anna-geller

from prefect import task, flow
from prefect import get_run_logger
from typing import Any


@task
def say_hi(user_name: str, question: str, answer: Any) -> None:
    logger = get_run_logger()
    logger.info("Hello from Prefect, %s! 👋", user_name)
    logger.info("The answer to the %s question is %s! 🤖", question, answer)

anna-geller

import asyncio
import textwrap

from client import from_dict
from dotenv import load_dotenv
import os


load_dotenv()

anna-geller

from airflow.decorators import dag, task
import pendulum

from airflow_prefect import send_prefect_event_callback


@dag(
    schedule=None,
    start_date=pendulum.datetime(2023, 1, 24, tz="UTC"),
    catchup=False,

anna-geller

from airflow.decorators import dag, task
import pendulum

from airflow_prefect import send_prefect_event_callback


@dag(
    schedule=None,
    start_date=pendulum.datetime(2023, 1, 24, tz="UTC"),
    catchup=False,

anna-geller

from airflow.hooks.base import BaseHook
import pendulum
import requests
import uuid


def get_prefect_event(context):
    prefect_event = [
        {
            "id": str(uuid.uuid4()),

anna-geller

from airflow.hooks.base import BaseHook
import pendulum
import requests
import uuid


def get_prefect_event(context):
    prefect_event = [
        {
            "id": str(uuid.uuid4()),

anna-geller

from prefect import get_run_logger


def enable_loguru_support() -> None:
    """Redirect loguru logging messages to the prefect run logger.

    This function should be called from within a Prefect task or flow before calling any module that uses loguru.
    This function can be safely called multiple times.

    Example Usage:

anna-geller

from prefect import flow, task
from loguru import logger
from prefect_utils.loguru import enable_loguru_support


def mycustom_function():
    logger.info("I'm a custom function")


@task

anna-geller

from datetime import timedelta
from prefect.tasks import task_input_hash
from prefect import task, flow
import time
from prefect.context import get_run_context


def cache_within_flow_run(context, parameters):
    id_ = get_run_context().flow_run.dict().get('id')
    key = f"{id_}-{task_input_hash(context, parameters)}"

anna-geller

from prefect import task, flow, get_run_logger
from prefect_dask import DaskTaskRunner
import time


@task
def extract() -> list:
    logger = get_run_logger()
    logger.info("extract")
    return [1, 2, 3, 4, 5, 6]