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def transform_timestamp_to_features(timestamp):
    # Convert timestamp to datetime
    dt = pd.to_datetime(timestamp)

    # Initialize a dictionary to store features
    features = {}

    # Date Features
    features["year"] = dt.year
    features["quarter"] = dt.quarter

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• Installing prophet (1.1.3): Failed

  ChefBuildError

  Backend subprocess exited when trying to invoke build_wheel
  
  running bdist_wheel
  running build
  running build_py
  creating build

fclesio

$ conda install -c conda-forge pip

$ conda install -c conda-forge 'lightgbm>=3.3.3'

$ conda install -c conda-forge cmdstan

$ export PROPHET_REPACKAGE_CMDSTAN=False

$ export PRECOMPILED_HEADERS=false

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apiVersion: v1
kind: Pod
metadata:
  name: test-proxy-deploy
spec:
  volumes:
  - name: secret-volume
    secret:
      secretName: cloud_sql_key_secret
  containers:

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[
  {
    "Id":"value",
    "prediction":"value",
    "status-code":200
  }
]

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{
   "message":"OK",
   "method":"POST",
   "status-code":200,
   "timestamp":"2022-01-01T00:00:00.000000",
   "url":"http://0.0.0.0:1201/predict",
   "data":{
      "prediction":[
         {
            "input_text":"Flash crashes is a scenario where the price of stocks plunges but then quickly recovers.",

fclesio

# Importação da biblioteca do Boto3 e 
# criação de sessão para acesso aos recursos
import boto3
sessao_boto = boto3.Session(region_name='us-east-1')
# Função para pegar a "ROLE" (papel) de execução 
# IAM dos recursos no Sage Maker 
from sagemaker import get_execution_role
ROLE = get_execution_role()

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

import os
import sys

sys.path.append(os.getcwd() + os.sep + os.pardir)

import random
import time

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import os
import sagemaker
from sagemaker.processing import Processor
from sagemaker.network import NetworkConfig
from sagemaker.session import Session
from time import strftime, gmtime


sagemaker_session = Session()

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import os
import boto3

COMPUTE_ENVIRONMENT_VERSION = 'v0_01'

aws_iam_boto_client \
    = boto3.client('iam')

aws_batch_boto_client \
    = boto3.client('batch')