Gary A. Stafford garystafford

## sam-local-invoke.sh
# variables (required by local lambda functions)
TABLE_NAME=your-dynamodb-table-name

# local testing (All CRUD functions)
sam local invoke PostMessageFunction \
  --event lambda_apigtw_to_dynamodb/events/event_postMessage.json
sam local invoke GetMessageFunction \
  --event lambda_apigtw_to_dynamodb/events/event_getMessage.json
sam local invoke GetMessagesFunction \
  --event lambda_apigtw_to_dynamodb/events/event_getMessages.json

## event_getMessage.json
{
  "body": "",
  "resource": "/",
  "path": "/message",
  "httpMethod": "GET",
  "isBase64Encoded": false,
  "queryStringParameters": {
    "time": "06:45:43"
  },
  "pathParameters": {

## parameter.yml
Parameters:
  DataBucketName:
    Type: String
    Description: S3 bucket where CSV files are placed
    Default: your-data-bucket-name-here

## build-package-deploy.sh
# variables
S3_BUILD_BUCKET=your_build_bucket_name
STACK_NAME=your_cloudformation_stack_name

# validate
sam validate --template template.yaml

aws cloudformation validate-template \
  --template-body file://template.yaml

## app.js
exports.getMessage = async (event, context) => {
    if (tableName == null) {
        tableName = process.env.TABLE_NAME;
    }
    params = {
        TableName: tableName,
        Key: {
            "date": event.pathParameters.date,
            "time": event.queryStringParameters.time
        }

## app.py
def lambda_handler(event, context):
    operations = {
        'DELETE': lambda dynamo, x: dynamo.delete_item(**x),
        'POST': lambda dynamo, x: dynamo.put_item(**x),
        'PUT': lambda dynamo, x: dynamo.update_item(**x),
        'GET': lambda dynamo, x: dynamo.get_item(**x),
        'GET_ALL': lambda dynamo, x: dynamo.scan(**x),
    }

    for record in event['Records']:

## app.py
def lambda_handler(event, context):
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = urllib.parse.unquote_plus(
        event['Records'][0]['s3']['object']['key'],
        encoding='utf-8'
    )
    messages = read_csv_file(bucket, key)
    process_messages(messages)

## sqs_message.json
{
    "TableName": "your-dynamodb-table-name",
    "Item": {
        "date": {
            "S": "2001-01-01"
        },
        "time": {
            "S": "09:01:05"
        },
        "location": {

## message_data.csv

          
            timestamp
            location
            source
            local_dest
            local_avg
            remote_dest
            remote_avg

            
              1559040909.3853335
              location-03
              wireless
              router-1
              4.39
              device-1
              9.09

            
              1559040919.5273902
              location-03
              wireless
              router-1
              0.49
              device-1
              16.75

            
              1559040929.6446512
              location-03
              wireless
              router-1
              0.56
              device-1
              8.31

            
              1559040939.7712135
              location-03
              wireless
              router-1
              1.64
              device-1
              9.4

            
              1559040949.891723
              location-03
              wireless
              router-1
              1.18
              device-1
              9.07

            
              1559040960.011338
              location-03
              wireless
              router-1
              0.42
              device-1
              8.4

            
              1559040970.1319716
              location-03
              wireless
              router-1
              1.73
              device-1
              8.66

            
              1559040980.2533505
              location-03
              wireless
              router-1
              0.67
              device-1
              8.61

            
              1559040990.3816211
              location-03
              wireless
              router-1
              1.27
              device-1
              10.87

## gimp_scale_batch.py
#!/usr/bin/python

# optimized for processing screen grabs
# copy and paste into GIMP Python Console
# open all images in Gimp to process
# script scales, sharpens, and exports all open images as PNGs
# Filters > Python-Fu > Console

import importlib