GuiMarthe / camus

A simpler way to use Aurora Serverless Data API with Python.

Camus

Camus is a raw SQL library enabling an ease integration with the new Aurora Serverless Data API. It is a fork of the powerful Records library.

Instalation

The recommended installation method is pipenv:

$ pipenv install camus

Basic Usage

First you need to have an Aurora cluster ARN and a Secret ARN. If don't have one yet, just follow the Data API Getting Started Guide.

With that in hands, let's drop some query to our database:

import camus

db = camus.Database(
    resource_arn="arn:aws:rds:us-east-1:123456789012:cluster:your-cluster-name",
    secret_arn="arn:aws:secretsmanager:us-east-1:123456789012:secret:your-secret-name-ByH87J",
    dbname="mydb",
)

rows = db.query("SELECT * FROM users")

You can grab one row at time (like in Records library)

>>> rows[0]
<camus.Record at 0x109bfbd30>

Or iterate over them:

 for r in rows:
     print(r.name, r.email)

Like mentioned before, Camus is a fork of the Records library, so almost all access pattern are equal:

  row.email
  row['email']
  row[3]

Other options include rows.as_dict() and rows.as_dict(ordered=True)

Transactions

Data API transactions are supported by Camus:

with db.transaction() as txid:
    db.query("INSERT INTO users (name, email) VALUES (:name, :email)", name="Rafael", email="[e-mail]")
    db.query("UPDATE posts SET title = :title WHERE id = :id", title="New Title", id=999)

If any exception is raised when executing any of the queries, a rollback is performed automatically.

That's all folks

Thanks for the awesome @kennethreitz for providing his knowledge on the excelent Records library and all the talks he has given over the years!