://docs.tamr.com/reference#create-a-project.

Type: str

unified_dataset()¶

Unified dataset for this project.

Returns: Unified dataset for this project.
Return type: Dataset

Published Clusters¶

Metric¶

class tamr_unify_client.mastering.published_cluster.metric.Metric(data)[source]¶

A metric for a published cluster.

This is not a BaseResource because it does not have its own API endpoint.

Parameters: data – The JSON entity representing this cluster.

property name¶

Type: str

property value¶

Type: str

Published Cluster¶

class tamr_unify_client.mastering.published_cluster.resource.PublishedCluster(data)[source]¶

A representation of a published cluster in a mastering project with version information. See https://docs.tamr.com/reference#retrieve-published-clusters-given-cluster-ids.

This is not a BaseResource because it does not have its own API endpoint.

Parameters: data – The JSON entity representing this PublishedCluster.

property id¶

Type: str

property versions¶

Type: list[PublishedClusterVersion]

Published Cluster Configuration¶

class tamr_unify_client.mastering.published_cluster.configuration.PublishedClustersConfiguration(client, data, alias=None)[source]¶

The configuration of published clusters in a project.

See https://docs.tamr.com/reference#the-published-clusters-configuration-object

property relative_id¶

Type: str

property versions_time_to_live¶

Type: str

spec()[source]¶

Returns a spec representation of this published cluster configuration.

Returns: The published cluster configuration spec.
Return type: :class`~tamr_unify_client.mastering.published_cluster.configuration.PublishedClustersConfigurationSpec`

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

Published Cluster Version¶

class tamr_unify_client.mastering.published_cluster.version.PublishedClusterVersion(data)[source]¶

A version of a published cluster in a mastering project.

This is not a BaseResource because it does not have its own API endpoint.

Parameters: data – The JSON entity representing this version.

property version¶

Type: str

property timestamp¶

Type: str

property name¶

Type: str

property metrics¶

Type: list[Metric]

property record_ids¶

Type: list[dict[str, str]]

Record Published Cluster¶

class tamr_unify_client.mastering.published_cluster.record.RecordPublishedCluster(data)[source]¶

A representation of a published cluster of a record in a mastering project with version information. See https://docs.tamr.com/reference#retrieve-published-clusters-given-record-ids.

This is not a BaseResource because it does not have its own API endpoint.

Parameters: data – The JSON entity representing this RecordPublishedCluster.

property entity_id¶

Type: str

property source_id¶

Type: str

property origin_entity_id¶

Type: str

property origin_source_id¶

Type: str

property versions¶

Type: list[RecordPublishedClusterVersion]

Record Published Cluster Version¶

class tamr_unify_client.mastering.published_cluster.record_version.RecordPublishedClusterVersion(data)[source]¶

A version of a published cluster in a mastering project.

This is not a BaseResource because it does not have its own API endpoint.

Parameters: data – The JSON entity representing this version.

property version¶

Type: str

property timestamp¶

Type: str

property cluster_id¶

Type: str

Operation¶

class tamr_unify_client.operation.Operation(client, data, alias=None)[source]¶

A long-running operation performed by Tamr. Operations appear on the “Jobs” page of the Tamr UI.

By design, client-side operations represent server-side operations at a particular point in time (namely, when the operation was fetched from the server). In other words: Operations will not pick up on server-side changes automatically. To get an up-to-date representation, refetch the operation e.g. op = op.poll().

classmethod from_response(client, response)[source]¶

Handle idiosyncrasies in constructing Operations from Tamr responses. When a Tamr API call would start an operation, but all results that would be produced by that operation are already up-to-date, Tamr returns HTTP 204 No Content

To make it easy for client code to handle these API responses without checking the response code, this method will either construct an Operation, or a dummy NoOp operation representing the 204 Success response.

Parameters

client (Client) – Delegate underlying API calls to this client.
response (requests.Response) – HTTP Response from the request that started the operation.

Returns

Operation

Return type

Operation

apply_options(asynchronous=False, **options)[source]¶

Applies operation options to this operation.

NOTE: This function should not be called directly. Rather, options should be passed in through a higher-level function e.g. refresh() .

Synchronous mode:: Automatically waits for operation to resolve before returning the operation.
asynchronous mode:: Immediately return the 'PENDING' operation. It is up to the user to coordinate this operation with their code via wait() and/or poll() .

Parameters

asynchronous (bool) – Whether or not to run in asynchronous mode. Default: False.
**options – When running in synchronous mode, these options are passed to the underlying wait() call.

Returns

Operation with options applied.

Return type

Operation

property type¶

Type: str

property description¶

Type: str

property state¶

Server-side state of this operation.

Operation state can be unresolved (i.e. state is one of: 'PENDING', 'RUNNING'), or resolved (i.e. state is one of: 'CANCELED', 'SUCCEEDED', 'FAILED'). Unless opting into asynchronous mode, all exposed operations should be resolved.

Note: you only need to manually pick up server-side changes when opting into asynchronous mode when kicking off this operation.

Usage:

>>> op.state # operation is currently 'PENDING'
'PENDING'
>>> op.wait() # continually polls until operation resolves
>>> op.state # incorrect usage; operation object state never changes.
'PENDING'
>>> op = op.poll() # correct usage; use value returned by Operation.poll or Operation.wait
>>> op.state
'SUCCEEDED'

poll()[source]¶

Poll this operation for server-side updates.

Does not update the calling Operation object. Instead, returns a new Operation.

Returns: Updated representation of this operation.
Return type: Operation

wait(poll_interval_seconds=3, timeout_seconds=None)[source]¶

Continuously polls for this operation’s server-side state.

Parameters

poll_interval_seconds (int) – Time interval (in seconds) between subsequent polls.
timeout_seconds (int) – Time (in seconds) to wait for operation to resolve.

Raises

TimeoutError – If operation takes longer than timeout_seconds to resolve.

Returns

Resolved operation.

Return type

Operation

succeeded()[source]¶

Convenience method for checking if operation was successful.

Returns: True if operation’s state is 'SUCCEEDED', False otherwise.
Return type: bool

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Projects¶

Attribute Configurations¶

Attribute Configuration¶

class tamr_unify_client.project.attribute_configuration.resource.AttributeConfiguration(client, data, alias=None)[source]¶

The configurations of Tamr Attributes.

See https://docs.tamr.com/reference#the-attribute-configuration-object

property relative_id¶

Type: str

property id¶

Type: str

property relative_attribute_id¶

Type: str

property attribute_role¶

Type: str

property similarity_function¶

Type: str

property enabled_for_ml¶

Type: bool

property tokenizer¶

Type: str

property numeric_field_resolution¶

Type: list

property attribute_name¶

Type: str

spec()[source]¶

Returns this attribute configuration’s spec.

Returns: The spec of this attribute configuration.
Return type: AttributeConfigurationSpec

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property resource_id¶

Type: str

Attribute Configuration Spec¶

class tamr_unify_client.project.attribute_configuration.resource.AttributeConfigurationSpec(client, data, api_path)[source]¶

A representation of the server view of an attribute configuration.

static of(resource)[source]¶

Creates an attribute configuration spec from an attribute configuration.

Parameters: resource (AttributeConfiguration) – The existing attribute configuration.
Returns: The corresponding attribute creation spec.
Return type: AttributeConfigurationSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new attribute configuration.

Returns: The empty spec.
Return type: AttributeConfigurationSpec

from_data(data)[source]¶

Creates a spec with the same client and API path as this one, but new data.

Parameters: data (dict) – The data for the new spec.
Returns: The new spec.
Return type: AttributeConfigurationSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_attribute_role(new_attribute_role)[source]¶

Creates a new spec with the same properties, updating attribute role.

Parameters: new_attribute_role (str) – The new attribute role.
Returns: A new spec.
Return type: AttributeConfigurationSpec

with_similarity_function(new_similarity_function)[source]¶

Creates a new spec with the same properties, updating similarity function.

Parameters: new_similarity_function (str) – The new similarity function.
Returns: A new spec.
Return type: AttributeConfigurationSpec

with_enabled_for_ml(new_enabled_for_ml)[source]¶

Creates a new spec with the same properties, updating enabled for ML.

Parameters: new_enabled_for_ml (bool) – Whether the builder is enabled for ML.
Returns: A new spec.
Return type: AttributeConfigurationSpec

with_tokenizer(new_tokenizer)[source]¶

Creates a new spec with the same properties, updating tokenizer.

Parameters: new_tokenizer (str) – The new tokenizer.
Returns: A new spec.
Return type: AttributeConfigurationSpec

with_numeric_field_resolution(new_numeric_field_resolution)[source]¶

Creates a new spec with the same properties, updating numeric field resolution.

Parameters: new_numeric_field_resolution (str) – The new numeric field resolution.
Returns: A new spec.
Return type: AttributeConfigurationSpec

with_attribute_name(new_attribute_name)[source]¶

Creates a new spec with the same properties, updating new attribute name.

Parameters: new_attribute_name (str) – The new attribute name.
Returns: A new spec.
Return type: AttributeConfigurationSpec

put()[source]¶

Updates the attribute configuration on the server.

Returns: The modified attribute configuration.
Return type: AttributeConfiguration

Attribute Configuration Collection¶

class tamr_unify_client.project.attribute_configuration.collection.AttributeConfigurationCollection(client, api_path)[source]¶

Collection of AttributeConfiguration

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection. E.g. "projects/1/attributeConfigurations"

by_resource_id(resource_id)[source]¶

Retrieve an attribute configuration by resource ID.

Parameters: resource_id (str) – The resource ID.
Returns: The specified attribute configuration.
Return type: AttributeConfiguration

by_relative_id(relative_id)[source]¶

Retrieve an attribute configuration by relative ID.

Parameters: relative_id (str) – The relative ID.
Returns: The specified attribute configuration.
Return type: AttributeConfiguration

by_external_id(external_id)[source]¶

Retrieve an attribute configuration by external ID.

Since attributes do not have external IDs, this method is not supported and will raise a NotImplementedError .

Parameters

external_id (str) – The external ID.

Returns

The specified attribute, if found.

Return type

AttributeConfiguration

Raises

KeyError – If no attribute with the specified external_id is found
LookupError – If multiple attributes with the specified external_id are found
NotImplementedError – AttributeConfiguration does not support external_id

stream()[source]¶

Stream attribute configurations in this collection. Implicitly called when iterating over this collection.

Returns: Stream of attribute configurations.
Return type: Python generator yielding AttributeConfiguration

Usage:

>>> for attributeConfiguration in collection.stream(): # explicit
>>>     do_stuff(attributeConfiguration)
>>> for attributeConfiguration in collection: # implicit
>>>     do_stuff(attributeConfiguration)

create(creation_spec)[source]¶

Create an Attribute configuration in this collection

Parameters: creation_spec (dict[str, str]) – Attribute configuration creation specification should be formatted as specified in the Public Docs for adding an AttributeConfiguration.
Returns: The created Attribute configuration
Return type: AttributeConfiguration

delete_by_resource_id(resource_id)¶

Deletes a resource from this collection by resource ID.

Parameters: resource_id (str) – The resource ID of the resource that will be deleted.
Returns: HTTP response from the server.
Return type: requests.Response

Attribute Mappings¶

Attribute Mapping¶

class tamr_unify_client.project.attribute_mapping.resource.AttributeMapping(client, data)[source]¶

see https://docs.tamr.com/reference#retrieve-projects-mappings AttributeMapping and AttributeMappingCollection do not inherit from BaseResource and BaseCollection. BC and BR require a specific URL for each individual attribute mapping (ex: /projects/1/attributeMappings/1), but these types of URLs do not exist for attribute mappings

property id¶

Type: str

property relative_id¶

Type: str

property input_attribute_id¶

Type: str

property relative_input_attribute_id¶

Type: str

property input_dataset_name¶

Type: str

property input_attribute_name¶

Type: str

property unified_attribute_id¶

Type: str

property relative_unified_attribute_id¶

Type: str

property unified_dataset_name¶

Type: str

property unified_attribute_name¶

Type: str

property resource_id¶

Type: str

spec()[source]¶

Returns a spec representation of this attribute mapping.

Returns: The attribute mapping spec.
Return type: AttributeMappingSpec

delete()[source]¶

Delete this attribute mapping.

Returns: HTTP response from the server
Return type: requests.Response

Attribute Mapping Spec¶

class tamr_unify_client.project.attribute_mapping.resource.AttributeMappingSpec(data)[source]¶

A representation of the server view of an attribute mapping

static of(resource)[source]¶

Creates an attribute mapping spec from a attribute mapping.

Parameters: resource (AttributeMapping) – The existing attribute mapping.
Returns: The corresponding attribute mapping spec.
Return type: AttributeMappingSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new attribute mapping.

Returns: The empty spec.
Return type: AttributeMappingSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_input_attribute_id(new_input_attribute_id)[source]¶

Creates a new spec with the same properties, updating the input attribute id.

Parameters: new_input_attribute_id (str) – The new input attribute id.
Returns: The new spec.
Return type: AttributeMappingSpec

with_relative_input_attribute_id(new_relative_input_attribute_id)[source]¶

Creates a new spec with the same properties, updating the relative input attribute id.

Parameters: new_relative_input_attribute_id (str) – The new relative input attribute Id.
Returns: The new spec.
Return type: AttributeMappingSpec

with_input_dataset_name(new_input_dataset_name)[source]¶

Creates a new spec with the same properties, updating the input dataset name.

Parameters: new_input_dataset_name (str) – The new input dataset name.
Returns: The new spec.
Return type: AttributeMappingSpec

with_input_attribute_name(new_input_attribute_name)[source]¶

Creates a new spec with the same properties, updating the input attribute name.

Parameters: new_input_attribute_name (str) – The new input attribute name.
Returns: The new spec.
Return type: AttributeMappingSpec

with_unified_attribute_id(new_unified_attribute_id)[source]¶

Creates a new spec with the same properties, updating the unified attribute id.

Parameters: new_unified_attribute_id (str) – The new unified attribute id.
Returns: The new spec.
Return type: AttributeMappingSpec

with_relative_unified_attribute_id(new_relative_unified_attribute_id)[source]¶

Creates a new spec with the same properties, updating the relative unified attribute id.

Parameters: new_relative_unified_attribute_id (str) – The new relative unified attribute id.
Returns: The new spec.
Return type: AttributeMappingSpec

with_unified_dataset_name(new_unified_dataset_name)[source]¶

Creates a new spec with the same properties, updating the unified dataset name.

Parameters: new_unified_dataset_name (str) – The new unified dataset name.
Returns: The new spec.
Return type: AttributeMappingSpec

with_unified_attribute_name(new_unified_attribute_name)[source]¶

Creates a new spec with the same properties, updating the unified attribute name.

Parameters: new_unified_attribute_name (str) – The new unified attribute name.
Returns: The new spec.
Return type: AttributeMappingSpec

Attribute Mapping Collection¶

class tamr_unify_client.project.attribute_mapping.collection.AttributeMappingCollection(client, api_path)[source]¶

Collection of AttributeMapping

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection.

stream()[source]¶

Stream attribute mappings in this collection. Implicitly called when iterating over this collection.

Returns: Stream of attribute mappings.
Return type: Python generator yielding AttributeMapping

by_resource_id(resource_id)[source]¶

Retrieve an item in this collection by resource ID.

Parameters: resource_id (str) – The resource ID.
Returns: The specified attribute mapping.
Return type: AttributeMapping

by_relative_id(relative_id)[source]¶

Retrieve an item in this collection by relative ID.

Parameters: relative_id (str) – The relative ID.
Returns: The specified attribute mapping.
Return type: AttributeMapping

create(creation_spec)[source]¶

Create an Attribute mapping in this collection

Parameters: creation_spec (dict[str, str]) – Attribute mapping creation specification should be formatted as specified in the Public Docs for adding an AttributeMapping.
Returns: The created Attribute mapping
Return type: AttributeMapping

delete_by_resource_id(resource_id)[source]¶

Delete an attribute mapping using its Resource ID.

Parameters: resource_id (str) – the resource ID of the mapping to be deleted.
Returns: HTTP response from the server
Return type: requests.Response

Project¶

class tamr_unify_client.project.resource.Project(client, data, alias=None)[source]¶

A Tamr project.

property name¶

Type: str

property external_id¶

Type: str

property description¶

Type: str

property type¶

A Tamr project type, listed in https://docs.tamr.com/reference#create-a-project.

Type: str

property attributes¶

Attributes of this project.

Returns: Attributes of this project.
Return type: AttributeCollection

unified_dataset()[source]¶

Unified dataset for this project.

Returns: Unified dataset for this project.
Return type: Dataset

as_categorization()[source]¶

Convert this project to a CategorizationProject

Returns: This project.
Return type: CategorizationProject
Raises: TypeError – If the type of this project is not "CATEGORIZATION"

as_mastering()[source]¶

Convert this project to a MasteringProject

Returns: This project.
Return type: MasteringProject
Raises: TypeError – If the type of this project is not "DEDUP"

add_input_dataset(dataset)[source]¶

Associate a dataset with a project in Tamr.

By default, datasets are not associated with any projects. They need to be added as input to a project before they can be used as part of that project

Parameters: dataset (Dataset) – The dataset to associate with the project.
Returns: HTTP response from the server
Return type: requests.Response

remove_input_dataset(dataset)[source]¶

Remove a dataset from a project.

Parameters: dataset (Dataset) – The dataset to be removed from this project.
Returns: HTTP response from the server
Return type: requests.Response

input_datasets()[source]¶

Retrieve a collection of this project’s input datasets.

Returns: The project’s input datasets.
Return type: DatasetCollection

attribute_configurations()[source]¶

Project’s attribute’s configurations.

Returns: The configurations of the attributes of a project.
Return type: AttributeConfigurationCollection

attribute_mappings()[source]¶

Project’s attribute’s mappings.

Returns: The attribute mappings of a project.
Return type: AttributeMappingCollection

spec()[source]¶

Returns this project’s spec.

Returns: The spec for the project.
Return type: ProjectSpec

delete()¶

Deletes this resource. Some resources do not support deletion, and will raise a 405 error if this is called.

Returns: HTTP response from the server
Return type: requests.Response

property relative_id¶

Type: str

property resource_id¶

Type: str

Project Spec¶

class tamr_unify_client.project.resource.ProjectSpec(client, data, api_path)[source]¶

A representation of the server view of a project.

static of(resource)[source]¶

Creates a project spec from a project.

Parameters: resource (Project) – The existing project.
Returns: The corresponding project spec.
Return type: ProjectSpec

static new()[source]¶

Creates a blank spec that could be used to construct a new project.

Returns: The empty spec.
Return type: ProjectSpec

from_data(data)[source]¶

Creates a spec with the same client and API path as this one, but new data.

Parameters: data (dict) – The data for the new spec.
Returns: The new spec.
Return type: ProjectSpec

to_dict()[source]¶

Returns a version of this spec that conforms to the API representation.

Returns: The spec’s dict.
Return type: dict

with_name(new_name)[source]¶

Creates a new spec with the same properties, updating name.

Parameters: new_name (str) – The new name.
Returns: The new spec.
Return type: ProjectSpec

with_description(new_description)[source]¶

Creates a new spec with the same properties, updating description.

Parameters: new_description (str) – The new description.
Returns: The new spec.
Return type: ProjectSpec

with_type(new_type)[source]¶

Creates a new spec with the same properties, updating type.

Parameters: new_type (str) – The new type.
Returns: The new spec.
Return type: ProjectSpec

with_external_id(new_external_id)[source]¶

Creates a new spec with the same properties, updating external ID.

Parameters: new_external_id (str) – The new external ID.
Returns: The new spec.
Return type: ProjectSpec

with_unified_dataset_name(new_unified_dataset_name)[source]¶

Creates a new spec with the same properties, updating unified dataset name.

Parameters: new_unified_dataset_name (str) – The new unified dataset name.
Returns: The new spec.
Return type: ProjectSpec

put()[source]¶

Commits these changes by updating the project in Tamr.

Returns: The updated project.
Return type: Project

Project Collection¶

class tamr_unify_client.project.collection.ProjectCollection(client, api_path='projects')[source]¶

Collection of Project s.

Parameters

client (Client) – Client for API call delegation.
api_path (str) – API path used to access this collection. Default: "projects".

by_resource_id(resource_id)[source]¶

Retrieve a project by resource ID.

Parameters: resource_id (str) – The resource ID. E.g. "1"
Returns: The specified project.
Return type: Project

by_relative_id(relative_id)[source]¶

Retrieve a project by relative ID.

Parameters: relative_id (str) – The resource ID. E.g. "projects/1"
Returns: The specified project.
Return type: Project

by_external_id(external_id)[source]¶

Retrieve a project by external ID.

Parameters

external_id (str) – The external ID.

Returns

The specified project, if found.

Return type

Project

Raises

KeyError – If no project with the specified external_id is found
LookupError – If multiple projects with the specified external_id are found

stream()[source]¶

Stream projects in this collection. Implicitly called when iterating over this collection.

Returns: Stream of projects.
Return type: Python generator yielding Project

Usage:

>>> for project in collection.stream(): # explicit
>>>     do_stuff(project)
>>> for project in collection: # implicit
>>>     do_stuff(project)

create(creation_spec)[source]¶

Create a Project in Tamr

Parameters: creation_spec (dict[str, str]) – Project creation specification should be formatted as specified in the Public Docs for Creating a Project.
Returns: The created Project
Return type: Project

delete_by_resource_id(resource_id)¶

Deletes a resource from this collection by resource ID.

Parameters: resource_id (str) – The resource ID of the resource that will be deleted.
Returns: HTTP response from the server.
Return type: requests.Response

Project Step¶

class tamr_unify_client.project.step.ProjectStep(client, data)[source]¶

A step of a Tamr project. This is not a BaseResource because it has no API path and cannot be directly retrieved or modified.

See https://docs.tamr.com/reference#retrieve-downstream-dataset-usage

Parameters

client (Client) – Delegate underlying API calls to this client.
data (dict) – The JSON body containing project step information.

property project_step_id¶

Type: str

property project_step_name¶

Type: str

property project_name¶

Type: str

property type¶

A Tamr project type, listed in https://docs.tamr.com/reference#create-a-project.

Type: str

project()[source]¶

Retrieves the Project this step is associated with.

Returns

This step’s project.

Return type

Project

Raises

KeyError – If no project with the specified name is found.
LookupError – If multiple projects with the specified name are found.