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#!/bin/bash

# Directory dei moduli
MODULES_DIR=".terraform/modules"
HASHES_FILE="tfmodules.lock.json"

# Scaricare i moduli
terraform init

# Funzione per calcolare l'hash di un modulo

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import appinsights from 'applicationinsights';
import winston from 'winston';
import { transports, format, Logger } from 'winston';

// Configura Application Insights
appinsights.setup(process.env.APPINSIGHTS_INSTRUMENTATIONKEY)
  .setAutoCollectConsole(false)
  .start();

const aiClient = appinsights.defaultClient;

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Analytics Analytics/Analytics.puml
Athena Analytics/Athena.puml
AthenaDataSourceConnectors Analytics/AthenaDataSourceConnectors.puml
CleanRooms Analytics/CleanRooms.puml
CloudSearch Analytics/CloudSearch.puml
CloudSearchSearchDocuments Analytics/CloudSearchSearchDocuments.puml
DataExchange Analytics/DataExchange.puml
DataExchangeforAPIs Analytics/DataExchangeforAPIs.puml
DataPipeline Analytics/DataPipeline.puml
DataZone Analytics/DataZone.puml

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terraform {
  required_version = ">= 1.0.0"

  backend "s3" {}

  required_providers {
    aws = {
      source                = "hashicorp/aws"
      version               = "= 4.63.0"
      configuration_aliases = [aws.alternate]

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# Create the whole infrastructure to run the Strapi CMS webserver
# and the static frontend that uses nextjs.

# Terraform provider configuration

variable "db_name" {
  description = "The name of the database"
  default     = "my_database"
}

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import { identity, pipe } from "fp-ts/lib/function";
import * as E from "fp-ts/lib/Either";
import * as t from "io-ts";
import { WithinRangeInteger } from "./numbers";

const _isNonEmptyUint8Array = (u: unknown): u is Uint8Array =>
  Array.isArray(u) && u.length > 0 && t.array(WithinRangeInteger(0, 256)).is(u);

export const NonEmptyUint8Array = new t.Type<Uint8Array, Uint8Array, unknown>(
  "NonEmptyUint8Array",

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import { pipe } from "fp-ts/lib/function";
import * as E from "fp-ts/lib/Either";
import * as t from "io-ts";
import { WithinRangeInteger } from "./numbers";

export const NonEmptyUint8Array = new t.Type<Uint8Array, String, Array<number>>(
  "NonEmptyUint8Array",
  (u): u is Uint8Array =>
    t.array(WithinRangeInteger(0, 256)).is(u) && u.length > 0,
  (u, c) =>

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import { isRight } from "fp-ts/lib/Either";
import { MobileNumberFromString, PatternString } from "../strings";

describe("MobileNumberFromString", () => {
  it("should fail", () => {
    const ps = MobileNumberFromString.decode("ABCD");
    expect(isRight(ps)).toBeFalsy();
  });
  it("should success", () => {
    const ps = MobileNumberFromString.decode("123456789");

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Comunicazione & progettazione

• limitare l'utilizzo della comunicazione sincrona (slack) per q&a
• partire dai doc gdrive per l'analisi dei requisiti, inserire lì i commenti e taggare le persone che possono rispondere
• durante la standup howdy alla domanda 'hai bisogno di aiuto' taggare le stesse persone per sollecitare una risposta
• usare le storie su pivotal per discutere l'implementazione quando i requisiti sono chiari
• usare le PR per discutere i dettagli implementativi
• inserire eventualmente dei commenti inline nelle PR per spiegare alcune scelte progettuali (non dovrebbe essere necessario se si usano bene i commenti nel codice :-)

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/**
 * we need a couple of patches and some utility functions
 * to the azure sdk, see 
 *     https://github.com/teamdigitale/io-developer-portal-backend/tree/master/patches
 */
// tslint:disable:no-console
import * as dotenv from "dotenv";
dotenv.config({ path: __dirname + "/../local.env" });

import ApiManagementClient from "azure-arm-apimanagement";