micromegas 0.26.0

Python analytics client for the Micromegas observability platform

Micromegas

Python analytics client for https://github.com/madesroches/micromegas/

📖 Complete Python API Documentation - Comprehensive guide with all methods, examples, and advanced patterns

Example usage

Query the 2 most recent log entries from the flightsql service

import datetime
import micromegas

# Connect to local server
client = micromegas.connect()
sql = """
SELECT time, process_id, level, target, msg
FROM log_entries
WHERE level <= 4
AND exe LIKE '%flight%'
ORDER BY time DESC
LIMIT 2
"""

now = datetime.datetime.now(datetime.timezone.utc)
begin = now - datetime.timedelta(minutes=2)
end = now
df = client.query(sql, begin, end)
print(df)

	time	process_id	level	target	msg
0	2024-10-03 18:17:56.087543714+00:00	1db06afc-1c88-47d1-81b3-f398c5f93616	4	acme_telemetry::trace_middleware	response status=200 OK uri=/analytics/query
1	2024-10-03 18:17:53.924037729+00:00	1db06afc-1c88-47d1-81b3-f398c5f93616	4	micromegas_analytics::lakehouse::query	query sql=
					SELECT time, process_id, level, target, msg
					FROM log_entries
					WHERE level <= 4
					AND exe LIKE '%analytics%'
					ORDER BY time DESC
					LIMIT 2

Query the 10 slowest top level spans in a trace within a specified time window

import datetime
import micromegas

client = micromegas.connect()

# First find a stream ID
end = datetime.datetime.now(datetime.timezone.utc)
begin = end - datetime.timedelta(hours=1)
streams = client.query_streams(begin, end, limit=1)

if not streams.empty:
    stream_id = streams['stream_id'].iloc[0]
    
    sql = """
    SELECT begin, end, duration, name
    FROM view_instance('thread_spans', '{}')
    WHERE depth=1
    ORDER BY duration DESC
    LIMIT 10
    """.format(stream_id)
    
    spans = client.query(sql, begin, end)
    print(spans)

	begin	end	duration	name
0	2024-10-03 18:00:59.308952900+00:00	2024-10-03 18:00:59.371890+00:00	62937100	FEngineLoop::Tick
1	2024-10-03 18:00:58.752476800+00:00	2024-10-03 18:00:58.784389+00:00	31912200	FEngineLoop::Tick
2	2024-10-03 18:00:58.701507300+00:00	2024-10-03 18:00:58.731479500+00:00	29972200	FEngineLoop::Tick
3	2024-10-03 18:00:59.766343100+00:00	2024-10-03 18:00:59.792513700+00:00	26170600	FEngineLoop::Tick
4	2024-10-03 18:00:59.282902100+00:00	2024-10-03 18:00:59.308952500+00:00	26050400	FEngineLoop::Tick
5	2024-10-03 18:00:59.816034500+00:00	2024-10-03 18:00:59.841376900+00:00	25342400	FEngineLoop::Tick
6	2024-10-03 18:00:58.897813100+00:00	2024-10-03 18:00:58.922769700+00:00	24956600	FEngineLoop::Tick
7	2024-10-03 18:00:59.860637+00:00	2024-10-03 18:00:59.885523700+00:00	24886700	FEngineLoop::Tick
8	2024-10-03 18:00:58.630051300+00:00	2024-10-03 18:00:58.654871500+00:00	24820200	FEngineLoop::Tick
9	2024-10-03 18:00:57.952279800+00:00	2024-10-03 18:00:57.977024+00:00	24744200	FEngineLoop::Tick

Quick Start

For a complete getting started guide, see the Python API Documentation.

Schema Reference

For complete schema information including all available tables, columns, and data types, see the Schema Reference.

SQL Reference

The Micromegas analytics service is built on Apache DataFusion. For SQL syntax and functions, see the Apache DataFusion SQL Reference.