Exemplo n.º 1
0
def test_python_builder_flask_distr_runnable(tmpdir,
                                             python_builder: PythonBuilder,
                                             pandas_data):
    args, env = _prepare_distribution(tmpdir, python_builder)

    from setup import setup_args
    _check_requirements(
        tmpdir,
        {
            *setup_args['install_requires'],
            'flasgger==0.9.3',  # server reqs
            'pandas==0.25.1',
            'scikit-learn==0.21.3',
            'numpy==1.17.3'
        })  # model reqs

    # TODO make ModelLoader.load cwd-independent
    server = subprocess.Popen(args, env=env, cwd=tmpdir)
    with pytest.raises(subprocess.TimeoutExpired):
        # we hope that 5 seconds is enough to determine that server didn't crash
        server.wait(5)

    try:
        client = HTTPClient()
        predictions = client.predict(pandas_data)
        np.testing.assert_array_almost_equal(predictions, [1, 0])
    finally:
        # our server runs for eternity, thus we should kill it to clean up
        # `server.kill` kills just shell script, Python subprocess still alive
        parent = psutil.Process(server.pid)
        for child in parent.children(recursive=True):
            child.kill()
        parent.kill()
Exemplo n.º 2
0
def main():
    try:
        value_a, value_b = float(sys.argv[1]), float(sys.argv[2])
    except (IndexError, ValueError):
        print(f'Usage: {sys.argv[0]} [float] [float]')
        return

    client = HTTPClient()
    df = pd.DataFrame({'a': [value_a], 'b': [value_b]})

    pred = client.predict(df)
    # pred is numpy array of shape (1,)
    print(pred.item())

    proba = client.predict_proba(df)
    # proba is numpy array of shape (1, 2)
    print(list(proba[0]))
Exemplo n.º 3
0
def test_python_build_context_flask_distr_runnable(tmpdir,
                                                   python_build_context,
                                                   pandas_data, server_reqs,
                                                   request):
    python_build_context: PythonBuildContext = request.getfixturevalue(
        python_build_context)
    args, env = _prepare_distribution(tmpdir, python_build_context)

    from setup import setup_args
    _check_requirements(
        tmpdir, {
            *setup_args['install_requires'], *server_reqs, 'pandas==1.0.3',
            'scikit-learn==0.22.2', 'numpy==1.18.2'
        })  # model reqs

    check_ebonite_port_free()

    # TODO make ModelLoader.load cwd-independent
    server = subprocess.Popen(args, env=env, cwd=tmpdir)
    with pytest.raises(subprocess.TimeoutExpired):
        # we hope that 5 seconds is enough to determine that server didn't crash
        server.wait(5)

    try:
        client = HTTPClient()
        predictions = client.predict(pandas_data)
        np.testing.assert_array_almost_equal(predictions, [1, 0])

        probas = client.predict_proba(pandas_data)
        np.testing.assert_array_almost_equal(np.argmax(probas, axis=1), [1, 0])
    finally:
        # our server runs for eternity, thus we should kill it to clean up
        # `server.kill` kills just shell script, Python subprocess still alive
        parent = psutil.Process(server.pid)
        for child in parent.children(recursive=True):
            child.kill()
        parent.kill()