Documentation

Client Library Reference

This section contains Client Library classes, methods, and attributes myst-alpha 0.21.0

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function authenticate_with_service_account

authenticate_with_service_account(
    key_file_path: Optional[pathlib.Path] = None
) → None

Authenticates the global client with service account credentials.

Args:

  • key_file_path: absolute path to service account key file; if this is not given, this will look for the key file path in the MYST_APPLICATION_CREDENTIALS environment variable

function authenticate

authenticate(
    credentials: Optional[myst.auth.credentials.Credentials] = None,
    use_console: bool = False,
    use_cache: bool = True
) → None

Authenticates the global client with user credentials.

Args:

  • credentials: custom credentials to use instead of getting credentials from user account; if provided, this method will prefer these over other authentication methods
  • use_console: whether or not to use the console for the user account authorization flow
  • use_cache: whether or not to reuse cached user credentials

class Client

HTTP client for interacting with the Myst Platform API.

method Client.**init**

__init__(
    credentials: Optional[myst.auth.credentials.Credentials] = None,
    timeout: Optional[int] = None,
    api_host: Optional[str] = None
)

A wrapper object providing convenient API access with credentials.

property Client.user_agent

Gets the User-Agent header string to send to the Myst API.

method Client.authenticate

authenticate(credentials: myst.auth.credentials.Credentials) → None

Authenticates this client using the given credentials.

method Client.request

request(
    method: str,
    path: str,
    response_class: Type[~ResponseModelType],
    params: Optional[Dict[str, Any]] = None,
    request_model: Optional[~RequestModelType] = None
) → ~ResponseModelType

Executes a request for the given HTTP method and URL, handling JSON serialization and deserialization.

Args:

  • method: HTTP verb to execute, e.g. "GET", "POST", etc.
  • path: path relative to the base URL, e.g. "/time_series/"
  • response_class: name of the model class to parse the response content into
  • params: HTTP query parameters
  • request_model: JSON-able model instance to pass in request body

Raises:

  • MystClientError: client error (HTTP 4xx), including further details in the case of 422
  • MystAPIError: server error (HTTP 500) or unrecognized error
  • NotFound: client error (HTTP 404)

Returns:
parsed and validated instance of indicated response class

function get_client

get_client() → Client

Returns the global Myst client instance.

function set_client

set_client(client: myst.client.Client) → None

Sets the global Myst client instance.

Useful for e.g. configuring timeouts globally.

Args:

  • client: the client to use

class Backtest

property Backtest.state

Returns the state of the backtest from the latest backtest job.

classmethod Backtest.create

create(
    project: Union[myst.resources.project.Project, str, uuid.UUID],
    title: str,
    model: Union[myst.resources.model.Model, str, uuid.UUID],
    test_start_time: myst.core.time.time.Time,
    test_end_time: myst.core.time.time.Time,
    fit_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    fit_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    fit_reference_timing: Union[myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming],
    predict_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    predict_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    predict_reference_timing: myst.models.timing.CronTiming,
    description: Optional[str] = None
) → Backtest

Creates a new backtest.

classmethod Backtest.get

get(
    project: Union[myst.resources.project.Project, str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → Backtest

Gets a backtest by its identifier.

method Backtest.get_job

get_job() → BacktestJob

Gets the latest job associated with this backtest.

Returns:
the backtest job

Raises:

  • ValueError: if the job uuid cannot be inferred from a recent run

method Backtest.get_result

get_result() → BacktestResult

Gets the latest result associated with a job for this backtest.

Returns:
the backtest result

Raises:

  • ValueError: if the job uuid cannot be inferred from a recent run

classmethod Backtest.list

list(
    project: Union[myst.resources.project.Project, str, uuid.UUID]
) → List[ForwardRef('Backtest')]

Lists all backtests associated with this project.

method Backtest.run

run() → BacktestJob

Runs the backtest.

method Backtest.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    model: Union[myst.resources.model.Model, str, uuid.UUID, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    test_start_time: Union[myst.core.time.time.Time, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    test_end_time: Union[myst.core.time.time.Time, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_reference_timing: Union[myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_reference_timing: Union[myst.models.timing.CronTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → Backtest

Updates a new backtest.

method Backtest.wait_until_completed

wait_until_completed() → None

Returns the backtest job once it has completed.

class HPO

property HPO.state

Returns the state of the HPO from the latest HPO job.

classmethod HPO.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    title: str,
    model: Union[ForwardRef('Model'), str, uuid.UUID],
    test_start_time: myst.core.time.time.Time,
    test_end_time: myst.core.time.time.Time,
    fit_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    fit_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    fit_reference_timing: Union[myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming],
    predict_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    predict_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    predict_reference_timing: myst.models.timing.CronTiming,
    search_algorithm: myst.resources.hpo.Hyperopt,
    search_space: Dict[str, Optional[myst.resources.hpo.Uniform, myst.resources.hpo.QUniform, myst.resources.hpo.LogUniform, myst.resources.hpo.QLogUniform]],
    description: Optional[str] = None
) → HPO

Creates a new HPO.

classmethod HPO.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → HPO

Gets a HPO by its identifier.

method HPO.get_job

get_job() → HPOJob

Gets the latest job associated with this HPO.

Returns:
the HPO job

Raises:

  • ValueError: if the job uuid cannot be inferred from a recent run

method HPO.get_result

get_result() → HPOResult

Gets the latest result associated with a job for this HPO.

Returns:
the HPO result

Raises:

  • ValueError: if the job state is not SUCCESS

classmethod HPO.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID]
) → List[ForwardRef('HPO')]

Lists all HPOs associated with this project.

method HPO.run

run() → HPOJob

Runs the HPO.

method HPO.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    model: Union[myst.resources.model.Model, str, uuid.UUID, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    test_start_time: Union[myst.core.time.time.Time, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    test_end_time: Union[myst.core.time.time.Time, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    fit_reference_timing: Union[myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    predict_reference_timing: Union[myst.models.timing.CronTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    search_algorithm: Union[myst.resources.hpo.Hyperopt, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    search_space: Optional[Dict[str, Union[myst.resources.hpo.Uniform, myst.resources.hpo.QUniform, myst.resources.hpo.LogUniform, myst.resources.hpo.QLogUniform]], NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → HPO

Updates an HPO.

method HPO.wait_until_completed

wait_until_completed() → None

Returns the hpo job once it has completed.

class Model

A node that learns its parameters during a training phase, and produces output during a prediction phase.

classmethod Model.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    title: str,
    connector: myst.connectors.model_connector.ModelConnector,
    description: Optional[str] = None
) → Model

Creates a new model node.

Args:

  • project: the project in which to create the model
  • title: the title of the model
  • connector: the model connector to use in the model node
  • description: a brief description of the model

Returns:
the newly created model

method Model.create_fit_policy

create_fit_policy(
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming],
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    active: bool = True
) → ModelFitPolicy

method Model.create_input

create_input(
    time_series: Union[myst.resources.time_series.TimeSeries, str, uuid.UUID],
    group_name: str,
    output_index: int = 0,
    label_indexer: Optional[Tuple[Union[int, str, List[Any]], ...], List[Any], int, str] = None
) → ModelInput

Creates a model input into this model.

Args:

  • time_series: the time series to feed into this model
  • group_name: the name of the input group on this model's connector to which to pass the data from this input
  • output_index: which time dataset, out of the sequence of upstream time datasets, to pass to this model
  • label_indexer: the slice of the upstream data to pass to this model

Returns:
the newly created input

method Model.fit

fit(
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming]
) → ModelFitJob

Create an ad hoc model fit job for this model.

classmethod Model.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → Model

Gets a specific model by its identifier.

method Model.get_fit_result

get_fit_result(uuid: Union[str, uuid.UUID]) → ModelFitResult

method Model.get_run_result

get_run_result(
    model_result: Union[myst.resources.result.ModelRunResultMetadata, str, uuid.UUID]
) → ModelRunResult

classmethod Model.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID]
) → List[ForwardRef('Model')]

Gets all models by project.

method Model.list_fit_policies

list_fit_policies() → List[myst.resources.policy.ModelFitPolicy]

method Model.list_fit_results

list_fit_results() → List[myst.resources.result.ModelFitResult]

method Model.list_inputs

list_inputs() → List[myst.resources.input.ModelInput]

Lists all model inputs into this model.

method Model.list_run_results

list_run_results() → List[myst.resources.result.ModelRunResultMetadata]

method Model.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    connector: Union[myst.connectors.model_connector.ModelConnector, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → Model

Updates model.

class ModelFitPolicy

Describes when and over what natural time range to run a fit job on a model.

classmethod ModelFitPolicy.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    model: Union[ForwardRef('Model'), str, uuid.UUID],
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming],
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    active: bool = True
) → ModelFitPolicy

Creates a fit policy for the model.

classmethod ModelFitPolicy.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    model: Union[ForwardRef('Model'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → ModelFitPolicy

Gets a specific fit policy by its identifier.

classmethod ModelFitPolicy.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    model: Union[ForwardRef('Model'), str, uuid.UUID]
) → List[ForwardRef('ModelFitPolicy')]

Lists all fit policies for the model.

method ModelFitPolicy.update

update(
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    active: Union[bool, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → ModelFitPolicy

Updates the fit policy for the model.

class Operation

A node that performs a specified transformation on its input.

In contrast to a model, an operation has no training phase and can only be run.

classmethod Operation.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    title: str,
    connector: myst.connectors.operation_connector.OperationConnector,
    description: Optional[str] = None
) → Operation

Creates a new operation node.

Args:

  • project: the project in which to create the operation
  • title: the title of the operation
  • connector: the operation connector to use in the operation node
  • description: a brief description of the operation

Returns:
the newly created operation

method Operation.create_input

create_input(
    time_series: Union[myst.resources.time_series.TimeSeries, str, uuid.UUID],
    group_name: str,
    output_index: int = 0,
    label_indexer: Optional[Tuple[Union[int, str, List[Any]], ...], List[Any], int, str] = None
) → OperationInput

Creates an input into this operation.

Args:

  • time_series: the time series to feed into this operation
  • group_name: the name of the input group on this operation's connector to which to pass the data from this input
  • output_index: which time dataset, out of the sequence of upstream time datasets, to pass to this operation
  • label_indexer: the slice of the upstream data to pass to this operation

Returns:
the newly created input

classmethod Operation.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → Operation

Gets a specific operation by its identifier.

classmethod Operation.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID]
) → List[ForwardRef('Operation')]

Gets all operations by project.

method Operation.list_inputs

list_inputs() → List[myst.resources.input.OperationInput]

Lists all inputs into this operation.

method Operation.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    connector: Union[myst.connectors.operation_connector.OperationConnector, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → Operation

Updates operation.

class Policy

Describes when and over what natural time range to run a particular type of job for a node.

Attributes:

  • project: the identifier of the project this policy belongs to
  • creator: the identifier of the user who created this resource
  • schedule_timing: when the policy is scheduled to run, whether recurrent or once
  • active: whether this policy is currently in effect
  • node: the identifier of the node this policy applies to
  • start_timing: the beginning of the natural time range for which this policy applies, inclusive
  • end_timing: the end of the natural time range for which this policy applies, exclusive

class Project

A workspace for creating and deploying graphs of time series.

A project collects the nodes and edges of the graph along with any policies used to execute the graph.

classmethod Project.create

create(
    title: str,
    description: Optional[str] = None,
    organization_sharing_enabled: bool = False,
    organization_sharing_role: Optional[myst.models.enums.OrgSharingRole] = None
) → Project

Creates a new project.

Args:

  • title: the title of the project
  • description: a brief description of the project
  • organization_sharing_enabled: whether the project should be shared with the organization
  • organization_sharing_role: the level of sharing access to this project to give users in the organization

Returns:
the newly created project

method Project.create_model

create_model(
    title: str,
    connector: myst.connectors.model_connector.ModelConnector,
    description: Optional[str] = None
) → Model

Creates a new model node in this project.

Args:

  • title: the title of the model
  • connector: specification of the connector this model should use
  • description: a brief description of the model

Returns:
the newly created model

method Project.create_operation

create_operation(
    title: str,
    connector: myst.connectors.operation_connector.OperationConnector,
    description: Optional[str] = None
) → Operation

Creates a new operation node in this project.

Args:

  • title: the title of the operation
  • connector: specification of the connector this operation should use
  • description: a brief description of the operation

Returns:
the newly created operation

method Project.create_source

create_source(
    title: str,
    connector: myst.connectors.source_connector.SourceConnector,
    description: Optional[str] = None
) → Source

Creates a new source node in this project.

Args:

  • title: the title of the source
  • connector: specification of the connector this source should use
  • description: a brief description of the source

Returns:
the newly created source

method Project.create_time_series

create_time_series(
    title: str,
    sample_period: myst.core.time.time_delta.TimeDelta,
    cell_shape: Tuple[int, ...] = (),
    coordinate_labels: Tuple[Tuple[Union[int, str], ...], ...] = (),
    axis_labels: Tuple[Union[int, str], ...] = (),
    description: Optional[str] = None
) → TimeSeries

Creates a new time series node in this project.

Args:

  • title: the title of the time series
  • sample_period: the frequency at which the data is sampled
  • cell_shape: the shape of the data in each cell of the time series
  • coordinate_labels: the labels for each coordinate of a cell in the time series
  • axis_labels: the labels for each axis of a cell in the time series
  • description: a brief description of the time series

Returns:
the newly created time series

method Project.create_time_series_from_recipe

create_time_series_from_recipe(
    recipe: 'TimeSeriesRecipe',
    title: Optional[str] = None,
    description: Optional[str] = None
) → TimeSeries

Creates a new time series node in this project based on a provided recipe.

Args:

  • recipe: the recipe used to create the time series
  • title: the title of the time series; if none is given, the recipe will supply a sensible default
  • description: the description of the time series

Returns:
the newly created time series

method Project.delete

delete(requires_confirmation: bool = True) → Project

Deletes the project.

Args:

  • requires_confirmation: whether or not the user is required to confirm the project title

Raises:

  • ValueError: if confirmation input title is not matched

Returns:
project that has been deleted

method Project.deploy

deploy(title: str) → Deployment

Deploys the current project.

Args:

  • title: the title for the deployment

Returns:
the newly created deployment

classmethod Project.filter

filter(title: str) → List[ForwardRef('Project')]

Filters all projects visible to the user by title.

Args:

  • title: the title of the project to filter

Returns:
list of projects that have the specified title

classmethod Project.get

get(uuid: Union[str, uuid.UUID]) → Project

Gets a specific project by its identifier.

classmethod Project.list

list() → List[ForwardRef('Project')]

Lists all projects visible to the user.

method Project.list_edges

list_edges() → List[myst.resources.edge.Edge]

Lists all edges in this project.

method Project.list_nodes

list_nodes() → List[myst.resources.node.Node]

Lists all nodes in this project.

method Project.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    organization_sharing_enabled: Union[bool, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    organization_sharing_role: Union[myst.models.enums.OrgSharingRole, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → Project

Updates the project.

Could not generate markdown for object type <class 'myst.settings.Settings'>

class Source

A node which produces data without any inputs.

classmethod Source.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    title: str,
    connector: myst.connectors.source_connector.SourceConnector,
    description: Optional[str] = None
) → Source

Creates a new source node.

Args:

  • project: the project in which to create the source
  • title: the title of the source
  • connector: the source connector to use in the source node
  • description: a brief description of the source

Returns:
the newly created source

classmethod Source.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → Source

Gets a specific source by its identifier.

classmethod Source.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID]
) → List[ForwardRef('Source')]

Gets all sources by project.

method Source.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    connector: Union[myst.connectors.source_connector.SourceConnector, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → Source

Updates source.

class Time

Container for time zone-aware time objects that can be mapped from and to various third-party time objects.

method Time.**init**

__init__(value: Union[ForwardRef('Time'), datetime.datetime, str]) → None

A Time container is initialized with a datetime or an ISO 8601 formatted string.

The full ISO 8601 format specification is YYYY-MM-DDThh:mm:ssZ. The Z suffix indicates the UTC time zone.

Note that we only support ISO strings that are in UTC, to avoid possible ambiguity around daylight savings.

Args:

  • value: ISO 8601 formatted string in UTC, or time zone-aware datetime

method Time.to_datetime

to_datetime() → datetime

Returns the datetime.datetime equivalent of this time.

method Time.to_iso_string

to_iso_string() → str

Returns the ISO 8601 formatted string representation of this time.

method Time.to_pandas_timestamp

to_pandas_timestamp() → Timestamp

Returns the pandas.Timestamp equivalent of this time.

classmethod Time.validate

validate(v: Any) → Time

class TimeArray

property TimeArray.cell_shape

The shape of the data in this time array at a single timestamp.

property TimeArray.empty

Returns True if this time array is empty, False otherwise.

property TimeArray.shape

The shape of this time array, where the time axis is included as the first dimension.

classmethod TimeArray.check_axis_labels

check_axis_labels(
    axis_labels: Tuple[Union[int, str], ...],
    values: Dict[str, Any]
) → Tuple[Union[int, str], ...]

Checks that the axis labels are unique and compatible with cell shape of values.

classmethod TimeArray.check_coordinate_labels

check_coordinate_labels(
    coordinate_labels: Tuple[Tuple[Union[int, str], ...], ...],
    values: Dict[str, Any]
) → Tuple[Tuple[Union[int, str], ...], ...]

Checks that the coordinate labels are unique in each axis and compatible with cell shape of values.

classmethod TimeArray.check_length_of_data_against_index

check_length_of_data_against_index(values: Dict[str, Any]) → Dict[str, Any]

classmethod TimeArray.check_time_range_parameters

check_time_range_parameters(values: Dict[str, Any]) → Dict[str, Any]

classmethod TimeArray.fill_in_axis_labels_if_none

fill_in_axis_labels_if_none(axis_labels: Any, values: Dict[str, Any]) → Any

Returns axis labels unchanged if not None, otherwise default integer-valued coordinate labels.

classmethod TimeArray.fill_in_coordinate_labels_if_none

fill_in_coordinate_labels_if_none(
    coordinate_labels: Any,
    values: Dict[str, Any]
) → Any

Returns coordinate labels unchanged if not None, otherwise default integer-valued coordinate labels.

classmethod TimeArray.from_numpy_masked_array

from_numpy_masked_array(
    numpy_masked_array: numpy.ma.core.MaskedArray,
    sample_period: myst.core.time.time_delta.TimeDelta,
    start_time: myst.core.time.time.Time,
    end_time: myst.core.time.time.Time,
    as_of_time: myst.core.time.time.Time,
    coordinate_labels: Optional[Tuple[Tuple[Union[int, str], ...], ...]] = None,
    axis_labels: Optional[Tuple[Union[int, str], ...]] = None
) → TimeArray

Constructs a time array from a numpy.ma.MaskedArray instance.

Args:

  • numpy_masked_array: numpy masked array
  • sample_period: sample period
  • start_time: start time
  • end_time: end time
  • as_of_time: as of time
  • coordinate_labels: labels for individual coordinates
  • axis_labels: names for individual axes

Returns:
time array

classmethod TimeArray.from_pandas_data_frame

from_pandas_data_frame(
    pandas_data_frame: pandas.core.frame.DataFrame,
    as_of_time: myst.core.time.time.Time,
    mask: Optional[numpy.ndarray] = None
) → TimeArray

Constructs a time array from a pandas.DataFrame instance.

In order to use this constructor, the pandas.DataFrame instance must be indexed by a pandas.DatetimeIndex with a specified frequency which is used to define the sample_period of the TimeArray.

Additionally, the columns must be instantiated with a named pandas.Index, which is used to define the axis_labels and coordinate_labels of the TimeArray.

Args:

  • pandas_data_frame: pandas data frame
  • as_of_time: as of time
  • mask: binary array with mask

Returns:
time array

Raises:

  • ValueError: if data frame does not represent a valid time array

classmethod TimeArray.from_pandas_object

from_pandas_object(
    pandas_object: Union[pandas.core.series.Series, pandas.core.frame.DataFrame],
    as_of_time: myst.core.time.time.Time,
    mask: Optional[numpy.ndarray] = None
) → TimeArray

Constructs a time array from a pandas.Series or pandas.DataFrame instance.

In order to use this constructor, the pandas object must be indexed by a pandas.DatetimeIndex with a specified frequency which is used to define the sample_period of the TimeArray.

Additionally, if the object is a series, it must be named with an integer or string, which is used to define the coordinate_labels of the TimeArray. If the object is a data frame, the columns must be instantiated with a named pandas.Index, which is used to define the axis_labels and coordinate_labels of the TimeArray.

Args:

  • pandas_object: a pandas series or data frame
  • as_of_time: as of time
  • mask: binary array with mask

Returns:
time array

Raises:

  • ValueError: if object is neither a pandas.Series or pandas.DataFrame

classmethod TimeArray.from_pandas_series

from_pandas_series(
    pandas_series: pandas.core.series.Series,
    as_of_time: myst.core.time.time.Time,
    mask: Optional[numpy.ndarray] = None
) → TimeArray

Constructs a time array from a pandas.Series instance.

In order to use this constructor, the pandas.Series instance must be indexed by a pandas.DatetimeIndex with a specified frequency which is used to define the sample_period of the TimeArray.

Additionally, the series must be named with an integer or string, which is used to define the coordinate_labels of the TimeArray.

Args:

  • pandas_series: pandas series
  • as_of_time: as of time
  • mask: binary array with mask

Returns:
time array

method TimeArray.to_numpy_masked_array

to_numpy_masked_array() → MaskedArray

Returns the numpy.ma.MaskedArray equivalent of this time array.

method TimeArray.to_pandas_data_frame

to_pandas_data_frame(apply_mask: Optional[bool] = True) → DataFrame

Returns the pandas.DataFrame equivalent of the values in this time array.

Note that the mask of this time array will need to be extracted separately, as this method does not preserve the mask data.

Args:

  • apply_mask: whether or not to apply the internal mask before creating the data frame

Returns:
data frame

Raises:

  • ValueError: if the cells are dimensionless

method TimeArray.to_pandas_object

to_pandas_object(
    apply_mask: Optional[bool] = True
) → Union[pandas.core.series.Series, pandas.core.frame.DataFrame]

The pandas.Series or pandas.DataFrame equivalent of the values in this time array.

Note that the mask of this time array will need to be extracted separately.

Args:

  • apply_mask: whether or not to apply the internal mask before creating the pandas object

Returns:
pandas object (series or dataframe)

method TimeArray.to_pandas_series

to_pandas_series(apply_mask: Optional[bool] = True) → Series

The pandas.Series equivalent of the values in this time array.

Note that the mask of this time array will need to be extracted separately, as this method does not preserve the mask data.

Args:

  • apply_mask: whether or not to apply the internal mask before creating the series

Returns:
pandas series

Raises:

  • ValueError: if the cells are not dimensionless

class TimeDelta

Container for time delta objects that can be mapped from and to various third-party time objects.

Note that TimeDelta respects calendar arithmetic for days, weeks, months, and years. This may cause mappings to some third-party time delta objects to fail, if they don't support this paradigm (e.g. datetime.timedelta).

method TimeDelta.**init**

__init__(
    value: Union[ForwardRef('TimeDelta'), pandas._libs.tslibs.offsets.DateOffset, pandas._libs.tslibs.offsets.Day, pandas._libs.tslibs.offsets.Hour, pandas._libs.tslibs.offsets.Minute, pandas._libs.tslibs.offsets.Second, datetime.timedelta, str]
) → None

A TimeDelta container is initialized with a date offset, time delta, or ISO 8601 formatted string.

The full ISO 8601 format specification is PnYnMnDTnHnMnS.

Note that we only support integer values for all n and thus do not have support for sub-second precision.

Args:

  • value: date offset, time delta, or ISO 8601 formatted string

method TimeDelta.to_datetime_timedelta

to_datetime_timedelta() → timedelta

Returns the datetime.timedelta equivalent of this time delta.

method TimeDelta.to_iso_string

to_iso_string() → str

Returns the ISO 8601 formatted string representation of this time.

method TimeDelta.to_pandas_date_offset

to_pandas_date_offset() → DateOffset

Returns the pandas.DateOffset equivalent of this time delta.

method TimeDelta.to_pandas_frequency

to_pandas_frequency() → DateOffset

Returns the pandas frequency equivalent of this time delta.

method TimeDelta.to_pandas_timedelta

to_pandas_timedelta() → Timedelta

Returns the pandas.Timedelta equivalent of this time delta.

classmethod TimeDelta.validate

validate(v: Any) → TimeDelta

class TimeSeries

A queryable, shareable node containing fixed-frequency, arbitrarily dimensioned time series data.

A time series stitches together data from multiple layers into a single stream, by consuming data from lower- precedence layers when data from higher-precedence layers is not available, and by consuming only the upstream data that is within the time range bounds set on each layer.

In addition to queries, a time series also supports inserts, which take precedence over data flowing through the input layers.

Attributes:

  • sample_period: the frequency at which the data is sampled
  • cell_shape: the shape of the data in each cell
  • coordinate_labels: the labels for each coordinate of a cell
  • axis_labels: the labels for each axis of a cell

classmethod TimeSeries.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    title: str,
    sample_period: myst.core.time.time_delta.TimeDelta,
    cell_shape: Tuple[int, ...] = (),
    coordinate_labels: Tuple[Tuple[Union[int, str], ...], ...] = (),
    axis_labels: Tuple[Union[int, str], ...] = (),
    description: Optional[str] = None
) → TimeSeries

Creates a new time series node.

Args:

  • project: the project in which to create the time series
  • title: the title of the time series
  • sample_period: the frequency at which the data is sampled
  • cell_shape: the shape of the data in each cell of the time series
  • coordinate_labels: the labels for each coordinate of a cell in the time series
  • axis_labels: the labels for each axis of a cell in the time series
  • description: a brief description of the time series

Returns:
the newly created time series

classmethod TimeSeries.create_from_recipe

create_from_recipe(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    recipe: 'TimeSeriesRecipe',
    title: Optional[str] = None,
    description: Optional[str] = None
) → TimeSeries

Creates a new time series node based on a provided recipe.

Args:

  • project: the project in which to create the time series
  • recipe: the recipe used to create the time series
  • title: the title of the time series; if none is given, the recipe will supply a sensible default
  • description: the description of the time series

Returns:
the newly created time series

method TimeSeries.create_layer

create_layer(
    node: Union[myst.resources.node.Node, str, uuid.UUID],
    order: int,
    output_index: int = 0,
    label_indexer: Optional[Tuple[Union[int, str, List[Any]], ...], List[Any], int, str] = None,
    start_timing: Optional[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming] = None,
    end_timing: Optional[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming] = None
) → TimeSeriesLayer

Creates a layer into this time series.

Args:

  • node: the node whose data will flow into this time series
  • order: integer specifying priority of this layer when combining multiple layers; lower order implies higher precedence
  • output_index: which time dataset, out of the sequence of upstream time datasets, to pass to this time series
  • label_indexer: the slice of the upstream data to pass to this time series
  • start_timing: the beginning of the natural time range this layer should produce data for; if None, there is no restriction on the beginning of the range
  • end_timing: the end of the natural time range this layer should produce data for; if None, there is no restriction on the end of the range

Returns:
the newly created time series layer

method TimeSeries.create_run_policy

create_run_policy(
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming],
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    active: bool = True
) → TimeSeriesRunPolicy

classmethod TimeSeries.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → TimeSeries

Gets a specific time series by its identifier.

method TimeSeries.get_run_result

get_run_result(uuid: Union[str, uuid.UUID]) → TimeSeriesRunResult

method TimeSeries.insert_time_array

insert_time_array(time_array: myst.core.data.time_array.TimeArray) → None

Inserts data from a TimeArray into this time series.

The data from this manual insertion will take precedence over the other layers flowing into this time series.

Args:

  • time_array: the array of data to be inserted

classmethod TimeSeries.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID]
) → List[ForwardRef('TimeSeries')]

Gets all time series by project.

method TimeSeries.list_layers

list_layers() → List[myst.resources.layer.TimeSeriesLayer]

Lists all layers into this time series.

method TimeSeries.list_run_policies

list_run_policies() → List[myst.resources.policy.TimeSeriesRunPolicy]

method TimeSeries.list_run_results

list_run_results() → List[myst.resources.result.TimeSeriesRunResultMetadata]

method TimeSeries.query_time_array

query_time_array(
    start_time: myst.core.time.time.Time,
    end_time: myst.core.time.time.Time,
    as_of_time: Optional[myst.core.time.time.Time] = None,
    as_of_offset: Optional[myst.core.time.time_delta.TimeDelta] = None
) → TimeArray

Queries this time series for data according to the given parameters.

At most one of as_of_time and as_of_offset may be specified. If as_of_time is specified, the query will return data as of that particular time. If as_of_offset is specified, the query will return data for a constant offset between the "natural" time and the as of time. If neither is specified, the API assumes an as_of_time of now.

Args:

  • start_time: the beginning of the natural time range to query over, inclusive
  • end_time: the end of the natural time range to query over, exclusive
  • as_of_time: the precise as of time to query
  • as_of_offset: the offset from as of time to query by, where as_of_offset = natural_time - as_of_time

Returns:
a time array containing data for the specified time range and as of time

Raises:

  • ValueError: if both as_of_time and as_of_offset are specified

method TimeSeries.run

run(
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming]
) → TimeSeriesRunJob

Create an ad hoc node run job for this time series.

method TimeSeries.update

update(
    title: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    sample_period: Union[myst.core.time.time_delta.TimeDelta, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    cell_shape: Union[Tuple[int, ...], NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    coordinate_labels: Union[Tuple[Tuple[Union[int, str], ...], ...], NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    axis_labels: Union[Tuple[Union[int, str], ...], NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    description: Union[str, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → TimeSeries

Updates time series.

class TimeSeriesRunPolicy

Describes when and over what natural time range to run a fit job on a model.

classmethod TimeSeriesRunPolicy.create

create(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    time_series: Union[ForwardRef('TimeSeries'), str, uuid.UUID],
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming],
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming],
    active: bool = True
) → TimeSeriesRunPolicy

Creates a run policy for the time series.

classmethod TimeSeriesRunPolicy.get

get(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    time_series: Union[ForwardRef('TimeSeries'), str, uuid.UUID],
    uuid: Union[str, uuid.UUID]
) → TimeSeriesRunPolicy

Gets a specific run policy by its identifier.

classmethod TimeSeriesRunPolicy.list

list(
    project: Union[ForwardRef('Project'), str, uuid.UUID],
    time_series: Union[ForwardRef('TimeSeries'), str, uuid.UUID]
) → List[ForwardRef('TimeSeriesRunPolicy')]

Lists all run policies for the time series.

method TimeSeriesRunPolicy.update

update(
    schedule_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.CronTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    start_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    end_timing: Union[myst.core.time.time.Time, myst.core.time.time_delta.TimeDelta, myst.models.timing.AbsoluteTiming, myst.models.timing.RelativeTiming, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>,
    active: Union[bool, NoneType, myst.models.types.Unset] = <myst.models.types.Unset object at 0x133651160>
) → TimeSeriesRunPolicy

Updates the run policy for the time series.

Updated about 2 years ago