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import json

print('Loading function')

def lambda_handler(event, context):
    return {"message": "isto é uma função"}

vicotrbb

lxml
boto

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FROM python:3.8-alpine AS installer

WORKDIR /app
COPY requirements.txt .

RUN apk add --no-cache --virtual .build-deps gcc libc-dev libxslt-dev && \
    apk add --no-cache libxslt && \
    apk del .build-deps

FROM public.ecr.aws/lambda/python:3.8

vicotrbb

import urllib.request
import urllib.parse
import http.cookiejar
import json
import time


def to_decimal(string):
    string = string.replace('.', '') \
        .replace(',', '.') \

vicotrbb

import re
import urllib.request
import urllib.parse
from datetime import datetime
import os
import boto3
import csv
from tempfile import TemporaryDirectory

from lxml.html import fragment_fromstring

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/* Estrutura de arquivos
|-- server.js
|-- src
| |-- user
|   |--user.controller.js
|   |--user.route.js
| |-- product
|   |--product.controller.js
|   |--product.route.js
| |-- order

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validation = data.sample(5)
data.drop(validation.index, axis=0, inplace=True)

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ref = {
    0: 'Iris-Setosa',
    1: 'Iris-Versicolour',
    2: 'Iris-Virginica'
}

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import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from sklearn.neural_network import MLPClassifier

iris_dataset = load_iris()
data = pd.DataFrame(iris_dataset.data, columns=iris_dataset.feature_names)
data['target'] = iris_dataset.target

vicotrbb

FROM python:3
COPY . /work
WORKDIR /work

EXPOSE 5000

RUN pip install --no-cache-dir -r requirements.txt

CMD gunicorn --workers 2 --bind 0.0.0.0:5000 app:app