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camus

A Records like database API that works with Aurora Serverless Data API

1.0.0
pipPyPI
Maintainers
1

Camus

Camus is a raw SQL library enabling an ease integration with the new Aurora Serverless Data API. Its API is based on the powerful Records library.

Camus Aurora Execution

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 in 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 tries to maintain the same API of the Records library, so you have the same access patterns:

  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="rafael@email.com")
    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!

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