Micromegas

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

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

For a remote or authenticated deployment, use micromegas.connect_with_profile("prod") instead of micromegas.connect() — it reads a named profile from ~/.micromegas/config.json and picks the auth mechanism it names (a static API key, OIDC, or none).

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)

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)

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.