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Python Quick Start

Get OptalCP running in Python in under 5 minutes.

Prerequisites​

  • Python 3.11 or later
  • pip (Python package installer)

Installation​

Install the Preview edition (free for evaluation):

pip install git+https://github.com/ScheduleOpt/optalcp-py-bin-preview@latest
tip

For academic research or production use, see Editions for other options.

Your First Scheduling Model​

Create a file test_optalcp.py:

import optalcp as cp

model = cp.Model()
x = model.interval_var(length=10, name="x")
y = model.interval_var(length=10, name="y")
model.end_before_start(x, y)  # y starts after x ends
model.minimize(y.end())
result = model.solve()
print(f"Objective: {result.objective}")

Run it:

python test_optalcp.py

You'll see the solver log first, then the output from your program:

────────────────────────────────────────────────────────────────────────────────
                              ScheduleOpt OptalCP
                           Version 2025.12.1 (Linux)
                   CPU: AMD Ryzen 9 5950X (16 physical cores)
────────────────────────────────────────────────────────────────────────────────
Input parse time: 00:00
   nbWorkers = 16                      (auto: 16 physical cores)
   preset = Default                    (auto: < 100,000 variables)
   noOverlapPropagationLevel = 4       (preset: Default)
   cumulPropagationLevel = 3           (preset: Default)
     Workers 0-7: searchType = LNS     (preset: Default)
    Workers 8-13: searchType = FDS     (preset: Default)
   Workers 14-15: searchType = FDSDual (preset: Default)
Input:
   0 integer variables, 2 interval variables, 1 constraints, 9.38kB
   00:00 Presolving..
Presolved:
   0 integer variables, 2 interval variables, 1 constraints, 9.37kB
   00:00 Presolve complete, starting search.
────────────────────────────────────────────────────────────────────────────────
   00:00 ↑ Lower bound 20 Worker 8
   00:00 ↓ Solution 20 Worker 8: FDS
   00:00 The current best solution is optimal.
────────────────────────────────────────────────────────────────────────────────
   Objective value: 20 (optimal)
       Lower bound: 20
         Solutions: 1
         LNS steps: 0 (0.00 per second)
          Restarts: 0 (0.00 per second)
          Branches: 156 (8706.41 per second)
             Fails: 10 (558.10 per second)
    Total duration: 00:00.02
            Memory: 146MB
────────────────────────────────────────────────────────────────────────────────
Objective: 20

Next Steps​

  • Tutorial — Learn scheduling concepts step-by-step
  • Editions — Compare Preview, Academic, and Full editions
  • Python API — Complete Python API documentation

See also​