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test: refactor
list_rows tests and add test for scalars (#829)
* test: refactor `list_rows` tests and add test for scalars * fix JSON formatting * add TODO for INTERVAL Arrow support * format tests
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,2 +1,2 @@ | ||
| {"bool_col": true, "bytes_col": "abcd", "date_col": "2021-07-21", "datetime_col": "2021-07-21 11:39:45", "geography_col": "POINT(-122.0838511 37.3860517)", "int64_col": "123456789", "numeric_col": "1.23456789", "bignumeric_col": "10.111213141516171819", "float64_col": "1.25", "string_col": "Hello, World", "time_col": "11:41:43.07616", "timestamp_col": "2021-07-21T17:43:43.945289Z"} | ||
| {"bool_col": null, "bytes_col": null, "date_col": null, "datetime_col": null, "geography_col": null, "int64_col": null, "numeric_col": null, "bignumeric_col": null, "float64_col": null, "string_col": null, "time_col": null, "timestamp_col": null} | ||
| {"bool_col": true, "bytes_col": "SGVsbG8sIFdvcmxkIQ==", "date_col": "2021-07-21", "datetime_col": "2021-07-21 11:39:45", "geography_col": "POINT(-122.0838511 37.3860517)", "int64_col": "123456789", "interval_col": "P7Y11M9DT4H15M37.123456S", "numeric_col": "1.23456789", "bignumeric_col": "10.111213141516171819", "float64_col": "1.25", "rowindex": 0, "string_col": "Hello, World!", "time_col": "11:41:43.07616", "timestamp_col": "2021-07-21T17:43:43.945289Z"} | ||
| {"bool_col": null, "bytes_col": null, "date_col": null, "datetime_col": null, "geography_col": null, "int64_col": null, "interval_col": null, "numeric_col": null, "bignumeric_col": null, "float64_col": null, "rowindex": 1, "string_col": null, "time_col": null, "timestamp_col": null} |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| {"bool_col": true, "bytes_col": "DQo=\n", "date_col": "9999-12-31", "datetime_col": "9999-12-31 23:59:59.999999", "geography_col": "POINT(-135.0000 90.0000)", "int64_col": "9223372036854775807", "numeric_col": "9.9999999999999999999999999999999999999E+28", "bignumeric_col": "9.999999999999999999999999999999999999999999999999999999999999999999999999999E+37", "float64_col": "+inf", "string_col": "Hello, World", "time_col": "23:59:59.99999", "timestamp_col": "9999-12-31T23:59:59.999999Z"} | ||
| {"bool_col": false, "bytes_col": "8J+Zgw==\n", "date_col": "0001-01-01", "datetime_col": "0001-01-01 00:00:00", "geography_col": "POINT(45.0000 -90.0000)", "int64_col": "-9223372036854775808", "numeric_col": "-9.9999999999999999999999999999999999999E+28", "bignumeric_col": "-9.999999999999999999999999999999999999999999999999999999999999999999999999999E+37", "float64_col": "-inf", "string_col": "Hello, World", "time_col": "00:00:00", "timestamp_col": "0001-01-01T00:00:00.000000Z"} | ||
| {"bool_col": true, "bytes_col": "AA==\n", "date_col": "1900-01-01", "datetime_col": "1900-01-01 00:00:00", "geography_col": "POINT(-180.0000 0.0000)", "int64_col": "-1", "numeric_col": "0.000000001", "bignumeric_col": "-0.00000000000000000000000000000000000001", "float64_col": "nan", "string_col": "こんにちは", "time_col": "00:00:00.000001", "timestamp_col": "1900-01-01T00:00:00.000000Z"} | ||
| {"bool_col": false, "bytes_col": "", "date_col": "1970-01-01", "datetime_col": "1970-01-01 00:00:00", "geography_col": "POINT(0 0)", "int64_col": "0", "numeric_col": "0.0", "bignumeric_col": "0.0", "float64_col": 0.0, "string_col": "", "time_col": "12:00:00", "timestamp_col": "1970-01-01T00:00:00.000000Z"} | ||
| {"bool_col": null, "bytes_col": null, "date_col": null, "datetime_col": null, "geography_col": null, "int64_col": null, "numeric_col": null, "bignumeric_col": null, "float64_col": null, "string_col": null, "time_col": null, "timestamp_col": null} | ||
| {"bool_col": true, "bytes_col": "DQo=\n", "date_col": "9999-12-31", "datetime_col": "9999-12-31 23:59:59.999999", "geography_col": "POINT(-135.0000 90.0000)", "int64_col": "9223372036854775807", "interval_col": "P-10000Y0M-3660000DT-87840000H0M0S", "numeric_col": "9.9999999999999999999999999999999999999E+28", "bignumeric_col": "9.999999999999999999999999999999999999999999999999999999999999999999999999999E+37", "float64_col": "+inf", "rowindex": 0, "string_col": "Hello, World", "time_col": "23:59:59.999999", "timestamp_col": "9999-12-31T23:59:59.999999Z"} | ||
| {"bool_col": false, "bytes_col": "8J+Zgw==\n", "date_col": "0001-01-01", "datetime_col": "0001-01-01 00:00:00", "geography_col": "POINT(45.0000 -90.0000)", "int64_col": "-9223372036854775808", "interval_col": "P10000Y0M3660000DT87840000H0M0S", "numeric_col": "-9.9999999999999999999999999999999999999E+28", "bignumeric_col": "-9.999999999999999999999999999999999999999999999999999999999999999999999999999E+37", "float64_col": "-inf", "rowindex": 1, "string_col": "Hello, World", "time_col": "00:00:00", "timestamp_col": "0001-01-01T00:00:00.000000Z"} | ||
| {"bool_col": true, "bytes_col": "AA==\n", "date_col": "1900-01-01", "datetime_col": "1900-01-01 00:00:00", "geography_col": "POINT(-180.0000 0.0000)", "int64_col": "-1", "interval_col": "P0Y0M0DT0H0M0.000001S", "numeric_col": "0.000000001", "bignumeric_col": "-0.00000000000000000000000000000000000001", "float64_col": "nan", "rowindex": 2, "string_col": "こんにちは", "time_col": "00:00:00.000001", "timestamp_col": "1900-01-01T00:00:00.000000Z"} | ||
| {"bool_col": false, "bytes_col": "", "date_col": "1970-01-01", "datetime_col": "1970-01-01 00:00:00", "geography_col": "POINT(0 0)", "int64_col": "0", "interval_col": "P0Y0M0DT0H0M0S", "numeric_col": "0.0", "bignumeric_col": "0.0", "float64_col": 0.0, "rowindex": 3, "string_col": "", "time_col": "12:00:00", "timestamp_col": "1970-01-01T00:00:00.000000Z"} | ||
| {"bool_col": null, "bytes_col": null, "date_col": null, "datetime_col": null, "geography_col": null, "int64_col": null, "interval_col": null, "numeric_col": null, "bignumeric_col": null, "float64_col": null, "rowindex": 4, "string_col": null, "time_col": null, "timestamp_col": null} |
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| # Copyright 2021 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| import datetime | ||
| import decimal | ||
|
|
||
| from google.cloud import bigquery | ||
| from google.cloud.bigquery import enums | ||
|
|
||
|
|
||
| def test_list_rows_empty_table(bigquery_client: bigquery.Client, table_id: str): | ||
| from google.cloud.bigquery.table import RowIterator | ||
|
|
||
| table = bigquery_client.create_table(table_id) | ||
|
|
||
| # It's a bit silly to list rows for an empty table, but this does | ||
| # happen as the result of a DDL query from an IPython magic command. | ||
| rows = bigquery_client.list_rows(table) | ||
| assert isinstance(rows, RowIterator) | ||
| assert tuple(rows) == () | ||
|
|
||
|
|
||
| def test_list_rows_page_size(bigquery_client: bigquery.Client, table_id: str): | ||
| num_items = 7 | ||
| page_size = 3 | ||
| num_pages, num_last_page = divmod(num_items, page_size) | ||
|
|
||
| to_insert = [{"string_col": "item%d" % i, "rowindex": i} for i in range(num_items)] | ||
| bigquery_client.load_table_from_json(to_insert, table_id).result() | ||
|
|
||
| df = bigquery_client.list_rows( | ||
| table_id, | ||
| selected_fields=[bigquery.SchemaField("string_col", enums.SqlTypeNames.STRING)], | ||
| page_size=page_size, | ||
| ) | ||
| pages = df.pages | ||
|
|
||
| for i in range(num_pages): | ||
| page = next(pages) | ||
| assert page.num_items == page_size | ||
| page = next(pages) | ||
| assert page.num_items == num_last_page | ||
|
|
||
|
|
||
| def test_list_rows_scalars(bigquery_client: bigquery.Client, scalars_table: str): | ||
| rows = sorted( | ||
| bigquery_client.list_rows(scalars_table), key=lambda row: row["rowindex"] | ||
| ) | ||
| row = rows[0] | ||
| assert row["bool_col"] # True | ||
| assert row["bytes_col"] == b"Hello, World!" | ||
| assert row["date_col"] == datetime.date(2021, 7, 21) | ||
| assert row["datetime_col"] == datetime.datetime(2021, 7, 21, 11, 39, 45) | ||
| assert row["geography_col"] == "POINT(-122.0838511 37.3860517)" | ||
| assert row["int64_col"] == 123456789 | ||
| assert row["numeric_col"] == decimal.Decimal("1.23456789") | ||
| assert row["bignumeric_col"] == decimal.Decimal("10.111213141516171819") | ||
| assert row["float64_col"] == 1.25 | ||
| assert row["string_col"] == "Hello, World!" | ||
| assert row["time_col"] == datetime.time(11, 41, 43, 76160) | ||
| assert row["timestamp_col"] == datetime.datetime( | ||
| 2021, 7, 21, 17, 43, 43, 945289, tzinfo=datetime.timezone.utc | ||
| ) | ||
|
|
||
| nullrow = rows[1] | ||
| for column, value in nullrow.items(): | ||
| if column == "rowindex": | ||
| assert value == 1 | ||
| else: | ||
| assert value is None | ||
|
|
||
|
|
||
| def test_list_rows_scalars_extreme( | ||
| bigquery_client: bigquery.Client, scalars_extreme_table: str | ||
| ): | ||
| rows = sorted( | ||
| bigquery_client.list_rows(scalars_extreme_table), | ||
| key=lambda row: row["rowindex"], | ||
| ) | ||
| row = rows[0] | ||
| assert row["bool_col"] # True | ||
| assert row["bytes_col"] == b"\r\n" | ||
| assert row["date_col"] == datetime.date(9999, 12, 31) | ||
| assert row["datetime_col"] == datetime.datetime(9999, 12, 31, 23, 59, 59, 999999) | ||
| assert row["geography_col"] == "POINT(-135 90)" | ||
| assert row["int64_col"] == 9223372036854775807 | ||
| assert row["numeric_col"] == decimal.Decimal(f"9.{'9' * 37}E+28") | ||
| assert row["bignumeric_col"] == decimal.Decimal(f"9.{'9' * 75}E+37") | ||
| assert row["float64_col"] == float("Inf") | ||
| assert row["string_col"] == "Hello, World" | ||
| assert row["time_col"] == datetime.time(23, 59, 59, 999999) | ||
| assert row["timestamp_col"] == datetime.datetime( | ||
| 9999, 12, 31, 23, 59, 59, 999999, tzinfo=datetime.timezone.utc | ||
| ) | ||
|
|
||
| nullrow = rows[4] | ||
| for column, value in nullrow.items(): | ||
| if column == "rowindex": | ||
| assert value == 4 | ||
| else: | ||
| assert value is None |