Update generated stubs

logfire-api/logfire_api/experimental/query_client.pyi

@@ -0,0 +1,89 @@
+from _typeshed import Incomplete
+from datetime import datetime
+from httpx import AsyncClient, Client, Response, Timeout
+from httpx._client import BaseClient
+from pyarrow import Table
+from types import TracebackType
+from typing import Any, Generic, TypeVar, TypedDict
+
+DEFAULT_TIMEOUT: Incomplete
+
+class QueryExecutionError(RuntimeError):
+    """Raised when the query execution fails on the server."""
+class QueryRequestError(RuntimeError):
+    """Raised when the query request is invalid."""
+
+class ColumnDetails(TypedDict):
+    """The details of a column in the row-oriented JSON-format query results."""
+    name: str
+    datatype: Any
+    bit_settings: str
+
+class ColumnData(ColumnDetails):
+    """The data of a column in the column-oriented JSON-format query results."""
+    values: list[Any]
+
+class QueryResults(TypedDict):
+    """The (column-oriented) results of a JSON-format query."""
+    columns: list[ColumnData]
+
+class RowQueryResults(TypedDict):
+    """The row-oriented results of a JSON-format query."""
+    columns: list[ColumnDetails]
+    rows: list[dict[str, Any]]
+T = TypeVar('T', bound=BaseClient)
+S = TypeVar('S', bound='LogfireQueryClient')
+R = TypeVar('R', bound='AsyncLogfireQueryClient')
+
+class _BaseLogfireQueryClient(Generic[T]):
+    base_url: Incomplete
+    read_token: Incomplete
+    timeout: Incomplete
+    client: Incomplete
+    def __init__(self, base_url: str, read_token: str, timeout: Timeout, client: type[T], **client_kwargs: Any) -> None: ...
+    def build_query_params(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None, row_oriented: bool = False) -> dict[str, str]: ...
+    def handle_response_errors(self, response: Response) -> None: ...
+
+class LogfireQueryClient(_BaseLogfireQueryClient[Client]):
+    """A synchronous client for querying Logfire data."""
+    def __init__(self, read_token: str, base_url: str = 'https://logfire-api.pydantic.dev/', timeout: Timeout = ..., **client_kwargs: Any) -> None: ...
+    def __enter__(self) -> S: ...
+    def __exit__(self, exc_type: type[BaseException] | None = None, exc_value: BaseException | None = None, traceback: TracebackType | None = None) -> None: ...
+    def query_json(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> QueryResults:
+        """Query Logfire data and return the results as a column-oriented dictionary."""
+    def query_json_rows(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> RowQueryResults:
+        """Query Logfire data and return the results as a row-oriented dictionary."""
+    def query_arrow(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> Table:
+        """Query Logfire data and return the results as a pyarrow Table.
+
+        Note that pyarrow must be installed for this method to succeed.
+
+        You can use `polars.from_arrow(result)` to convert the returned table to a polars DataFrame.
+        """
+    def query_csv(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> str:
+        """Query Logfire data and return the results as a CSV-format string.
+
+        Use `polars.read_csv(StringIO(result))` to convert the returned CSV to a polars DataFrame.
+        """
+
+class AsyncLogfireQueryClient(_BaseLogfireQueryClient[AsyncClient]):
+    """An asynchronous client for querying Logfire data."""
+    def __init__(self, read_token: str, base_url: str = 'https://logfire-api.pydantic.dev/', timeout: Timeout = ..., **async_client_kwargs: Any) -> None: ...
+    async def __aenter__(self) -> R: ...
+    async def __aexit__(self, exc_type: type[BaseException] | None = None, exc_value: BaseException | None = None, traceback: TracebackType | None = None) -> None: ...
+    async def query_json(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> QueryResults:
+        """Query Logfire data and return the results as a column-oriented dictionary."""
+    async def query_json_rows(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> RowQueryResults:
+        """Query Logfire data and return the results as a row-oriented dictionary."""
+    async def query_arrow(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> Table:
+        """Query Logfire data and return the results as a pyarrow Table.
+
+        Note that pyarrow must be installed for this method to succeed.
+
+        You can use `polars.from_arrow(result)` to convert the returned table to a polars DataFrame.
+        """
+    async def query_csv(self, sql: str, min_timestamp: datetime | None = None, max_timestamp: datetime | None = None, limit: int | None = None) -> str:
+        """Query Logfire data and return the results as a CSV-format string.
+
+        Use `polars.read_csv(StringIO(result))` to convert the returned CSV to a polars DataFrame.
+        """