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