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How to use merge_shards method in localstack

Best Python code snippet using localstack_python

transformer.py

Source:transformer.py

...136                label=int(cancer),137                size=size,138                threads=threads,139                dataset=dataset)140def merge_shards(in_files, fname):141    with tf.python_io.TFRecordWriter(fname, options=OPTIONS) as writer:142        for in_file in in_files:143            for record in tf.python_io.tf_record_iterator(in_file, options=OPTIONS):144                writer.write(record)145def merge_shards_in_folder(transformed_folder, transformed_out, size=(256, 256)):146    healthy = []147    cancer = []148    for file in os.listdir(transformed_folder):149        path = os.path.join(transformed_folder, file)150        if not file.startswith('label') or not file.endswith('tfrecord'):151            continue152        if file.startswith('label_1'):153            cancer.append(path)154        elif file.startswith('label_0'):155            healthy.append(path)156        else:157            raise ValueError('Invalid file: ' + str(path))158    merge_shards(healthy, os.path.join(transformed_out, 'healthy.tfrecord'))159    merge_shards(cancer, os.path.join(transformed_out, 'cancer.tfrecord'))160def load_inbreast_mask(mask_path, imshape=(4084, 3328)):161    """162    This function loads a osirix xml region as a binary numpy array for INBREAST163    dataset164    @mask_path : Path to the xml file165    @imshape : The shape of the image as an array e.g. [4084, 3328]166    return: numpy array where positions in the roi are assigned a value of 1.167    """168    def load_point(point_string):169        x, y = tuple([float(num) for num in point_string.strip('()').split(',')])170        return y, x171    mask_shape = np.transpose(imshape)172    mask = np.zeros(mask_shape)173    with open(mask_path, 'rb') as mask_file:...

test_inserts.py

Source:test_inserts.py

...31        table.add(None)32        table.add("test")33        table.add({})3435        table.merge_shards()36        result = jx.sort(table.all_records(), ".")3738        expected = [42, "test", NULL, NULL]3940        self.assertEqual(result, expected)4142    def test_array(self):43        dataset = self.dataset44        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)45        table.add({"b": [1, 2, 3, 4, 5, 6]})46        table.merge_shards()47        result = jx.sort(table.all_records(), "a")4849        expected = [{"b": [1, 2, 3, 4, 5, 6]}]50        self.assertEqual(result, expected)5152    def test_one_then_many_then_merge(self):53        dataset = self.dataset54        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)55        table.add({"a": 1, "b": {"c": 1, "d": 1}})56        table.add({"a": 2, "b": [{"c": 1, "d": 1}, {"c": 2, "d": 2}]})5758        table.merge_shards()59        result = jx.sort(table.all_records(), "a")6061        expected = [62            {"a": 1, "b": {"c": 1, "d": 1}},63            {"a": 2, "b": [{"c": 1, "d": 1}, {"c": 2, "d": 2}]},64        ]6566        self.assertEqual(result, expected)6768    def test_one_then_deep_arrays1(self):69        dataset = self.dataset70        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)71        table.add({"a": 1, "b": {"c": [{"e": "e"}, {"e": 1}]}})72        table.add({"a": 2, "b": {"c": 1}})7374        table.merge_shards()75        result = jx.sort(table.all_records(), "a")7677        expected = [78            {"a": 1, "b": {"c": [{"e": "e"}, {"e": 1}]}},79            {"a": 2, "b": {"c": 1}},80        ]8182        self.assertEqual(result, expected)8384    def test_one_then_deep_arrays2(self):85        dataset = self.dataset86        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)87        table.add({"a": 1, "b": {"c": [{"e": "e"}, {"e": 1}]}})88        table.add({"a": 2, "b": {"c": 1}})89        table.add({"a": 3, "b": [{"c": [{"e": 2}, {"e": 3}]}, {"c": 42}]})9091        table.merge_shards()92        result = jx.sort(table.all_records(), "a")9394        expected = [95            {"a": 1, "b": {"c": [{"e": "e"}, {"e": 1}]}},96            {"a": 2, "b": {"c": 1}},97            {"a": 3, "b": [{"c": [{"e": 2}, {"e": 3}]}, {"c": 42}]},98        ]99100        self.assertEqual(result, expected)101102    def test_inject_arrays(self):103        dataset = self.dataset104        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)105106        table.add({"a": 1, "b": {"c": {"e": 42}}})107        table.add({"a": 3, "b": [{"c": {"e": 2}}, {"c": {"e": 3}}]})108109        table.merge_shards()110        result = jx.sort(table.all_records(), "a")111112        expected = [113            {"a": 1, "b": {"c": {"e": 42}}},114            {"a": 3, "b": [{"c": {"e": 2}}, {"c": {"e": 3}}]},115        ]116117        self.assertEqual(result, expected)118119    def test_has_arrays(self):120        dataset = self.dataset121        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)122123        table.add({"a": 1, "b": {"c": {"e": 42}}})124        table.add({"a": 3, "b": [{"c": {"e": 2}}, {"c": {"e": 3}, "f": 42}]})125126        table.merge_shards()127        result = jx.sort(table.all_records(), "a")128129        expected = [130            {"a": 1, "b": {"c": {"e": 42}}},131            {"a": 3, "b": [{"c": {"e": 2}}, {"c": {"e": 3}}]},132        ]133134        self.assertEqual(result, expected)135136    def test_zero_array(self):137        dataset = self.dataset138        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)139140        table.add({"a": 3, "b": []})141142        table.merge_shards()143        result = jx.sort(table.all_records(), "a")144145        expected = [146            {"a": 3, "b": NULL},147        ]148149        self.assertEqual(result, expected)150151    def test_null(self):152        dataset = self.dataset153        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)154155        table.add({"a": 3, "b": None})156157        table.merge_shards()158        result = jx.sort(table.all_records(), "a")159160        expected = [161            {"a": 3, "b": NULL},162        ]163164        self.assertEqual(result, expected)165166    def test_infinity(self):167        dataset = self.dataset168        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)169170        table.add({"a": 3, "b": -math.inf})171172        table.merge_shards()173        result = jx.sort(table.all_records(), "a")174175        expected = [176            {"a": 3, "b": NULL},177        ]178179        self.assertEqual(result, expected)180181    @skipIf(PY2, "no enums for python 2")182    def test_enum(self):183        class Status(Enum):184            PASS = 0185            FAIL = 1186            INTERMITTENT = 2187188        dataset = self.dataset189        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)190191        table.add({"a": Status.PASS})192193        table.merge_shards()194        result = jx.sort(table.all_records(), "a")195196        expected = [197            {"a": "PASS"},198        ]199200        self.assertEqual(result, expected)201202    def test_encoding_on_deep_arrays(self):203        dataset = self.dataset204        table = dataset.create_or_replace_table(table=tests.table_name(), sharded=True)205        table.add({"__a": 1, "__b": {"__c": [{"__e": "e"}, {"__e": 1}]}})206        table.add({"__a": 2, "__b": {"__c": 1}})207        table.add({"__a": 3, "__b": [{"__c": [{"__e": 2}, {"__e": 3}]}]})208209        table.merge_shards()210        result = jx.sort(table.all_records(), "__a")211212        expected = [213            {"__a": 1, "__b": {"__c": [{"__e": "e"}, {"__e": 1}]}},214            {"__a": 2, "__b": {"__c": 1}},215            {"__a": 3, "__b": {"__c": [{"__e": 2}, {"__e": 3}]}},216        ]217218        self.assertEqual(result, expected)219220    def test_top_level_field_order(self):221        dataset = self.dataset222223        table = dataset.create_or_replace_table(224            table=tests.table_name(),225            sharded=True,226            schema={"push": {"id": {"_i_": "integer"}}, "etl": {"timestamp": {"_t_": "time"}}},227            # REVERSE ALPHABTICAL ORDER228            top_level_fields=OrderedDict([229                ("push", {"id": "_push_id"}),230                ("etl", {"timestamp": "_etl_timestamp"})231            ]),232        )233        today = Date.today()234        now = Date.now()235        table.add({"push": {"id": 1}, "etl": {"timestamp": today}, "a": 1})236        table.add({"push": {"id": 2}, "etl": {"timestamp": now}, "b": 2})237238        table.merge_shards()239        result = jx.sort(table.all_records(), "push.id")240241        expected = [242            {"push": {"id": 1}, "etl": {"timestamp": today}, "a": 1},243            {"push": {"id": 2}, "etl": {"timestamp": now}, "b": 2},244        ]245
...

merge.py

Source:merge.py

2from mo_logs import startup, constants, Log3def merge(config):4    container = bigquery.Dataset(config.destination)5    index = container.get_or_create_table(config.destination)6    index.merge_shards()7def main():8    try:9        config = startup.read_settings()10        constants.set(config.constants)11        Log.start(config.debug)12        merge(config.push)13    except Exception as e:14        Log.error("Problem with etl", cause=e)15    finally:16        Log.stop()17if __name__ == "__main__":...

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