noverde-serpens 2.7.5

A set of Python utilities, recipes and snippets

serpens

A set of Python utilities, recipes and snippets.

• SQS Utilities
• API Utilities
• Schema
• CSV Utils
• DynamoDB Documents

SQS Utilities

• This utility is a decorator that iterate by each sqs record.

• For each sqs record will be inserted a record object (from type sqs.Record) as argument that will process the sqs messages.

from serpens import sqs

@sqs.handler
def message_processor(record: sqs.Record):
    # code to process each sqs message
    print(record.body)

Record

• The client function that will process the sqs messages will receive an instance of sqs.Record dataclass. This class has the follow structure:

class Record:
    data: Dict[Any, Any]
    body: Union[dict, str]
    message_attributes: Dict[Any, Any]
    queue_name: str
    sent_datetime: datetime

Record attributes

• data: Contain all data from SQS message. This attribute is assigned in each iteration in SQS message.
• body: Return data["body"] converted to dict or str.
• message_attributes: Return the data["messageAttributes"] converted to dict.
• queue_name: Return the queue name extracted from data["eventSourceARN"].
• sent_datetime: Return the data["attributes"]["SentTimestamp"] converted to datetime.

API Utilities

• This utility is a wrapper to simplify working with lambda handlers. The decorator api.handler will decorate a function that will process a lambda and this function will receive a request argument (from type api.Request).

from serpens import api

@api.handler
def lambda_handler(request: api.Request):
    # Code to process the lambda
    print(request.body)

Request class

• The function that will process the lambda will receive an instance of sqs.Request dataclass. This class has the follow structure:

from serpens.api import AttrDict

class Request:
    authorizer: AttrDict
    body: Union[str, dict]
    path: AttrDict
    query: AttrDict
    headers: AttrDict
    identity: AttrDict

• Note: the objects from type AttrDict are objects built by a dict where the dict's key is an attribute of object. For example:

from serpens.api import AttrDict

obj = AttrDict({"foo": "bar"})
obj.foo # bar

Schema

• The Schema is a base class for create new classes with follow features:

• Static type check
• Method to convert an object to dict
• Method to create an object from json
• Method to create an object from dict
• Method to dump an object to string

Create a schema

from serpens.schema import Schema
from dataclasses import dataclass

@dataclass
class PersonSchema(Schema):
    name: str
    age: int

Create a schema object

person = PersonSchema('Mike', 30)

print(person.name)
print(person.age)

Create a schema object from a dict.

person_obj = PersonSchema.load({'name': 'Mike', 'age': 18})

print(person_obj.name)
print(person_obj.age)

Create a schema object from a json string.

import json
data = json.dumps({'name': 'mike', 'age': 20})
person_obj = PersonSchema.loads(data)

print(person_obj.name)
print(person_obj.age)

Convert a schema object to dict.

p1 = PersonSchema('Mike', 30)
person_dct = PersonSchema.dump(p1)

print(person_dct['name'])
print(person_dct['age'])

Convert a schema object to json string.

p1 = PersonSchema('Mike', 30)
person_str = PersonSchema.dumps(p1)

print(person_str)

CSV Utils

• Utility for read and write csv. This utility is useful for read csv with BOM or read csv encoded as ISO-8859.

Read CSV

from serpens import csvutils as csv

dict_reader = csv.open_csv_reader('fruits_iso8859.csv')

for record in dict_reader:
    print(record)

Write CSV

from serpens import csvutils as csv

writer = csv.open_csv_writer('out.csv')
writer.writerow(["id", "name"])
writer.writerow(["1", "Açaí"])

del writer

Database

This utilities are useful for working with database.

Migrate databases

• This migrations use yoyo-migration.

from serpens import database

database_url = "postgres://user:password@host/db"
path = "/path/to/migrations" # yoyo migrations

database.migrate(database_url, path)

Create a Pony Database instance

"The Database object manages database connections using a connection pool."

from serpens import database

database_url = "postgres://user:password@host/db"
db = database.setup(database_url)
print(db.provider_name)

DynamoDB Documents

Serpens provides a base class (called BaseDocument) for working with tables from DynamoDB.

Create a document mapping a DynamoDB table

from serpens.document import BaseDocument
from dataclasses import dataclass

@dataclass
class PersonDocument(BaseDocument):
    _table_name_ = 'person'
    id: str
    name: str

Save data in DynamoDB table

person = PersonDocument(id="1", name="Ana")
person.save()

Get data from key

• Obs: If the search doesn't find an item by its key, the return is None

person = PersonDocument.get_by_key({"id": "1"})

person.id # 1
person.name # Ana

Get table

person_table = PersonDocument.get_table()
person_table # dynamodb.Table(name='person')