aio-ormsql 0.0.5

Simple asynchronous MySQL ORM class.

aio_ormsql

Simple asynchronous MySQL ORM class.

Easy install

pip3 install aio_ormsql

Required

• pip3 install asyncio aiomysql
• Python 3.6+

Example usage

1. Do imports:

from aio_ormsql.db import DataBase
from aio_ormsql.classes Table, Column, WHERE

Where:

• DataBase - class for working with MySQL
• Table - class for creating a new table
• Column - class for creating a columns
• WHERE - class for creating where statements

2. Follow examples ans see their output:

Examples

Creating table

tbl = Table(
    'tests',
    Column('id', int),
    Column('tname', str)
)

Connection to database

db = DataBase('admin', 'admin', 'tests')
await db.connect()

Simple WHERE statement

where = WHERE(
    tbl.tname == 'admin'
)
print(where)

# Output:
# WHERE `tname`='admin'

Another WHERE statement

where2 = WHERE(
    (tbl.id >= 20) | (tbl.tname == 'admin')
)
print(where2)

# Output:
# WHERE `id`>=20 OR `tname`='admin'

SELECT example

statement = await db.select(
    [tbl.id, tbl.tname], where=where, table=tbl, back=True
)
print(statement)

# Output:
# SELECT DISTINCT `id`, `tname` FROM `tests` WHERE `tname`='admin'

SELECT example 2

statement2 = await db.select(
    [tbl.id, tbl.tname], False, where2, table=tbl, back=True
)
print(statement2)

# Output:
# SELECT`id`, `tname` FROM `tests` WHERE `id`>=20 OR `tname`='admin'

INSERT example

statement3 = await db.insert(
    {
        tbl.id: 123,
        tbl.tname: 'Johan'
    },
    tbl,
    back=True
)
print(statement3)

# Output:
# INSERT INTO `tests` (`id`, `tname`) VALUES (123, 'Johan')

INSERT example 2

statement4 = await db.update(
    {
        tbl.id: '123',
        tbl.tname: 'Admin'
    },
    WHERE(tbl.tname == 'Johan'),
    tbl,
    back=True
)
print(statement4)

# Output:
# UPDATE `tests` SET `id`=123, `tname`='Admin' WHERE `tname`='Johan'

Working with large DB

array = db.fetch_gen(await db.select(
    [tbl.id, tbl.tname], back=True
))

async for item in array:
    print('New pair:', item)
    # And you can see row-by-row output

Closing connection and wait for completing tasks

await db.close()