Use Pydantic Models to handle AWS DynamoDB tables
Project description
Welcome to Coraline
Coraline is a Python library that aims to use Pydantic models to work with AWS DynamoDB tables.
Install
$ pip install coraline
Documentation
- TODO
Quick Start:
import uuid
from enum import Enum
from coraline import CoralModel, KeyField, HashType
from pydantic import SecretStr, Field
class UserType(Enum):
USER = "USER"
ADMIN = "ADMIN"
class Users(CoralModel):
user_id: uuid.UUID = KeyField(default=lambda: uuid.uuid4(), hash_key=HashType.HASH, alias="userId")
user_type: UserType = KeyField(..., hash_type=HashType.RANGE, alias="userType")
name: str
age: int = Field(..., gt=0)
password: SecretStr
Users.get_or_create_table()
new_user = Users(name="John Doe", user_type=UserType.USER, age=30, password="123456")
new_user.save()
This class will create a DynamoDB table named Users
, with PAY_PER_REQUEST
billing mode and using default AWS
session, with the following fields:
userId
as a String. It's the Table's Hash Key.userType
as a String. It's the Table's Range Key.name
as a Stringemail
as a Numberpassword
as a String
Configuring the table
Use the CoralConfig
class to configure your table.
import uuid
from enum import Enum
from coraline import CoralModel, KeyField, HashType, CoralConfig, BillingMode
from pydantic import SecretStr, Field
class UserType(Enum):
USER = "USER"
ADMIN = "ADMIN"
def to_camel(string: str) -> str:
return ''.join(word.capitalize() for word in string.split('_'))
# CoralModel is a subclass of Pydantic's BaseModel
class Users(CoralModel):
# CoralConfig is a subclass of Pydantic's ConfigDict
model_config = CoralConfig(
table_name="MyUsers",
billing_mode=BillingMode.PROVISIONED,
read_capacity_units=5,
write_capacity_units=5,
alias_generator=to_camel,
extra_table_params={
"DeletionProtectionEnabled": True,
"Tags": [
{
"Key": "Project",
"Value": "MyProject"
}
]
}
)
# KeyField is a sub method of Pydantic's Field
user_id: uuid.UUID = KeyField(default=lambda: uuid.uuid4(), hash_key=HashType.HASH)
user_type: UserType = KeyField(..., hash_type=HashType.RANGE)
name: str
age: int = Field(..., gt=0)
password: SecretStr
For Table Name, Billing Methods, you can use the BillingMode
and Capacity Units constants. For any other parameter
accepted by boto3
's create_table
use the extra_table_params
parameter.
Configuring the Client
To configure boto3's client credentials, Coraline will:
- Check for Class specific configuration in
model_config
- Check for Coraline Environment Variables (
ex.
CORALINE_AWS_REGION
,CORALINE_AWS_ACCESS_KEY_ID
,CORALINE_AWS_SECRET_ACCESS_KEY
) - Check for AWS Environment Variables (ex.
AWS_REGION
,AWS_ACCESS_KEY_ID
,AWS_SECRET_ACCESS_KEY
)
Env Example:
# Add to .env file:
AWS_REGION="local"
CORALINE_ENDPOINT_URL="http://localhost:8000"
Class Example:
class Users(CoralModel):
model_config = CoralConfig(
aws_region="local",
endpoint_url="http://localhost:8000"
)
Basic Operations
Get or Create Table
Use to get Table info or create the table if it doesn't exist.
Users.get_or_create_table()
Check if Record exists
Use to check if a record exists in the table. You need to pass on the parameters all hash and range keys defined in Model:
user_exists = Users.exists(user_id="12345678-1234-1234-1234-123456789012", user_type=UserType.USER)
Get Record
Use to get a record from the table. You need to pass on the parameters all hash and range keys defined in Model:
user = Users.get(user_id="12345678-1234-1234-1234-123456789012", user_type=UserType.USER)
Save Record
Use to save a record in the table. You need to pass on the parameters all hash and range keys defined in Model:
new_user = Users(name="John Doe", user_type=UserType.USER, age=30, password="123456")
new_user.save()
Using boto3's Client
You can use boto3's client to perform any operation you need. Just use the get_client
method:
new_user = Users(name="John Doe", user_type=UserType.USER, age=30, password="123456")
new_user.save()
new_user.get_client().create_backup(TableName=new_user.get_table_name(), BackupName="MyBackup")
Future Implementations
- Add support for Query and Scan operations
- Add support for Global and Local Secondary Indexes
- Add Documentation
Not working?
Don't panic. Get a towel and, please, open an issue.
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