Shantanu's Blog

Let's assume we have a list of "good" numbers and we need to find the relevance of a number for e.g. 103 to this list. In this case the weight of 103 in the context of the given list is 3.94 We can calculate the weight of all numbers, sort and take top 4 or 5

Here is how to generate test data for this exercise...

mylist=[100, 101, 102, 104, 105, 106, 107, 220, 221, 289, 290, 542, 544 ]
import pandas as pd
columnA=pd.DataFrame(mylist)

secondlist=[103, 299, 999, 108, 543]
import pandas as pd
row1=pd.DataFrame(secondlist)

for i in row1[0]:
    columnA[i] = 1/ abs(columnA[0] - i) 

# dataframe looks like this excel sheet
columnA




mypd=columnA.sum()

mypd.sort_values(inplace=True,ascending=False)

mypd
0      2831.000000
103       3.948958
108       2.551252
543       2.030021
299       0.280611
999       0.017591
dtype: float64

It is possible to pass through the entire request body with a mapping template like this:

#set($inputRoot = $input.path('$'))
{
    "body" : $input.json('$')
}

If you wanted to pass in a subset of the request body change the '$' selector to the desired JsonPath.

Here is 3 lines of code that will push a record to elasticsearch via kinesis firehose. It can be used for streaming data.

import boto3

firehose_client = boto3.client('firehose', region_name="us-east-1")

response = firehose_client.put_record(
            DeliveryStreamName='kfh',
            Record={
                'Data': json.dumps({'client_name': 'pqr', 'client_code': 8})
            }
        )
_____

The equivalent AWS Lambda function will look something like this.

import boto3
import json

firehose_client = boto3.client('firehose', region_name="us-east-1")

def lambda_handler(event, context):

    myRecord={'client_name': str(event['client_name']), 'client_code': int(event['client_code']) }

    response = firehose_client.put_record(
            DeliveryStreamName='kn_to_es',
            Record={'Data': json.dumps(myRecord)}
        )

    return response

1) There is no need to run each container as deamon. We can call the container as and when required like this...

[root@ip-172-31-8-33 ec2-user]# docker run ubuntu echo "hello world"
hello world

We can also use python to execute such command.

How to install:

pip install -e git+https://github.com/deepgram/sidomo.git#egg=sidomo

How to use:

from sidomo import Container

with Container('ubuntu') as c:
    for output_line in c.run('echo hello world'):
        print(output_line)


2) Docker containers can also be used for testing purpose. selenium browser testing is possible using docker. for e.g.

## http://testdetective.com/selenium-grid-with-docker/

docker run -d -P --name selenium-hub selenium/hub

docker run -d --link selenium-hub:hub selenium/node-firefox

docker run -d -P --link selenium-hub:hub selenium/node-chrome


3) There are other containers those can be used and the list can be found here...

https://blog.jessfraz.com/post/docker-containers-on-the-desktop/

Some of the containers from the above link are listed:

# run tor proxies
docker run -d --restart always -v /etc/localtime:/etc/localtime:ro  -p 9050:9050 --name torproxy jess/tor-proxy

docker run -d --restart always -v /etc/localtime:/etc/localtime:ro --link torproxy:torproxy -p 8118:8118 --name privoxy jess/privoxy


# help the tor network by running a bridge relay!
docker run -d -v /etc/localtime:/etc/localtime --restart always -p 9001:9001 --name tor-relay jess/tor-relay -f /etc/tor/torrc.bridge

# IRC Client
docker run -it -v /etc/localtime:/etc/localtime -v $HOME/.irssi:/home/user/.irssi --read-only --name irssi jess/irssi

# email app
docker run -it -v /etc/localtime:/etc/localtime -e GMAIL -e GMAIL_NAME -e GMAIL_PASS -e GMAIL_FROM -v $HOME/.gnupg:/home/user/.gnupg --name mutt jess/mutt


# text based twitter client
docker run -it -v /etc/localtime:/etc/localtime -v $HOME/.rainbow_oauth:/root/.rainbow_oauth -v $HOME/.rainbow_config.json:/root/.rainbow_config.json --name rainbowstream jess/rainbowstream

# lynx browser
docker run -it --name lynx jess/lynx

# chrome
docker run -it --net host --cpuset-cpus 0 --memory 512mb -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=unix$DISPLAY -v $HOME/Downloads:/root/Downloads -v $HOME/.config/google-chrome/:/data --device /dev/snd --name chrome jess/chrome

I have written an API to generate RSS feed of any pinterest user and all the boards owned by him / her. This has been done using Amazon API gateway and AWS Lambda. Here is how it works...

The pinterest feed discovery will be available after supplying the pin url, somehting like this...

https://f84jmref3f.execute-api.us-east-1.amazonaws.com/stag/pintorss?url=http://in.pinterest.com/shantanuo/buy/

["http://in.pinterest.com/shantanuo/buy.rss", ["http://in.pinterest.com/shantanuo/feed.rss", "http://in.pinterest.com/shantanuo/my-wishlist.rss", "http://in.pinterest.com/shantanuo/truth.rss", "http://in.pinterest.com/shantanuo/tips.rss"]]

The first feed url returns the exact feed of "buy" board. There are other boards owned by the user "shantanuo". They are also returned as list.
_____

And here is the source code:

1) API Gateway:
a) Method Execution - Get Method Request - URL Query String Parameters - add a variable call url
b) Method Execution - Get Integration Request - Mapping Templates - Content-Type - application/json - Mapping template

{"url": "$input.params('url')"}

The above will link the variables received from the API gateway to the lambda function event dictionary.

2) Lambda function:

def lambda_handler(event, context):
    myurl=event['url']
    x=feedspot(myurl)
    return x.url_others()

The feedspot class can be copied from ...

https://gist.github.com/shantanuo/e6112e464276e4ccbc34c36620b811f8

# CMD and ENTRYPOINT
CMD is the default command to execute when an image is run. The default ENTRYPOINT is /bin/sh -c and CMD is passed into that as an argument. We can override ENTRYPOINT in our Dockerfile and make our container behave like an executable taking command line arguments (with default arguments in CMD in our Dockerfile).

docker can overwrite entrypoint like this...
docker run -ti --entrypoint=bash cassandra

# In this case we override the command but entrypoint remains ls
docker run training/ls -l
# in Dockerfile
ENTRYPOINT /bin/ls
CMD ["-a"]

# volumes in #docker are read-write by default but there's an :ro flag
# Use —rm with #docker whenever you use -it to have containers automatically clean themselves up.

# Docker User Interface:
docker run -d -p 9000:9000 -v /var/run/docker.sock:/docker.sock --name dockerui abh1nav/dockerui:latest -e="/docker.sock"

# docker clean up container
docker run -v /var/run/docker.sock:/var/run/docker.sock -v /var/lib/docker:/var/lib/docker --rm martin/docker-cleanup-volumes --dry-run

# install docker machine
curl -L https://github.com/docker/machine/releases/download/v0.6.0/docker-machine-`uname -s`-`uname -m` > /usr/local/bin/docker-machine && \
chmod +x /usr/local/bin/docker-machine

# copy files using shell tricks
$ docker exec -i kickass_yonath sh -c ‘mkdir -p /home/e1/e2'
$ docker exec -i kickass_yonath sh -c 'cat > /home/e1/e2/test.txt' < ./test.txt

# Clean up lots of containers at once (ubuntu based in this case) with:
$ docker ps -a | grep ubuntu | awk ‘{print $1}’ | xargs docker stop
$ docker ps -a | grep ubuntu | awk ‘{print $1}’ | xargs docker rm

# Clean up lots of images at once (in this case where they have no name) with:
$ docker images | grep ‘’ | awk ‘{print $3}’ | xargs docker rmi

# Just pipe docker ps output to less -S so that the table rows are not wrapped:
docker ps -a | less -S

Amazon lambda functions can be tested locally using docker as explained in this article...

https://aws.amazon.com/blogs/compute/cloudmicro-for-aws-speeding-up-serverless-development-at-the-coca-cola-company/

_____

git clone https://github.com/Cloudmicro/lambda-dynamodb-local.git

cd lambda-dynamodb-local

docker-compose up -d

docker-compose run --rm -e FUNCTION_NAME=hello lambda-python
_____

If docker compose is not installed, then follow these steps:

curl -L https://github.com/docker/compose/releases/download/1.7.0/docker-compose-`uname -s`-`uname -m` > /usr/local/bin/docker-compose

chmod +x /usr/local/bin/docker-compose

Pattern is a web mining module for Python. It has tools for:

    Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM parser
    Natural Language Processing: part-of-speech taggers, n-gram search, sentiment analysis, WordNet
    Machine Learning: vector space model, clustering, classification (KNN, SVM, Perceptron)
    Network Analysis: graph centrality and visualization.

https://github.com/clips/pattern

(Not yet compatible with python version 3)

Here is how to create a two column file with numbers and some text separated by comma.

with open('mp.csv', 'w') as f:
    for i in range(9819800000, 9819838475):
        f.write("%s, \"not qualified\" \n" % i)

short, elegant, usable, easy to read code in python gets my job done quickly !

docker run --name mysqlwp -e MYSQL_ROOT_PASSWORD=dockerRootMySQL \
-e MYSQL_DATABASE=wordpress \
-e MYSQL_USER=wordpress \
-e MYSQL_PASSWORD=wordpresspwd \
-d mysql

docker run --name wordpress --link mysqlwp:mysql -p 80:80 \
-e WORDPRESS_DB_NAME=wordpress \
-e WORDPRESS_DB_USER=wordpress \
-e WORDPRESS_DB_PASSWORD=wordpresspwd \
-d wordpress
_____

vi /tmp/uploads.ini

file_uploads = On
memory_limit = 256M
upload_max_filesize = 256M
post_max_size = 300M
max_execution_time = 600

docker run --name wordpress2 --link mysqlwp:mysql -p 80:80  -m 64m \
-e WORDPRESS_DB_PASSWORD=wordpresspwd  \
-v "/opt/wordpress":/var/www/html \
-v "/tmp/uploads.ini:/usr/local/etc/php/conf.d/uploads.ini" \
-d wordpress

# Using #docker locally accessible site can be started using -p 127.0.0.1::80

# open refine utility
# docker run --privileged -v /openrefine_projects/:/mnt/refine -p 35181:3333 -d psychemedia/ou-tm351-openrefine

here are the commands to start prometheus on port 9090 and cadvisor on 8080

git clone https://github.com/vegasbrianc/prometheus.git

cd prometheus/

/usr/local/bin/docker-compose  up -d

# create a new directory and use it for the project
mkdir vg
cd vg

# install docker compose
curl -L https://github.com/docker/compose/releases/download/1.6.2/docker-compose-`uname -s`-`uname -m` > /usr/local/bin/docker-compose

chmod +x /usr/local/bin/docker-compose

# download compose example

git clone https://github.com/vegasbrianc/docker-compose-demo.git .

# start
/usr/local/bin/docker-compose up -d

# status
/usr/local/bin/docker-compose ps

# test
curl 0.0.0.0

# scale
/usr/local/bin/docker-compose scale web=5

# logs
/usr/local/bin/docker-compose logs

This container has adminer.php that you can point to 80 port of the host machine. The exposed port from container is 80

docker run -d -p 80:80 clue/adminer

Download the adminer file and save it to /tmp/ folder.

wget http://www.adminer.org/latest.php -O /tmp/index.php

Oracle:
docker run -d -p 8080:80 -v /tmp/:/app lukaszkinder/apache-php-oci8-pdo_oci

MongoDB:
docker run -d -p 8070:80 -v /tmp:/var/www/html ishiidaichi/apache-php-mongo-phalcon

1) Create mysql data directory
mkdir -p /opt/Docker/masterdb/data

2) Create my.cnf file
mkdir -p /opt/Docker/masterdb/cnf

vi /opt/Docker/masterdb/cnf/config-file.cnf
# Config Settings:
[mysqld]
server-id=1

innodb_buffer_pool_size = 2G
innodb_log_file_size=212M
binlog_format=ROW
log-bin

3) Run docker image

docker run --name masterdb -v /opt/Docker/masterdb/cnf:/etc/mysql/conf.d -v /opt/Docker/masterdb/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=mysecretpass -d shantanuo/mysql

Official docker image for mysql using simply mysql:5.5
You can also use percona or an image by oracle using percona:5.5 OR mysql/mysql-server:5.5

$ sudo docker run --detach=true --name node1 -h node1 erkules/galera:basic --wsrep-cluster-name=local-test --wsrep-cluster-address=gcomm://

$ sudo docker run --detach=true --name node2 -h node2 --link node1:node1 erkules/galera:basic --wsrep-cluster-name=local-test --wsrep-cluster-address=gcomm://node1
$ sudo docker run --detach=true --name node3 -h node3 --link node1:node1 erkules/galera:basic --wsrep-cluster-name=local-test --wsrep-cluster-address=gcomm://node1

# sudo docker exec -ti node1 mysql
mysql> show status like "wsrep_cluster_size";
+--------------------+-------+
| Variable_name      | Value |
+--------------------+-------+
| wsrep_cluster_size | 3     |
+--------------------+-------+
1 row in set (0.00 sec)

_____


deploy Galera Cluster over multiple servers

By design, Docker containers are reachable using port-forwarded TCP ports only, even if the containers have IP addresses. Set up port forwarding for all TCP ports that are required for Galera to operate.

docker run -d -p 3306:3306 -p 4567:4567 -p 4444:4444 -p 4568:4568 --name nodea erkules/galera:basic --wsrep-cluster-address=gcomm:// --wsrep-node-address=10.10.10.10
docker run -d -p 3306:3306 -p 4567:4567 -p 4444:4444 -p 4568:4568 --name nodeb erkules/galera:basic --wsrep-cluster-address=gcomm://10.10.10.10 --wsrep-node-address=10.10.10.11
docker run -d -p 3306:3306 -p 4567:4567 -p 4444:4444 -p 4568:4568 --name nodec erkules/galera:basic --wsrep-cluster-address=gcomm://10.10.10.10 --wsrep-node-address=10.10.10.12
docker exec -t nodea mysql -e 'show status like "wsrep_cluster_size"'

+--------------------+-------+
| Variable_name      | Value |
+--------------------+-------+
| wsrep_cluster_size |     3 |
+--------------------+-------+

It is possible to create a new user with sudo permissions on an ec2 instance. We can enable password authentication and remove pem file dependency. The security can be managed by "security group".

1) Add a user called "dev" and set the password
sudo useradd -s /bin/bash -m -d /home/dev  -g root dev
sudo passwd dev

2) All sudo access to the dev user
sudo visudo

dev  ALL=(ALL:ALL) ALL

3) Enable password authentication in config file
vi /etc/ssh/sshd_config
PasswordAuthentication yes
#PasswordAuthentication no

4) Restart ssh
sudo /etc/init.d/sshd restart

Other solution:

# Turn on password authentication
sudo sed -i 's/^PasswordAuthentication.*/PasswordAuthentication yes/' /etc/ssh/sshd_config
# Reload SSHd configuration
sudo service sshd reload
# Set a password for the ec2-user
sudo passwd ec2-user