Category Archives: Docker Containers

News from the blog 2021-10-10

I published this book to help developers to understand and use Docker.

It is not targeted to SysAdmins, is aimed to Developers that want to get an operative know how by examples very quickly, and easy to read.

  • University classes are restarted, and I fixed my tower.

For the Cloud computing degree this semester VMWare is used intensively.

I have a dedicated tower with an AMD Ryzen 7 processor, a Samsung NMVe drive PCIe 4.0, which provides me a throughput of 6GB/second (six Gigabytes, so 48 Gbit/second), SAS drives and SATA too. It’s a little monster with 64 GB of RAM and 2.5 Gbps NIC.

It was not starting.

The problem was in the Video card, which made loosely contact to the motherboard.

I had to disconnect everything until I found what it was, but after moving the video card to another PCI slot, it worked.

I knew it was some sort of short circuit / bad contact as the fans were turning for a second and turning off immediately.

After this, the computer works fine but it will poweroff in about 4h and 12 hours. I’ve been testing and removing each component until I believe is the PSU. I’ve ordered a new one from a Dutch provider with web store in Ireland that my former colleague Thomas showed me one year and half ago.

Since England leaved the EU, it is impossible to buy from amazon.co.uk without experiencing problems in the border and delays.

If you want to learn how to assemble a PC, fix the problems and upgrade your laptop, I wrote this book:

https://leanpub.com/pc-assemble/

If you are curious about what I use in my day to day:

  1. A tower for developing and reading my email, with Linux, Intel i7 7800X (12 cores) and 64 GB of RAM, with Nvidia graphics card
  2. A tower for holding Virtual Machines, with Linux, AMD Ryzen 7 3700x (16 cores) and 64 GB of RAM, with Nvidia graphics card
  3. An upgraded HP laptop for programming in the cafe, is a Windows 10, with 16 GB of RAM
  4. Raspberry Pi 4 and 3, from time to time
  5. A laptop for programming, for Work, 16 GB of RAM
  6. A tower for programming, for Work, at the office, 32 GB of RAM
  7. I also had a Dell computer which battery inflated elevating the touchpad, an Acer 11.6 Latop very lightweight which screen died cracked apparently (it’s a mistery to me how this happened as I removed from the bag and it was cracked. That little laptop accompanied me during years, to many countries, as for a while I carried it with me 100% of the time. At that time if the companies I worked for had outages they were losing thousands of euros per hour, so as CTO I fixed broken stuff even in a restaurant. Believe when I recommend you and your teams to use Unit Testing) and a 15.6″ Acer with 16GB of RAM that was part of the payment of an Start up I was CTO for, and which screen flicks intermittently and I managed to fix it by applying a pressure point to a connector, so I managed to use as fixed computer at the beginning of being in Ireland. I was not using it much, as I had two laptops from work when working for Sanmina, a Dell with 16 GB of RAM and Core i7 with two external monitors and an Intel Xeon with 32GB of RAM, heavy weight, but very useful for my job (programming, doing demos, having VMs…).

I’ve assembled all my PC from the scratch, piece by piece, and I force myself to do it so I keep up to date of the upcoming technologies, buses, etc…

  • My students are doing well. Congrats to Albert for getting 8.67 from 10 in his university programming course exams!.
  • Diablo 2 Resurrected is published and I am in the credits :)

I’m in the credits of all our games since I joined, but I’m happy every time I see myself and my colleagues on them. :)

This release includes SubProcessUtils which is a class that allows you to execute commands to the shell (or without shell) and capture the STDOUT, STDERR, and Exit Code very easily.

I’ve used my libraries for a hackaton PoC for work, for Monitoring one aspect of one of our top games side, and I coded it super quickly. :)

They loved it and we have a meeting scheduled to create a Service from my PoC. :)

News from the blog 2021-09-20

  • I’ve published a very simple game, Tic Tac Toe, that I created for my Python 3 Exercises for Beginners book.
  • I’ve raised back the price for my books to normal levels.
    I’ve been keeping the price to the minimum to help people that wanted to learn during covid-19. I consider that who wanted to learn has already done it.

I still have bundles with a somewhat reduced price, and I authorized LeanPub platform to do discounts up to 50% at their discretion.

Bundle of four books in https://leanpub.com/b/python3-exercises-zfs-assemble-computer

https://leanpub.com/b/python3-exercises-zfs-assemble-computer

  • I’ve been deleting AMIs, Snapshots, Volumes and backups from Amazon instances I’ll no longer use.

I’ve migrated to Docker some sites and WordPress sites and now I’m CSP (Cloud Service Provider) agnostic. I can deploy wherever I want.

We pay per GB used of storage, so my money will get a better usage.

As I said in my old article from 2013, The Cloud is for Scaling. For Startups and for Enterprises. It is too expensive for small and medium companies.

  • For those studying Python there is a Virtual Meetup about Data Analysis, in Spanish ,the 23th of September

https://www.meetup.com/tech-barcelona/events/280791310/

More meetups:

https://www.meetup.com/tech-barcelona/

Have a cheap Ubuntu in your Windows or Mac with Docker

I had this idea after one my Python and Linux students with two laptops, a Mac OS X and a Windows one explained me that the Mac OS X is often taken by their daughters, and that the Windows 10 laptop has not enough memory to run PyCharm and Virtual Box fluently. She wanted to have a Linux VM to practice Linux, and do the Bash exercises.

So this article explains how to create a Ubuntu 20.04 LTS Docker Container, and execute a shell were you can practice Linux, Ubuntu, Bash, and you can use it to run Python, Apache, PHP, MySQL… as well, if you want.

You need to install Docker for Windows of for Mac:

Docker for Windows is very handy and visual

Just pay attention to your type of processor: Mac with Intel chip or Mac with apple chip.

The first thing is to create the Dockerfile.

FROM ubuntu:20.04

MAINTAINER Carles Mateo

ARG DEBIAN_FRONTEND=noninteractive

RUN apt update && \
    apt install -y vim python3-pip &&  \
    apt install -y net-tools mc htop less strace zip gzip lynx && \
    pip3 install pytest && \
    apt-get clean

RUN echo "#!/bin/bash\nwhile [ true ]; do sleep 60; done" > /root/loop.sh; chmod +x /root/loop.sh

CMD ["/root/loop.sh"]

So basically the file named Dockerfile contains all the blueprints for our Docker Container to be created.

You see that I all the installs and clean ups in one single line. That’s because Docker generates a layer of virtual disk per each line in the Dockerfile. The layers are persistent, so even if in the next line we delete the temporary files, the space used will not be recovered.

You see also that I generate a Bash file with an infinite loop that sleeps 60 seconds each loop and save it as /root/loop.sh This is the file that later is called with CMD, so basically when the Container is created will execute this infinite loop. Basically we give to the Container a non ending task to prevent it from running, and exiting.

Now that you have the Dockerfile is time to build the Container.

For Mac open a terminal and type this command inside the directory where you have the Dockerfile file:

sudo docker build -t cheap_ubuntu .

I called the image cheap_ubuntu but you can set the name that you prefer.

For Windows 10 open a Command Prompt with Administrative rights and then change directory (cd) to the one that has your Dockerfile file.

docker.exe build -t cheap_ubuntu .
Image being built… (some data has been covered in white)

Now that you have the image built, you can create a Container based on it.

For Mac:

sudo docker run -d --name cheap_ubuntu cheap_ubuntu

For Windows (you can use docker.exe or just docker):

docker.exe run -d --name cheap_ubuntu cheap_ubuntu

Now you have Container named cheap_ubuntu based on the image cheap_ubuntu.

It’s time to execute an interactive shell and be able to play:

sudo docker exec -it cheap_ubuntu /bin/bash

For Windows:

docker.exe exec -it cheap_ubuntu /bin/bash
Our Ubuntu terminal inside Windows

Now you have an interactive shell, as root, to your cheap_ubuntu Ubuntu 20.04 LTS Container.

You’ll not be able to run the graphical interface, but you have a complete Ubuntu to learn to program in Bash and to use Linux from Command Line.

You will exit the interactive Bash session in the container with:

exit

If you want to stop the Container:

sudo docker stop cheap_ubuntu

Or for Windows:

docker.exe stop cheap_ubuntu

If you want to see what Containers are running do:

sudo docker ps

News of the blog 2021-08-16

  • I completed my ZFS on Ubuntu 20.04 LTS book.
    I had an error in an actual hard drive so I added a Troubleshooting section explaining how I fixed it.
  • I paused for a while the advance of my book Python: basic exercises for beginners, as my colleague Michela is translating it to Italian. She is a great Engineer and I cannot be more happy of having her help.
  • I added a new article about how to create a simple web Star Wars game using Flask.
    As always, I use Docker and a Dockerfile to automate the deployment, so you can test it without messing with your local system.
    The code is very simple and easy to understand.
mysql> UPDATE wp_options set option_value='blog.carlesmateo.local' WHERE option_name='siteurl';
Query OK, 1 row affected (0.02 sec)
Rows matched: 1 Changed: 1 Warnings: 0

This way I set an entry in /etc/hosts and I can do all the tests I want.

  • I added a new section to the blog, is a link where you can see all the articles published, ordered by number of views.
    /posts_and_views.php

Is in the main page, just after the recommended articles.
Here you can see the source code.

  • I removed the Categories:
    • Storage
      • ZFS
  • In favor of:
    • Hardware
      • Storage
        • ZFS
  • So the articles with Categories in the group deleted were reassigned the Categories in the second group.
  • Visually:
    • I removed some annoying lines from the Quick Selection access.
      They came from inherited CSS properties from my WordPress, long time customized, and I created new styles for this section.
    • I adjusted the line-height to avoid separation between lines being too much.
  • I added a link in the section of Other Engineering Blogs that I like, to the great https://github.com/lesterchan site, author of many super cool WordPress plugins.

A sample Flask application

Today I bring you a game made with Python and Flask extracted from my book Python 3 Combat Guide.

It is a very simple game where you have to choose what Star wars robot you prefer.

Then an internal counter, kept in a static variable, is updated.

I display the time as well, to show the use of a in import and dynamic contents printed as well.

I added a Dockerfile and a bash script to build the Docker Image, so you can run the Docker Container without installing anything in your computer.

You can download the code from here:

https://gitlab.com/carles.mateo/python-flask-r2d2

Or clone the project:

git clone https://gitlab.com/carles.mateo/python-flask-r2d2.git

Then build the image with the script I provided:

sudo ./build_docker.sh 

After Docker Image flask_app is built, you can run a Docker Container based on it with:

sudo docker run -d -p 5000:5000 --name flask_app flask_app

After you’re done, in order to stop the Container type:

sudo docker stop flask_app

Here is the source code of the Python file flask_app.py:

#
# flask_app.py
#
# Author: Carles Mateo
# Creation Date: 2020-05-10 20:50 GMT+1
# Description: A simple Flask Web Application
#              Part of the samples of https://leanpub.com/pythoncombatguide
#              More source code for the book at https://gitlab.com/carles.mateo/python_combat_guide
#

from flask import Flask
import datetime


def get_datetime(b_milliseconds=False):
    """
    Return the datetime with miliseconds in format YYYY-MM-DD HH:MM:SS.xxxxx
    or without milliseconds as YYYY-MM-DD HH:MM:SS
    """
    if b_milliseconds is True:
        s_now = str(datetime.datetime.now())
    else:
        s_now = str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))

    return s_now


app = Flask(__name__)

# Those variables will keep their value as long as Flask is running
i_votes_r2d2 = 0
i_votes_bb8 = 0


@app.route('/')
def page_root():
    s_page = "<html>"
    s_page += "<title>My Web Page!</title>"
    s_page += "<body>"
    s_page += "<h1>Time now is: " + get_datetime() + "</h1>"
    s_page += """<h2>Who is more sexy?</h2>
<a href="r2d2"><img src="static/r2d2.png"></a> <a href="bb8"><img width="250" src="static/bb8.jpg"></a>"""
    s_page += "</body>"
    s_page += "</html>"

    return s_page


@app.route('/bb8')
def page_bb8():
    global i_votes_bb8

    i_votes_bb8 = i_votes_bb8 + 1

    s_page = "<html>"
    s_page += "<title>My Web Page!</title>"
    s_page += "<body>"
    s_page += "<h1>Time now is: " + get_datetime() + "</h1>"
    s_page += """<h2>BB8 Is more sexy!</h2>
                <img width="250" src="static/bb8.jpg">"""
    s_page += "<p>I have: " + str(i_votes_bb8) + "</p>"
    s_page += "</body>"
    s_page += "</html>"

    return s_page


@app.route('/r2d2')
def page_r2d2():
    global i_votes_r2d2

    i_votes_r2d2 = i_votes_r2d2 + 1

    s_page = "<html>"
    s_page += "<title>My Web Page!</title>"
    s_page += "<body>"
    s_page += "<h1>Time now is: " + get_datetime() + "</h1>"
    s_page += """<h2>R2D2 Is more sexy!</h2>
                <img src="static/r2d2.png">"""
    s_page += "<p>I have: " + str(i_votes_r2d2) + "</p>"
    s_page += "</body>"
    s_page += "</html>"

    return s_page


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000, debug=True)

As always, the naming of the variables is based on MT Notation.

The Dockerfile is very straightforward:

FROM ubuntu:20.04

MAINTAINER Carles Mateo

ARG DEBIAN_FRONTEND=noninteractive

RUN apt update && \
    apt install -y vim python3-pip &&  pip3 install pytest && \
    apt-get clean

ENV PYTHON_COMBAT_GUIDE /var/python_combat_guide

RUN mkdir -p $PYTHON_COMBAT_GUIDE

COPY ./ $PYTHON_COMBAT_GUIDE

ENV PYTHONPATH "${PYTHONPATH}:$PYTHON_COMBAT_GUIDE/src/:$PYTHON_COMBAT_GUIDE/src/lib"

RUN pip3 install -r $PYTHON_COMBAT_GUIDE/requirements.txt

# This is important so when executing python3 -m current directory will be added to Syspath
# Is not necessary, as we added to PYTHONPATH
#WORKDIR $PYTHON_COMBAT_GUIDE/src/lib

EXPOSE 5000

# Launch our Flask Application
CMD ["/usr/bin/python3", "/var/python_combat_guide/src/flask_app.py"]

A small Python + MySql + Docker program as a sample

This article can be found in my book Python Combat Guide.

I wrote this code and article in order to help my Python students to mix together Object Oriented Programming, MySql, and Docker.

You can have everything in action with only downloading the code and running the docker_build.sh and docker_run.sh scripts.

You can download the source code from:

https://gitlab.com/carles.mateo/python-mysql-example

and clone with:

git clone https://gitlab.com/carles.mateo/python-mysql-example.git

Installing the MySql driver

We are going to use Oracle’s official MySql driver for Python.

All the documentation is here:

https://dev.mysql.com/doc/connector-python/en/

In order to install we will use pip.

To install it in Ubuntu:

pip install mysql-connector-python

In Mac Os X you have to use pip3 instead of pip.

However we are going to run everything from a Docker Container so the only thing you need is to have installed Docker.

If you prefer to install MySql in your computer (or Virtual Box instance) directly, skip the Docker steps.

Dockerfile

The Dockerfile is the file that Docker uses to build the Docker Container.

Ours is like that:

FROM ubuntu:20.04

MAINTAINER Carles Mateo

ARG DEBIAN_FRONTEND=noninteractive

RUN apt update && apt install -y python3 pip mysql-server vim mc wget curl && apt-get clean
RUN pip install mysql-connector-python

EXPOSE 3306

ENV FOLDER_PROJECT /var/mysql_carles

RUN mkdir -p $FOLDER_PROJECT

COPY docker_run_mysql.sh $FOLDER_PROJECT
COPY start.sql $FOLDER_PROJECT
COPY src $FOLDER_PROJECT

RUN chmod +x /var/mysql_carles/docker_run_mysql.sh

CMD ["/var/mysql_carles/docker_run_mysql.sh"]

The first line defines that we are going to use Ubuntu 20.04 (it’s a LTS version).

We install all the apt packages in a single line, as Docker works in layers, and what is used as disk space in the previous layer is not deleted even if we delete the files, so we want to run apt update, install all the packages, and clean the temporal files in one single step.

I also install some useful tools like: vim, mc, less, wget and curl.

We expose to outside the port 3306, in case you want to run the Python code from your computer, but having the MySql in the Container.

The last line executes a script that starts the MySql service, creates the table, the user, and add two rows and runs an infinite loop so the Docker does not finish.

build_docker.sh

build_docker.sh is a Bash script that builds the Docker Image for you very easily.

It stops the container and removes the previous image, so your hard drive does not fill with Docker images if you do modifications.

It checks for errors building and it also remembers you how to run and debug the Docker Container.

#!/bin/bash

# Execute with sudo

s_DOCKER_IMAGE_NAME="blog_carlesmateo_com_mysql"

printf "Stopping old image %s\n" "${s_DOCKER_IMAGE_NAME}"
sudo docker stop "${s_DOCKER_IMAGE_NAME}"

printf "Removing old image %s\n" "${s_DOCKER_IMAGE_NAME}"
sudo docker rm "${s_DOCKER_IMAGE_NAME}"

printf "Creating Docker Image %s\n" "${s_DOCKER_IMAGE_NAME}"
sudo docker build -t ${s_DOCKER_IMAGE_NAME} . --no-cache

i_EXIT_CODE=$?
if [ $i_EXIT_CODE -ne 0 ]; then
printf "Error. Exit code %s\n" ${i_EXIT_CODE}
exit
fi

echo "Ready to run ${s_DOCKER_IMAGE_NAME} Docker Container"
echo "To run type: sudo docker run -d -p 3306:3306 --name ${s_DOCKER_IMAGE_NAME} ${s_DOCKER_IMAGE_NAME}"
echo "or just use run_in_docker.sh"
echo
echo "Debug running Docker:"
echo "docker exec -it ${s_DOCKER_IMAGE_NAME} /bin/bash"
echo

docker_run.sh

I also provide a script named docker_run.sh that runs your Container easily, exposing the MySql port.

#!/bin/bash

# Execute with sudo

s_DOCKER_IMAGE_NAME="blog_carlesmateo_com_mysql"

docker run -d -p 3306:3306 --name ${s_DOCKER_IMAGE_NAME} ${s_DOCKER_IMAGE_NAME}

echo "Showing running Instances"
docker ps

As you saw before I named the image after blog_carlesmateo_com_mysql.

I did that so basically I wanted to make sure that the name was unique, as the build_docker.sh deletes an image named like the name I choose, I didn’t want to use a generic name like “mysql” that may lead to you to delete the Docker Image inadvertently.

docker_run_mysql.sh

This script will run when the Docker Container is launched for the first time:

#!/bin/bash

# Allow to be queried from outside
sed -i '31 s/bind-address/#bind-address/' /etc/mysql/mysql.conf.d/mysqld.cnf

service mysql start

# Create a Database, a user with password, and permissions
cd /var/mysql_carles
mysql -u root < start.sql

while [ true ]; do sleep 60; done

With sed command we modify the line 31 of the the MySQL config file so we can connect from Outside the Docker Instance (bind-address: 127.0.0.1)

As you can see it executes the SQL contained in the file start.sql as root and we start MySql.

Please note: Our MySql installation has not set a password for root. It is only for Development purposes.

start.sql

The SQL file that will be ran inside our Docker Container.

CREATE DATABASE carles_database;


CREATE USER ‘python’@’localhost’ IDENTIFIED BY ‘blog.carlesmateo.com-db-password’;
CREATE USER ‘python’@’%’ IDENTIFIED BY ‘blog.carlesmateo.com-db-password’;
GRANT ALL PRIVILEGES ON carles_database.* TO ‘python’@’localhost’;
GRANT ALL PRIVILEGES ON carles_database.* TO ‘python’@’%’;


USE carles_database;


CREATE TABLE car_queue (
i_id_car int,
s_model_code varchar(25),
s_color_code varchar(25),
s_extras varchar(100),
i_right_side int,
s_city_to_ship varchar(25)
);

INSERT INTO car_queue (i_id_car, s_model_code, s_color_code, s_extras, i_right_side, s_city_to_ship) VALUES (1, "GOLF2021", "BLUE7", "COND_AIR, GPS, MULTIMEDIA_V3", 0, "Barcelona");
INSERT INTO car_queue (i_id_car, s_model_code, s_color_code, s_extras, i_right_side, s_city_to_ship) VALUES (2, "GOLF2021_PLUGIN_HYBRID", "BLUEMETAL_5", "COND_AIR, GPS, MULTIMEDIA_V3, SECURITY_V5", 1, "Cork");

As you can see it creates the user “python” with the password ‘blog.carlesmateo.com-db-password’ for access local and remote (%).

It also creates a Database named carles_database and grants all the permissions to the user “python”, for local and remote.

This is the user we will use to authenticate from out Python code.

Then we switch to use the carles_database and we create the car_queue table.

We insert two rows, as an example.

select_values_example.py

Finally the Python code that will query the Database.

import mysql.connector

if __name__ == "__main__":
    o_conn = mysql.connector.connect(user='python', password='blog.carlesmateo.com-db-password', database='carles_database')
    o_cursor = o_conn.cursor()

    s_query = "SELECT * FROM car_queue"

    o_cursor.execute(s_query)

    for a_row in o_cursor:
        print(a_row)

    o_cursor.close()
    o_conn.close()

Nothing special, we open a connection to the MySql and perform a query, and parse the cursor as rows/lists.

Please note: Error control is disabled so you may see any exception.

Executing the Container

First step is to build the Container.

From the directory where you cloned the project, execute:

sudo ./build_docker.sh

Then run the Docker Container:

sudo ./docker_run.sh

The script also performs a docker ps command, so you can see that it’s running.

Entering the Container and running the code

Now you can enter inside the Docker Container:

docker exec -it blog_carlesmateo_com_mysql /bin/bash

Then change to the directory where I installed the sample files:

cd /var/mysql_carles

And execute the Python 3 example:

python3 select_values_example.py

Tying together MySql and a Python Menu with Object Oriented Programming

In order to tie all together, and specially to give a consistent view to my students, to avoid showing only pieces but a complete program, and to show a bit of Objects Oriented in action I developed a small program which simulates the handling of a production queue for Volkswagen.

MySQL Library

First I created a library to handle MySQL operations.

lib/mysqllib.py

import mysql.connector


class MySql():

    def __init__(self, s_user, s_password, s_database, s_host="127.0.0.1", i_port=3306):
        self.s_user = s_user
        self.s_password = s_password
        self.s_database = s_database
        self.s_host = s_host
        self.i_port = i_port

        o_conn = mysql.connector.connect(host=s_host, port=i_port, user=s_user, password=s_password, database=s_database)
        self.o_conn = o_conn

    def query(self, s_query):
        a_rows = []

        o_cursor = self.o_conn.cursor()

        o_cursor.execute(s_query)

        for a_row in o_cursor:
            a_rows.append(a_row)

        o_cursor.close()

        return a_rows

    def insert(self, s_query):

        o_cursor = self.o_conn.cursor()

        o_cursor.execute(s_query)
        i_inserted_row_count = o_cursor.rowcount

        # Make sure data is committed to the database
        self.o_conn.commit()

        return i_inserted_row_count

    def delete(self, s_query):

        o_cursor = self.o_conn.cursor()

        o_cursor.execute(s_query)
        i_deleted_row_count = o_cursor.rowcount

        # Make sure data is committed to the database
        self.o_conn.commit()

        return i_deleted_row_count


    def close(self):

        self.o_conn.close()

Basically when this class is instantiated, a new connection to the MySQL specified in the Constructor is established.

We have a method query() to send SELECT queries.

We have a insert method, to send INSERT, UPDATE queries that returns the number of rows affected.

This method ensures to perform a commit to make sure changes persist.

We have a delete method, to send DELETE Sql queries that returns the number of rows deleted.

We have a close method which closes the MySql connection.

A Data Object: CarDO

Then I’ve defined a class, to deal with Data and interactions of the cars.

do/cardo.py


class CarDO():

    def __init__(self, i_id_car=0, s_model_code="", s_color_code="", s_extras="", i_right_side=0, s_city_to_ship=""):
        self.i_id_car = i_id_car
        self.s_model_code = s_model_code
        self.s_color_code = s_color_code
        self.s_extras = s_extras
        self.i_right_side = i_right_side
        self.s_city_to_ship = s_city_to_ship

        # Sizes for render
        self.i_width_id_car = 6
        self.i_width_model_code = 25
        self.i_width_color_code = 25
        self.i_width_extras = 50
        self.i_width_side = 5
        self.i_width_city_to_ship = 15

    def print_car_info(self):
        print("Id:", self.i_id_car)
        print("Model Code:", self.s_model_code)
        print("Color Code:", self.s_color_code)
        print("Extras:", self.s_extras)
        s_side = self.get_word_for_driving_side()
        print("Drive by side:", s_side)
        print("City to ship:", self.s_city_to_ship)

    def get_word_for_driving_side(self):
        if self.i_right_side == 1:
            s_side = "Right"
        else:
            s_side = "Left"

        return s_side

    def get_car_info_for_list(self):

        s_output = str(self.i_id_car).rjust(self.i_width_id_car) + " "
        s_output += self.s_model_code.rjust(self.i_width_model_code) + " "
        s_output += self.s_color_code.rjust(self.i_width_color_code) + " "
        s_output += self.s_extras.rjust(self.i_width_extras) + " "
        s_output += self.get_word_for_driving_side().rjust(self.i_width_side) + " "
        s_output += self.get_s_city_to_ship().rjust(self.i_width_city_to_ship)

        return s_output

    def get_car_header_for_list(self):
        s_output = str("Id Car").rjust(self.i_width_id_car) + " "
        s_output += "Model Code".rjust(self.i_width_model_code) + " "
        s_output += "Color Code".rjust(self.i_width_color_code) + " "
        s_output += "Extras".rjust(self.i_width_extras) + " "
        s_output += "Drive".rjust(self.i_width_side) + " "
        s_output += "City to Ship".rjust(self.i_width_city_to_ship)

        i_total_length = self.i_width_id_car + self.i_width_model_code + self.i_width_color_code + self.i_width_extras + self.i_width_side + self.i_width_city_to_ship
        # Add the space between fields
        i_total_length = i_total_length + 5

        s_output += "\n"
        s_output += "=" * i_total_length

        return s_output

    def get_i_id_car(self):
        return self.i_id_car

    def get_s_model_code(self):
        return self.s_model_code

    def get_s_color_code(self):
        return self.s_color_code

    def get_s_extras(self):
        return self.s_extras

    def get_i_right_side(self):
        return self.i_right_side

    def get_s_city_to_ship(self):
        return self.s_city_to_ship

Initially I was going to have a CarDO Object without any logic. Only with Data.

In OOP the variables of the Instance are called Properties, and the functions Methods.

Then I decided to add some logic, so I can show what’s the typical use of the objects.

So I will use CarDO as Data Object, but also to do few functions like printing the info of a Car.

Queue Manager

Finally the main program.

We also use Object Oriented Programming, and we use Dependency Injection to inject the MySQL Instance. That’s very practical to do Unit Testing.

from lib.mysqllib import MySql
from do.cardo import CarDO


class QueueManager():

    def __init__(self, o_mysql):
        self.o_mysql = o_mysql

    def exit(self):
        exit(0)

    def main_menu(self):
        while True:
            print("Main Menu")
            print("=========")
            print("")
            print("1. Add new car to queue")
            print("2. List all cars to queue")
            print("3. View car by Id")
            print("4. Delete car from queue by Id")
            print("")
            print("0. Exit")
            print("")

            s_option = input("Choose your option:")
            if s_option == "1":
                self.add_new_car()
            if s_option == "2":
                self.see_all_cars()
            if s_option == "3":
                self.see_car_by_id()
            if s_option == "4":
                self.delete_by_id()

            if s_option == "0":
                self.exit()

    def get_all_cars(self):
        s_query = "SELECT * FROM car_queue"

        a_rows = self.o_mysql.query(s_query)
        a_o_cars = []

        for a_row in a_rows:
            i_id_car = a_row[0]
            s_model_code = a_row[1]
            s_color_code = a_row[2]
            s_extras = a_row[3]
            i_right_side = a_row[4]
            s_city_to_ship = a_row[5]

            o_car = CarDO(i_id_car=i_id_car, s_model_code=s_model_code, s_color_code=s_color_code, s_extras=s_extras, i_right_side=i_right_side, s_city_to_ship=s_city_to_ship)
            a_o_cars.append(o_car)

        return a_o_cars

    def get_car_by_id(self, i_id_car):
        b_success = False
        o_car = None

        s_query = "SELECT * FROM car_queue WHERE i_id_car=" + str(i_id_car)

        a_rows = self.o_mysql.query(s_query)

        if len(a_rows) == 0:
            # False, None
            return b_success, o_car

        i_id_car = a_rows[0][0]
        s_model_code = a_rows[0][1]
        s_color_code = a_rows[0][2]
        s_extras = a_rows[0][3]
        i_right_side = a_rows[0][4]
        s_city_to_ship = a_rows[0][5]

        o_car = CarDO(i_id_car=i_id_car, s_model_code=s_model_code, s_color_code=s_color_code, s_extras=s_extras, i_right_side=i_right_side, s_city_to_ship=s_city_to_ship)
        b_success = True

        return b_success, o_car

    def replace_apostrophe(self, s_text):
        return s_text.replace("'", "´")

    def insert_car(self, o_car):

        s_sql = """INSERT INTO car_queue 
                                (i_id_car, s_model_code, s_color_code, s_extras, i_right_side, s_city_to_ship) 
                         VALUES 
                                (""" + str(o_car.get_i_id_car()) + ", '" + o_car.get_s_model_code() + "', '" + o_car.get_s_color_code() + "', '" + o_car.get_s_extras() + "', " + str(o_car.get_i_right_side()) + ", '" + o_car.get_s_city_to_ship() + "');"

        i_inserted_row_count = self.o_mysql.insert(s_sql)

        if i_inserted_row_count > 0:
            print("Inserted", i_inserted_row_count, " row/s")
            b_success = True
        else:
            print("It was impossible to insert the row")
            b_success = False

        return b_success

    def add_new_car(self):
        print("Add new car")
        print("===========")

        while True:
            s_id_car = input("Enter new ID: ")
            if s_id_car == "":
                print("A numeric Id is needed")
                continue

            i_id_car = int(s_id_car)

            if i_id_car < 1:
                continue

            # Check if that id existed already
            b_success, o_car = self.get_car_by_id(i_id_car=i_id_car)
            if b_success is False:
                # Does not exist
                break

            print("Sorry, this Id already exists")

        s_model_code = input("Enter Model Code:")
        s_color_code = input("Enter Color Code:")
        s_extras = input("Enter extras comma separated:")
        s_right_side = input("Enter R for Right side driven:")
        if s_right_side.upper() == "R":
            i_right_side = 1
        else:
            i_right_side = 0
        s_city_to_ship = input("Enter the city to ship the car:")

        # Sanitize SQL replacing apostrophe
        s_model_code = self.replace_apostrophe(s_model_code)
        s_color_code = self.replace_apostrophe(s_color_code)
        s_extras = self.replace_apostrophe(s_extras)
        s_city_to_ship = self.replace_apostrophe(s_city_to_ship)

        o_car = CarDO(i_id_car=i_id_car, s_model_code=s_model_code, s_color_code=s_color_code, s_extras=s_extras, i_right_side=i_right_side, s_city_to_ship=s_city_to_ship)
        b_success = self.insert_car(o_car)

    def see_all_cars(self):
        print("")

        a_o_cars = self.get_all_cars()

        if len(a_o_cars) > 0:
            print(a_o_cars[0].get_car_header_for_list())
        else:
            print("No cars in queue")
            print("")
            return

        for o_car in a_o_cars:
            print(o_car.get_car_info_for_list())

        print("")

    def see_car_by_id(self, i_id_car=0):
        if i_id_car == 0:
            s_id = input("Car Id:")
            i_id_car = int(s_id)

        s_id_car = str(i_id_car)

        b_success, o_car = self.get_car_by_id(i_id_car=i_id_car)
        if b_success is False:
            print("Error, car id: " + s_id_car + " not located.")
            return False

        print("")
        o_car.print_car_info()
        print("")

        return True

    def delete_by_id(self):

        s_id = input("Enter Id of car to delete:")
        i_id_car = int(s_id)

        if i_id_car == 0:
            print("Invalid Id")
            return

        # reuse see_car_by_id
        b_found = self.see_car_by_id(i_id_car=i_id_car)
        if b_found is False:
            return

        s_delete = input("Are you sure you want to DELETE. Type Y to delete: ")
        if s_delete.upper() == "Y":
            s_sql = "DELETE FROM car_queue WHERE i_id_car=" + str(i_id_car)
            i_num = self.o_mysql.delete(s_sql)

            print(i_num, " Rows deleted")

            # if b_success is True:
            #     print("Car deleted successfully from the queue")


if __name__ == "__main__":

    try:

        o_mysql = MySql(s_user="python", s_password="blog.carlesmateo.com-db-password", s_database="carles_database", s_host="127.0.0.1", i_port=3306)

        o_queue_manager = QueueManager(o_mysql=o_mysql)
        o_queue_manager.main_menu()
    except KeyboardInterrupt:
        print("Detected CTRL + C. Exiting")

This program talks to MySQL, that we have started in a Docker previously.

We have access from inside the Docker Container, or from outside.

The idea of this simple program is to use a library for dealing with MySql, and objects for dealing with the Cars. The class CarDO contributes to the render of its data in the screen.

To enter inside the Docker once you have generated it and is running, do:

docker exec -it blog_carlesmateo_com_mysql /bin/bash

Then:

cd /var/mysql_carles 
python3 queue_manager.py

Bonus

I added a file called queue_manager.php so you can see how easy is to render a HTML page with data coming from the Database, from PHP.

A base Dockerfile for my Jenkins deployments

So I share with you my base Jenkins Dockerfile, so you can spawn a new Jenkins for your projects.

The Dockerfile installs Ubuntu 20.04 LTS as base image and add the required packages to run jenkins but also Development and Testing tools to use inside the Container to run Unit Testing on your code, for example. So you don’t need external Servers, for instance.

You will need 3 files:

  • Dockerfile
  • docker_run_jenkins.sh
  • requirements.txt

The requirements.txt file contains your PIP3 dependencies. In my case I only have pytest version 4.6.9 which is the default installed with Ubuntu 20.04, however, this way, I enforce that this and not any posterior version will be installed.

File requirements.txt:

pytest==4.6.9

The file docker_run_jenkins.txt start Jenkins when the Container is run and it will wait until the initial Admin password is generated and then it will display it.

File docker_run_jenkins.sh:

#!/bin/bash

echo "Starting Jenkins..."

service jenkins start

echo "Configure jenkins in http://127.0.0.1:8080"

s_JENKINS_PASSWORD_FILE="/var/lib/jenkins/secrets/initialAdminPassword"

i_PASSWORD_PRINTED=0

while [ true ];
do
    sleep 1
    if [ $i_PASSWORD_PRINTED -eq 1 ];
    then
        # We are nice with multitasking
        sleep 60
        continue
    fi

    if [ ! -f "$s_JENKINS_PASSWORD_FILE" ];
    then
        echo "File $s_FILE_ORIGIN does not exist"
    else
        echo "Password for Admin is:"
        cat $s_JENKINS_PASSWORD_FILE
        i_PASSWORD_PRINTED=1
    fi
done

That file has the objective to show you the default admin password, but you don’t need to do that, you can just start a shell into the Container and check manually by yourself.

However I added it to make it easier for you.

And finally you have the Dockerfile:

FROM ubuntu:20.04

LABEL Author="Carles Mateo" \
      Email="jenkins@carlesmateo.com" \
      MAINTAINER="Carles Mateo"

# Build this file with:
# sudo docker build -f Dockerfile -t jenkins:base .
# Run detached:
# sudo docker run --name jenkins_base -d -p 8080:8080 jenkins:base
# Run seeing the password:
# sudo docker run --name jenkins_base -p 8080:8080 -i -t jenkins:base
# After you CTRL + C you will continue with:
# sudo docker start
# To debug:
# sudo docker run --name jenkins_base -p 8080:8080 -i -t jenkins:base /bin/bash

ARG DEBIAN_FRONTEND=noninteractive

ENV SERVICE jenkins

RUN set -ex

RUN echo "Creating directories and copying code" \
    && mkdir -p /opt/${SERVICE}

COPY requirements.txt \
    docker_run_jenkins.sh \
    /opt/${SERVICE}/

# Java with Ubuntu 20.04 LST is 11, which is compatible with Jenkins.
RUN apt update \
    && apt install -y default-jdk \
    && apt install -y wget curl gnupg2 \
    && apt install -y git \
    && apt install -y python3 python3.8-venv python3-pip \
    && apt install -y python3-dev libsasl2-dev libldap2-dev libssl-dev \
    && apt install -y python3-venv \
    && apt install -y python3-pytest \
    && apt install -y sshpass \
    && wget -qO - https://pkg.jenkins.io/debian-stable/jenkins.io.key | apt-key add - \
    && echo "deb http://pkg.jenkins.io/debian-stable binary/" > /etc/apt/sources.list.d/jenkins.list \
    && apt update \
    && apt -y install jenkins \
    && apt-get clean

RUN echo "Setting work directory and listening port"
WORKDIR /opt/${SERVICE}

RUN chmod +x docker_run_jenkins.sh

RUN pip3 install --upgrade pip \
    && pip3 install -r requirements.txt


EXPOSE 8080


ENTRYPOINT ["./docker_run_jenkins.sh"]

Build the Container

docker build -f Dockerfile -t jenkins:base .

Run the Container displaying the password

sudo docker run --name jenkins_base -p 8080:8080 -i -t jenkins:base

You need this password for starting the configuration process through the web.

Visit http://127.0.0.1:8080 to configure Jenkins.

Configure as usual

Resuming after CTRL + C

After you configured it, on the terminal, press CTRL + C.

And continue, detached, by running:

sudo docker start jenkins_base

The image is 1.2GB in size, and will allow you to run Python3, Virtual Environments, Unit Testing with pytest and has Java 11 (not all versions of Java are compatible with Jenkins), use sshpass to access other Servers via SSH with Username and Password…

Solving the problem when running a Docker Container: standard_init_linux.go:190: exec user process caused “no such file or directory”

When you see this error for the first time it can be pretty ugly to detect why it happens.

At personal level I use only Linux for my computers, with an exception of a windows laptop that I keep for specific tasks. But my employers often provide me laptops with windows.

I suffered this error for first time when I inherited a project, in a company I joined time ago. And I suffered some time later, by the same reason, so I decided to explain it easily.

In the project I inherited the build process was broken, so I had to fix it, and when this was done I got the mentioned error when trying to run the Container:

standard_init_linux.go:190: exec user process caused "no such file or directory"

The Dockerfile was something like this:

FROM docker-io.battle.net/alpine:3.10.0

LABEL Author="Carles Mateo" \
      Email="docker@carlesmateo.com" \
      MAINTAINER="Carles Mateo"

ENV SERVICE cservice

RUN set -ex

RUN echo "Creating directories and copying code" \
    && mkdir -p /opt/${SERVICE}
    
COPY config.prod \
    config.dev \
    config.st \
    requirements.txt \
    utils.py \
    cservice.py \
    tests/test_cservice.py \
    run_cservice.sh \
    /opt/${SERVICE}/

RUN echo "Setting work directory and listening port"
WORKDIR /opt/${SERVICE}
EXPOSE 7000

RUN echo "Installing dependencies" \
    && apk add build-base openldap-dev python3-dev py-pip \
    && pip3 install --upgrade pip \
    && pip3 install -r requirements.txt \
    && pip3 install pytest

ENTRYPOINT ["./run_cservice.sh"]

So the project was executing a Bash script run_cservice.sh, via Dockerfile ENTRYPOINT.

That script would do the necessary amends depending if the Container is launched with prod, dev, or staging parameter.

I debugged until I saw that the Container never executed this in the expected way.

A echo “Debug” on top of the Bash Script would be enough to know that very basic call was never executed. The error was first.

After much troubleshooting the Container I found that the problem was that the Bash script, that was copied to the container with COPY in the Dockerfile, from a Windows Machines, contained CRLF Windows carriage return. While for Linux and Mac OS X carriage return is just a character, LF.

In that company we all use Windows. And trying to build the Container worked after removing the CRLF, but the Bash script with CRLF was causing that problem.

When I replace the CRLF by Unix type LF, and rebuild the image, and ran the container, it worked lovely.

A very easy, manual way, to do this in Windows, is opening your file with Notepad++ and setting LF as carriage return. Save the file, rebuild, and you’ll see your Container working.

Please note that in the Dockerfile provided I install pytest Framework and a file calles tests/test_cservice.py. That was not in the original Dockerfile, but I wanted to share with you that I provide Unit Testing that can be ran from a Linux Container, for all my projects. What normally I do is to have two Dockerfiles. One for the Production version to be deployed, another for running Unit Testing, and some time functional testing as well, from inside the Docker Container. So strictly speaking for the production version, I would not copy the tests/test_cservice.py and install pytest. A different question are internal Automation Tools, where it may be interested providing a All-in-One image, that can run the Unit Testing before start the service. It is interesting to provide some debugging tools in out Internal Automation Tools, so we can troubleshoot what’s going on in case of problems. Take a look at my previous article about Python version for Docker and Automation tools, for more considerations.

Refreshing settings in a Docker immutable image with Python and Flask

This is a trick to restart a Service that is running on a immutable Docker, with some change, and you need to refresh the values very quickly without having to roll the CI/CD Jenkins Pipeline and uploading a new image.

So why would you need to do that?.

I can think about possible scenarios like:

  • Need to roll out an urgent fix in a time critical manner
  • Jenkins is broken
  • Somebody screw it on the git master branch
  • Docker Hub is down
  • GitHub is down
  • Your artifactory is down
  • The lines between your jumpbox or workstation and the secure Server are down and you have really few bandwidth
  • You have to fix something critical and you only have a phone with you and SSH only
  • Maybe the Dockerfile had latest, and the latest image has changed
FROM os:latest

The ideal is that if you work with immutable images, you roll out a new immutable image and that’s it.

But if for whatever reason you need to update this super fast, this trick may become really handy.

Let’s go for it!.

Normally you’ll start your container with a command similar to this:

docker run -d --rm -p 5000:5000 api_carlesmateo_com:v7 prod 

The first thing we have to do is to stop the container.

So:

docker ps

Locate your container across the list of running containers and stop it, and then restart without the –rm:

docker stop container_name
docker run -d -p 5000:5000 api_carlesmateo_com:v7 prod

the –rm makes the container to cleanup. By default a container’s file system persists even after the container exits. So don’t start it with –rm.

Ok, so login to the container:

docker exec -it container_name /bin/sh 

Edit the config you require to change, for example config.yml

If what you have to update is a password, and is encoded in base64, encode it:

echo -n "ThePassword" | base64
VGhlUGFzc3dvcmQ=

Stop the container. You can do it by stopping the container with docker stop or from inside the container, killing the listening process, probably a Python Flask.

If your Dockerfile ends with something like:

ENTRYPOINT ["./webservice.py"]

And webservice.py has Python Flask code similar to this:

#!/usr/bin/python3
#
# webservice.py
#
# Author: Carles Mateo
# Creation Date: 2020-05-10 20:50 GMT+1
# Description: A simple Flask Web Application
#              Part of the samples of https://leanpub.com/pythoncombatguide
#              More source code for the book at https://gitlab.com/carles.mateo/python_combat_guide
#


from flask import Flask, request
import logging

# Initialize Flask
app = Flask(__name__)


# Sample route so http://127.0.0.1/carles
@app.route('/carles', methods=['GET'])
def carles():
    logging.critical("A connection was established")
    return "200"

logging.info("Initialized...")

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=5000, debug=True)

Then you can kill the process, and so ending the container, from inside the container by doing:

ps -ax | grep webservice
 5750 root     56:31 {webservice.py} /usr/bin/python /opt/webservice/webservice.py
kill -9 5790

This will finish the container the same way as docker stop container_name.

Then start the container (not run)

docker start container_name

You can now test from outside or from inside the container. If from inside:

/opt/webservice # wget localhost:5000/carles
Connecting to localhost:5000 (127.0.0.1:5000)
carles               100% |**************************************************************************************************************|     3  0:00:00 ETA
/opt/webservice # cat debug.log
2020-05-06 20:46:24,349 Initialized...
2020-05-06 20:46:24,359  * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
2020-05-06 20:46:24,360  * Restarting with stat
2020-05-06 20:46:24,764 Initialized...
2020-05-06 20:46:24,771  * Debugger is active!
2020-05-06 20:46:24,772  * Debugger PIN: 123-456-789
2020-05-07 13:18:43,890 127.0.0.1 - - [07/May/2020 13:18:43] "GET /carles HTTP/1.1" 200 -

if you don’t use YAML files or what you need is to change the code, all this can be avoided as when you update the Python code, Flash realizes that and reloads. See this line in the logs:

2020-05-07 13:18:40,431  * Detected change in '/opt/webservice/wwebservice.py', reloading

The webservice.py autoreloads because we init Flask with debug set to on.

You can also start a container with shell directly:

sudo docker run -it ctop /bin/bash

The Ethernet standards group announces a new 800 GbE specification

Here is the link to the new: https://www.pcgamer.com/amp/the-ethernet-standards-group-developed-a-new-speed-so-fast-it-had-to-change-its-name/

And this makes me think about all the Architects that are using Memcached and Redis in different Servers, in Networks of 1Gbps and makes me want to share with you what a nonsense, is often, that.

So the idea of having Memcache or Redis is just to cache the queries and unload the Database from those queries.

But 1Gbps is equivalent to 125MB (Megabytes) per second.

Local RAM Memory in Servers can perform at 24GB and more (24,000,000 Megabytes) per second, even more.

A PCIE NVMe drive at 3.5GB per second.

A local SSD drive without RAID 550 MB/s.

A SSD in the Cloud, varies a lot on the provider, number of drives, etc… but I’ve seen between 200 MB/s and 2.5GB/s aggregated in RAID.

In fact I have worked with Servers equipped with several IO Controllers, that were delivering 24GB/s of throughput writing or reading to HDD spinning drives.

If you’re in the Cloud. Instead of having 2 Load Balancers, 100 Front Web servers, with a cluster of 5 Redis with huge amount of RAM, and 1 MySQL Master and 1 Slave, all communicating at 1Gbps, probably you’ll get a better performance having the 2 LBs, and 11 Front Web with some more memory and having the Redis instance in the same machine and saving the money of that many small Front and from the 5 huge dedicated Redis.

The same applies if you’re using Docker or K8s.

Even if you just cache the queries to drive, speed will be better than sending everything through 1 Gbps.

This will matter for you if your site is really under heavy load. Most of the sites just query the MySQL Server using 1 Gbps lines, or 2 Gbps in bonding, and that’s enough.