How to use the pastas.Project function in pastas

def test_create_project():
    pr = ps.Project(name="test")
    return pr

def load_project(data):
    """Method to load a Pastas project.

    Parameters
    ----------
    data: dict
        Dictionary containing all information to construct the project.

    Returns
    -------
    mls: Pastas.Project class
        Pastas Project class object

    """

    mls = ps.Project(name=data["name"])

    mls.metadata = data["metadata"]
    mls.file_info = data["file_info"]

    oseries = DataFrame(data["oseries"], columns=data["oseries"].keys()).T
    mls.oseries = mls.oseries.append(oseries, sort=False)

    stresses = DataFrame(data=data["stresses"],
                         columns=data["stresses"].keys()).T
    mls.stresses = mls.stresses.append(stresses, sort=False)

    for ml_name, ml in data["models"].items():
        name = str(ml["oseries"]["name"])
        ml_name = str(ml_name)
        ml["oseries"]["series"] = mls.oseries.loc[name, "series"]
        if ml["stressmodels"]:

"""This file contains an example of the use of the Project class.

R.A. Collenteur - Artesia Water 2017

"""

import pastas as ps

# Create a simple model taken from example.py
obs = ps.read_dino('data/B58C0698001_1.csv')
rain = ps.read_knmi('data/neerslaggeg_HEIBLOEM-L_967-2.txt', variables='RD')
evap = ps.read_knmi('data/etmgeg_380.txt', variables='EV24')

# Create a Pastas Project
mls = ps.Project(name="test_project")

mls.add_series(obs, "GWL", kind="oseries", metadata=dict())
mls.add_series(rain, name="Prec", kind="prec", metadata=dict())
mls.add_series(evap, name="Evap", kind="evap", metadata=dict())

ml = mls.add_model(oseries="GWL")
sm = ps.StressModel2([mls.stresses.loc["Prec", "series"],
                      mls.stresses.loc["Evap", "series"]],
                     ps.Exponential, name='recharge')
ml.add_stressmodel(sm)
n = ps.NoiseModel()
ml.add_noisemodel(n)
ml.solve(freq="D", warmup=1000, report=False)

mls.to_file("test_project.pas")