There are several possibilities for concatenating 1D arrays, e.g.,

import numpy as np

np.r_[a, a]
np.stack([a, a]).reshape(-1)
np.hstack([a, a])
np.concatenate([a, a])

All those options are equally fast for large arrays; for small ones, concatenate has a slight edge:

The plot was created with perfplot:

import numpy
import perfplot

perfplot.show(
    setup=lambda n: numpy.random.rand(n),
    kernels=[
        lambda a: numpy.r_[a, a],
        lambda a: numpy.stack([a, a]).reshape(-1),
        lambda a: numpy.hstack([a, a]),
        lambda a: numpy.concatenate([a, a]),
    ],
    labels=["r_", "stack+reshape", "hstack", "concatenate"],
    n_range=[2 ** k for k in range(19)],
    xlabel="len(a)",
)