Python decorators for dummies

If you’re going through interviews for the positions of Python developer, or looking forward to preparing for one, or just a curios developer, you better have your head clear around the concept of decorators in Python programming language.
I won’t be delving into ‘what are design patterns’ , and why should you make use of it, whenever possible. The post is merely about understanding and writing decorators in Python. You can find plethora of posts about Python decorators, the motivation for me is, that everyone has their own way of explaining, especially a technical concept.

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Deploy Django with NginX, Gunicorn, PostgreSQL, virtualenv

Step 0 – Update and upgrade

We are using Ubuntu 16.04 LTS for this tutorial
ubuntu version
apt-get update update the list of available packages and their versions, but it does not install or upgrade any packages. apt-get upgrade actually installs newer versions of the packages you have. After updating the lists, the package manager knows about available updates for the software you have installed.
$ sudo apt-get update
$ sudo apt-get upgrade

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Deploy Django using Docker Compose

Related posts
With the adaptation of micro-service architecture i.e. various components as independent services, docker community came up with docker-compose (previously FIg). Using a single (YAML) configuration file (docker-compose.yml) to specify all the components, which docker compose build and spawn as independent services i.e. docker containers.
Use-case: You have a web project, with web application developed using Django, using a Postgres database, redis as caching engine, and NginX for serving over the web. Using docker-compose you can deploy this stack with a single command:
docker-compose build --no-cache && docker-compose up
The complete project is available here.
This blog post is about using docker compose, for deploying your Django application with Postgres, Redis, and Nginx. It is presumed, you already have your Django project, and want to deploy your full stack.

High level steps

  1. Install and start Docker compose
  2. Setup project – presume you already have a Django project.
  3. Create Dockerfile(s) and docker-compose.yml
  4. Build service images – docker-compose build
  5. Create database and database migrations – docker-compose run web python manage.py migrate
  6. Start services containers – docker-compose up
  7. View in browser http://127.0.0.1

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OpenStack all-in-one setup on CentOS

OpenStack is an open-source cloud operating system for setting up IAAS (infrastructure as a service). OpenStack provides a flexible solution for both public and private clouds, covering the two important requirements i.e. cloud must be simple to implement and massively scalable. For production a minimal OpenStack setup requires at-least 2 separate machine, one controller and one compute node. To get started with OpenStack, a common practice is to setup an all-in-one deployment i.e. using a single machine.
This guide is about setting-up an all-in-one setup for OpenStack Queens, the latest release.

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Configure static IP address on CentOS

After a fresh installation CentOS uses DHCP (dhclient -v) to assign an IP to the machine, which keep in changing on reboots, or service restarts, etc.

Use-case: Various service setups, especially involving a clustered configuration we need to set a fixed IP for each machine, so they can communication with each other, in case of DHCP the installation may break on the reboot, as anyone of the machine gets a new IP address. So the first step is to set a static IP address. Continue reading “Configure static IP address on CentOS” →

Install XAMPP stack on Ubuntu 16.04 using terminal

Apache is the widely used web server, and PHP is a dominant technology when it comes to CMS frameworks i.e. WordPress, Drupal, etc. For this reason the deployment of the stack has been made effortless with XAMPP PHP development environment. XAMPP is an acronym, where X stands for any operating system (WAMP for Windows, LAMP for Linux), A for Apache web server, M for MySQL or MariaDB database engine, and PP stands for PHP and Perl. The post is about setting-up PHP development environment XAMPP on Ubuntu 16.04, suing terminal.

Step 0 – Login and update

First of all login into your Ubuntu machine using SSH – for a regular it’s recommended to add your SSH public key.
ssh <username>@<hostname/IP>

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All you need to know about SSH

Introduction

SSH stands for Secure SHell, a tool developed by SSH Communication Security Ltd, for secure remote log-in and command execution. It’s a secure alternative of it’s predecessors rlogin, rsh, etc. SSH has become industry de-facto for securely communicating with remote machines i.e. the entire session is encrypted.
The SSH is based on public-key cryptography (also known as asymmetric cryptography), a cryptography system employing key pair i.e. a public key which is meant to be shared, and private key which has to be kept safe and secret, only known to the owner. This pair serves two purpose 1. authentication, the public key verifies the owner of the paired private key, and 2. encryption, the public key encrypts the message, and only the paired private key can decrypt it. In simple words, you can share your public key (content of ~/.ssh/id_rsa.pub) with anyone via email, for example: to access a remote machine securely and without password, all you need to do is copy your public key to authorized_keys (default – ~/.ssh/authorized_keys) file.

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DB partition trigger with PostgreSQL

Database partitioning is about logically splitting one large table into smaller physical pieces, such that improving query performance.  DB partitioning is a good alternate for indexing multiple columns, reducing index size, hence the memory in use. Few common pros of database partitioning:
  • Improved performance – data operations (CRUD) can be performed on a smaller volume of data, for example, in case of collecting data overtime, putting old data in separate partition might help with performance.
  • Bulk create and delete can be efficient by adding or removing separate partitions.
  • Time based partition can be helpful in cleaning old seldom-used data i.e. month based partition we can simply set a cron job for cleaning 12 month old partition, without effecting the table portion heavily in use for ADD, UPDATE, etc.
  • Improved scalability – In case of very large tables, you can partition and have them hosted on a separate server.
There are 2 main approaches to database partitioning:
  • Horizontal partitioning (Sharding) – a table is split horizontally, such that each partition is a subset of the table, having the same schema (i.e. number of fields/columns).
  • Vertical partitioning – a table is split on the fields/columns, such that each subset has separate schema. A common use-case for vertical partitioning is to partition table fields on the basis of pattern of use i.e. frequently accessed fields are to be grouped together, and the less frequently accessed are put in a separate partition.
This blog post is about setting automatic horizontal partitioning (month based) on a table in PostgreSQL.
The high-level steps are:
  1. Create table, or select an existing one.
  2. Execute partitioning function or procedure
  3. Table trigger – to call the partition procedure.
  4. View for parent-child tables (optional)
  5. Verification.

Step 1 – Create Table

CREATE TABLE partition_test(id BIGINT, created_datetime DATE);
Output:
Create table

Step 2 – Trigger function

CREATE OR REPLACE FUNCTION test_partition_function() RETURNS trigger AS
$BODY$
DECLARE
partition_date TEXT;
partition TEXT;
BEGIN
partition_date := to_char(NEW.created_datetime,'YYYY_MM');
partition := TG_RELNAME || '_' || partition_date;
IF NOT EXISTS(SELECT relname FROM pg_class WHERE relname=partition) THEN
RAISE NOTICE 'A partition has been created %',partition;
EXECUTE 'CREATE TABLE ' || partition || ' () INHERITS (' || TG_RELNAME || ');';
END IF;
EXECUTE 'INSERT INTO ' || partition || ' SELECT(' || TG_RELNAME || ' ' || quote_literal(NEW) || ').* RETURNING id;';
RETURN NULL;
END;
$BODY$
LANGUAGE plpgsql VOLATILE
COST 100;
Output:
partition function

Step 3 – Table trigger

CREATE TRIGGER partition_test_trg
AFTER INSERT ON partition_test
FOR EACH ROW EXECUTE PROCEDURE test_partition_function();
Output:
table trigger

Step 4 – Viewing the partition (optional)

CREATE VIEW show_partitions AS
SELECT nmsp_parent.nspname AS parent_schema,
parent.relname AS parent,
nmsp_child.nspname AS child_schema,
child.relname AS child
FROM pg_inherits
JOIN pg_class parent ON pg_inherits.inhparent = parent.oid
JOIN pg_class child ON pg_inherits.inhrelid = child.oid
JOIN pg_namespace nmsp_parent ON nmsp_parent.oid = parent.relnamespace
JOIN pg_namespace nmsp_child ON nmsp_child.oid = child.relnamespace
WHERE parent.relname='partition_test' ;
Output:
db view

Step 5 – Verification (optional)

Let’s test using the show_partitions view, if we have any partitions yet
select * from show_partitions;
Output:
view partition

insert in partition_test

insert into partition_test values (1, '2018-01-19');
Output:
db_part_6

Few more inserts for the same month

insert into partition_test values (2, '2018-01-22');
insert into partition_test values (3, '2018-01-29');

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Install Python 3.6 on Ubuntu 14.04 and 16.04 LTS

A regular Ubuntu release comes up with 9 months of support, except the LTS (Long Term Support) versions.  Ubuntu 14.04 and 16.04 being the LTS are still widely in use at production level. Being a Python developer the first thing I need to on having a fresh Ubuntu 14.04, or 16.04 machine is update Python. Ubuntu 14.04 has Python 3.4 and 16.04 comes with Python 3.5. This blog post is about installing Python 3.6 on your Ubuntu 14.04, or 16.04 LTS.

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