pylemetry 0.1.4

A Python metrics library

Pylemetry

Add metrics to your Python applications with Pylemetry

Currently, three meters are supported, Counter, Gauge, and Timer

Counter

The counter meter allows you to keep track of the number of times a block of code is executed. A Counter can be created either directly

from pylemetry.meters import Counter


def some_method() -> None:
    counter = Counter()

    for _ in range(100):
        counter.add()  # counter += 1 is also supported

    counter.get_count()  # 100

or via a decorator

from pylemetry import Registry
from pylemetry.decorators import count


@count()
def some_method() -> None:
    ...


@count("named_counter")
def another_method() -> None:
    ...


def main() -> None:
    for _ in range(100):
        some_method()
        another_method()

    counter = Registry().get_counter("some_method")
    counter.get_count()  # 100

    counter = Registry.get_counter("named_counter")
    counter.get_count()  # 100

When using this meter via a decorator, the meter gets added to the global Registry, with the method name it's decorating as the meter name. Alternatively, you can provide a name for the meter as a parameter to the decorator

Gauge

A Gauge meter allows you to keep track of varying metrics, e.g. memory usage or items on a queue. This meter currently isn't supported as a decorator

from pylemetry import Registry
from pylemetry.meters import Gauge


def some_method() -> None:
    gauge = Gauge()
    
    Registry().add_gauge("sample_gauge", gauge)

The Gauge supports incrementing, decrementing, and setting a value directly

from pylemetry import Registry


gauge = Registry().get_gauge("sample_gauge")

gauge.add(10)
gauge += 1.5
gauge.get_value()  # 11.5

gauge.subtract(10)
gauge -= 8.5
gauge.get_value()  # -8

gauge.set_value(7.5)
gauge.get_value()  # 7.5

Timer

A Timer meter allows for tracking the time taken for a block of code. This can be done either directly

from pylemetry.meters import Timer


def some_method() -> None:
    timer = Timer()

    for _ in range(100):
        with timer.time():
            ...

    timer.get_count()  # 100
    timer.get_mean_tick_time()  # Mean execution time of the code block

or via a decorator

from pylemetry import Registry
from pylemetry.decorators import time


@time()
def some_method() -> None:
    ...


@time("named_timer")
def another_method() -> None:
    ...


def main() -> None:
    for _ in range(100):
        some_method()
        another_method()
        
    timer = Registry().get_timer("some_method")
    timer.get_count()  # 100
    timer.get_mean_tick_time()  # Mean execution time of the some_method function
    timer.get_max_tick_time()  # Maximum execution time of the some_method function
    timer.get_min_tick_time()  # Minimum execution time of the some_method function

    timer = Registry().get_timer("named_timer")
    timer.get_count()  # 100
    ...

When using this meter via a decorator, the meter gets added to the global Registry, with the method name it's decorating as the meter name. Alternatively, you can provide a name for the meter as a parameter to the decorator

The Registry

Pylemetry maintains a global registry of meters, allowing you to share a meter across multiple files, or reference metrics from a central location. This registry is also used to keep track of all metrics created by decorators, with those meters registered using the method name they are decorating

from pylemetry import Registry
from pylemetry.meters import Counter, Gauge, Timer


counter = Counter()
gauge = Gauge()
timer = Timer()

Registry().add_counter("example", counter)
Registry().add_gauge("example", gauge)
Registry().add_timer("example", timer)

Each meter type has an add_meter, get_meter and remove_meter method to manage meters in the Registry, each requiring a unique meter name.

The Registry can be cleared through the clear() method