Skip to main content

Test BigQuery query using BigQuery

Project description

BigQueryのクエリをテストするためのツール

Run pytest

BigQueryへのクエリロジックのテストができます

Basic Usage

Simple

from bqqtest import QueryTest
from google.cloud import bigquery

# expected
expected_schema = [
    {"name": "name", "type": "STRING", "mode": "NULLABLE"},
    {"name": "value", "type": "INT64", "mode": "NULLABLE"},
]
expected_datum = [["abc", 100], ["bbb", 333]]
expected = {"schema": expected_schema, "datum": expected_datum}

# actual
target_schema = [
    {"name": "name", "type": "STRING", "mode": "NULLABLE"},
    {"name": "value", "type": "INT64", "mode": "NULLABLE"},
]
target_datum = [["abc", 100], ["bbb", 333]]
tables = {"test.target_table": {"schema": target_schema, "datum": target_datum}}
eval_query = {"query": "SELECT * FROM test.target_table", "params": []}

qt = QueryTest(bigquery.Client(), expected, tables, eval_query)
success, diff = qt.run()
success  # True

Group By

from bqqtest import QueryTest
from google.cloud import bigquery

# expected
expected_schema = [
    {"name": "item", "type": "STRING", "mode": "NULLABLE"},
    {"name": "total", "type": "INT64", "mode": "NULLABLE"},
]
expected_datum = [["abc", 300], ["bbb", 333]]
expected = {"schema": expected_schema, "datum": expected_datum}

# actual
target_schema = [
    {"name": "item", "type": "STRING", "mode": "NULLABLE"},
    {"name": "value", "type": "INT64", "mode": "NULLABLE"},
]
target_datum = [["abc", 100], ["bbb", 333], ["abc", 200]]
tables = {"test.target_table": {"schema": target_schema, "datum": target_datum}}
eval_query = {
    "query": "SELECT item, SUM(value) AS total FROM test.target_table GROUP BY item",
    "params": [],
}

qt = QueryTest(bigquery.Client(), expected, tables, eval_query)
success, diff = qt.run()
success  # True

Multi Table

from bqqtest import QueryTest
from google.cloud import bigquery


# expected
expected_schema = [
    {"name": "item", "type": "STRING", "mode": "NULLABLE"},
    {"name": "value", "type": "INT64", "mode": "NULLABLE"},
]
expected_datum = [["abc", 100], ["bbb", 333], ["xxxx", 888], ["zzzz", 999]]
expected = {"schema": expected_schema, "datum": expected_datum}

# actual
target_schema = [
    {"name": "item", "type": "STRING", "mode": "NULLABLE"},
    {"name": "value", "type": "INT64", "mode": "NULLABLE"},
]
target_datum1 = [["abc", 100], ["bbb", 333]]
target_datum2 = [["xxxx", 888], ["zzzz", 999]]
tables = {
    "test.table1": {"schema": target_schema, "datum": target_datum1},
    "test.table2": {"schema": target_schema, "datum": target_datum2},
}
eval_query = {
    "query": "SELECT * FROM `test.table1` UNION ALL SELECT * FROM `test.table2`",
    "params": [],
}

qt = QueryTest(bigquery.Client(), expected, tables, eval_query)
success, diff = qt.run()
success  # True

特徴

see also https://qiita.com/tamanobi/items/9434ca0dbd5f0d3018d9

  • WITH を利用して、 BigQuery に保存されないテストデータを一時的に生成します。
    • BigQuery は保存されているデータ走査した量とAPIリクエスト数で課金されるため、費用抑えてユニットテストができます。
    • 料金の詳細は、 BigQuery の公式ドキュメントを参照してください
  • テストをするために、クエリを書き直す必要はありません
    • ライブラリ内部では、対象テーブルの Identifier を書き換えてテーブルを差し替えます

注意

BigQuery へ直接クエリを発行します。

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bqqtest-0.6.0.tar.gz (10.7 kB view hashes)

Uploaded Source

Built Distribution

bqqtest-0.6.0-py3-none-any.whl (12.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page