# This file was auto-generated by Fern from our API Definition. import typing from json.decoder import JSONDecodeError from ..core.api_error import ApiError from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper from ..core.http_response import AsyncHttpResponse, HttpResponse from ..core.request_options import RequestOptions from ..core.unchecked_base_model import construct_type from ..errors.unprocessable_entity_error import UnprocessableEntityError from ..types.breakdown_types import BreakdownTypes from ..types.http_validation_error import HttpValidationError from ..types.metric_type import MetricType from ..types.usage_aggregation_interval import UsageAggregationInterval from ..types.usage_characters_response_model import UsageCharactersResponseModel class RawUsageClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._client_wrapper = client_wrapper def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, aggregation_bucket_size: typing.Optional[int] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[UsageCharactersResponseModel]: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". aggregation_bucket_size : typing.Optional[int] Aggregation bucket size in seconds. Overrides the aggregation interval. metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[UsageCharactersResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/usage/character-stats", method="GET", params={ "start_unix": start_unix, "end_unix": end_unix, "include_workspace_metrics": include_workspace_metrics, "breakdown_type": breakdown_type, "aggregation_interval": aggregation_interval, "aggregation_bucket_size": aggregation_bucket_size, "metric": metric, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( UsageCharactersResponseModel, construct_type( type_=UsageCharactersResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) class AsyncRawUsageClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._client_wrapper = client_wrapper async def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, aggregation_bucket_size: typing.Optional[int] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[UsageCharactersResponseModel]: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". aggregation_bucket_size : typing.Optional[int] Aggregation bucket size in seconds. Overrides the aggregation interval. metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[UsageCharactersResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/usage/character-stats", method="GET", params={ "start_unix": start_unix, "end_unix": end_unix, "include_workspace_metrics": include_workspace_metrics, "breakdown_type": breakdown_type, "aggregation_interval": aggregation_interval, "aggregation_bucket_size": aggregation_bucket_size, "metric": metric, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( UsageCharactersResponseModel, construct_type( type_=UsageCharactersResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)