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#!/bin/bash

export PKG_DIR="python"

rm -rf ${PKG_DIR} && mkdir -p ${PKG_DIR}

docker run --rm -v $(pwd):/foo -w /foo lambci/lambda:build-python3.6 \
    pip install -r requirements.txt --no-deps -t ${PKG_DIR}

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pandas==0.23.4
pytz==2018.7

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service: sample-service       # Name of the service, which is used as a prefix to all function names. TODO: Update to your custom name.

frameworkVersion: ">=1.34.0"  # Layers are supported from version 1.34

provider:
  name: aws                   # Assuming this is for AWS Lambda.
  stage: dev                  # Name of the stage, typically either dev/staging/prod (or production), this is also added to all function names. TODO: Update to your custom name.
  profile: some-aws-profile   # Name of the pre-configured AWS profile that is founnd in ~/.aws/confidentials.  TODO: Update to your profile.
  region: some-region         # Name of the region to deploy all functions to. TODO: Update to your custom region.
  runtime: python3.6          # AWS Lambda runtime

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import numpy as np
import pandas as pd


def handler(event, context):
    dates = pd.date_range('20181201', periods=6)
    df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
    print(df)

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START RequestId: 2cee0f93-f97c-11e8-be81-1d3426460e67 Version: $LATEST
                   A         B         C         D
2018-12-01  0.837058 -0.997650  0.333986 -0.266099
2018-12-02 -1.824489  0.306344  2.331290  0.520816
2018-12-03  1.605077 -1.516653  0.161290  0.163109
2018-12-04  0.740779  0.481298 -0.111764 -0.548484
2018-12-05  0.861482  0.630950 -0.588095 -2.114341
2018-12-06 -0.511081 -0.181257  0.068638 -1.685518
END RequestId: 2cee0f93-f97c-11e8-be81-1d3426460e67
REPORT RequestId: 2cee0f93-f97c-11e8-be81-1d3426460e67	Duration: 297.16 ms	Billed Duration: 300 ms 	Memory Size: 128 MB	Max Memory Used: 90 MB	

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{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Description": "The AWS CloudFormation template for this Serverless application",
  "Resources": {
    "ServerlessDeploymentBucket": {
      "Type": "AWS::S3::Bucket"
    },
    "DataAnalysisLogGroup": {
      "Type": "AWS::Logs::LogGroup",
      "Properties": {

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FROM amazonlinux:latest
WORKDIR /
RUN yum update -y
RUN yum group install "Development Tools" -y
RUN yum install -y git zip wget
RUN wget https://releases.hashicorp.com/terraform/0.11.7/terraform_0.11.7_linux_amd64.zip && unzip terraform_0.11.7_linux_amd64.zip
RUN chmod +x terraform
COPY . .
RUN chmod +x /run.sh
CMD ["/run.sh"]

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# iam_sagemaker.tf
resource "aws_iam_role" "sm_notebook_instance_role" {
  name = "sm-notebook-instance-role"
  ...
}
resource "aws_iam_policy" "sm_notebook_instance_policy" {
  name        = "sm-notebook-instance-policy"
  description = "Policy for the Notebook Instance to manage training jobs, models and endpoints"
  ...
}

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resource "aws_sagemaker_notebook_instance" "basic" {
  name          = "FraudDetectionNotebookInstance"
  role_arn      = "${aws_iam_role.sm_notebook_instance_role.arn}"
  instance_type = "ml.t2.medium"
  lifecycle_config_name = "${aws_sagemaker_notebook_instance_lifecycle_configuration.basic_lifecycle.name}"
}
resource "aws_sagemaker_notebook_instance_lifecycle_configuration" "basic_lifecycle" {
  name     = "BasicNotebookInstanceLifecycleConfig"
  on_start = "${base64encode(data.template_file.instance_init.rendered)}"
}