dolon 0.2.0

A performance tracer application.

Read here for full documentation

Dolon

The name Dolon comes from a spy in Homer’s Iliad.

dolon is a library that interfaces with the mnemic service to trace real time data; requires Python 3.6 or later and talks to the mnemic service that must be running in an accessible host.

dolon’s recommended way to install it is to use pip:

pip install dolon

Mnemic

Mnemic refers to the ability to retain memory.

mnemic is the backend that dolon talks to and also exposes the related front end as a web page. The easiest way to install it is using docker.

docker run --name mnemic-db -e POSTGRES_PASSWORD=postgres123 -p 15432:5432 -d jpazarzis/mnemic-db
docker run --name mnemic-back-end --add-host host.docker.internal:host-gateway -p 12013:12013/udp  -e POSTGRES_CONN_STR='postgresql://postgres:postgres123@172.17.0.1:15432/mnemic' -e BACK_END_PORT='12013'  -d jpazarzis/mnemic-backend
docker run --name mnemic-front-end -e POSTGRES_CONN_STR='postgresql://postgres:postgres123@172.17.0.1:15432/mnemic'  -e FRONT_END_PORT='12111' -p 12111:12111  -d jpazarzis/mnemic-front-end

High level View

The following picture shows the components that are involved in mnemic:

The backend consists of a service that runs as a docker container. It receives messages from the application to profile and stores then in the database. It also exposes a UI client making the profiling data discoverable and visible by a browser session.

Quick Example

"""Mnemic hello_word program."""

import asyncio
import random

import tracemalloc

tracemalloc.start()

import dolon.trace_client as tc


async def tracer():
    """Plain vanilla tracer."""
    tracer_name = "hello-world"
    host = "localhost"
    port = 12013
    frequency = 1
    await tc.start_tracer(
        tracer_name,
        frequency,
        host,
        port,
        tc.mem_allocation,
        tc.active_tasks,
        tc.cpu_percent
    )


async def time_and_memory_consuming_func():
    """Allocates some memory for some time!"""
    _ = [i for i in range(10000)]
    await asyncio.sleep(random.uniform(0.1, 3))


async def main():
    """The main function to profile."""
    while 1:
        asyncio.ensure_future(time_and_memory_consuming_func())
        await asyncio.sleep(0.4)


if __name__ == '__main__':
    loop = asyncio.get_event_loop()
    asyncio.ensure_future(tracer())
    loop.run_until_complete(main())

After running the above program for several minutes the screen that we will see when accessing the UI from the browser using localhost:12111 will be similar to the following:

If we stop and restart the program then as we can see in the following picture we will see another key in the tree control under the same trace run name (hello-world in our example) which will acculate the new tracing info: