def test_datetime64(): np = pytest.importorskip("numpy") t1 = np.datetime64(t0) assert str2dt(t1) == t0 t1 = np.array([np.datetime64(t0), np.datetime64(t0)]) assert (str2dt(t1) == t0).all()
def test_pandas_time(): pandas = pytest.importorskip('pandas') t = pandas.Series(t0) assert (str2dt(t) == t0).all() t = pandas.Series([t0, t0]) assert (str2dt(t) == t0).all()
def test_types(): assert str2dt(t0) == t0 # passthrough assert str2dt('2014-04-06T08:00:00') == t0 ti = [str2dt('2014-04-06T08:00:00'), str2dt('2014-04-06T08:01:02')] to = [t0, datetime(2014, 4, 6, 8, 1, 2)] assert ti == to # even though ti is numpy array of datetime and to is list of datetime t1 = [t0, t0] assert (np.asarray(str2dt(t1)) == t0).all()
def test_xarray_time(): xarray = pytest.importorskip('xarray') t = {'time': t0} ds = xarray.Dataset(t) assert str2dt(ds['time']) == t0 t2 = {'time': [t0, t0]} ds = xarray.Dataset(t2) assert (str2dt(ds['time']) == t0).all()
def test_xarray_time(): xarray = pytest.importorskip("xarray") t = {"time": t0} ds = xarray.Dataset(t) assert str2dt(ds["time"]) == t0 t2 = {"time": [t0, t0]} ds = xarray.Dataset(t2) assert (str2dt(ds["time"]) == t0).all()
def test_types(): np = pytest.importorskip("numpy") assert str2dt(t0) == t0 # passthrough assert str2dt("2014-04-06T08:00:00") == t0 ti = [str2dt("2014-04-06T08:00:00"), str2dt("2014-04-06T08:01:02")] to = [t0, datetime(2014, 4, 6, 8, 1, 2)] assert ti == to # even though ti is numpy array of datetime and to is list of datetime t1 = [t0, t0] assert (np.asarray(str2dt(t1)) == t0).all()
def test_str2dt(): assert str2dt('2014-04-06T08:00:00Z') == datetime(2014, 4, 6, 8, tzinfo=UTC) ti = [str2dt('2014-04-06T08:00:00Z'), str2dt('2014-04-06T08:01:02Z')] to = [ datetime(2014, 4, 6, 8, tzinfo=UTC), datetime(2014, 4, 6, 8, 1, 2, tzinfo=UTC) ] assert ti == to # even though ti is numpy array of datetime and to is list of datetime
def test_datetime64(): t1 = np.datetime64(t0) assert str2dt(t1) == t0 t1 = np.array([np.datetime64(t0), np.datetime64(t0)]) assert (str2dt(t1) == t0).all()