我一直在使用 OR-Tools 和 SCIP 求解器，特别是使用以下设置：
self.solver = pywraplp.Solver.CreateSolver('SCIP')
self.solver.EnableOutput()
status = self.solver.Solve()
当求解器运行时，
EnableOutputtime | node | left |LP iter|LP it/n|mem/heur|mdpt |vars |cons |rows |cuts |sepa|confs|strbr| dualbound | primalbound | gap | compl.
111s| 8200 | 131 |980573 | 83.9 | 63M | 69 | 693 |1489 |1195 |6281 | 0 | 13k|5395 | 1.302965e+04 | 1.401400e+04 | 7.55%| 77.77%
112s| 8300 | 60 |992733 | 84.2 | 63M | 69 | 693 |1498 | 801 |6443 | 1 | 13k|5446 | 1.317840e+04 | 1.401400e+04 | 6.34%| 91.13%
对于我的特定用例，我想在解算器运行时每 10 秒从该输出捕获特定数据点（例如间隙）。 OR-Tools 中是否有内置方法来提取此数据？我怀疑 OR-Tools 可能不会通过标准 Python 输出和错误通道进行打印，这使得捕获输出成为一项挑战。或者，如果这是推荐的方法，我愿意使用外部工具或方法监视和解析控制台输出。我想指出的是，我已经尝试使用
sys任何指导、建议或解决方法将不胜感激。
在我的笔记本电脑上使用 CP-SAT 与 10 名工人一起求解：
Starting search at 0.43s with 10 workers.
8 full problem subsolvers: [core, default_lp, max_lp, no_lp, pseudo_costs, quick_restart, quick_restart_no_lp, reduced_costs]
8 incomplete subsolvers: [feasibility_pump, graph_arc_lns, graph_cst_lns, graph_dec_lns, graph_var_lns, rins/rens, rnd_cst_lns, rnd_var_lns]
3 helper subsolvers: [neighborhood_helper, synchronization_agent, update_gap_integral]
#Bound 0.50s best:inf next:[23500,53657720] default_lp initial_propagation
#Bound 1.71s best:inf next:[23909,53657720] max_lp
#1 8.33s best:713602 next:[23909,713601] pseudo_costs fixed_bools:0/9208
#2 8.43s best:713306 next:[23909,713305] quick_restart_no_lp fixed_bools:0/8813
#3 8.49s best:712603 next:[23909,712602] rnd_var_lns(d=0.50 s=662 t=0.10 p=0.00 stall=0) [hint]
#4 8.71s best:712307 next:[23909,712306] quick_restart_no_lp fixed_bools:0/8816
#5 8.71s best:585314 next:[23909,585313] rens_lp_lns(d=0.68 s=661 t=0.10 p=0.45 stall=0)
#6 8.83s best:560203 next:[23909,560202] quick_restart_no_lp fixed_bools:0/10569
#7 8.89s best:559907 next:[23909,559906] quick_restart_no_lp fixed_bools:0/10569
#8 8.90s best:559870 next:[23909,559869] quick_restart_no_lp fixed_bools:0/10569
#9 9.20s best:534845 next:[23909,534844] quick_restart_no_lp fixed_bools:0/10591
#10 9.26s best:534808 next:[23909,534807] graph_dec_lns(d=0.50 s=667 t=0.10 p=0.00 stall=0) [hint]
#11 9.28s best:534549 next:[23909,534548] quick_restart_no_lp fixed_bools:0/10624
#Bound 9.43s best:534549 next:[25971,534548] max_lp
#12 9.44s best:534512 next:[25971,534511] quick_restart_no_lp fixed_bools:0/11988
#13 9.48s best:509785 next:[25971,509784] quick_restart_no_lp fixed_bools:0/14778
#14 9.52s best:509760 next:[25971,509759] rnd_cst_lns(d=0.29 s=669 t=0.10 p=0.00 stall=0)
#15 9.67s best:484760 next:[25971,484759] quick_restart_no_lp fixed_bools:0/14790
#16 9.67s best:484649 next:[25971,484648] quick_restart_no_lp fixed_bools:0/14790
#17 9.68s best:484499 next:[25971,484498] quick_restart_no_lp fixed_bools:0/14790
#18 9.70s best:484425 next:[25971,484424] quick_restart_no_lp fixed_bools:0/14791
#19 9.74s best:389511 next:[25971,389510] rnd_var_lns(d=0.71 s=668 t=0.10 p=1.00 stall=0)
#20 9.88s best:389361 next:[25971,389360] quick_restart_no_lp fixed_bools:0/14808
#21 10.06s best:364361 next:[25971,364360] quick_restart_no_lp fixed_bools:0/14810
#22 10.10s best:364215 next:[25971,364214] rnd_var_lns(d=0.54 s=674 t=0.10 p=0.50 stall=0)
#23 10.14s best:339215 next:[25971,339214] quick_restart_no_lp fixed_bools:0/14865
#24 10.26s best:339178 next:[25971,339177] quick_restart_no_lp fixed_bools:0/14913
#25 10.29s best:289311 next:[25971,289310] graph_dec_lns(d=0.71 s=673 t=0.10 p=1.00 stall=0)
#26 10.45s best:289198 next:[25971,289197] quick_restart_no_lp fixed_bools:0/15076
...
#166 95.55s best:34389 next:[27962,34388] quick_restart_no_lp fixed_bools:1109/23063
#167 95.89s best:34239 next:[27962,34238] quick_restart_no_lp fixed_bools:1109/23065
#168 95.99s best:34202 next:[27962,34201] quick_restart_no_lp fixed_bools:1109/23068
#169 97.47s best:34165 next:[27962,34164] quick_restart_no_lp fixed_bools:1109/23163
#170 97.52s best:34128 next:[27962,34127] quick_restart_no_lp fixed_bools:1109/23170
#Bound 98.71s best:34128 next:[27982,34127] max_lp
#171 102.18s best:33980 next:[27982,33979] graph_cst_lns(d=0.47 s=1530 t=0.10 p=0.51 stall=5)
#172 102.34s best:33832 next:[27982,33831] quick_restart_no_lp fixed_bools:1109/23338
#173 123.31s best:33715 next:[27982,33714] rnd_var_lns(d=0.81 s=1724 t=0.10 p=0.51 stall=4)
#174 123.43s best:33567 next:[27982,33566] graph_arc_lns(d=0.19 s=1727 t=0.10 p=0.49 stall=64)
#175 123.85s best:33530 next:[27982,33529] rnd_var_lns(d=0.83 s=1730 t=0.10 p=0.51 stall=0)
#176 125.95s best:33306 next:[27982,33305] graph_dec_lns(d=0.82 s=1747 t=0.10 p=0.51 stall=3)
#177 126.20s best:33232 next:[27982,33231] quick_restart_no_lp fixed_bools:1109/23889
#178 178.46s best:33076 next:[27982,33075] graph_dec_lns(d=0.81 s=2209 t=0.10 p=0.51 stall=10)
#179 179.19s best:33002 next:[27982,33001] graph_dec_lns(d=0.79 s=2215 t=0.10 p=0.50 stall=0)
#180 179.24s best:32632 next:[27982,32631] rnd_var_lns(d=0.84 s=2216 t=0.10 p=0.51 stall=0)
#181 188.15s best:32032 next:[27982,32031] graph_var_lns(d=0.36 s=2290 t=0.10 p=0.51 stall=17)
#182 192.88s best:31882 next:[27982,31881] graph_dec_lns(d=0.81 s=2329 t=0.10 p=0.51 stall=2)