caissify-pairings 0.2.0

Chess tournament pairing engines for Python — FIDE Dutch System (A.7-conformant) plus a simple casual Swiss engine for club play.

caissify-pairings

Chess tournament pairing engines for Python. Ships two engines:

• dutch — the FIDE Dutch System (C.04.3), cross-validated against the FIDE-endorsed reference bbpPairings to full A.7 conformance. Use this for rated tournaments.
• casual — a small, deterministic Swiss engine for club nights and non-rated events. Simpler, more readable, no FIDE guarantees.

Engine	Use case	FIDE A.7	Complexity
dutch	Rated / official tournaments	✅ 0 discrepancies on 70k rounds	High (full C.04.3)
casual	Club nights, ladders, non-rated events	❌ (not the goal)	Low — ~300 LOC

What you get

• A programmable pairing engine — use it as a library, call it from a web service, or wrap it in a tournament-director UI.
• TRF16 parser and writer.
• A Free Pairings Checker (FPC) — validate a TRF file against the engine.
• A Random Tournament Generator (RTG) — generate simulated tournaments for testing.
• A simple JSON-over-stdin CLI.

FIDE A.7 conformance

The FIDE Swiss Pairings Programs Commission evaluates endorsed pairing software using the A.7 test: a program is expected to produce pairings that match an already-endorsed program on at least 4990 of 5000 random tournaments (≤ 10 discrepancies).

Measured against bbpPairings (FIDE-endorsed, C++) using our Random Tournament Generator + Free Pairings Checker pipeline:

Benchmark	Rounds checked	Discrepancies	FIDE target	Result
5000 × 20-player / 9-round	45,000	0	≤ 10	✅ PASS
5000 × 10-player / 5-round	25,000	0	≤ 10	✅ PASS

See doc/ENGINE_STATUS.md for the full story and doc/DIVERGENCE_TESTING.md for the methodology.

Note. A.7 conformance is a technical criterion. caissify-pairings is not yet FIDE-endorsed — endorsement is a separate administrative process with the FIDE SPP Commission.

Installation

pip install caissify-pairings

Requires Python 3.10+. The only runtime dependency is networkx (for maximum-weight matching).

Quick start — library

from caissify_pairings import generate_pairings

players = [
    {"id": 1, "name": "Carlsen",  "score": 2.0, "rating": 2830,
     "starting_number": 1, "color_hist": ["white", "black"],
     "float_history": [], "bye_count": 0},
    {"id": 2, "name": "Firouzja", "score": 2.0, "rating": 2785,
     "starting_number": 2, "color_hist": ["black", "white"],
     "float_history": [], "bye_count": 0},
    {"id": 3, "name": "Ding",     "score": 1.5, "rating": 2780,
     "starting_number": 3, "color_hist": ["white", "black"],
     "float_history": [], "bye_count": 0},
    {"id": 4, "name": "Nepo",     "score": 1.5, "rating": 2775,
     "starting_number": 4, "color_hist": ["black", "white"],
     "float_history": [], "bye_count": 0},
]

pairings = generate_pairings(
    system="dutch",
    players=players,
    previous_pairings={(1, 3), (2, 4)},
    round_number=3,
    total_rounds=9,
)

for p in pairings:
    print(f"Table {p['table']}: {p['white_id']} vs {p['black_id']}")

Command-line usage

# Pair a round from a JSON state on stdin, write pairings to stdout
caissify-pairings < tournament_state.json

# Validate a FIDE TRF file against the Dutch engine
caissify-pairings-check tournament.trf

# Generate random tournaments for testing
caissify-pairings-rtg --players 20 --rounds 9 -n 100 -o ./output/

Input JSON schema

{
  "system": "dutch",
  "players": [
    {
      "id": 1,
      "name": "Player Name",
      "score": 0.0,
      "rating": 2400,
      "starting_number": 1,
      "color_hist": [],
      "float_history": [],
      "bye_count": 0
    }
  ],
  "previous_pairings": [[1, 3], [2, 4]],
  "round_number": 1,
  "total_rounds": 9,
  "bye_value": 1.0,
  "max_byes_per_player": 1
}

Output JSON schema

[
  {"white_id": 1, "black_id": 4, "table": 1},
  {"white_id": 3, "black_id": 2, "table": 2}
]

What works today

• FIDE Dutch System (C.04.3, Feb 2026 spec) — full A.7 conformance against bbpPairings on 20p/9r and 10p/5r benchmarks (see above).
• Casual Swiss engine — opt-in via system="casual" for club-level events where FIDE conformance is not required.
• Full TRF16 round-trip parsing/writing.
• Free Pairings Checker (FPC) for validating existing TRF files.
• Random Tournament Generator (RTG) for test corpora.
• Pure-Python, single runtime dependency (networkx).

Casual engine — quick start

from caissify_pairings import generate_pairings

pairings = generate_pairings(
    system="casual",
    players=players,
    previous_pairings=set(),
    round_number=1,
    total_rounds=5,
    bye_type="F",            # "F" full-point, "H" half-point, "U" PAB, …
    max_byes_per_player=1,   # each player gets at most one bye
)

The casual engine follows a very small rulebook:

1. Players sorted by (-score, -rating, id).
2. Round 1 uses the Dutch half-split (top half vs bottom half).
3. Later rounds pair greedily within score groups; unmatched players float down one bracket.
4. Odd fields award one bye to the lowest-scored eligible player.
5. Colours: perfect alternation > avoid a 3-in-a-row streak > minimise colour imbalance.

It never mutates your input dicts. Use dutch if you need FIDE A.7 behaviour — the two engines share the exact same input/output contract, so switching is a one-line change.

What does not work yet

Being honest up front — these are known limitations you will hit if your use-case is beyond them:

• Only Dutch and casual Swiss are implemented. No Accelerated Dutch, Burstein, Monrad, or round-robin generators yet.
• Large-tournament fixture match rates are lower against pre-recorded bbpPairings outputs for 40+ players (e.g. 40p/9r reports ~11% exact pair agreement on a handful of fixtures). The 5000-tournament A.7 conformance benchmark tops out at 20p/9r, where the engine is at 0 discrepancies; at larger scales tie-breaking divergences are expected.
• No tournament-director UI. This is an engine / library, not a standalone product.
• No FIDE endorsement. A.7 conformance is met technically; endorsement is a separate process that has not been pursued.
• API is not stabilised. Version 0.x may introduce breaking changes. API will be frozen at 1.0.0.

If any of these block you, please open an issue — priorities are driven by real user needs.

Using an engine directly

from caissify_pairings.engines.dutch import dutch_pairings

pairings = dutch_pairings(
    players=players,
    previous_pairings=set(),
    round_number=1,
    total_rounds=9,
)

Extending

New pairing systems plug in via a small registry.

from caissify_pairings.base import BasePairingEngine

class MyEngine(BasePairingEngine):
    name = "my_system"

    def generate_pairings(self) -> list[dict]:
        ...

Register it in caissify_pairings/engines/__init__.py to expose it through the top-level generate_pairings(system="my_system", ...) call.

Testing

# Fast suite (skip @slow 5000-tournament benchmarks)
pytest -m "not slow"

# Full suite including FIDE A.7 benchmarks (takes ~25 min)
pytest

Release process (maintainers)

Secrets live in a git-ignored .env at the repo root.

cp .env.example .env
# edit .env and set PYPI_API_TOKEN=pypi-...

Then, after bumping the version in pyproject.toml, updating CHANGELOG.md, committing, and tagging vX.Y.Z:

scripts/release.sh --dry-run   # build + twine check only
scripts/release.sh --test      # upload to TestPyPI
scripts/release.sh             # upload to PyPI

The script builds an sdist + wheel in an isolated venv, runs twine check, uploads to the chosen index, and then verifies by installing the published version in a throwaway venv.

Never commit .env. Rotate your PyPI token if it has ever been shared or exposed.

Acknowledgements

Cross-validated against the FIDE-endorsed reference implementations:

• bbpPairings by Bierema Boyzvoort Media Foundation — Apache-2.0.
• JaVaFo by Roberto Ricca.

Thanks to their authors for making these tools freely available.

License

MIT — see LICENSE.