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/*
purchase table example

transaction_date        |    customer_id    |    purchase_price    |    category

2022-01-01                    customer_A           $10                  jewelry 

2022-01-02                    customer_A           $1                   t-shirts

...

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import boto3

dynamodb = boto3.resource("dynamodb")

params = {
    "TableName": "customer_purchase_ts",
        "KeySchema": [
            {"AttributeName": "customer_id", "KeyType": "HASH"}
        ],
        "LocalSecondaryIndexes": [

achad4

import boto3

dynamodb = boto3.resource("dynamodb")

params = {
    'TableName': "customer_purchase_ts",
    "KeySchema": [
            {"AttributeName": "customer_id", "KeyType": "HASH"},
            {"AttributeName": "transaction_date_epoch", "KeyType": "RANGE"}
        ],

achad4

import boto3
from datetime import datetime
import numpy as np
from fastapi import FastAPI

app = FastAPI()
dynamodb = boto3.resource("dynamodb")
s3 = boto3.client('s3')

achad4

import ...
import fire


class CustomerModel(BaseModel):

    def __init__(self):
        super().__init__()

    def train_model(lookback_days=30: int):

achad4

from airflow.models import Variable
from airflow import DAG
from airflow.operators.python_operator import PythonOperator



MODEL_ENTRY_POINT = "customer_model.py"

# This dynamic configuration mechanism is not ideal but makes for an easy demo
model_version = Variable.get("model_version")

achad4

from airflow.models import Variable
from airflow import DAG
from airflow.operators.python_operator import PythonOperator


def train_model(lookback_days=30: int):
    """
    Trains a model using data from the past <lookback_days> and persists to a model store
    """
    ...

achad4

WITH transaction AS (
    SELECT transaction_id,
           customer_id,
           state,
           amount_spent_usd
    FROM < FACT_TABLE_TRANSACTION >
),
     customer_spend AS (
         SELECT customer_id,
                state,

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WITH transaction AS (
    SELECT transaction_id,
           customer_id,
           state,
           amount_spent_usd
    FROM FACT_TABLE_TRANSACTION
),
     customer_spend AS (
         SELECT customer_id,
                state,

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WITH month_0 AS
         (
             SELECT user_id,
                    metric_a
             FROM analytics_table
             WHERE execution_date = < month_0 >
         ),
     month_1 AS
         (
             SELECT user_id,