Source code for langchain_community.document_loaders.datadog_logs

from datetime import datetime, timedelta
from typing import List, Optional

from langchain_core.documents import Document

from langchain_community.document_loaders.base import BaseLoader


[docs]class DatadogLogsLoader(BaseLoader): """Load `Datadog` logs. Logs are written into the `page_content` and into the `metadata`. """
[docs] def __init__( self, query: str, api_key: str, app_key: str, from_time: Optional[int] = None, to_time: Optional[int] = None, limit: int = 100, ) -> None: """Initialize Datadog document loader. Requirements: - Must have datadog_api_client installed. Install with `pip install datadog_api_client`. Args: query: The query to run in Datadog. api_key: The Datadog API key. app_key: The Datadog APP key. from_time: Optional. The start of the time range to query. Supports date math and regular timestamps (milliseconds) like '1688732708951' Defaults to 20 minutes ago. to_time: Optional. The end of the time range to query. Supports date math and regular timestamps (milliseconds) like '1688732708951' Defaults to now. limit: The maximum number of logs to return. Defaults to 100. """ # noqa: E501 try: from datadog_api_client import Configuration except ImportError as ex: raise ImportError( "Could not import datadog_api_client python package. " "Please install it with `pip install datadog_api_client`." ) from ex self.query = query configuration = Configuration() configuration.api_key["apiKeyAuth"] = api_key configuration.api_key["appKeyAuth"] = app_key self.configuration = configuration self.from_time = from_time self.to_time = to_time self.limit = limit
[docs] def parse_log(self, log: dict) -> Document: """ Create Document objects from Datadog log items. """ attributes = log.get("attributes", {}) metadata = { "id": log.get("id", ""), "status": attributes.get("status"), "service": attributes.get("service", ""), "tags": attributes.get("tags", []), "timestamp": attributes.get("timestamp", ""), } message = attributes.get("message", "") inside_attributes = attributes.get("attributes", {}) content_dict = {**inside_attributes, "message": message} content = ", ".join(f"{k}: {v}" for k, v in content_dict.items()) return Document(page_content=content, metadata=metadata)
[docs] def load(self) -> List[Document]: """ Get logs from Datadog. Returns: A list of Document objects. - page_content - metadata - id - service - status - tags - timestamp """ try: from datadog_api_client import ApiClient from datadog_api_client.v2.api.logs_api import LogsApi from datadog_api_client.v2.model.logs_list_request import LogsListRequest from datadog_api_client.v2.model.logs_list_request_page import ( LogsListRequestPage, ) from datadog_api_client.v2.model.logs_query_filter import LogsQueryFilter from datadog_api_client.v2.model.logs_sort import LogsSort except ImportError as ex: raise ImportError( "Could not import datadog_api_client python package. " "Please install it with `pip install datadog_api_client`." ) from ex now = datetime.now() twenty_minutes_before = now - timedelta(minutes=20) now_timestamp = int(now.timestamp() * 1000) twenty_minutes_before_timestamp = int(twenty_minutes_before.timestamp() * 1000) _from = ( self.from_time if self.from_time is not None else twenty_minutes_before_timestamp ) body = LogsListRequest( filter=LogsQueryFilter( query=self.query, _from=_from, to=f"{self.to_time if self.to_time is not None else now_timestamp}", ), sort=LogsSort.TIMESTAMP_ASCENDING, page=LogsListRequestPage( limit=self.limit, ), ) with ApiClient(configuration=self.configuration) as api_client: api_instance = LogsApi(api_client) response = api_instance.list_logs(body=body).to_dict() docs: List[Document] = [] for row in response["data"]: docs.append(self.parse_log(row)) return docs