How can sqlalchemy be used for partitioning in Postgres?

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SQLAlchemy can be used for partitioning in Postgres by utilizing the PostgreSQL-specific partitioning features.

To create partitions using SQLAlchemy, the following steps can be followed:

1. Create a partitioned table with a partition key column. This will be the column used to partition the data.

from sqlalchemy import Table, Column, Integer, String
from sqlalchemy.schema import CheckConstraint
from sqlalchemy.dialects.postgresql import INTEGER

metadata = MetaData()

parent_table = Table(
    'parent_table',
    metadata,
    Column('id', Integer, primary_key=True),
    Column('name', String),
    Column('partition_key', INTEGER),
    CheckConstraint('partition_key >= 0 AND partition_key < 10', name='partition_key_check')
)

1. Create child tables that inherit from the parent table and specify the partition key value range for each child table.

child_table_0 = Table(
    'child_table_0',
    metadata,
    Column('id', Integer, primary_key=True),
    Column('name', String),
    Column('partition_key', INTEGER),
    CheckConstraint('partition_key = 0', name='partition_key_check')
)

child_table_1 = Table(
    'child_table_1',
    metadata,
    Column('id', Integer, primary_key=True),
    Column('name', String),
    Column('partition_key', INTEGER),
    CheckConstraint('partition_key = 1', name='partition_key_check')
)

 ...

1. Use SQLAlchemy's Table.partition method to specify which child table a row should be inserted or queried from based on its partition key value.

# Insert data into the partitioned table
conn.execute(parent_table.insert(), [
    {'name': 'Foo', 'partition_key': 0},
    {'name': 'Bar', 'partition_key': 1},
    {'name': 'Baz', 'partition_key': 2},
    ...
])

# Query data from a specific child table
result = conn.execute(child_table_0.select())