API — Scheduling

pyworkforce.scheduling

Both schedulers share the same constructor signature (except cost_dict) and the same solve() output. They validate that every shifts_coverage array and every required_resources row has exactly periods entries.

MinAbsDifference

MinAbsDifference(num_days, periods, shifts_coverage, required_resources,
                 max_period_concurrency, max_shift_concurrency,
                 max_search_time=120.0, num_search_workers=2)

Minimizes the total absolute difference between required and scheduled resources per period.

MinRequiredResources

MinRequiredResources(num_days, periods, shifts_coverage, required_resources,
                     max_period_concurrency, max_shift_concurrency,
                     cost_dict=None, max_search_time=240.0, num_search_workers=2)

Minimizes the (optionally weighted) number of scheduled resources while covering every period.

• cost_dict (dict, optional) — {shift_name: cost}; must contain exactly the same shift names as shifts_coverage. Defaults to a cost of 1 per shift.

Common parameters

• num_days (int) — days to schedule.
• periods (int) — periods per day.
• shifts_coverage (dict) — {shift_name: [0/1, …]}, length periods.
• required_resources (list) — shape [num_days, periods].
• max_period_concurrency (int) — max resources per period.
• max_shift_concurrency (int) — max resources per shift.
• max_search_time (float) — solver time limit, seconds.
• num_search_workers (int) — solver worker threads.

solve()

Returns a dict (also stored as solution_):

• status — "OPTIMAL", "FEASIBLE" or "INFEASIBLE".
• cost — objective value (-1 if infeasible).
• resources_shifts — list of {"day", "shift", "resources"}.

See the scheduling guide.