concurrent-c-node

JavaScript — and every npm package — from Python.

Part of Concurrent-C — a strict C11-superset preprocessor: .ccs lowers to plain C and compiles with your host C compiler. (This bridge itself is pure Python.)

import cc_node

js = cc_node.create()                # an Isolation Domain: one node child
_ = js.require('lodash')             # resolved from YOUR cwd's node_modules
_.chunk([1, 2, 3, 4, 5], 2)          # [[1, 2], [3, 4], [5]]
_.sortBy([{'n': 3}, {'n': 1}], 'n')  # dicts cross as objects, and back

semver = js.require('semver')
semver.satisfies('1.2.3', '^1.0.0')  # True

js.destroy()                         # or: with cc_node.create() as js: ...

The bridge is pure Python, stdlib only — no compiled code, no dependencies, nothing to build. The domain is a spawned node child (~28ms to first call), so you get real Node: full stdlib, native addons, whatever npm installs. Promise-based APIs look synchronous from Python, and bulk data crosses through shared memory — an 8MB array in 9ms where the same values as a JSON list take 583ms.

pip install concurrent-c-node   # needs node on PATH (or point at one)

Import stays import cc_node. The mirror of concurrent-c-python — same domain model, same materialization rules, pointed the other way:

• Values: plain data (finite numbers, strings, booleans, None, lists/dicts of the same) crosses by value; everything else is a live handle owned by the domain — attribute access is property lookup (methods arrive bound), calls are calls, str() is String(). Non-finite floats cross tagged, never silently nulled.
• The domain rules hold: handles never cross bridges; stats() is the handle ledger and release() drops one early; destroy() is idempotent, every door answers bridge is closed after, and the child dies with the bridge (and on host exit, via stdin EOF).

Async is free

A thenable result is awaited in the child before the reply, so promise-based package APIs need nothing special — no event loop on the Python side, no await:

fetchish = js.eval('async (x) => { return { doubled: x * 2 } }')
fetchish(21)                         # {'doubled': 42} — just a call

Whatever an npm package's API returns — value or promise — the call site reads the same.

Callbacks: Python functions as JS functions

A Python callable passed as an argument crosses as a JS function, and may be called back any number of times — including from inside async JS code:

mapped = js.eval('(f) => [1, 2, 3].map(f)')(lambda x, *rest: x * 10)
# [10, 20, 30] — JS conventions apply: map passes (value, index, array),
# so a lambda takes *rest.  Exceptions cross both ways, messages intact.

Nested callbacks compose (the wire alternates strictly), and a Python exception inside one surfaces as the JS error at the call site — and vice versa.

Buffers: typed arrays, shared memory

bytes, array.array, and 1-D numpy arrays cross as Float64Array / Int32Array / Uint8Array / … and come back as numpy arrays (or array.array without numpy):

import array
total = js.eval('(a) => a.reduce((s, x) => s + x, 0)')
total(array.array('d', range(1_000_000)))   # crosses via shared memory

Small buffers inline; big ones spill through shared memory — one memcpy per side, the receiver consumes the spill file, and the sender sweeps it if the child died first. Nothing strays, and nothing is silently truncated: an unsupported type is an articulate error.

Choosing the node

Same ambient-first rule as the rest of the family: the domain runs whatever node your project runs.

1. create(node='/path/to/node') from code — per-domain.
2. CC_NODE_BIN in the environment.
3. node on PATH.

And which packages it sees is the working directory's node_modules — require resolves exactly as node itself would there. Run Python in your project, get your project's packages: npm install next to your program is the whole setup.

Measured

From examples/bench_wire.py on a 4-vCPU x86-64 box, node 22 / python 3.11 (dated baselines under perf/baselines/ in the repo):

The wire is strict request/response JSON over stdio with the shared-memory spill for bulk data — the same discipline concurrent-c-python's isolated domains speak, mirrored. True pinned zero-copy leases remain future work.

A worked tour (builtin Node modules, chains, callbacks, thenables, buffers — no npm install needed): examples/use_node.py.

And when the hot path is YOUR code rather than an npm package, skip the wire entirely: a page of Concurrent-C (or C) exports as a native module for Python and Node both — 40-90ns calls, stable-ABI artifacts. See Native modules for Node and Python.