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-# JustAPI: a Python web framework with a Rust core — the story, the numbers, and what I actually learned
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-
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-> **Read this first.** I built JustAPI — I'm Swadhin Biswas — with agentic AI as
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-> a guide: AI helped me design, implement, debug, and document a large part of
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-> this project. I am not claiming this is the best framework in the world, and
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-> I am not claiming every number here was measured on your hardware. I am
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-> describing what I built, why I built it, what I verified, and — just as
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-> important — what I tried that did not work. The documentation site is large,
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-> much of it written with AI assistance, and not everything in it is
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-> independently verified. If you find a claim that seems wrong, it probably
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-> is. Verify it, and open an issue.
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->
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-> **What this article is:** a technical write-up. **What it is not:** marketing.
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-
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-
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-## 1. What JustAPI is
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-
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-JustAPI is a Python web framework where the web server, the router, the TLS
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-termination, the request validation, the JSON serialization, and the database
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-access all run in Rust. Your Python code handles the application logic. That is
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-the entire premise, and it is the one sentence that explains every design
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-decision in the project.
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-
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-```python
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-from justapi import JustAPIApp
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-
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-app = JustAPIApp()
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-
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-@app.get("/")
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-def hello():
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- return {"Hello": "World"}
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-
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-app.run() # a real server, not a dev server
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-```
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-
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-That is a complete program. It gives you HTTP/1.1 and HTTP/2, TLS, routing with
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-path and query parameters, JSON serialization, automatic OpenAPI docs at
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-`/docs`, and a server that does not need uvicorn or gunicorn. All of it runs in
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-Rust. The Python process just runs your handler.
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-
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-The package is on PyPI (`pip install justapi`), it works on Linux, macOS, and
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-Windows, and there are wheels for the free-threaded build of CPython 3.14t.
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-
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-
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-## 2. Why I built it (the story)
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-
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-The starting point was a simple observation that most Python web frameworks
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-treat as a given: **the framework runs in Python.** FastAPI runs on Starlette,
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-Starlette runs on uvicorn, and uvicorn is a Python event loop with a lot of
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-asyncio machinery between the socket and your handler. Robyn and Granian moved
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-the *server* to Rust, but the request still crosses into Python for routing,
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-validation, and serialization.
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-
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-I asked a different question: what if almost nothing crossed into Python?
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-What if the framework — the thing that does the same work on every request —
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-lived entirely in Rust, and Python only ran the code that is different for each
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-application?
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-
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-That question shaped a project with an unusual constraint, which I wrote down
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-early and enforced throughout: **if a feature can be implemented in Rust, it
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-must be implemented in Rust.** Not "can be implemented faster in Rust" — *can
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-be implemented in Rust*. Python in the framework is reserved for the parts that
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-have to be Python: the glue between Rust values and your handlers.
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-
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-I did not do this alone. I worked with agentic AI throughout — using it as an
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-engineering guide. I made the architecture decisions; the AI helped me turn
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-them into working code, find the bugs I could not see, write the tests, and
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-keep the project honest when I wanted to skip the boring parts. There are
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-parts of this codebase I understand completely, parts I understand well enough
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-to maintain, and parts the AI wrote that I reviewed and tested but would be
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-lying if I said I could reproduce from memory. I am not hiding that; it is
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-part of how this project exists.
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-
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-The project then went through the standard engineering motions, in order:
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-
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-1. A minimal server: tokio + hyper, a PyO3 boundary, one route. Measured
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- 766k req/s on the hello-world fixture.
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-2. A native router (matchit radix trie, 51ns average lookup on 500 routes).
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-3. A memory pipeline (per-request arena, buffer pools).
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-4. Middleware in Rust: CORS, security headers, JWT, rate limiting.
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-5. Serialization in Rust (serde_json, optional simd-json).
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-6. TLS with rustls — no OpenSSL dependency.
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-7. A native API surface, replacing the ASGI shim.
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-8. Database access via sqlx: SQLite, PostgreSQL, MySQL, DuckDB.
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-9. WebSockets, SSE, background tasks, a scheduler, a plugin system.
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-10. Operational tooling: OpenTelemetry, Prometheus metrics, health checks,
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- circuit breakers.
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-
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-None of this was fast in the sense of "one weekend." It was fast in the sense
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-of "the numbers are in the repo, the tests pass, and the failures are
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-documented."
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-
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-The release history tells part of the story on its own:
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-
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-| Version | What changed |
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-|---|---|
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-| 2.0.8 | Multi-threaded tokio server, free-threaded CPython support, async handler fix (14× async throughput) |
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-| 2.0.9 | Native async DB awaits, Rust-native SSE, type stubs, tokenless CI publishing, first PyPI release |
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-| 2.0.10 | The CLI shipped in the wheel (it was a stub before) |
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-
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-
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-## 3. The architecture
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-
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-The request path is a pipeline, and almost every stage is Rust:
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-
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-```
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-Kernel (epoll/io_uring)
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- → tokio connection manager (multi-threaded)
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- → TLS (rustls)
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- → HTTP parse (hyper)
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- → Router (matchit, ~51ns lookup)
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- → Middleware chain (auth, CORS, rate-limit, compression)
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- → Python boundary (zero-copy PyO3, GIL pool)
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- → Your Python handler
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- → Rust serializer (serde_json / simd-json)
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- → Response write → socket
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-```
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-
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-The crate layout mirrors the pipeline:
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-
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-```
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-justapi/
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-├── crates/
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-│ ├── justapi-core/ # networking, routing, middleware, serialization, DB pool
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-│ ├── justapi-py/ # PyO3 bindings + the Python package
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-│ ├── justapi-cli/ # the `justapi-cli` binary (serve, create, check, profile)
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-│ └── justapi-bench/ # benchmark harness
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-├── python/justapi/ # pip-installable package (maturin-built)
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-├── BENCHMARKS.md # append-only performance ledger
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-├── DECISIONS.md # ADR log (ADR-001 through ADR-093)
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-└── PLAN.md # roadmap with an honesty status on every phase
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-```
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-
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-The dependency graph is intentionally small:
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-
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-```
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-justapi-cli → justapi-core
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-justapi-py → justapi-core
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-justapi-bench → justapi-core
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-```
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-
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-## 4. The numbers (verified, with the hardware caveat)
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-
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-All numbers below are from `BENCHMARKS.md`, measured on a single machine with
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-100 concurrent connections and 30-second runs. **Your machine will differ.**
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-What matters is the *ratio* on the same hardware, not the absolute numbers.
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-
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-| Framework | Hello-world req/s | JSON echo req/s | p99 hello-world | RSS |
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-|---|---|---|---|---|
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-| JustAPI (native fast path) | 766k | 782k | 0.48 ms | 12 MB |
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-| Granian (ASGI) | 314k | 145k | 0.74 ms | 37 MB |
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-| Robyn | 39k | — | — | — |
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-| FastAPI + Uvicorn | 36k | 33k | 24.63 ms | 29 MB |
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-
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-The "native fast path" needs two things: a route registered with `native=True`
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-and a `Schema`. In that configuration, Rust validates the body and writes the
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-response — Python never runs. Without a schema, you get the Python handler
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-path, which is GIL-bound at roughly 60–120k req/s on this hardware, same as any
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-other Python framework.
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-
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-Other verified numbers:
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-
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-- Route lookup: 51ns average on a 500-route table.
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-- Native CRUD SELECT: 181k req/s — 125× FastAPI on the same SQLite fixture.
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-- Native async DB awaits: 320 RPS vs 6 RPS for the blocking path on a slow
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- query (a 2M-row recursive CTE) — 53×.
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-- Multi-worker prefork (`justapi serve --workers 4`): 1.88× throughput
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- (99.7k RPS vs 53k).
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-- Free-threaded CPython 3.14t, CPU-bound Python handler: 12.4× vs
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- GIL-locked — the GIL ceiling disappears.
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-
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-**What I do not claim:** there is no "beats every framework on every
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-workload" claim here. Light async handlers (no I/O, just `asyncio.sleep`) sit
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-at 4–12k req/s — the asyncio loop floor — and I measured that Granian's
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-direct loop dispatch is faster on that specific shape. I do not hide it; it is
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-in the benchmarks and in the article below.
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-
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-## 5. The async story: what I tried, and what the measurements said
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-
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-This is the most important section in this article, because it is where I
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-spent the most effort proving myself wrong.
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-
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-The initial async path was bad. An async handler doing `await
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-asyncio.sleep(0.001)` served about **808 RPS** — a hard ceiling, not
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-contention. The single GIL worker was blocking on each coroutine's full
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-duration, serializing every async request. Fixing that (ADR-083) took async
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-throughput from ~800 to **11,758 RPS** — 14× — by making completion
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-callback-driven instead of blocking.
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-
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-Then I got ambitious. The plan was: "make the awaits Rust-native." If a
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-Python coroutine's `await` could complete on tokio instead of on the asyncio
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-loop, per-await overhead would drop, and I would beat Granian on async.
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-
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-I built four approaches and measured every one:
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-
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-| Approach | Per-await overhead | Verdict |
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-|---|---|---|
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-| `future_into_py` (Rust future wrapped as an asyncio.Future) | 2× slower than `asyncio.sleep` | The wrapper + cross-runtime wakeup costs more than the loop's own timer |
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-| `into_future` (coroutine → Rust future) | tied at best | Requires a running asyncio loop for task-locals; does not decouple |
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-| Hand-rolled driver, GIL attach per await | ~1125 µs/await | Thread-state setup dominates |
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-| Hand-rolled driver, persistent thread | ~3.4 µs/await solo | **86× worse concurrent** (thread per coroutine) |
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-| asyncio loop (status quo) | ~45 µs/await | The only mechanism that scales |
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-
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-The multiplexing driver — one persistent Rust thread stepping many coroutines,
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-the design that should have worked — measured **16 µs/await vs asyncio's
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-0.56 µs/await on pure stepping** (ADR-091). The absolute floor, a bare
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-`await noop()` in asyncio, is **0.039 µs**.
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-
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-The conclusion, written into the ADR log: *the Python coroutine `send()`
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-stepping is the irreducible floor, and asyncio already runs it at the minimum
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-possible rate. Any Rust wrapper around `send()` adds overhead; it cannot
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-subtract it.* A multi-loop dispatch experiment (ADR-092) also came back
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-neutral-to-worse: the GIL worker is the single dispatch point, so extra loops
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-only added GIL contention.
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-
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-I stopped. That is the part of engineering nobody writes articles about: the
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-work you delete. The async path stays on asyncio, which is the right answer,
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-and I went back to making the *operations* native instead of the coroutine.
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-
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-## 6. Native operations: where the real win is
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-
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-Since I cannot make Python coroutines faster, I made the framework operations
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-they await faster — by taking Python out of them.
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-
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-**Native async DB awaits (`query_async`).** A normal async handler doing a
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-database query would block the asyncio loop thread for the whole query. One
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-slow Postgres query froze every other async handler on the server.
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-`await app.db.query_async(...)` runs the SQL on the DB's own multi-threaded
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-tokio runtime with the GIL released. The loop is never blocked. Measured: 53×
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-faster than the blocking path on slow queries, and it is the only path that is
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-*safe* for real databases with network latency.
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-
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-**Rust-native SSE (`sse_native`).** A stream of events is generated entirely
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-in Rust — tokio timers, an mpsc channel, the HTTP layer drains it. Zero Python
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-per event. 100k events stream instantly.
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-
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-**`@native_async`.** A marker that routes async handlers to the fastest
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-dispatch path, and on free-threaded CPython enables true parallel dispatch
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-across workers.
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-
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-The pattern is consistent: Python declares the operation, Rust executes it,
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-and nothing in the middle is Python.
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-
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-## 7. Bugs I found in my own framework (and fixed)
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-
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-The honest part of any framework article is the bug list. Some highlights:
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-
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-**Write-path collapse.** Concurrent Python-handler writes dropped to ~3 RPS at
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-11 connections (from ~150 at 10). The request-scoped auto-transaction was
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-double-acquiring pool connections — 2N for N writes. Removed. (ADR-080)
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-
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-**GIL pool not fork-safe.** A forked child inherited the parent's initialized
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-GIL pool whose worker threads did not exist, so every Python request hung and
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-returned 504s. The pool now tracks its PID and rebuilds after fork. This was
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-also the root cause of a long-standing flaky test. (ADR-081)
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-
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-**Pydantic models as `body_schema` were broken.** `validate_body` treated a
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-Pydantic model class as a plain callable and invoked
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-`BaseModel(body_dict)`, which raised `TypeError`. This broke the single most
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-important FastAPI migration path. Fixed by validating through
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-`model_json_schema()` in the Rust engine. It shipped fixed in 2.0.9.
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-
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-**`app.run()` required an address.** The README quickstart showed
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-`app.run()` with no arguments, which crashed with a `TypeError`. Now defaults
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-to `127.0.0.1:8000`.
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-
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-**The CLI in the wheel was a stub.** The PyPI package's `justapi` command
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-printed a help message and did nothing else. It shipped fixed in 2.0.10
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-(serve, create, check, openapi — and it delegates to the Rust CLI when
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-installed).
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-
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-**Unix-only APIs were not cfg-gated.** `UnixListener`-based functions failed
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-to compile on Windows. Gated with `#[cfg(unix)]`.
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-
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-Each of these is in the changelog with the commit that fixed it. None of them
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-was found by reading the code. They were found by running things, by
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-benchmarking, and by trying to use the framework the way a user would.
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-
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-## 8. What JustAPI ships that no other Python framework ships
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-
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-- **HTTP/3 (QUIC)** — feature-gated, serves Python handlers over QUIC through
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- the full native pipeline. As far as I know, the only Python framework with
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- a working HTTP/3 transport.
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-- **Free-threaded CPython wheels** (3.14t) with auto-detected parallel
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- dispatch.
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-- **Rust-native SSE** where the stream never touches Python.
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-- **Multi-worker prefork with auto-scaling** built into the CLI.
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-- **OIDC trusted publishing** — the release pipeline uses zero tokens; a tag
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- push builds 9 platform wheels and publishes them.
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-
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-## 9. The honest caveats (read this before using it)
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-
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-1. **The documentation site is large and much of it is AI-written.** I
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- generated a lot of the docs with AI assistance. I verified the code and
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- the benchmarks; I did not independently verify every sentence in every
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- doc page. If you rely on a doc page, test the behavior yourself. Some doc
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- pages were already found to describe APIs that did not exist, and I fixed
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- them as I found them. There are probably more.
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-
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-2. **The LLM/inference features are unverified.** Phases 41–52 of the roadmap
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- (inference engine, KV cache, continuous batching, OpenAI-compatible server)
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- are implemented but were never run with real GPU weights. The only honest
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- status is "implemented, not verified." They are not part of the release
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- story, and I do not make performance claims about them. (ADR-067)
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-
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-3. **The absolute numbers are from one machine.** Ratios matter; absolutes
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- depend on hardware, OS, and load generator.
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-
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-4. **The roadmap contains 17 "implemented but unverified" phases.** I mark
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- them 🟡 in PLAN.md. That is not a typo. It means: code exists, tests pass,
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- and the real-world claim is not proven.
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-
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-5. **Async light handlers are loop-bound.** If your handler is
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- `await asyncio.sleep(0.001); return {}`, JustAPI is not faster than
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- Granian. I measured it. Use the native operations for DB/SSE/IO work.
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-
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-6. **There is no 1M RPS claim here.** The roadmap phase title once said
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- "1M RPS tuning." I never measured 1M RPS. I changed the status to
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- reflect that. (The phase overclaims; I say so in PLAN.md.)
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-
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-7. **First impressions matter, and mine were rough.** The first published
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- CLI was a stub. `app.run()` crashed without an argument. The docs had
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- fabricated API references. All fixed, but if you are evaluating the
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- project, the version history is honest about the rough edges.
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-
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-## 10. How to actually use it
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-
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-```bash
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-pip install justapi==2.0.10
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-```
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-
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-```python
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-# main.py
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-from justapi import JustAPIApp, native_async
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-from pydantic import BaseModel
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-
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-app = JustAPIApp()
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-app.set_database("sqlite://app.db")
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-
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-class Item(BaseModel):
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- name: str
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-
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-@app.get("/")
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-def root():
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- return {"Hello": "World"}
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-
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-@app.get("/items/{item_id}")
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-async def get_item(item_id: int):
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- return await app.db.query_async(
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- "SELECT * FROM items WHERE id = ?", [item_id])
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-
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-@app.post("/items", body_schema=Item)
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-def create(request):
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- data = request.json()
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- return app.db.execute(
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- "INSERT INTO items (name) VALUES (?)", [data["name"]])
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-
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-# Rust-native SSE: no Python per event
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-app.sse_native("/events", count=1000, interval_ms=0)
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-
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-app.run() # defaults to 127.0.0.1:8000
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-```
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-
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-Then:
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-
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-```bash
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-python main.py
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-justapi check main.py # validate routes without serving
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-justapi serve 0.0.0.0:8080 # or use the CLI
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-```
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-
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-For the high-performance Rust CLI:
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-
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-```bash
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-cargo install justapi-cli # provides serve --workers N --reload, create, profile
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-```
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-
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-## 11. Where to verify everything in this article
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-
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-| Claim | Source |
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-|---|---|
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-| Benchmarks, methodology, hardware | `BENCHMARKS.md` in the repo |
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-| Architecture decisions (all 93) | `DECISIONS.md` — ADR-001 through ADR-093 |
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-| Roadmap status incl. unverified phases | `PLAN.md` (the honesty key is at the top) |
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-| Async experiments and their failure | ADR-090, ADR-091, ADR-092 |
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-| Native async DB awaits | ADR-093 |
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-| Bug fixes | `CHANGELOG.md` (2.0.8 → 2.0.10) |
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-| Code | https://github.com/swadhinbiswas/JustAPI |
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-| Docs | https://justapi.pages.dev |
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-
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-
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-## 12. The thing I actually learned
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-
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-The takeaway of this project is not "Rust is faster than Python." Everyone
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-knows that. The takeaway is more specific and more useful:
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-
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-**The performance of a Python web framework is decided by how much Python
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-runs per request — and the parts you cannot remove, you should not try to make
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-faster by rewriting them in Rust.**
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-
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-I tried to make asyncio faster by moving it to Rust. The measurements said
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-no. I made the operations *around* asyncio native instead, and that worked:
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-53× on slow database queries, 125× on native CRUD, zero-Python SSE. The
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-framework's job is to decide which parts of a request are yours and which are
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-the framework's — and then to make the framework's parts not run Python at
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-all.
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-
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-That, and the discipline to write down the failures, is what JustAPI is.
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-
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-There is a second lesson, specific to how I built this: **agentic AI is a
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-force multiplier, not a substitute for judgment.** The AI guided me through
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-Rust lifetimes, PyO3 FFI, and tokio internals I had never touched before. It
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-also wrote things that were wrong, and I only caught them because I
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-benchmarked, tested, and read the output. Use the tool; verify the work.
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-
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-
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-*Written by Swadhin Biswas, maintainer of JustAPI, with agentic AI as a
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-guide. Corrections welcome — open an issue at
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-https://github.com/swadhinbiswas/JustAPI/issues. If a number here disagrees
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-with your measurement, your measurement wins.*
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-Show HN: JustAPI — a Python web framework where the framework itself is Rust
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-
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-I spent months building a Python web framework where almost nothing in the
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-request path is Python. Networking, TLS, routing, validation, serialization,
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-database access — all Rust. Your handler is the only Python in the pipeline.
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-
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-Why: every Python framework treats "the framework runs in Python" as a given.
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-FastAPI sits on Starlette on uvicorn, and even Rust-served frameworks like
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-Granian cross into Python for routing and serialization. I asked what happens
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-if the framework work never crosses into Python at all.
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-
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-The measured numbers (one machine, 100 concurrent connections, 30s runs —
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-ratios matter more than absolutes):
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-
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- hello-world: 766k req/s (native fast path) vs Granian 314k, FastAPI 36k
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- JSON echo: 782k req/s vs Granian 145k, FastAPI 33k
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- route lookup: 51ns on a 500-route table
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- native CRUD SELECT: 181k req/s — 125x FastAPI on the same SQLite fixture
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- native async DB: 53x faster than the blocking path on slow queries
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- memory: 12 MB RSS vs Granian 37 MB, FastAPI 29 MB
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-
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-The part I'm most proud of is what didn't work.
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-
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-I spent real effort trying to make asyncio faster by moving it to Rust —
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-driving Python coroutines from tokio. I built four approaches and measured
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-every one. The best result was 16 microseconds per await vs asyncio's 0.56
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-microseconds on pure stepping. The absolute floor, a bare "await noop()" in
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-asyncio, is 0.039 microseconds. Python's coroutine stepping is the irreducible
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-cost, and asyncio already pays it at the minimum rate. Any Rust wrapper only
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-adds overhead. So I stopped, documented it in the ADR log (090-092), and
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-instead made the operations the coroutines await native — DB queries run on
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-Rust's tokio runtime with the GIL released, SSE streams never touch Python.
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-
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-What you get that other Python frameworks don't:
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-
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- - HTTP/3 (QUIC) through the full native pipeline (feature-gated)
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- - free-threaded CPython 3.14t wheels with auto-detected parallel dispatch
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- - Rust-native SSE — zero Python per event
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- - multi-worker prefork with auto-scaling in the CLI
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- - tokenless PyPI publishing (OIDC trusted publisher — tag push = release)
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-
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-Bugs I found in my own framework, because I benchmarked instead of assuming:
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- - concurrent Python writes collapsed to 3 RPS at 11 connections (a
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- double-acquire in request-scoped transactions)
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- - the GIL pool wasn't fork-safe — every request 504'd after a fork
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- - Pydantic models as body_schema crashed with a TypeError (broke the
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- FastAPI migration path)
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- - app.run() required an address, so the README's first example crashed
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- - the CLI shipped in the wheel was a stub; fixed in 2.0.10
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- - Unix-only code wasn't cfg-gated; Windows didn't compile
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-
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-The honest caveats, because you will find these if you try it:
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- - the docs are large and much of it is AI-written; not every page is
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- independently verified. If a doc claims something, test it.
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- - the LLM/inference features (OpenAI-compatible server, KV cache, etc.) are
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- implemented but never run with real GPU weights. No claims.
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- - light async handlers (just asyncio.sleep, no I/O) are 4-12k req/s — the
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- asyncio floor. Granian is faster on that shape. Measured, not hidden.
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- - there is no "beats everything" claim. There is a benchmark ledger and a
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- roadmap that marks 17 phases as "implemented, not verified."
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-
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-I built this with agentic AI as a guide — it helped write a lot of the code
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-and docs, and it also wrote things that were wrong, which I only caught by
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-benchmarking and testing everything myself. Treat the AI-written parts with
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-suspicion.
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-
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-If you want the real write-up (with architecture diagram and the full async
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-failure log): https://github.com/swadhinbiswas/JustAPI/blob/main/ARTICLE.md
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-
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-PyPI: https://pypi.org/project/justapi/
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-Repo: https://github.com/swadhinbiswas/JustAPI
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-Benchmark ledger: https://github.com/swadhinbiswas/JustAPI/blob/main/BENCHMARKS.md
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-ADR log (all 93 decisions, including the failures): https://github.com/swadhinbiswas/JustAPI/blob/main/DECISIONS.md
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-
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-Swadhin Biswas
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0