magisch-corvee-script/magisch_corvee_script.py

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#! /usr/bin/env nix-shell
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#!nix-shell -i python3 -p python3 python3Packages.pyyaml -I nixpkgs=flake:nixpkgs
# pip install pyyaml pyscipopt pyright
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import sys
import yaml
import re
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import argparse
from collections import OrderedDict, defaultdict
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from pyscipopt import Model, quicksum
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from typing import Any, Tuple, TypeVar
from dataclasses import dataclass, field
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conf = yaml.safe_load(open('config.yaml', 'r'))
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DEFAULT_CONFIG = {
"max_load_person": 6
}
config = DEFAULT_CONFIG | conf['config']
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config['ignore'].append('')
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QUADRATIC = False
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@dataclass
class TaskConfig:
personen: list[str]
workload: int
req: list[int]
name: str
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hardcode: list[str] | None = None
lookup: list[str] = field(default_factory=list)
tasks: dict[str, TaskConfig] = OrderedDict({k: TaskConfig(**({"name": k} | t)) for k, t in conf['tasks'].items()})
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X = TypeVar("X")
def index(x: dict[X, Any]) -> dict[X, int]:
return {v: k for k, v in enumerate(x)}
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daily_workloads = \
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[sum(task.workload * task.req[d] for task in tasks.values()) for d in range(config['days'])]
ALL_DAYS: set[int] = set(range(config['days']))
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class Person(object):
def __init__(self, name: str, conf={"dagen":ALL_DAYS}):
self.name = name
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self.can: set[str] = set()
self.loves: set[str] = set()
self.hates: set[str] = set()
self.does: set[Tuple[int, str]] = set() # hardcoded
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self.has_prefs = False
self.conf = conf
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self.conf['dagen'] = set(conf['dagen'])
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def vrolijkheid(self):
res = config['days'] - len(self.does)
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for (_,t) in self.does:
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if t in self.loves:
res += config['weights']['likes']
if t in self.hates:
res -= config['weights']['hates']
return res
def workload(self, tasks):
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return sum(tasks[t].workload for (_,t) in self.does)
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def cost(self, num_people):
return round(sum((daily_workloads[d] for d in self.conf['dagen'])) / num_people)
# probabilistic round: int(math.floor(x + random.random()))
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def read_people(conf_ppl) -> dict[str, Person]:
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people = OrderedDict()
for x in conf_ppl:
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val = {"dagen": ALL_DAYS}
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if isinstance(x, dict):
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x,val = x.popitem()
people[x.lower()] = Person(x, val)
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return people
# deal with loves/hates
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def make_task_lut(tasks: dict[str, TaskConfig]):
task_lut = defaultdict(set)
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for t, taskconf in tasks.items():
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for lookup in taskconf.lookup:
task_lut[lookup] |= {t.lower()}
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task_re = re.compile(config['task_re'])
def lookup_tasks(tasks):
return set.union(*(task_lut[x.strip()] for x in task_re.split(tasks) if x not in config['ignore']))
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return lookup_tasks
def read_prefs(pref_file, tasks, people):
lookup_tasks = make_task_lut(tasks)
# read the wiki corvee table
for [name, loves, hates] in ((q.strip().lower() for q in x.split('\t')) for x in pref_file):
p = people[name]
p.has_prefs = True
p.loves |= set(lookup_tasks(loves))
p.hates |= set(lookup_tasks(hates))
for name, p in people.items():
if not p.has_prefs:
print("warning: no preferences for", name, file=sys.stderr)
# deal with capability and hardcode
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def set_capabilities(tasks: dict[str, TaskConfig], people: dict[str, Person]):
for (task,conf) in tasks.items():
if conf.personen == 'iedereen':
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for p in people.values():
p.can.add(task)
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elif conf.personen == 'liefhebbers':
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for p in people.values():
if task in p.loves:
p.can.add(task)
else:
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for p in conf.personen:
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people[p.lower()].can.add(task)
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if conf.hardcode is not None:
for day, pers in enumerate(conf.hardcode):
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people[pers.lower()].does.add((day, task))
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def write_tasks(people, tasks, file=sys.stdout):
for name, p in people.items():
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days = [[] for i in range(config['days'])]
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for (d,t) in p.does:
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days[d].append((t, t in p.loves, t in p.hates))
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def q(w):
return ",".join([t + (" <3" if love else "") + (" :(" if hate else "") for (t,love,hate) in w])
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days_fmt = " {} ||" * len(days)
days_filled = days_fmt.format(*map(q, days))
print("| {} ||{} {} || {}".format(name, days_filled, p.vrolijkheid(), p.workload(tasks)), file=file)
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print("|-")
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def scipsol(people: dict[str, Person], tasks: dict[str, TaskConfig]):
max_loads: dict[Tuple[str, int], int] = {}
for i,p in people.items():
if 'max_load' in p.conf: # max_load override for Pol
for d,load in enumerate(p.conf['max_load']):
max_loads[(i,d)] = load
# filter days that the person does not exist
for d in ALL_DAYS - p.conf['dagen']:
max_loads[(i,d)] = 0
m = Model()
does = {}
happiness = []
stdevs = []
errors = []
for pname, person in people.items():
workloads = []
p_error = m.addVar(vtype="I", name=f"{pname}_error", lb=0, ub=None)
for d in ALL_DAYS:
pdt = []
for task in tasks:
var = m.addVar(vtype="B", name=f"{pname}_does_{task}@{d}")
pdt.append(var)
does[(pname, d, task)] = var
# a person only does what (s)he is capable of
if task not in person.can:
m.addCons(var == 0)
workloads.append(var * tasks[task].workload)
for task in person.loves:
happiness.append(does[(pname, d, task)] * config['weights']['likes'])
for task in person.hates:
happiness.append(does[(pname, d, task)] * (config['weights']['hates'] * -1))
# max_load_person: a person only has one task per day at most
m.addCons(quicksum(pdt) <= max_loads.get((pname, d), 1))
m.addCons(p_error >= person.cost(len(people)) - quicksum(workloads))
m.addCons(p_error >= quicksum(workloads) - person.cost(len(people)))
errors.append(p_error)
stdevs.append((person.cost(len(people)) - quicksum(workloads)) ** 2)
# min_load_person: person has at least 1 task
m.addCons(quicksum([does[(pname, d, task)] for d in ALL_DAYS for task in tasks]) >= 1)
# duplicate_jobs: a person does not perform the same job on all days
for task in tasks:
m.addCons(quicksum(does[(pname, d, task)] for d in ALL_DAYS) <= len(ALL_DAYS) - 1)
# max_load_person_total
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m.addCons(quicksum([does[(pname, d, task)] * tasks[task].workload for d in ALL_DAYS for task in tasks]) <= config['max_load_person'])
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# hardcode constraint
for d, task in person.does:
m.addCons(does[(pname, d, task)] == 1)
# all_allocated: each task in allocated
for j in tasks:
for d in ALL_DAYS:
m.addCons(quicksum(does[(p, d, j)] for p in people) == tasks[j].req[d])
objective = m.addVar(name="objvar", vtype="C", lb=None, ub=None)
m.setObjective(objective, "maximize")
if QUADRATIC:
m.addCons(objective <= quicksum(happiness) - quicksum(stdevs) / 2)
else:
if args.max_total_error is not None:
m.addCons(quicksum(errors) <= args.max_total_error)
m.addCons(objective <= quicksum(happiness) - quicksum(errors))
m.setObjective(objective, "maximize")
m.solveConcurrent()
for pname, person in people.items():
for d in ALL_DAYS:
for task in tasks:
if m.getVal(does[(pname, d, task)]):
person.does.add((d, task))
write_tasks(people, tasks)
print("Totale vrolijkheid:", sum(p.vrolijkheid() for p in people.values()))
print("workload deviation:", m.getVal(quicksum(stdevs)))
parser = argparse.ArgumentParser()
parser.add_argument("-q", "--quadratic", action="store_true")
parser.add_argument("--max_total_error", type=int, default=None)
args = parser.parse_args()
QUADRATIC = args.quadratic
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people = read_people(conf['people'])
with open('prefs_table', 'r') as pref_file:
read_prefs(pref_file, tasks, people)
set_capabilities(tasks, people)
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scipsol(people, tasks)