fitsolver-client

A minimal, dependency-free ctypes client for the FitSolver C ABI (fitsolver_lib). JSON in, JSON out -- the same contract as fitsolver.solve(), but without needing a compiled CPython extension.

Install

As a normal dependency (portal team, deployments)

Released wheels vendor the native fitsolver_lib inside the package, so there is nothing else to build or configure:

pip install fitsolver-client

# requirements.txt / pyproject.toml
fitsolver-client>=0.2.0

One wheel is published per OS (Linux manylinux_2_28, macOS x86_64 + arm64, Windows x64); each is valid for every Python >= 3.9. See .github/workflows/wheels.yml for how they are built and published.

From a local checkout (multi-repo development)

pip install -e path/to/FantasticSolver/python/fitsolver_client \
  --config-settings editable_mode=compat

editable_mode=compat writes a plain-path .pth instead of an import hook, so editors / Pylance resolve import fitsolver_client statically. An editable install has no vendored library; it uses your local build/ (see below), so a cmake --build is picked up with no reinstall.

The shared library

Resolution order at the first solve() call:

1. FITSOLVER_LIB_PATH -- exact path to the .dll / .so / .dylib.
2. FITSOLVER_REPO_ROOT -- looked up under <root>/build/.
3. A build/ directory found by walking up from this package's location (covers pip install -e from inside a FitSolver checkout).
4. fitsolver_client/_libs/ -- the copy vendored into a release wheel.

Importing the package never fails on its own; only solve() does, with SolverUnavailableError, if none of the above resolve.

To build the library for a local checkout:

cmake -B build
cmake --build build --config Release --target fitsolver_lib

Building a wheel by hand

cmake --build build --config Release --target fitsolver_lib
python python/fitsolver_client/tools/vendor_lib.py --build-dir build
python -m build --wheel python/fitsolver_client
# optional: normalise the tag to py3-none-<platform>
python -m wheel tags --python-tag py3 --abi-tag none \
  --platform-tag win_amd64 --remove python/fitsolver_client/dist/*.whl

Releasing a new version to PyPI

PyPI versions are immutable, so a release is always a deliberate version bump + tag. Publishing is automated (.github/workflows/wheels.yml) and uses Trusted Publishing (OIDC) -- no API token. Do it whenever the native fitsolver_lib behaviour changes (the wheels vendor the compiled library) or the client code itself changes.

1. Bump the version. Edit version in python/fitsolver_client/pyproject.toml (semver: patch for a bug-fix-only lib rebuild, minor for new/changed packing behaviour, major for a breaking request/response change). Note the same version in this README's install snippet.

2. Commit it on main.

   git add python/fitsolver_client/pyproject.toml python/fitsolver_client/README.md
   git commit -m "fitsolver-client: release vX.Y.Z"
   git push origin main
   

   The push runs the wheels workflow in build-and-smoke-test-only mode (no upload) -- check it is green before tagging.

3. Tag and push the tag -- this is what publishes to PyPI.

   git tag vX.Y.Z          # tag name must match the pyproject version, with a leading v
   git push origin vX.Y.Z
   

   The tag push triggers the full matrix: per-OS wheels (Linux manylinux_2_28, macOS universal2, Windows x64) + an sdist, each smoke-tested in a clean venv, then publish-pypi uploads them.

4. Verify. pip install fitsolver-client==X.Y.Z in a fresh venv; check https://pypi.org/project/fitsolver-client/ shows the new files.

5. Bump consumers. Update fitsolver-client>=X.Y.Z in fantastic-portal/backend/pyproject.toml (and anywhere else it is pinned).

First-time setup (already done for this project)

On PyPI: Account -> Publishing -> add a pending publisher -- project fitsolver-client, owner FantasticDivision, repo Solver, workflow wheels.yml, environment pypi. Create a matching pypi environment under the GitHub repo's Settings -> Environments. No secrets are stored.

Usage

import fitsolver_client

response = fitsolver_client.solve({
    "items": [
        {"ItemCode": "ITM-001", "ItemReference": "Widget A",
         "Width": 100, "Length": 200, "Depth": 50, "Weight": 1.0},
    ],
    "boxes": [
        {"Reference": "SML", "Width": 150, "Length": 150, "Depth": 150,
         "MaxWeight": 8.5},
    ],
})

See the FitSolver README's "Request / response JSON schema" section for the exact shape of the request and response dicts.