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url = 'https://api.twitter.com/1.1/account_activity/all/env-beta/subscriptions.json'
r = twitter.post(url)

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from requests_oauthlib import OAuth1Session
import urllib

CONSUMER_KEY = 'adsklfjlaksdjfasldfk'
CONSUMER_SECRET = 'aksdjfkjljasdfljLIJSDLKFjlskdjflaskjdfa'
ACCESS_TOKEN = '0923840928349082390283-kljadsflkJKLDfjdslkjklajkljdsfls'
ACCESS_SECRET = '098asdfkljLSkdjfsda09uaskdjflLKJESF'

twitter = OAuth1Session(CONSUMER_KEY,
                        client_secret=CONSUMER_SECRET,

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def crc(event, context):
    """ Returns a CRC (Challenge Response Check) to keep this webhook
    secure. https://goo.gl/kFdJgV for more details. """
    # Short circuit ping from CloudWatch Events
    if event.get('source', None) == 'aws.events':
        print('ping')
        return
    
    import base64
    import hmac

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import uuid
import json
import boto3
from botocore.vendored import requests

"""
CloudFormation Template has the following components:

# A defintion of your lambda function (what's included below) that
# creates your custom resource

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#!/usr/bin/env python

import boto3
import os
from botocore.exceptions import ClientError

# CONFIGURATION
BUCKET_NAME = 'mybucketname'
DRY_RUN = True
S3 = boto3.client('s3')

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---
swagger: "2.0"
info:
  version: "1.0"
  title: "s3-sns-lambda"
basePath: "/dev"
schemes:
- "https"
paths:
  /:

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  ApiGatewayApi:
    Type: AWS::Serverless::Api
    Properties:
      DefinitionUri: ./swagger.yaml
      StageName: !Ref ApiGatewayStage
      Variables:
        LambdaFunctionName: !Ref LambdaSNS
  LambdaSNS:
    Type: AWS::Serverless::Function
    Properties:

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def sendResponse(event, reason, status):
    response = {
        'Status': status,
        'Reason': reason,
        'PhysicalResourceId': 'physical-resource-id',
        'StackId': event['StackId'],
        'RequestId': event['RequestId'],
        'LogicalResourceId': event['LogicalResourceId']
    }
    print(response)

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from aws_xray_sdk.core import xray_recorder
def get_random_ints(count):
    """Returns a list of random integers of size count.
    """
    print 'Generating random ints'
    subsegment = xray_recorder.begin_subsegment('generating_random_ints')
    my_nums = []
    for i in range(count):
        my_nums.append(randrange(10000))
    xray_recorder.end_subsegment()

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  CodePipelineServiceRole:
    Type: AWS::IAM::Role
    Properties:
      Path: /
      AssumeRolePolicyDocument: |
        {
            "Statement": [{
                "Effect": "Allow",
                "Principal": { "Service": [ "codepipeline.amazonaws.com" ]},
                "Action": [ "sts:AssumeRole" ]