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impulse_query_engine.analyze.metadata.time_series_expression

TimeSeriesSelector​

class TimeSeriesSelector(TimeSeriesExpression, RequiresDeserialization)

__init__​

def __init__(expr, uses_alias: bool = False)

Initialize a TimeSeriesSelector.

Arguments:

  • expr (TagExpression): Tag expression to select.

dtype​

def dtype()

Returns the Spark data type.

Returns:

pyspark.sql.types.DataType: Data type (BinaryType).

deserialize​

def deserialize(d)

Deserialize sample series after collection/toPandas.

Arguments:

  • d (Any): Data to deserialize.

Returns:

SampleSeries: Deserialized sample series.

build​

def build(cache: SeriesCache) -> SampleSeries

Instantiate a SampleSeries from given cache data.

Arguments:

  • cache (SeriesCache): Cache containing time series data.

Returns:

SampleSeries: Built sample series.

get_required_tag_exprs​

def get_required_tag_exprs() -> set[TagExpression]

Get required tag expressions.

Returns:

set of TagExpression: Required tag expressions.

required_tags​

def required_tags() -> set[str]

Get required tag keys.

Returns:

set of str: Required tag keys.

get_selector_expr​

def get_selector_expr()

Get selector expression.

Returns:

Any: Selector expression.

with_alias​

def with_alias(*args)

Create an alias selector.

Arguments:

  • *args: Aliases to use.

Returns:

TimeSeriesAliasSelector: Alias selector.

__str__​

def __str__()

String representation.

Returns:

str: String representation.

as_dict​

def as_dict() -> dict[str, Any]

Dictionary representation.

Returns:

dict: Dictionary representation.

from_dict​

def from_dict(obj: dict)

Construct from dictionary.

Arguments:

  • obj (dict): Dictionary containing selector data.

Returns:

TimeSeriesSelector: Selector instance.

TimeSeriesAliasSelector​

class TimeSeriesAliasSelector(TimeSeriesExpression)

__init__​

def __init__(*aliases)

Initialize a TimeSeriesAliasSelector.

Arguments:

  • *aliases (TimeSeriesSelector): Aliases to select.

dtype​

def dtype()

Returns the Spark data type.

Returns:

pyspark.sql.types.DataType: Data type (BinaryType).

build​

def build(cache: SeriesCache) -> SampleSeries

Build the time series from cache.

Arguments:

  • cache (SeriesCache): Cache containing time series data.

Returns:

SampleSeries: Built sample series.

get_required_tag_exprs​

def get_required_tag_exprs() -> set[TagExpression]

Get required tag expressions.

Returns:

set of TagExpression: Required tag expressions.

required_tags​

def required_tags() -> set[str]

Get required tag keys.

Returns:

set of str: Required tag keys.

get_selector_expr​

def get_selector_expr()

Get selector expression.

Returns:

Any: Selector expression.

__str__​

def __str__()

String representation.

Returns:

str: String representation.

TimeSeriesOp​

class TimeSeriesOp(TimeSeriesExpression)

__init__​

def __init__(operation, optype, *args, **kwargs)

Initialize a TimeSeriesOp.

Arguments:

  • operation (callable): The operation to apply.
  • optype (str): Type of operation.
  • *args: Arguments (like (TimeSeriesSelector<TagOp<eq(TagSelector<channel_name>,Vehicle Speed Sensor)>>, 1)) for the operation.
  • **kwargs: Keyword arguments for the operation.

get_required_tag_exprs​

def get_required_tag_exprs() -> set[TagExpression]

Get required tag expressions.

Returns:

set of TagExpression: Required tag expressions.

required_tags​

def required_tags() -> set[str]

Get required tag keys.

Returns:

set of str: Required tag keys.

get_selector_expr​

def get_selector_expr()

Get selector expression.

Returns:

Any: Selector expression.

build​

def build(cache: SeriesCache)

Build the time series from cache.

Arguments:

  • cache (SeriesCache): Cache containing time series data.

Returns:

Any: Built time series object.

__str__​

def __str__()

String representation.

Returns:

str: String representation.

as_dict​

def as_dict() -> dict[str, Any]

Dictionary representation.

Returns:

dict: Dictionary representation.

from_dict​

def from_dict(obj)

Construct from dictionary.

Arguments:

  • obj (dict): Dictionary containing operation data.

Returns:

TimeSeriesOp: Operation instance.

TimeSeriesUDF​

class TimeSeriesUDF(TimeSeriesOp)

__init__​

def __init__(func, *args, **kwargs)

Initialize a TimeSeriesUDF.

Arguments:

  • func (callable): The user-defined function to apply.
  • *args: Arguments for the UDF.
  • **kwargs: Keyword arguments for the UDF.

build​

def build(cache: SeriesCache)

Build the time series from cache using the UDF.

Arguments:

  • cache (SeriesCache): Cache containing time series data.

Returns:

Any: Result of applying the UDF to the built arguments.

__str__​

def __str__()

Return the string representation of the TimeSeriesUDF.

Returns:

str: String representation.

CallableTimeSeriesExpression​

class CallableTimeSeriesExpression()

__init__​

def __init__(func)

Initialize a CallableTimeSeriesExpression.

Arguments:

  • func (callable): Function to wrap.

__call__​

def __call__(*args, **kwargs)

Create a TimeSeriesUDF with the wrapped function.

Arguments:

  • *args: Arguments for the function.
  • **kwargs: Keyword arguments for the function.

Returns:

TimeSeriesUDF: UDF-wrapped expression.