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=^..^= Pounce

PyPI version Build Status Python 3.14+ License: MIT Status: Beta

Pure Python ASGI server for Python 3.14t, with a frozen config model and a low-overhead HTTP/1.1 fast path.

import pounce

pounce.run("myapp:app")

What is Pounce?

Pounce is a Python ASGI server for Python 3.14+, with a worker model designed for free-threaded Python 3.14t. It runs standard ASGI applications, supports streaming responses, and gives you a clear upgrade path from process-based servers such as Uvicorn.

Pounce's built-in HTTP/1.1 parser is optimized for the sync worker hot path, its ServerConfig object is frozen after construction, and thread-worker reloads use generational worker swaps with drain behavior.

On Python 3.14t, worker threads share one interpreter and one copy of your app. On GIL builds, Pounce falls back to multi-process workers automatically.

Why people pick it:

  • ASGI-first — Runs standard ASGI apps with CLI and programmatic entry points
  • Free-threading native — True thread parallelism with a frozen shared ServerConfig
  • Fast-path parsing — Built-in HTTP/1.1 parser for sync workers with tested smuggling and header-limit checks
  • Protocol extras — HTTP/2, HTTP/3, and WebSocket are install-gated optional paths with protocol-specific support boundaries
  • Thread-worker reloads — Rolling restart uses generational worker swap with drain behavior on supported worker modes
  • Observable surfaces — Typed lifecycle events, optional Prometheus metrics, OpenTelemetry, and Server-Timing headers
  • Optional helpers — TLS, compression, static files, middleware, rate limiting, and request queueing stay opt-in
  • Migration path — Familiar CLI for teams moving from Uvicorn-style deployments

See docs/design/core-contract.md for the supported core, optional helpers, and proof required for public claims.

Use Pounce For

  • Serving ASGI apps — Tunable workers, TLS, graceful shutdown, and deployment controls
  • Free-threaded Python deployments — Shared-memory worker threads on Python 3.14t
  • Streaming workloads — Server-sent events, streamed HTML, and token-by-token responses
  • Teams migrating from Uvicorn — Similar CLI shape with a different worker model

Framework Compatibility

Tested in CI with 48 integration tests across every major ASGI framework:

Framework Status Features Verified
FastAPI 0.135+ Full Routing, Pydantic validation, dependency injection, middleware, exception handlers, lifespan, WebSocket, streaming, OpenAPI schema
Starlette 1.0+ Full Routing, BaseHTTPMiddleware, lifespan with state, streaming, WebSocket, background tasks, exception handlers
Django 6.0+ Full Async views, URL routing, path params, JSON body, query params, middleware, error handling
Litestar 2.21+ Core Routing, dependency injection, middleware, lifespan, streaming, exception handlers. WebSocket: known routing issue

Pounce achieves compatibility through correct ASGI 3.0 implementation — no framework-specific code or workarounds.


Performance

Pounce is designed to make the pure-Python request path competitive while keeping the server core free of C extensions. In a sustained Chirp-shaped GitHub Actions snapshot, four Pounce workers completed every request at a fixed 1,000 req/s target:

Python / Pounce mode Completed req/s p99 p999 Peak RSS Errors
3.14 / processes 1,000 0.436 ms 0.721 ms 196.7 MiB 0
3.14t / threads 1,000 0.443 ms 0.521 ms 108.0 MiB 0

The thread-mode sample used about 45% less aggregate peak RSS than the process sample. These are medians from three 120-second samples on GitHub-hosted Ubuntu runners with four persistent connections, not maximum-throughput results or universal targets. The benchmark evidence notes include the uvicorn, Hypercorn, and Granian results, scheduler drops, commands, and raw artifact caveats.

Run pounce bench --workers 4 --compare to reproduce on your machine. For release or PR evidence, use python benchmarks/run_benchmark.py --repeat 5 --artifact-output results.json so the run carries the metadata required by benchmarks/artifact-schema.json and grouped variance across samples. The scheduled/release workflow adds two-minute fixed-rate p50/p99/p999 evidence for Python 3.14 process workers and Python 3.14t thread workers, with uvicorn, Hypercorn, and Granian comparisons where supported.

Key optimizations in the sync worker path:

  • Fast HTTP/1.1 parser — Direct bytes parsing is benchmarked separately from h11 and covers method validation, header size limits, duplicate Content-Length, and Content-Length/Transfer-Encoding ambiguity
  • Keep-alive connections — Connection reuse eliminates TCP handshake overhead
  • Shared socket distribution — Single accept queue for thread workers avoids macOS SO_REUSEPORT limitations

Installation

pip install bengal-pounce

Requires Python 3.14+

Optional extras:

pip install bengal-pounce[h2]     # HTTP/2 stream multiplexing
pip install bengal-pounce[ws]     # WebSocket via wsproto
pip install bengal-pounce[tls]    # TLS with truststore
pip install bengal-pounce[h3]     # HTTP/3 (QUIC/UDP, requires TLS)
pip install bengal-pounce[full]   # All protocol extras

Quick Start

Usage Command
Programmatic pounce.run("myapp:app")
CLI pounce serve --app myapp:app
Multi-worker pounce serve --app myapp:app --workers 4
TLS pounce serve --app myapp:app --ssl-certfile cert.pem --ssl-keyfile key.pem
HTTP/3 pounce serve --app myapp:app --http3 --ssl-certfile cert.pem --ssl-keyfile key.pem
Dev reload pounce serve --app myapp:app --reload
App factory pounce serve --app myapp:create_app()
Testing with TestServer(app) as server: ...

Most settings also live in pounce.toml or pyproject.toml under [tool.pounce]. Run pounce config schema --output-format toml-template for every available field.


Features

Feature Description Docs
Deployment Production workers, compression, observability, and shutdown behavior Deployment →
Migration Move from Uvicorn with similar CLI concepts Migrate from Uvicorn →
HTTP/1.1 h11 (async) + fast built-in parser (sync) HTTP/1.1 →
HTTP/2 Optional stream multiplexing via h2 HTTP/2 →
HTTP/3 Optional QUIC/UDP via bengal-zoomies, with real-socket lifecycle and benchmark proof HTTP/3 →
WebSocket Optional RFC 6455 support via wsproto; WS-over-H2 requires h2 + ws extras WebSocket →
Static Files Pre-compressed files, ETags, range requests Static Files →
Middleware ASGI3 middleware stack support Middleware →
OpenTelemetry Optional distributed tracing (OTLP) OpenTelemetry →
Lifecycle Logging Structured JSON event logging Logging →
Graceful Shutdown Mode-scoped connection draining for deploys Shutdown →
Dev Error Pages Rich tracebacks with syntax highlighting Errors →
TLS SSL with truststore integration TLS →
Compression zstd (stdlib PEP 784) + gzip + WS compression Compression →
Workers Auto-detect: threads (3.14t) or processes (GIL) Workers →
Auto Reload Graceful restart on file changes Reload →
Rate Limiting Optional per-IP token bucket with 429 responses Rate Limiting →
Request Queueing Optional bounded queue with 503 load shedding Request Queueing →
Prometheus Optional /metrics endpoint Metrics →
Sentry Optional error tracking and performance monitoring Sentry →
Introspection Opt-in /_pounce/info endpoint for live config, build, and runtime identity (loopback-only by default) Introspection →
Testing TestServer + pytest fixture for integration tests Testing →
Benchmarking Built-in pounce bench command with comparative analysis Bench →
Lifecycle Events Public API for typed connection/request events API →

📚 Full documentation: lbliii.github.io/pounce | Complete Feature List →


Usage

Programmatic Configuration — Full control from Python
import pounce

pounce.run(
    "myapp:app",
    host="0.0.0.0",
    port=8000,
    workers=4,
)
How It Works — Adaptive worker model

With workers=1, Pounce uses the direct single-worker async path. With multiple workers and worker_mode="auto", Python 3.14t resolves to sync thread workers in one shared process, while a GIL build resolves to async process workers. The supervisor detects the runtime through sys._is_gil_enabled(). Startup output and /_pounce/info expose the resolved model.

worker_mode="subinterpreter" is explicit and uses isolated async workers even when workers=1; embedded Server callers must provide an importable app_path="module:attribute".

A request flows through: socket accept -> protocol parser -> ASGI scope construction -> app(scope, receive, send) -> response serialization -> socket write. Async workers use h11; sync workers use a fast built-in parser for lower latency.

Protocol Extras — Install only what you need
Protocol Backend Install
HTTP/1.1 h11 (async) / fast built-in parser (sync) built-in
HTTP/2 h2 (stream multiplexing, priority signals) bengal-pounce[h2]
WebSocket wsproto (HTTP/1 WebSocket; WS-over-H2 also requires h2) bengal-pounce[ws]
TLS stdlib ssl + truststore bengal-pounce[tls]
HTTP/3 bengal-zoomies (QUIC/UDP) bengal-pounce[h3]
All Everything above bengal-pounce[full]

Compression uses Python 3.14's stdlib compression.zstd — zero external dependencies.

Testing — Real server for integration tests
from pounce.testing import RoundRobinTestProxy, TestServer
import httpx

def test_homepage(my_app):
    with TestServer(my_app) as server:
        resp = httpx.get(f"{server.url}/")
        assert resp.status_code == 200

The pounce_server pytest fixture is auto-registered when pounce is installed:

def test_api(pounce_server, my_app):
    server = pounce_server(my_app)
    resp = httpx.get(f"{server.url}/health")
    assert resp.status_code == 200

For multi-instance HTTP/SSE tests, run two TestServer instances behind RoundRobinTestProxy([first, second]); each new TCP connection is pinned to the next backend.


Key Ideas

  • Free-threading first. Threads, not processes. One interpreter, N event loops, and a frozen shared ServerConfig. On GIL builds, falls back to multi-process automatically.
  • Pure Python. No Rust, no C extensions in the server core. Debuggable, hackable, readable.
  • Typed end-to-end. Frozen config, typed ASGI definitions, and no new type suppressions without review.
  • Lean dependencies. Two required runtime deps: h11 for HTTP/1.1 parsing and milo-cli for the CLI. The request hot path depends only on h11; everything else is optional.
  • Observable by design. Lifecycle events are public API — from pounce import BufferedCollector, ResponseCompleted. Frameworks build dashboards on typed events, not log parsing.
  • Framework tested. Verified against FastAPI, Starlette, Django, and Litestar with 48 integration tests.
  • Optional helpers. Static files, middleware, rate limiting, request queueing, Prometheus metrics, Sentry, and OpenTelemetry are available without becoming mandatory request-path dependencies.

Documentation

📚 lbliii.github.io/pounce

Section Description
Get Started Installation and quickstart
Protocols HTTP/1.1, HTTP/2, WebSocket, HTTP/3
Configuration Server config, TLS, CLI
Deployment Workers, compression, production
Extending ASGI bridge, custom protocols
Tutorials Uvicorn migration guide
Troubleshooting Common issues and fixes
Reference API documentation
About Architecture, performance, FAQ

Development

git clone https://github.com/lbliii/pounce.git
cd pounce
uv sync --group dev
pytest

See CONTRIBUTING.md for setup, feedback loops, and recipes (how to add a test, a config field, or an error). Read AGENTS.md for the project's design philosophy and stop-and-ask escape hatches.


The Bengal Ecosystem

A structured reactive stack — every layer written in pure Python for 3.14t free-threading.

ᓚᘏᗢ Bengal Static site generator Docs
∿∿ Purr Content runtime
⌁⌁ Chirp Web framework Docs
=^..^= Pounce ASGI server ← You are here Docs
)彡 Kida Template engine Docs
ฅᨐฅ Patitas Markdown parser Docs
⌾⌾⌾ Rosettes Syntax highlighter Docs

Python-native. Free-threading ready. No npm required.


License

MIT

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=^..^= Pounce — Free-threading-native ASGI server for Python 3.14+ with real thread parallelism and streaming-first I/O

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