prometheus-async
Async helpers for prometheus_client.
Decision gist · record as of 2026-08-14
Yes, if you run async applications and need Prometheus metrics. The package is actively maintained, has no known vulnerabilities, low install friction, and solves a real gap in the official client's async support. Skip it if you only use synchronous code or don't need Prometheus integration.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; asyncio support requires an async runtime (asyncio or Twisted).
- Low install friction with three straightforward runtime dependencies.
- Actively maintained with a recent release and ongoing commits; marked Production/Stable and supports current Python versions.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
last release 2026-03-24 (143 days) · last repo commit 2026-08-04 · 185 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 253,190 downloads/mo, #8,524 on PyPI
Alternatives
Verify before relying
pip install prometheus-async
from prometheus_client import Histogram
from prometheus_async.aio import time
import asyncio
REQ_TIME = Histogram("req_time_seconds", "time spent in requests")
@time(REQ_TIME)
async def my_handler():
await asyncio.sleep(1)
return "done"- Whether the package's metric exposure methods for synchronous applications offer concrete advantages over prometheus-client's built-in methods beyond thread-based execution.
- Performance characteristics and overhead of the async wrapper compared to direct prometheus-client usage.
What it is and what it does
prometheus-async bridges the official Prometheus Python client and async frameworks by providing decorators and helpers that work with asyncio and Twisted. It lets you instrument async code paths with Prometheus metrics—timers, histograms, counters—using the same metric objects from prometheus-client, but with async-aware wrappers that don't block event loops.
The package is most useful for async web services and event-driven applications where you need to collect metrics without introducing synchronous bottlenecks. For synchronous applications, it also offers helper functions to expose metrics in separate threads. It depends on prometheus-client for the core metric types, typing-extensions for type hints, and wrapt for function wrapping.
Use it for
- Instrument async HTTP handlers in aiohttp or FastAPI with request timing and error counters.
- Collect metrics from Twisted async applications without blocking the reactor.
- Expose Prometheus metrics endpoints in async web services using thread-safe helpers.
- Decorate async functions to automatically record execution time and call counts.
- Monitor async task queues and background job systems in event-driven architectures.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run async applications and need Prometheus metrics.
The package is actively maintained, has no known vulnerabilities, low install friction, and solves a real gap in the official client's async support. Skip it if you only use synchronous code or don't need Prometheus integration.
Install
prometheus-async on PyPI
Before you install
Low install friction with three straightforward runtime dependencies. Actively maintained with a recent release and ongoing commits; marked Production/Stable and supports current Python versions.
Requires Python 3.9 or later; asyncio support requires an async runtime (asyncio or Twisted).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install prometheus-async
from prometheus_client import Histogram
from prometheus_async.aio import time
import asyncio
REQ_TIME = Histogram("req_time_seconds", "time spent in requests")
@time(REQ_TIME)
async def my_handler():
await asyncio.sleep(1)
return "done"Verify before relying
- Whether the package's metric exposure methods for synchronous applications offer concrete advantages over prometheus-client's built-in methods beyond thread-based execution.
- Performance characteristics and overhead of the async wrapper compared to direct prometheus-client usage.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesprometheus-clienttyping-extensionswrapt |
| Maintenance | Actively maintained 143 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 253,190 / month, #8,524 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Typing :: Typed |
Evidence: prometheus_async-26.1.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “prometheus async metrics”
- prometheus-asyncAdds async/await support to Prometheus metrics collection for asyncio…
- aioprometheusA Prometheus client library for asyncio applications that collects…
- fan-toolsA collection of internal testing utilities, async helpers, and…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also prometheus-client · prometheus-client-python-speedups · py-grpc-prometheus · treq · django-prometheus · prometheus-flask-exporter · aioprometheus · prometheus-api-client · prometheus-fastapi-instrumentator · starlette-exporter