# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Project overview

`platz` (German: "Sitzplatzverteilung" / seating arrangement) is a genetic-algorithm-based
solver that assigns people to tables ("Tische") for an event, given group memberships, table
sizes/neighbor relationships, and a penalty scheme. It reads an XML order/guest list and INI
table layout, runs a small custom GA framework to search for a good seating, and writes the
result to text/CSV output files.

**This is Python 2 code** (print statements, `ConfigParser`, `sets.Set`, `UserList`,
`string.split`, old-style `raise Exception, "msg"`, `xrange`, `dict.has_key`,
`dict.iteritems`). It will not run under Python 3 without a 2to3-style port. There is no
`requirements.txt`, build system, test suite, or linter configured in this repo — a Python 2
interpreter with only the standard library is sufficient to run it.

## Running the program

Entry point is `libs/platz.py`, invoked via the wrapper scripts in `bin/`, which set up
environment variables and `PYTHONPATH` before calling it — the scripts never take a script
argument, they just launch `platz.py`:

- `bin/run` (bash, for Linux/macOS) — hardcodes `PLATZ=/Users/sm/develop/python/platz`
- `bin/run.bat` (Windows) — hardcodes `PLATZ=h:\develop\python\platz` and a Python 2.4 interpreter path

Both scripts set `PLATZ_CFG`, `PLATZ_LIBS`, `PLATZ_WORK` and add `PLATZ_LIBS` to
`PYTHONPATH`, then run `python $PLATZ_LIBS/platz.py`. **The hardcoded paths at the top of
these scripts must be edited to match wherever this repo is actually checked out** before
they will work.

Configuration is driven by `cfg/platz.cfg`, which points (via `$PLATZ_CFG`/`$PLATZ_WORK`
env-var expansion) to:
- `cfg/zyklus.cfg` — defines the GA run schedule ("Zyklus"): a sequence of actions
  (`e`=erzeugen/create, `s`=selektieren/select-best, `S`=random-select, `m`=mutieren/mutate,
  `j`=behalten/keep parents, `z`=neue Generation/advance generation) each with a count.
- `cfg/strafen.cfg` — the penalty ("Strafpunkte") table: cost of splitting a group across
  tables (by group size and number of splits), cost of a lone person, and per-table
  under-utilization penalties.
- A per-run working directory under `work/<name>/` (e.g. `work/test1/`, `work/test2/`)
  containing:
  - `tische.ini` — table definitions: id, `Nummer`, `Hof` (venue/court), `Plaetze` (seats),
    `Nachbarliste` (neighbor table ids), `Koordinaten`.
  - `bestellung.xml` — the guest order: `<Gruppe>` blocks containing `<Person>` (with
    `Vorname`/`Nachname`/optional `Titel`) and an `<Anzahl>` (reservation count per person
    template — this expands into that many identical bookings), plus optional `<Tisch>` to
    pin a VIP group to a specific table.
  - Output: `TischePersonen.txt` (table → seated people) and `PersonenTische.csv`
    (person → table, sorted).

## Architecture

Two library modules under `libs/`, imported via `PYTHONPATH=$PLATZ_LIBS`:

### `ga.py` — generic genetic-algorithm scaffolding
Domain-agnostic and reusable in principle:
- `Loesung` ("Solution") — base class for anything bred/mutated/selected by the GA. Meant to
  be subclassed; `Sitzplatzverteilung` in `Strukturdaten.py` is the concrete solution type
  used here.
- `Zyklus` ("Cycle") — parses `Abfolge`/`Anzahl` strings (from `zyklus.cfg`) into the ordered
  list of GA actions and their counts for one run.
- `Farm` — owns the population (`Pool`/`PoolNeu`), and executes a `Zyklus` action-by-action
  against instances of a given solution class (passed as `Klasse` plus its constructor
  args/kwargs). `Bester()` returns the fittest (`max()`) solution found; solutions are ordered
  via `__cmp__` on `self.value`.

### `Strukturdaten.py` — domain model for this specific seating problem
- `Person`, `Gruppe` (group — a `Set` of people, splittable via `teilen()`), `Tisch` (table —
  a `Gruppe` subclass with a seat capacity and neighbor-table ids).
- Container/index classes: `Personen`, `Gruppen`, `Tische`, and `Plaetze` ("Seats") which
  indexes tables by how many free seats they currently have, to answer "give me a table with
  at least N free seats" or "give me two neighboring tables that together fit two groups of
  given sizes" efficiently during placement/mutation.
- `Strafliste` ("Penalty list") — loads `strafen.cfg` and computes penalty points for: splitting
  a group (`gibPunkte('Trennung', ...)`, recursing to smaller group sizes if no exact rule is
  configured), a person sitting with no group-mate at their table (`'allein'`), a person having
  no group-mate at a *neighboring* table (`'nichtNachbar'`), and poor seat utilization at a
  table (`'Tischbesetzung'`).
- `Sitzplatzverteilung` ("Seating arrangement") — the actual `Loesung` subclass bred by the GA.
  Constructor seats VIPs first at pinned tables, then randomly seats groups either
  largest-first or smallest-first (coin flip), splitting a group across two neighboring tables
  when no single table has enough free seats, recursively splitting further if needed, then
  calls `bewerten()` to score the arrangement per `Strafliste`. `mutieren()` picks the
  worst-scoring groups (`SchlechteGruppenTopX`), evicts them, and reseats them, hoping for a
  better score. `speichern()` writes the two output files.
- `XMLConfig` — parses `bestellung.xml` into `Personen`/`Gruppen`/VIP-group/VIP-seat-map,
  expanding each `<Person>` template by its sibling `<Anzahl>` into that many individual
  bookings, and treating any `<Gruppe>` containing a `<Tisch>` tag as a VIP group pinned to
  that table rather than going through normal GA placement.

### Data flow through `platz.py` (`__main__`)
1. Read `platz.cfg` to locate the other config/data files (env-var expansion via
   `os.path.expandvars`).
2. Load `Zyklus` (GA schedule), `Strafliste` (penalties), `Tische` (table layout).
3. Load `bestellung.xml` via `XMLConfig` → people, groups, VIP group, VIP seat map.
4. Build a `Farm(Zyklus, Sitzplatzverteilung, Tische=..., Gruppen=..., Strafen=...,
   VIPListe=..., VIPs=...)`, which runs the whole GA cycle in its constructor.
5. Take `Farm.Bester()` and call `.speichern(...)` to write the output files.

Both `libs/platz.py` and `libs/Strukturdaten.py` also have self-test code under
`if __name__ == '__main__':` that exercises the classes directly with hardcoded sample data —
useful as a reference for how the classes are meant to be constructed and used.