def parse_api(api):
    data = {"url_prefix": "", "auth_header": ""}
    data["docs"] = api.docs
    if api.url_prefix:
        data["url_prefix"] = api.url_prefix
    if api.auth:
        data["auth_header"] = api.auth.auth_header
    resources = []
    for name, res in api.resources.items():
        reaource = {"name": name, "docs": res["docs"]}
        actions = [dict(x._asdict()) for x in res["actions"]]
        reaource["actions"] = actions
        resources.append(reaource)
    data["resources"] = resources
    return data
Generates output predictions for the input samples,
dataset/ETHPy150Open guyskk/flask-restaction/flask_restaction/apiinfo.py/parse_api--crossover with--dataset/ETHPy150Open fchollet/keras/keras/engine/training.py/Model.predict