sqlalchemy-iris
An InterSystems IRIS dialect for SQLAlchemy.
Pre-requisites
This dialect requires SQLAlchemy, InterSystems DB-API driver, and iris-embedded-python-wrapper. They are
specified as requirements so pip will install them if they are not already in place. To install, just:
pip install sqlalchemy-iris
Or to use InterSystems official driver support
pip install sqlalchemy-iris[intersystems]
Usage
In your Python app, you can connect to the database via:
from sqlalchemy import create_engine
engine = create_engine("iris://_SYSTEM:SYS@localhost:1972/USER")
To use with Python Embedded mode through iris-embedded-python-wrapper, when run next to IRIS
from sqlalchemy import create_engine
engine = create_engine("iris+emb://USER")
The legacy path form iris+emb:///USER is also supported.
To use with InterSystems official driver, does not work in Python Embedded mode
from sqlalchemy import create_engine
engine = create_engine("iris+intersystems://_SYSTEM:SYS@localhost:1972/USER")
IRIS Cloud SQL requires SSLContext
url = engine.URL.create(
drivername="iris",
host=host,
port=443,
username='SQLAdmin',
password=password,
database='USER',
)
sslcontext = ssl.create_default_context(cafile="certificateSQLaaS.pem")
engine = create_engine(url, connect_args={"sslcontext": sslcontext})
InterSystems IRIS
You can run your instance of InterSystems IRIS Community Edition with Docker
docker run -d --name iris \
-p 1972:1972 \
-p 52773:52773 \
-e IRIS_USERNAME=_SYSTEM \
-e IRIS_PASSWORD=SYS \
intersystemsdc/iris-community:preview
Examples
IRISVector
from sqlalchemy import Column, MetaData, Table, select
from sqlalchemy.sql.sqltypes import Integer, UUID
from sqlalchemy_iris import IRISVector
from sqlalchemy import create_engine
from sqlalchemy.orm import DeclarativeBase
import uuid
DATABASE_URL = "iris://_SYSTEM:SYS@localhost:1972/USER"
engine = create_engine(DATABASE_URL, echo=False)
# Create a table metadata
metadata = MetaData()
def main():
demo_table = Table(
"demo_table",
metadata,
Column("id", Integer, primary_key=True, autoincrement=True),
Column("uuid", UUID),
Column("embedding", IRISVector(item_type=float, max_items=3)),
)
demo_table.drop(engine, checkfirst=True)
demo_table.create(engine, checkfirst=True)
with engine.connect() as conn:
conn.execute(
demo_table.insert(),
[
{"uuid": uuid.uuid4(), "embedding": [1, 2, 3]},
{"uuid": uuid.uuid4(), "embedding": [2, 3, 4]},
],
)
conn.commit()
result = conn.execute(
demo_table.select()
).fetchall()
print("result", result)
main()
Port 1972 is used for binary communication (this driver, xDBC and so on), and 52773 is for web (Management Portal, IRIS based web-applications and API's).
The System Management Portal is available by URL: http://localhost:52773/csp/sys/UtilHome.csp
1 maintainer
Metadata
1 maintainer
Release files for sqlalchemy-iris 0.20.0
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|---|---|---|---|---|
| sqlalchemy_iris-0.20.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 78.2 kB
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