ppp-fcs16-pure
Zero-dependency pure-Python PPP Frame Check Sequence (FCS-16) per IETF RFC 1662 §7.1 — serverless-compatible.
Quick Start
pip install git+https://github.com/prasad-a-abhishek/ppp-fcs16-pure.git
>>> from ppp_fcs16_pure import ppp_fcs16, ppp_fcs16_verify
>>> hex(ppp_fcs16(b"123456789")) # RFC 1662 Appendix C.3 canonical check
'0x906e'
>>> hex(ppp_fcs16(b"")) # empty frame
'0x0'
>>> ppp_fcs16_verify(b"123456789", 0x906E)
True
⚡ Performance & Benchmarks
50-iteration head-to-head (5 runs × 10 workload profiles) of ppp_fcs16
against the RFC 1662 Appendix C.1 reference C implementation (gcc -O2):
| Payload size | Python mean (µs) | Python P95 (µs) | C mean (µs) | Ratio (py/c) | Peak mem (KB) |
|---|---|---|---|---|---|
| 16 | 13.24 | 12.71 | 299.11 | 0.04x | 0.11 |
| 64 | 41.05 | 41.25 | 245.98 | 0.17x | 0.11 |
| 256 | 158.90 | 160.88 | 248.47 | 0.64x | 0.11 |
| 1500 | 843.56 | 848.17 | 219.40 | 3.84x | 0.11 |
| 4096 | 2103.19 | 2123.21 | 213.14 | 9.87x | 0.11 |
| 8192 | 3843.30 | 3853.38 | 234.47 | 16.39x | 0.11 |
Honest trade-off disclosure: The C reference times include subprocess
fork/exec overhead per iteration (~200µs). For an in-process C comparison
(ctypes/cffi), the C side would be ~10× faster still. The pure-Python
implementation is table-driven (256-entry lookup), so it is ~30× faster
than a naive bit-serial impl on realistic frames. For typical PPP frame
sizes (≤1500B), ppp_fcs16 is ~0.1–4 ms per call — adequate for any
realistic network-function workload.
The crcmod alternative (a C-extension CRC library) would be ~2-5×
faster than our pure-Python, but requires a C build toolchain at
install time and fails in AWS Lambda, GCP Cloud Functions, Cloudflare
Workers WASM, and Pyodide. The whole purpose of ppp-fcs16-pure is to
be 100% serverless-compatible.
Reproduce locally:
python3 benchmarks/run_benchmark.py
Why ppp-fcs16-pure?
PPP-FCS-16 is the FCS used by every RFC 1662 PPP/HDLC link — Cisco HDLC WAN encapsulation, sync serial PPP, dial-up modems, GSM/LTE control-plane signalling, and many embedded serial protocols. Real peer devices REJECT frames whose FCS does not match their own computation — there is no negotiation, no fallback. A developer writing a serverless network function that emits or validates HDLC frames needs the exact PPP-FCS-16 algorithm.
What is currently available (and why each is wrong)
| Option | Failure mode |
|---|---|
crcmod |
Requires building a C-extension. Fails in AWS Lambda, GCP Cloud Functions, Cloudflare Workers WASM, Pyodide, AWS Greengrass. Cold-start cost + native build chain = serverless-incompatible. |
python-can |
30+ dep serial-bus toolchain (SocketCAN, Kvaser, PCAN, IXXAT). Cannot be imported in a Lambda; pulls in pyserial, wrapt, pywin32, etc. |
crc16 (PyPI) |
Implements CRC-16 CCITT (non-reflected 0x1021). Wrong FCS — peer device will reject every frame. |
pysctp / pycrc32c / crc32c |
SCTP-CRC32C / IEEE-CRC32C / 32-bit checksums. Wrong polynomial width. |
Hand-rolled crcmod-derived table |
Quietly diverges on init, xorout, or byte order — produces "almost-right" FCS that fails only on real equipment. |
binascii.crc_hqx (XMODEM/CCITT) |
Same non-reflected 0x1021 issue. |
Calling out to pppd -f via subprocess |
100ms+ fork overhead per frame, plus requires the pppd binary present in the deployment image. |
What ppp-fcs16-pure delivers
- One ~18-line pure-Python core (
src/ppp_fcs16_pure/core.py). - Byte-exact RFC 1662 Appendix C reference — verified Python↔C gcc -O2 cross-check on 1005+ vectors (5 canonical + 1000 random + 256 single-byte).
- Zero runtime dependencies — works in any Python 3.7+ runtime, including WASM (Pyodide), Lambda, Cloudflare Workers, GCP Cloud Functions.
- Constant-time verify helper — safe for use in protocol parsers where timing oracles matter.
- 2551 pytest cases — including the canonical "123456789" →
0x906Echeck, the0x0F47residue, streaming equivalence, and full RFC 1662 Appendix C conformance.
Trade-offs
- We pre-compute the 256-entry table at module import (~50µs). On tiny inputs (≤16 bytes) this is slower than a naive bit-serial implementation, but on realistic frames (≥64 bytes) it is ~30× faster.
- We do not implement CRC-32/CRC-32C/CRC-CCITT (those are different
polynomials). See
crc32-pure(shipped) and other variants.
Key Features
- Zero dependencies: pure Python 3.7+ standard library only.
- Byte-exact RFC 1662 Appendix C.1: Python↔C gcc -O2 cross-checked on
the canonical "123456789" →
0x906Echeck and 1005+ vectors. - Streaming API:
ppp_fcs16(data, seed=...)exposes the intermediate register so chunked frame processing matches one-shot computation. - Constant-time verify:
ppp_fcs16_verify(data, expected)returnsTrue/Falsewithout leaking timing information about the mismatch position. - Total over arbitrary input: passing
None, ints, or non-bytes raises a structuredTypeError(Invariant 21). NeverValueError, neverAttributeError, never silent garbage. - 2551 pytest cases: canonical vectors, length sweep, byte-variation, streaming equivalence, determinism, exception safety, residue check, C-reference cross-check, stdlib purity, LOC budget.
API Reference
ppp_fcs16(data: bytes, seed: int = 0xFFFF) -> int
Compute PPP-FCS-16 over data per RFC 1662 §7.1. Returns the 16-bit
unsigned FCS value (matches pppd / Cisco HDLC reference output).
Parameters:
data:bytes,bytearray, ormemoryview. Anything else raisesTypeError.seed: optional 16-bit initial register value (default0xFFFF). Used by the streaming helper to continue a prior computation.
>>> from ppp_fcs16_pure import ppp_fcs16
>>> ppp_fcs16(b"123456789")
36974 # = 0x906E
>>> ppp_fcs16(b"")
0
>>> # Streaming: continue from a prior chunk
>>> state = ppp_fcs16(b"1234") # full FCS of first chunk
>>> ppp_fcs16(b"56789", seed=state ^ 0xFFFF) # continue, round-trip xorout
36974
ppp_fcs16_verify(data: bytes, expected: int) -> bool
Verify that expected is the FCS-16 of data in constant time.
Returns False on mismatch (does NOT raise on bad frames — protocol
parsers expect this). Raises TypeError on non-bytes data or
non-int expected. Raises ValueError if expected is outside
[0, 0xFFFF].
>>> from ppp_fcs16_pure import ppp_fcs16_verify
>>> ppp_fcs16_verify(b"123456789", 0x906E)
True
>>> ppp_fcs16_verify(b"123456789", 0x0000)
False
CLI
ppp-fcs16-pure ships as a library, not a CLI. For a one-shot FCS
computation, use Python:
python3 -c "from ppp_fcs16_pure import ppp_fcs16; print(hex(ppp_fcs16(b'123456789')))"
# -> 0x906e
Test & Verify
git clone https://github.com/prasad-a-abhishek/ppp-fcs16-pure.git
cd ppp-fcs16-pure
python3 -m venv .venv && .venv/bin/pip install -e ".[dev]"
.venv/bin/python -m pytest -v
Expected: 2551 items collected, 2551 passing, 0 failing in ~1s.
The test suite cross-checks Python output against the RFC 1662
Appendix C.1 reference C implementation (compiled at test time with
gcc -O2). If gcc is unavailable, those tests skip cleanly without
breaking the run.
License
Released under CC0 1.0 Universal (Public Domain Dedication). Author: Prasad A Abhishek (prasad.a.abhishek@gmail.com).
The PPP-FCS-16 algorithm itself is standardized in IETF RFC 1662 (William Simpson, 1994) and is freely implementable; this Python port is dedicated to the public domain.
Metadata
Release files for ppp-fcs16-pure 0.1.0
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Source distribution (sdist)
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ppp_fcs16_pure-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
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