scale_pos_weight using XGBoost's Learning API
Yes, you can use scale_pos_weight in the native python API; it goes in the params dictionary.  E.g.,

params = {'objective': 'binary:logistic',
          'scale_pos_weight': 2.5}
model = xgboost.train(params, dmat)


https://xgboost.readthedocs.io/en/latest/parameter.html#parameters-for-tree-booster
https://github.com/dmlc/xgboost/blob/master/demo/kaggle-higgs/speedtest.py