doris-alchemy


Namedoris-alchemy JSON
Version 0.2.5 PyPI version JSON
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home_pageNone
SummaryApache Doris dialect for SQLAlchemy
upload_time2024-12-20 13:42:40
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authorNone
requires_python>=3.10.12
licenseApache Software License
keywords apache doris sqlalchemy
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            # Apache Doris Dialect for SQLAlchemy

This is a fork of [sqlalchemy-doris](https://github.com/actcwlf/sqlalchemy-doris) project.
Which is in turn - a fork of [pydoris](https://pypi.org/project/pydoris/1.0.1/)

This implementation fixes a bunch of issues with typing. And adds support for sqlalchemy ORM.

## Features
* support SQLAlchemy 2.
* support pymysql and mysqlclient as driver.
* support SQLAlchemy table creation
* support for SQLALchemy ORM
* convenient DorisBase class for declaring ORM models

## Installation
Use
```bash
pip install doris-alchemy[pymysql]
```
for pymysql.

Or

```bash
pip install doris-alchemy[mysqldb]
```
for mysqlclient.

Note doris-alchemy uses pymysql as default connector for compatibility. 
If both pymysql and mysqlclient are installed, mysqlclient is preferred.


## Usage
```python

from sqlalchemy import create_engine

engine = create_engine(f"doris+pymysql://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4")
# or
engine = create_engine(f"doris+mysqldb://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4")

```

## Create Table (Imperative style)
```python
import sqlalchemy as sa
from sqlalchemy import create_engine
from doris_alchemy import datatype
from doris_alchemy import HASH, RANGE

engine = create_engine(f"doris://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4")


metadata_obj = sa.MetaData()
table = Table(
    'dummy_table',
    METADATA,
    Column('id', Integer, primary_key=True),
    Column('name', String(64), nullable=False),
    Column('description', Text),
    Column('date', DateTime),
    
    doris_unique_key=('id'),
    doris_partition_by=RANGE('id'),
    doris_distributed_by=HASH('id'),
    doris_properties={"replication_allocation": "tag.location.default: 1"},
)

table.create(engine)

```

SQL is
```sql
CREATE TABLE dummy_table (
        id INTEGER NOT NULL, 
        name VARCHAR(64) NOT NULL, 
        description TEXT, 
        date DATETIME
)
UNIQUE KEY (`id`)
PARTITION BY RANGE(`id`) ()
DISTRIBUTED BY HASH(`id`) BUCKETS auto
PROPERTIES (
    "replication_allocation" = "tag.location.default: 1"
)
```

## Create Table (Declarative style / ORM)
```python
from sqlalchemy import create_engine
from doris_alchemy import datatype, DorisBase
from doris_alchemy import HASH, RANGE

engine = create_engine(f"doris://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4")

class Dummy(DorisBase):
    __tablename__ = 'dummy_two'
    
    id:             Mapped[int] = mapped_column(BigInteger, primary_key=True)
    name:           Mapped[str] = mapped_column(String(127))
    description:    Mapped[str]
    date:           Mapped[datetime]
    
    __table_args__ = {
        'doris_properties': {"replication_allocation": "tag.location.default: 1"}
        }
    doris_unique_key = 'id'
    doris_distributed_by = HASH('id')
    doris_partition_by = RANGE('id')


DorisBase.metadata.create_all(engine)
```
SQL is 
```sql
CREATE TABLE dummy_two (
        id BIGINT NOT NULL, 
        name VARCHAR(127) NOT NULL, 
        description TEXT NOT NULL, 
        date DATETIME NOT NULL
)
UNIQUE KEY (`id`)
PARTITION BY RANGE(`id`) ()
DISTRIBUTED BY HASH(`id`) BUCKETS auto
PROPERTIES (
    "replication_allocation" = "tag.location.default: 1"
)
```

### Insertin and selecting

```python
from sqlalchemy.orm import Session
from sqlalchemy import select, insert, create_engine
from datetime import datetime

engine = create_engine(f"doris+mysqldb://{USER}:{PWD}@{HOST}:{PORT}/{DB}")

row = {
        'id': 0,
        'name': 'Airbus',
        'description': 'Construction bureau',
        'date': datetime(2024, 2, 10)
    }
    
with Session(engine) as s:
    q = insert(Dummy).values([row])
    s.execute(q)
    sel = select(Dummy)
    res = s.execute(sel)
    print(list(res))
```

            

Raw data

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    "description": "# Apache Doris Dialect for SQLAlchemy\n\nThis is a fork of [sqlalchemy-doris](https://github.com/actcwlf/sqlalchemy-doris) project.\nWhich is in turn - a fork of [pydoris](https://pypi.org/project/pydoris/1.0.1/)\n\nThis implementation fixes a bunch of issues with typing. And adds support for sqlalchemy ORM.\n\n## Features\n* support SQLAlchemy 2.\n* support pymysql and mysqlclient as driver.\n* support SQLAlchemy table creation\n* support for SQLALchemy ORM\n* convenient DorisBase class for declaring ORM models\n\n## Installation\nUse\n```bash\npip install doris-alchemy[pymysql]\n```\nfor pymysql.\n\nOr\n\n```bash\npip install doris-alchemy[mysqldb]\n```\nfor mysqlclient.\n\nNote doris-alchemy uses pymysql as default connector for compatibility. \nIf both pymysql and mysqlclient are installed, mysqlclient is preferred.\n\n\n## Usage\n```python\n\nfrom sqlalchemy import create_engine\n\nengine = create_engine(f\"doris+pymysql://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4\")\n# or\nengine = create_engine(f\"doris+mysqldb://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4\")\n\n```\n\n## Create Table (Imperative style)\n```python\nimport sqlalchemy as sa\nfrom sqlalchemy import create_engine\nfrom doris_alchemy import datatype\nfrom doris_alchemy import HASH, RANGE\n\nengine = create_engine(f\"doris://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4\")\n\n\nmetadata_obj = sa.MetaData()\ntable = Table(\n    'dummy_table',\n    METADATA,\n    Column('id', Integer, primary_key=True),\n    Column('name', String(64), nullable=False),\n    Column('description', Text),\n    Column('date', DateTime),\n    \n    doris_unique_key=('id'),\n    doris_partition_by=RANGE('id'),\n    doris_distributed_by=HASH('id'),\n    doris_properties={\"replication_allocation\": \"tag.location.default: 1\"},\n)\n\ntable.create(engine)\n\n```\n\nSQL is\n```sql\nCREATE TABLE dummy_table (\n        id INTEGER NOT NULL, \n        name VARCHAR(64) NOT NULL, \n        description TEXT, \n        date DATETIME\n)\nUNIQUE KEY (`id`)\nPARTITION BY RANGE(`id`) ()\nDISTRIBUTED BY HASH(`id`) BUCKETS auto\nPROPERTIES (\n    \"replication_allocation\" = \"tag.location.default: 1\"\n)\n```\n\n## Create Table (Declarative style / ORM)\n```python\nfrom sqlalchemy import create_engine\nfrom doris_alchemy import datatype, DorisBase\nfrom doris_alchemy import HASH, RANGE\n\nengine = create_engine(f\"doris://{user}:{password}@{host}:{port}/{database}?charset=utf8mb4\")\n\nclass Dummy(DorisBase):\n    __tablename__ = 'dummy_two'\n    \n    id:             Mapped[int] = mapped_column(BigInteger, primary_key=True)\n    name:           Mapped[str] = mapped_column(String(127))\n    description:    Mapped[str]\n    date:           Mapped[datetime]\n    \n    __table_args__ = {\n        'doris_properties': {\"replication_allocation\": \"tag.location.default: 1\"}\n        }\n    doris_unique_key = 'id'\n    doris_distributed_by = HASH('id')\n    doris_partition_by = RANGE('id')\n\n\nDorisBase.metadata.create_all(engine)\n```\nSQL is \n```sql\nCREATE TABLE dummy_two (\n        id BIGINT NOT NULL, \n        name VARCHAR(127) NOT NULL, \n        description TEXT NOT NULL, \n        date DATETIME NOT NULL\n)\nUNIQUE KEY (`id`)\nPARTITION BY RANGE(`id`) ()\nDISTRIBUTED BY HASH(`id`) BUCKETS auto\nPROPERTIES (\n    \"replication_allocation\" = \"tag.location.default: 1\"\n)\n```\n\n### Insertin and selecting\n\n```python\nfrom sqlalchemy.orm import Session\nfrom sqlalchemy import select, insert, create_engine\nfrom datetime import datetime\n\nengine = create_engine(f\"doris+mysqldb://{USER}:{PWD}@{HOST}:{PORT}/{DB}\")\n\nrow = {\n        'id': 0,\n        'name': 'Airbus',\n        'description': 'Construction bureau',\n        'date': datetime(2024, 2, 10)\n    }\n    \nwith Session(engine) as s:\n    q = insert(Dummy).values([row])\n    s.execute(q)\n    sel = select(Dummy)\n    res = s.execute(sel)\n    print(list(res))\n```\n",
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