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{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowAllUsersToListAccounts",
            "Effect": "Allow",
            "Action": [
                "iam:ListAccountAliases",
                "iam:ListUsers",
                "iam:GetAccountPasswordPolicy",

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#!/usr/bin/env python
""" Short description of this Python module.

Longer description of this module.

This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.

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Continuous deployment of React websites to Amazon S3

This sample includes a continuous deployment pipiline for websites built with React. We use AWS CodePipeline, CodeBuild, and SAM to deploy the application. To deploy the application to S3 using SAM we use a custom CloudFormation resource.

Files included

• buildspec.yml: YAML configuration for CodeBuild, this file should be in the root of your code repository
• configure.js: Script executed in the build step to generate a config.json file for the application, this is used to include values exported by other CloudFormation stacks (separate services of the same application).
• index.js: Custom CloudFormation resource that publishes the website to an S3 bucket. As you can see from the buildspec and SAM template, this function is located in a s3-deployment-custom-resource sub-folder of the repo
• app-sam.yaml: Serverless Application model YAML file. This configures the S3 bucket and the cu

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#!/usr/bin/python
#
# List Active Okta Users
#

import requests
import json

token = 'WHATEVER_YOUR_TOKEN_IS'
limit = '200'

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#!/usr/bin/python
#
# List Active Okta Users
#

import requests
import json
import pprint
import csv

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# Python logger in AWS Lambda has a preset format. To change the format of the logging statement, remove the logging handler 
# and add a new handler with the required format

logger = logging.getLogger()
for h in logger.handlers:
  logger.removeHandler(h)

h = logging.StreamHandler(sys.stdout)

# use whatever format you want here

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# A virtualenv running Python3.6 on Amazon Linux/EC2 (approximately) simulates the Python 3.6 Docker container used by Lambda
# and can be used for developing/testing Python 3.6 Lambda functions
# This script installs Python 3.6 on an EC2 instance running Amazon Linux and creates a virtualenv running this version of Python
# This is required because Amazon Linux does not come with Python 3.6 pre-installed 
# and several packages available in Amazon Linux are not available in the Lambda Python 3.6 runtime

# The script has been tested successfully on a t2.micro EC2 instance (Root device type: ebs; Virtualization type: hvm)
# running Amazon Linux AMI 2017.03.0 (HVM), SSD Volume Type - ami-c58c1dd3
# and was developed with the help of AWS Support

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# This script allows Python functions in AWS Lambda to query an Oracle RDS instance
# It is meant to run on an EC2 instance running Amazon Linux

# The script has been tested successfully on a t2.micro EC2 instance (Root device type: ebs; Virtualization type: hvm)
# running Amazon Linux AMI 2017.03.0 (HVM), SSD Volume Type - ami-c58c1dd3
# and was developed with the help of AWS Support

# Steps:
# - install Oracle Instant Client
# - create virtualenv

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# Create and upload a deployment package for a Python Lambda function
# Assumes EC2 instance is associated with an IAM role with permissions to access S3 & Lambda
# Ref: http://docs.aws.amazon.com/lambda/latest/dg/lambda-python-how-to-create-deployment-package.html
 
# This script is meant to be used after virtualenv has been setup to connect to Oracle RDS 
# see https://gist.github.com/niranjv/2a576a13afe1b323e9e9600ed7de03ef


# Steps:
# - create temp dir

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var request = require('request');
var cheerio = require('cheerio');
var fs = require('fs');

var auth = {
	'user': 'appleid',
	'pass': 'mypassword',
	'sendImmediately': false
};