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        "author": "Lofton Harmon",
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        "description": "# py-data-api - Data API Client for Python\n\npy-data-api is a user-friendly client which supports SQLAlchemy models.\nAlso, the package includes DB API 2.0 Client and SQLAlchemy Dialects.\n\n## Features\n- A user-friendly client which supports SQLAlchemy models\n- SQLAlchemy Dialects (experimental)\n- DB API 2.0 compatible client [PEP 249](https://www.python.org/dev/peps/pep-0249/)\n\n## What's AWS Aurora Serverless's Data API?\nhttps://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html\n\n## This project is an experimental phase.\nWarning: Some interface will be changed.\n\n## How to install\npydataapi requires Python 3.6.1 or later \n```bash\n$ pip install pydataapi\n```\n\n## Example\n\n```python\nfrom typing import List\n\nfrom sqlalchemy import Column, Integer, String\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.orm import Query\nfrom sqlalchemy.sql import Insert\n\nfrom pydataapipostgres import DataAPI, transaction, Result, Record\n\n\nclass Pets(declarative_base()):\n    __tablename__ = 'pets'\n    id = Column(Integer, primary_key=True, autoincrement=True)\n    name = Column(String(255, collation='utf8_unicode_ci'), default=None)\n\n\ndatabase: str = 'test'\nresource_arn: str = 'arn:aws:rds:us-east-1:123456789012:cluster:serverless-test-1'\nsecret_arn: str = 'arn:aws:secretsmanager:us-east-1:123456789012:secret:serverless-test1'\n\n\ndef example_with_statement():\n    # DataAPI supports with statement for handling transaction\n    with DataAPI(database=database, resource_arn=resource_arn, secret_arn=secret_arn) as data_api:\n\n        # start transaction\n\n        insert: Insert = Insert(Pets, {'name': 'dog'})\n        # INSERT INTO pets (name) VALUES ('dog')\n\n        # `execute` accepts SQL statement as str or SQL Alchemy SQL objects\n        result: Result = data_api.execute(insert)\n        print(result.number_of_records_updated)\n        # 1\n\n        query = Query(Pets).filter(Pets.id == 1)\n        result: Result = data_api.execute(query)  # or data_api.execute('select id, name from pets')\n        # SELECT pets.id, pets.name FROM pets WHERE pets.id = 1\n\n        # `Result` like a Result object in SQL Alchemy\n        print(result.scalar())\n        # 1\n\n        print(result.one())\n        # [Record<id=1, name='dog'>]\n\n        # `Result` is Sequence[Record]\n        records: List[Record] = list(result)\n        print(records)\n        # [Record<id=1, name='dog'>]\n\n        # Record is Sequence and Iterator\n        record = records[0]\n        print(record[0])\n        # 1\n        print(record[1])\n        # dog\n\n        for column in record:\n            print(column)\n            # 1 ...\n\n        # show record as dict()\n        print(record.dict())\n        # {'id': 1, 'name': 'dog'}\n\n        # batch insert\n        insert: Insert = Insert(Pets)\n        data_api.batch_execute(insert, [\n            {'id': 2, 'name': 'cat'},\n            {'id': 3, 'name': 'snake'},\n            {'id': 4, 'name': 'rabbit'},\n        ])\n\n        result = data_api.execute('select * from pets')\n        print(list(result))\n        # [Record<id=1, name='dog'>, Record<id=2, name='cat'>, Record<id=3, name='snake'>, Record<id=4, name='rabbit'>]\n\n        # result is a sequence object\n        for record in result:\n            print(record)\n            # Record<id=1, name='dog'> ...\n\n        # commit\n\n\ndef example_decorator():\n    pet_names: List[str] = ['dog', 'cat', 'snake']\n    add_pets(pet_names)\n\n\n@transaction(database=database, resource_arn=resource_arn, secret_arn=secret_arn)\ndef add_pets(data_api: DataAPI, pet_names: List[str]) -> None:\n    # start transaction\n    for pet_name in pet_names:\n        data_api.execute(Insert(Pets, {'name': pet_name}))\n        # some logic ...\n\n    # commit\n\n\ndef example_simple_execute():\n    data_api = DataAPI(resource_arn, secret_arn, database=database)\n    result: Result = data_api.execute('show tables')\n    print(result.scalar())\n    # Pets\n\n\ndef example_rollback():\n    with DataAPI(resource_arn, secret_arn) as data_api:\n        data_api.execute(Insert(Pets, {'name': 'dog'}))\n        # you can rollback by Exception\n        raise Exception\n\n\ndef example_rollback_with_custom_exception():\n    class OriginalError(Exception):\n        pass\n\n    with DataAPI(resource_arn, secret_arn, rollback_exception=OriginalError) as data_api:\n\n        data_api.execute(Insert(Pets, {'name': 'dog'}))\n        # some logic ...\n\n        # rollback when happen `rollback_exception`\n        raise OriginalError  # rollback\n\n        # raise Exception <- DataAPI don't rollback\n\ndef example_driver_for_sqlalchemy():\n    from sqlalchemy.engine import create_engine\n    engine = create_engine(\n        'mysql+pydataapi://',\n        connect_args={\n            'resource_arn': 'arn:aws:rds:us-east-1:123456789012:cluster:dummy',\n            'secret_arn': 'arn:aws:secretsmanager:us-east-1:123456789012:secret:dummy',\n            'database': 'test'}\n    )\n\n    result: ResultProxy = engine.execute(\"select * from pets\")\n    print(result.fetchall())\n\n```\n\n\n",
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