kepler 0.2.2

Fast, easy, pretty and readable program instrumentation.

Kepler

Wish you could see stuff like this about your program?

Kepler meticulously tracks your program, and creates simply and easily readable reports to help you understand what they're doing.

Kepler is not a replacement for a good profiling tool, nor is it necessarily a great production implementation tool. Kepler is designed to be that go-to tool in your toolbelt for quick and dirty measurements of your programs.

Installing Kepler

pip install kepler

Kepler in action

The first thing you should do with Kepler is annotate a function or two you want to time with @kepler.time, and then add a kepler.report() call to your amin function.

Here's the script that produced the screenshot above:

import kepler, random, time

@kepler.time("do some stuff")
def do_some_stuff():
    split = kepler.stopwatch("watch")
    for i in kepler.time("loop", range(20)):
        with kepler.time("sleep"):
            time.sleep(random.random() / 100)
        if i % 2 == 1:
            with kepler.time("overhead"):
                split("odd")
        else:
            with kepler.time("overhead"):
                split("even")

@kepler.time
def main():
    with kepler.time("sloooow"):
        time.sleep(0.3)
    do_some_stuff()

main()
kepler.report()

Roadmap

✅ Changelog

• Import and export reports as json
• Report directly from json -- try python -m kepler.report < tests/data/simple_log.json
• Testing for units, json import and export

🔜 Up next

• Track system metrics

🌈 Before 1.0

• Export traces to pandas
• Flamegraphs
• Integrate with open-telemetry
• Track and report other metrics besidings timings
• Thorough unit testing
• Docs
• Examples
• Logo