How to use the pyexcel.get_array function in pyexcel

def test_isave_to_database(self):
        Base.metadata.drop_all(engine)
        Base.metadata.create_all(engine)
        self.session = Session()
        myinput = TestInput()
        myinput.isave_to_database(file_name=self.testfile,
                                  session=self.session,
                                  table=Signature)
        array = pe.get_array(session=self.session, table=Signature)
        assert array == self.data
        self.session.close()

def test_get_array_from_dict(self):
        adict = {"X": [1, 4], "Y": [2, 5], "Z": [3, 6]}
        result = pe.get_array(adict=adict)
        eq_(result, self.test_data)

def test_download(self):
        response = self.app.get("/download")
        ret = pe.get_array(file_type="csv", file_content=response.data)
        print(ret)
        self.assertEqual(
            ret,
            [
                ["REVIEW_DATE", "AUTHOR", "ISBN", "DISCOUNTED_PRICE"],
                ["1985/01/21", "Douglas Adams", "0345391802", 5.95],
                ["1990/01/12", "Douglas Hofstadter", "0465026567", 9.95],
                [
                    "1998/07/15",
                    'Timothy "The Parser" Campbell',
                    "0968411304",
                    18.99,
                ],
                ["1999/12/03", "Richard Friedman", "0060630353", 5.95],
                ["2004/10/04", "Randel Helms", "0879755725", 4.5],
            ],

def read_deepsoil_results(name):
    data = pyexcel.get_array(file_name=str(FPATH_DATA / (name + '.xlsx')))
    names = ','.join(string.ascii_uppercase[:len(data[0])])
    records = np.rec.fromrecords(data, names=names)

    def extract_cols(records, cols, first, last, names):
        return {
            name: records[col][first:last].astype(float)
            for col, name in zip(cols, names)
        }

    d = dict()
    # Read the time series
    d['time_series'] = extract_cols(
        records, 'ABCDE', 1, 11800,
        ['time', 'accel', 'strain', 'stress', 'arias_int'])
    # Read the response spectrum
    d['resp_spec'] = extract_cols(records, 'GH', 1, 114, ['period', 'psa'])

["id", "name"],
            [1, "News"],
            [2, "Sports"]
        ]
        for upload_file_type in ['xls', 'ods']:
            with app.app_context():
                db.drop_all()
                db.create_all()
            print("Uploading %s" % upload_file_type)
            file_name = "test.%s" % upload_file_type
            io = pe.save_as(array=array, dest_file_type=upload_file_type)
            response = self.app.post('/upload/categories',
                                     buffered=True,
                                     data={"file": (io, file_name)},
                                     content_type="multipart/form-data")
            ret = pe.get_array(file_type="xls", file_content=response.data)
            assert array == ret

def get_array(self, **keywords):
        """
        Get a list of lists from the file

        :param sheet_name: For an excel book, there could be multiple
                           sheets. If it is left unspecified, the
                           sheet at index 0 is loaded. For 'csv',
                           'tsv' file, *sheet_name* should be None anyway.
        :param keywords: additional key words
        :returns: A list of lists
        """
        params = self.get_params(**keywords)
        return pe.get_array(**params)

def load_feeder_info_from_file(path):
    # Read from local file
    print('Fetching feeder data from: {}'.format(path))
    for row in pyexcel.get_array(file_name=path, start_row=1): # skip header
        if(row[0] != "Stop"):
            # Add a new feeder using these values
            available_feeders.append(Feeder(feeder_ID=row[1],
                device_name=clear_utf8_characters(row[2]),
                stack_x_offset=stof(row[3]),
                stack_y_offset=stof(row[4]),
                height=stof(row[5]),
                speed=stoi(row[6]),
                head=stoi(row[7]),
                angle_compensation=stoi(row[8]),
                feed_spacing=stoi(row[9]),
                place_component=(row[10] == 'Y'),
                check_vacuum=(row[11] == 'Y'),
                use_vision=(row[12] == 'Y'),
                centroid_correction_x=stof(row[13]),
                centroid_correction_y=stof(row[14]),