lariat_client package

lariat_client.lariat_client

A Python module to interact with Lariat API and perform various operations like querying indicators, fetching datasets, etc.

class lariat_client.lariat_client.Dataset(data_source: str, source_id: str, name: str, id: int, query: str, schema: Dict)

Bases: object

A class representing a dataset in Lariat.

Variables:

data_source (str) – The type of data source (e.g., ‘athena’).
source_id (str) – The unique ID of the data source.
name (str) – The name of the raw dataset.
schema (Dict) – The schema of the raw dataset.

get_indicators() → List[Indicator]

Gets the indicators that query this dataset.

Returns:: A list of the indicators that query this dataset.
Return type:: List[Indicator]

get_schema() → Dict

Gets the schema for the dataset.

Returns:: A json representation of the dataset schema.
Return type:: json

get_schema_fields() → List[Field]

Gets the schema’s fields for the dataset.

Returns:: A list of the flattened schema fields of the dataset.
Return type:: List[Field]

class lariat_client.lariat_client.Field(dataset_id: int, name: str)

Bases: object

A class representing a dataset’s field in Lariat.

Variables:

dataset_id (int) – the unique ID of a dataset.
name (str) – The name of the field.

class lariat_client.lariat_client.Filter(clauses: List[FilterClause], operator: str)

Bases: object

A class representing a filter to use when querying metrics.

Variables:

clauses (list) – A list of filter clauses to apply when querying metrics.
operator (str) – The operator to apply to the filter clauses. The options for this are [any, all]. The default operator is ‘all’. ‘any’ corresponds to an “OR”ing of the clauses, and ‘all’ corresponds to an “AND”ing of the clauses

class lariat_client.lariat_client.FilterClause(field: str, operator: str, values: str | List[str])

Bases: object

A class representing a clause to filter metrics by.

Variables:

field (str) – The field to filter on.
operator (str) – The operator to apply to the filter values. Supported operators: [in, not_in, eq, neq]
values (list or str) – A string or list of values to filter on.

class lariat_client.lariat_client.Indicator(id: int, dataset_id: int, dataset_name: str, query: str, aggregations: List[str], name: str, dimensions: List[str], tags: List[str])

Bases: object

A class representing a Lariat indicator.

Variables:

id (int) – The unique ID of the indicator.
dataset_id (int) – The unique ID of the dataset associated with the indicator.
dataset_name (str) – The name of the dataset associated with the indicator.
query (str) – The SQL query used to compute the indicator.
aggregations (List[str]) – The list of aggregation functions applied to the indicator.
name (str) – The name of the indicator.
dimensions (List[str]) – The list of dimensions used to group the indicator.
tags (List[str]) – The list of tags associated with the indicator.

get_dimension_values(dimensions: List[str] = None) → Dict[str, List[str]]

Fetches the unique values of the specified dimensions for the indicator.

Parameters:: dimensions (List[str], optional) – The list of dimensions to fetch values for. If not provided, all dimensions will be fetched.
Returns:: A dictionary with dimension names as keys and lists of unique values as values.
Return type:: Dict[str, List[str]]

class lariat_client.lariat_client.MetricRecord(evaluation_time: int, value: float, dimensions: Dict[str, str])

Bases: object

A class representing a record returned when querying metrics.

Variables:

evaluation_time (int) – The epoch timestamp associated with the indicator’s evaluation.
value (str) – The value of the metric at this evaluation time.
dimensions (dict) – A dictionary mapping of a metric’s dimensional names to values.

to_dict() → Dict[str, str]

Gets a dictionary representation of the metric record.

Returns:

A dictionary holding the evalution time, value, and: dimensions of the metric record.

Return type:

Dict[str, str]

class lariat_client.lariat_client.MetricRecordList(group_by_fields: List[str], records)

Bases: object

A class representing a collection of metric records.

A MetricRecordList is printed out as a json string by default. It can be converted to a pandas dataframe via the to_df() function and can be written out as a csv via the to_csv() function.

Variables:

group_by_fields (list) – The epoch timestamp associated with the indicator’s evaluation.
records (list) – A list of metric records returned by a query.

to_csv(filename, header=True): Writes the MetricRecord list to a csv.

to_df() → DataFrame

Converts the MetricRecord list into a pandas dataframe.

Returns:: A Dataframe consisting of the metric records returned by an indicator query.
Return type:: Pandas DataFrame

class lariat_client.lariat_client.RawDataset(source_id: str, data_source: str, name: str, schema)

Bases: object

A class representing a raw dataset in Lariat.

Variables:

source_id (str) – The unique ID of the data source.
data_source (str) – The type of data source (e.g., ‘athena’).
name (str) – The name of the raw dataset.
schema (Dict) – The schema of the raw dataset.

class lariat_client.lariat_client.RawQuery(indicator_id: int, from_ts: datetime, to_ts: datetime = None, group_by: List[str] = None, aggregate: str = None, query_filter: Filter = None, extra_args: Dict = None)

Bases: object

A class representing a RawQuery to the Lariat metrics store.

A RawQuery may be sent to the API via raw_query.send() to retrive a MetricRecordList

add_query_argument(key: str, value: str)

send() → MetricRecordList

to_json() → Dict

lariat_client.lariat_client.configure(api_key: str, application_key: str)

Configures the Lariat API credentials.

Parameters:

api_key (str) – The API key to use for authentication.
application_key (str) – The application key to use for authentication.

lariat_client.lariat_client.get_dataset(name: str, source_id: str) → Dataset | None

Gets the dataset corresponding to a given name source_id.

Parameters:

name – The name of the dataset.
source_id – The source of the dataset.

Returns:

A dataset corresponding to the given name and source.

Return type:

Union[Dataset,None]

lariat_client.lariat_client.get_datasets(name: str = None) → List[Dataset]

Gets the datasets corresponding to a given name source_id.

Parameters:: name (optional str) – The name of the dataset.
Returns:: A list of datasets belonging to the user.
Return type:: List[Dataset]

lariat_client.lariat_client.get_indicator(id: int) → Indicator

Gets the indicator corresponding to the provided id.

Parameters:: id (int) – The indicator unique identifier.
Returns:: The indicator corresponding to the provided id.
Return type:: Indicator

lariat_client.lariat_client.get_indicators(datasets: List[Dataset] = [], tags: List[str] = [], fields: List[Field] = []) → List[Indicator]

Gets the indicators corresponding to optional filters.

Parameters:

datasets (list) – A list of datasets to get corresponding indicators for.
tags (list) – A list of tags to filter the indicators by.
fields (list) – A list of fields that the indicators should include.

Returns:

A list of corresponding indicators.

Return type:

List[Indicator]

lariat_client.lariat_client.get_raw_datasets(dataset_ids: List[int]) → List[RawDataset]

Gets the raw datasets given a list of dataset ids.

Parameters:: dataset_ids (list) – A list of dataset ids to filter on.
Returns:: A list of raw datasets that the provided dataset_ids are created from.
Return type:: List[RawDataset]

lariat_client.lariat_client.query(indicator_id: int, from_ts: datetime, to_ts: datetime = None, group_by: List[str] = None, aggregate: str = None, query_filter: Filter = None) → MetricRecordList

Queries a provided indicator for its metric data,.

Parameters:

indicator (indicator_id) – Indicator id to query.
from_ts (datetime.datetime) – The start time for the indicator evaluation.
to_ts (datetime.datetime) – The end time for the indicator evaluation.
group_by (list) – A list of strings to group the metrics data by.
aggregate (str) – An optional aggregation function to apply to the metric. Options for aggregate include [“sum”,”avg”,”median”,”p75”,”p25”,”max”,”min”,”count”,”distinct”]
query_filter (filter) – A filter function to apply to the metric.

Returns:

An object that contains the list of records output by the query.

Return type:

MetricRecordList

lariat_client.lariat_client.query_streaming(indicator_id: str, from_ts: datetime, to_ts: datetime = None, group_by: List[str] = None, aggregate: str = None, query_filter: Filter = None) → MetricRecordList

Queries a provided indicator for its metric data,.

Parameters:

indicator (indicator_id) – Indicator id to query.
from_ts (datetime.datetime) – The start time for the indicator evaluation.
to_ts (datetime.datetime) – The end time for the indicator evaluation.
group_by (list) – A list of strings to group the metrics data by.
aggregate (str) – An optional aggregation function to apply to the metric. Options for aggregate include [“sum”,”avg”,”median”,”p75”,”p25”,”max”,”min”,”count”,”distinct”]
query_filter (filter) – A filter function to apply to the metric.

Returns:

An object that contains the list of records output by the query.

Return type:

MetricRecordList