Skip to main content

Microframework for python aws lambdas

Project description

braincube-aws-core

Microframework for Python AWS lambdas.

Language pypi License

Installation

pip install braincube-aws-core

Built With

  • asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
  • pydantic - Data validation using Python type hints.
  • pypika - Python Query Builder.

Application Controllers Example

import asyncio

from uuid import uuid4
from http import HTTPStatus

from core.app.data import HTTPRequest, HTTPResponse
from core.app.app_module import AppModule
from core.app.app_controller import AppController

from pydantic import BaseModel


class AccountDto(BaseModel):
    iban: str
    bban: str


data = {
    "a0a412d9-87ef-474b-9ac8-b682ec5e0fb3": AccountDto(iban="EUR27100777770209299700", bban="EURC12345612345678"),
    "5ebc25bd-e152-4a70-b251-d68e43be581e": AccountDto(iban="GR27100777770209299700", bban="GRC12345612345678"),
}

app = AppController("/accounts")


@app.get("/{id}")
async def get_account(request: HTTPRequest) -> HTTPResponse:
    account = data.get(request.path_params["id"])
    return HTTPResponse(HTTPStatus.OK if account else HTTPStatus.NO_CONTENT, account)


@app.post()
async def create_account(request: HTTPRequest[AccountDto]) -> HTTPResponse:
    data[uuid4()] = request.body
    return HTTPResponse(HTTPStatus.CREATED)


loop = asyncio.get_event_loop()

module = AppModule([app])


def main(event, context):
    return loop.run_until_complete(module.serve(event, context))

Dependency Injection Example

from core.di.injector import inject
from core.dal.postgres_connection import get_pool, Pool


@inject("data_warehouse_pool")
async def provide_warehouse_pool() -> Pool:
    return await get_pool()


@inject(qualifier="pool:data_warehouse_pool")
class BankService:

    def __init__(self, pool: Pool):
        self._pool = pool

Postgres Repository Example

from core.app.data import HTTPRequest
from core.utils.data import Order, OrderType
from core.dal.data import Key, Schema, Column, Relation, SimpleColumn, JoinType, JoinThrough, StatementField
from core.dal.postgres_connection import get_pool, Pool
from core.dal.postgres_repository import PostgresRepository

# schema definition
equities = Schema(
    table="equities",
    alias="e",
    primary_key=["id"],
    columns=[
        Column("id", updatable=False, insertable=False),
        Column("name"),
        Column("type"),
        Column("issuer_id", alias="issuerId"),
        Column("industry_sector", alias="industrySector"),
        Column("isin"),
        Column("reference"),
        Column("bloomberg_code", alias="bloombergCode"),
        Column("market_symbol", alias="marketSymbol"),
        Column("currency"),
        Column("country", ),
        Column("min_amount", alias="minAmount"),
    ],
    statement_fields=[
        StatementField("isTypeOne", statement="CASE WHEN e.type = 1 then True else False END")
    ],
    order=[
        Order(type=OrderType.asc, alias="name")
    ],
    relations=[
        Relation(
            table="parties",
            alias="p",
            columns=[
                SimpleColumn("name"),
                SimpleColumn("short_name", alias="shortName"),
            ],
            join_forced=False,
            join_type=JoinType.left,
            join_through=JoinThrough(from_column_name="issuer_id", to_column_name="id")
        )
    ]
)


# repository definition
class EquitiesRepo(PostgresRepository):

    def __init__(self, pool: Pool):
        super().__init__(pool, equities)


# repository usage

request = HTTPRequest()

repo = EquitiesRepo(await get_pool())

await repo.find_by_pk(Key(request.path_params["id"]), request.query_params.fields)

await repo.exists_by_pk(Key("9448a57b-f686-4935-b152-566baab712db"))

await repo.find_one(
    request.query_params.fields,
    conditions=request.query_params.conditions,
    order=request.query_params.order)

await repo.find_all(
    request.query_params.fields,
    conditions=request.query_params.conditions,
    order=request.query_params.order)

await repo.find_all_by_pk(
    [
        Key("9448a57b-f686-4935-b152-566baab712db"),
        Key("43c8ec37-9a59-44eb-be90-def391ba2f02")
    ],
    aliases=request.query_params.fields,
    order=request.query_params.order)

await repo.find_many(
    request.query_params.fields,
    conditions=request.query_params.conditions,
    page=request.query_params.page,
    order=request.query_params.order)

await repo.insert({
    "name": "Bursa de Valori Bucuresti SA",
    "type": 1,
    "industrySector": 40,
    "isin": "ROBVBAACNOR0",
    "bloombergCode": "BBG000BBWMC5",
    "marketSymbol": "BVB RO Equity",
    "currency": "RON",
    "country": "RO",
})

await repo.insert_bulk(
    aliases=["name", "type", "industrySector", "isin", "bloombergCode", "marketSymbol", "currency", "country"],
    data=[
        ["Bursa de Valori Bucuresti SA", 1, 40, "ROBVBAACNOR0", "BBG000BBWMC5", "BVB RO Equity", "RON", "RO"],
        ["Citigroup Inc", 1, 40, "US1729674242", "BBG000FY4S11", "C US Equity", "USD", "US"],
        ["Coca-Cola HBC AG", 1, 49, "CH0198251305", "BBG004HJV2T1", "EEE GA Equity", "EUR", "GR"],
    ]
)

await repo.update({
    "type": 1,
    "isin": 40,
}, request.query_params.conditions, request.query_params.fields)

await repo.update_by_pk(Key("9448a57b-f686-4935-b152-566baab712db"), {
    "type": 1,
    "isin": 40
})

await repo.delete(request.query_params.conditions, ["id", "name", "type"])

await repo.delete_by_pk(Key("9448a57b-f686-4935-b152-566baab712db"), ["id", "name", "type"])

await repo.fetch("SELECT * FROM equities WHERE type = $1 and isin = $2", [1, "TREEGYO00017"])

await repo.fetch_one("SELECT * FROM equities WHERE id = $1", ["2b67122a-f47e-41b1-b7f7-53be5ca381a0"])

await repo.execute("DELETE FROM equities WHERE id = $1", ["2b67122a-f47e-41b1-b7f7-53be5ca381a0"])

Query params format

fields=name, type, industrySector, isin, bloombergCode, parties_name, parties_shortName
type=1
isin=range(40, 49)
id=any(9448a57b-f686-4935-b152-566baab712db, 43c8ec37-9a59-44eb-be90-def391ba2f02)
page_no=1
page_size=50
top_size=50
order=name, id DESC

Local Development Requirements

To use the SAM CLI, you need the following tools.

Run server locally

# open ssh tunel
sudo sh ssh_tunnel_Analog_JBox.sh
# apply code changes to docker image
sam-api$ sam build
# start server locally on http://127.0.0.1:3000
sam-api$ sam local start-api --warm-containers EAGER
# or run function locally using event.json as parameter
sam-api$ sam local invoke ApiFunction --event events/event.json

Deploy to AWS

sam build --use-container
sam deploy --capabilities CAPABILITY_NAMED_IAM --guided --profile analog_user --region eu-west-1

Build and deploy new package version using twine

python3 -m pip install --upgrade pip
python3 -m pip install --upgrade build
python3 -m pip install --upgrade twine
python3 -m build
twine upload --skip-existing dist/*

Resources

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

braincube-aws-core-0.0.29.tar.gz (21.9 kB view details)

Uploaded Source

Built Distribution

braincube_aws_core-0.0.29-py3-none-any.whl (27.0 kB view details)

Uploaded Python 3

File details

Details for the file braincube-aws-core-0.0.29.tar.gz.

File metadata

  • Download URL: braincube-aws-core-0.0.29.tar.gz
  • Upload date:
  • Size: 21.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for braincube-aws-core-0.0.29.tar.gz
Algorithm Hash digest
SHA256 5afebe656980e1a4893430e2b03faaac2879f6336d38f3f13f78332cd53161c9
MD5 9870260fb0e5fc98efd853afcd12aa0f
BLAKE2b-256 6b56c874cd2f6f0f739d1a6b3abf5444759e47481915f3a8d3be6cffa26b75a5

See more details on using hashes here.

Provenance

File details

Details for the file braincube_aws_core-0.0.29-py3-none-any.whl.

File metadata

File hashes

Hashes for braincube_aws_core-0.0.29-py3-none-any.whl
Algorithm Hash digest
SHA256 dbc3515a97e759d0c2cb6624c137a9d761751dcd2ebed7f2baf4b069129caf39
MD5 a58ebae72dec34d94c3405be4cf6c5cf
BLAKE2b-256 ed4c5fe01a423d415b5ede138335defecc078669b6a9c8915e42f24620dae162

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page