python code to approximate an arbitrary 2*2 unitary matrix with gates H,T and Z

Question

I'm new to programming, tried different options, compiled programs myself, took them from websites, but they didn't work, for example, the program:

import numpy as np
from qiskit import QuantumCircuit
from qiskit.extensions import HGate, TGate, SGate
from qiskit.quantum_info import Operator
from qiskit.compiler import transpile
from qiskit.transpiler.passes import Unroller
from qiskit.visualization import plot_histogram
from qiskit import Aer

# вентиль, который нужно разложить
matrix = np.array([[1, 1j], [1j, 1]]) / np.sqrt(2)
my_gate = Operator(matrix)

# функция для сравнения двух квантовых операций
def are_operators_close(op1, op2, eps=1e-8):
    return np.allclose(op1, op2, rtol=0, atol=eps, equal_nan=False)

# алгоритм Solovay-Kitaev для разложения вентиля в последовательность H, T, S
def sk_decomposition(gate, eps=0.01, depth=3):
    # инициализация квантовой схемы
    circuit = QuantumCircuit(1)
    gates = [HGate(), TGate(), SGate()]

    # применение алгоритма Solovay-Kitaev
    for d in range(depth):
        for gate in gates:
            for sign in [1, -1]:
                theta = sign * np.arccos(1 - 2 * eps)
                circuit.rz(theta, 0)
                circuit.append(gate, [0])
                circuit.rz(-theta, 0)
        eps = eps / 2

    # извлечение последовательности вентилей из разложенной матрицы
    backend = Aer.get_backend('statevector_simulator')
    decomposed_circuit = transpile(circuit, backend=backend, basis_gates=['u', 'h', 'cx', 'id'])
    decomposed_result = backend.run(decomposed_circuit).result()
    decomposed_state = decomposed_result.get_statevector()
    decomposed_matrix = np.outer(decomposed_state, np.conj(decomposed_state))
    sequence = ''
    for gate in [HGate(), TGate(), SGate()]:
        if are_operators_close(decomposed_matrix, gate):
            sequence += '0'
        else:
            for i in range(3):
                decomp = np.linalg.matrix_power(gate.to_matrix(), i)
                if are_operators_close(decomposed_matrix, decomp):
                    sequence += str(i)
                    break

    # конвертация последовательности из цифр в последовательность из букв H, T, S
    sequence_letters = ''.join(['HTS'[int(x)] for x in sequence])

    return sequence_letters

# запуск алгоритма Solovay-Kitaev для вентиля my_gate
sequence = sk_decomposition(my_gate)
print(sequence)

I get an error:

...,line 27, in sk_decomposition
    circuit.append(gate(), [0])
TypeError: 'module' object is not callable

how to fix the program or where is there a working code with the Solovey-Kitaev algorithm?