DEV Community: kubona Martin Yafesi

The Complete Guide to Setting Up Postgresql on Windows 11 and WSL2

kubona Martin Yafesi — Sat, 26 Apr 2025 17:01:42 +0000

TL;DR
Start on your data engineering journey by installing WSL2 with Ubuntu on Windows 11 and setting up Postgresql in the Linux environment. The Postgresql set-up will accept both internal and external connections. Just this setup is enough to get started with data engineering

Introduction

Modern data engineering stacks use PostgreSQL as the standard for relational databases. PostgreSQL offers direct installation on Windows, Linux, MacOS, BSD, and Solaris Operating systems. However most professional data engineers often prefer running it in Linux for better performance, and similarity with production environments, and less compatibility issues.

70% of computer users around the world are using the Windows Operating system. While this is the case, 80% of production servers (Computers that power the apps and websites you use every day) are running on Linux. Naturally as humans love visually appealing systems which is why our number one choice for Operating system will be windows. Linux on the other end is mostly used through the Command Line Interface (CLI) which might not be visually appealing. With the CLI, you run a series of commands to get stuff done on your computer. However recent developments in the Linux Operating System have seen the introduction of the Graphical User Interface (GUI) to enable users not bother with the command line and instead adopt the approach to tap and click icons just like in Windows. But since 80% of the production servers is powered by Linux, and without GUIs, we are somehow left with no choice but to figure out a way of learning commands behind the GUIs. The challenge presents itself to developers, data engineers, analysts as to whether they need to get another computer that can run separately with Linux. Or even consider Dual Booting (While computer boots, you chose the OS you want to use ). The quick win without breaking the bank is using the Windows Subsystem for Linux (WSL2).

WLS2 gives us the best of both worlds: Windows' user-friendly interface with Linux's robust developer environment. By the end of this guide, you'll have:

A fully functional PostgreSQL server running in WSL2
External connectivity configured for Windows tools
A production-like environment for local development and testing

Let's turn your Windows 11 machine into a professional-grade PostgreSQL development environment!

Prerequisites ( What we actually Need to get up and running )

Before starting, ensure you have:

Windows 11 Home or Pro edition (Home is sufficient)
Virtualization enabled in your BIOS/UEFI settings
Administrative access to your Windows machine
Internet connection for downloading packages
15-20 minutes of your time

The Definite Step by Step Guide

Step 1: Enable WSL2 & Install Ubuntu-22.04

To install WSL2, simply open Powershell on your Windows 11 device as Administrator and run the following command to install a specific Linux distribution like Ubuntu-22.04

wsl --install -d Ubuntu-22.04

If you want to install any other Linux distributions available in WSL2, you can consider checking them out by running this command in Powershell

wsl --list --online

or wsl -l -o

A full detailed guide on setting up WSL2 and Ubuntu-22.04 is available at Install WSL | Microsoft Learn

Step 2: Download PostgreSQL Installer for Windows

Download website

Navigate to https://www.postgresql.org/download/windows/ and install Postgresql for windows

Click on "Download the installer" (it redirects to EnterpriseDB).
Choose the latest stable version (e.g., PostgreSQL 16 or 15) for your Windows.
Download the installer .exe file.

Install PostgreSQL on Windows

Run the installer:

Click Next → Choose an installation directory (default is OK).

Select Components (keep defaults: PostgreSQL Server, pgAdmin, StackBuilder, Command Line Tools).

Set a Password for the PostgreSQL superuser (postgres). (Important! Remember this password.)

Set Port Number: default is 5432.

Set Locale: default is OK.

Install.

✅ After installation, it starts Postgresql as a Windows service automatically.

You can ignore the StackBuilder Wizard

pgAdmin Setup

After installation, you also get pgAdmin installed.

Open pgAdmin → set a Master Password → login to your server using:

Username: postgres

Password: (the one you set during install)

Well done, you have successfully installed Postgresql on your Windows 11 Computer

Step 3: Install PostgreSQL on WSL Ubuntu

Now that Postgress is installed and running on Windows we can also set it up for our wsl environment. This assumes that you have completed step number 1: Enabling WSL2 and installation of Ubuntu-22.04,

Now let's install PostgreSQL:

Update your package lists:

sudo apt update && sudo apt upgrade -y

Install PostgreSQL and its extensions:

sudo apt install postgresql postgresql-contrib -y

Verify installation:

psql --version

You should see output like psql (PostgreSQL) 16.8 (version may vary).

Start PostgreSQL service:

sudo service postgresql start

Check status:

sudo service postgresql status

Create a PostgreSQL User Matching Your WSL Username

Get your WSL username:

Whoami

sudo -u postgres createuser --interactive

# Enter username: kubona

# Shall the new role be a superuser? (y/n): y

Set a password (optional):

Setup .bashrc to Default to postgres DB with Your User

Open up the .bashrc using the nano editor

nano ~/.bashrc

Add the following at the bottom:

export PGUSER=kubona

export PGDATABASE=postgres

Apply changes by exiting the nano editor( Ctrl +X , Y, Enter ) then run

source ~/.bashrc

Now you can run the psql command on the terminal to access the postgres CLI interface

psql

Edit postgresql.conf to Allow External Connections (for pgAdmin)

Edit the config file:

sudo nano /etc/postgresql/16/main/postgresql.conf

Find and set the line starting with # listen_addresses = ‘localhost’ and then change it to ( Remove the # at the beginning;

listen_addresses = '*'

Update pg_hba.conf to Allow External Authentication

Edit pg_hba.conf:

sudo nano /etc/postgresql/16/main/pg_hba.conf

Add this line at the bottom:

host  all  all  0.0.0.0/0  md5

Restart PostgreSQL to Apply Changes

sudo service postgresql restart

Find WSL IP Address to Use in pgAdmin

Get WSL's IP address (from Windows PowerShell or CMD):

wsl hostname -I

This might return something like 172.27.94.100. Use this as the host in pgAdmin.

Step 4: Add Connection in pgAdmin on Windows

Open pgAdmin

Go to Add New Server
In the General tab:
Name: WSL PostgreSQL
In the Connection tab:
Host: (e.g., 172.27.94.100)
Port: 5432
Maintenance DB: postgres
Username: kubona
Password: yourpassword
✅ Save Password

Click Save — it should connect

Step 5: Connect from WSL and Prepare for Windows Tools

Let's verify everything works within WSL first:

Connect to PostgreSQL as the postgres user:

sudo -u postgres psql

Create a test database:

sql

CREATE DATABASE testdb;

\c testdb

CREATE TABLE test (id serial PRIMARY KEY, name varchar(50));

INSERT INTO test (name) VALUES ('Test connection successful!');

SELECT * FROM test;

\q

You should see your test data displayed.

Conclusion

A pat on the back for making it till this far, Kudos!!

You've successfully set up a professional PostgreSQL environment on Windows 11 using WSL2. This hybrid approach gives you the development environment used by data engineers while keeping the Windows features you enjoy.

Next in Our Data Engineering Foundations Series

Now that you have PostgreSQL running on WSL2, our next article will show you how to:

Configure DBeaver as your PostgreSQL GUI client
Set up database users and permissions
Create your first data engineering project schema

Timing will never be perfect for you to start, today is here just get started!

Do you have any questions, challenges or recommendations, feel free to engage in the comments section below.

Docker 101!

kubona Martin Yafesi — Tue, 17 Aug 2021 13:17:44 +0000

Welcome dear reader to yet another learning opportunity. I applaud you for the commitment devoted to become a better version of yourself. Always here to remind you,

Every master was once a beginner
Whatever tech stack you choose to follow, do not underestimate the small beginnings! Stick to it!

Since we started this learning journey together, we have looked at a few principles and mastered some techniques, absolutely beginner level. Some of these have been;

Python Basics, Pythons 101!
Introduction to Python Functions
Feel free to check them out.

Diving right in …

We are getting started with our topic for the day. Hope you are refreshed and have a clear mind. This article assumes no prior experience with Docker or any of the terms used, sit back, read along and enjoy.

To explain what Docker is, we will first dig a few decades back before the docker world. Problem scenarios will be used to understand how docker came about, why it is important in your software development work flow, and basic usage examples.

The Problems before docker.

Scenario 1

You have just landed your first tech developer job, before anytime elapses, your very first assignment rolls in from the Chief Technical Officer.

The assignment...

You are required to develop an application for a very needy segment of the population, the blind!!.

How you start, lets see!!

From your expertise, basing on the app requirements, you decide on a set of tools that will enable you complete the task before hand.
Your application say will require these dependencies to run;

An operating system
Python
A database like Postgres
Flask

Installing app dependencies manually

Task before hand is installing all these tools to your local system. Phew!!! That looks tiresome already. Remember while installing them manually, you are only getting versions specific to your machine/laptop.

Coding, collaborations, testing

So until now, you are very comfortable coding the real-world application that solves a pressing need in your community.
Your boss has given you a deadline to complete the first module of the application. Yikes!!! Deadline day is here and the module is complete. You send the code over to the operations team, to test the application.

A few days later ...

Operations Team manager:

Hey, The code you sent me cannot run on my system, no app!!

A big problem arises
Can you see it?

Why did that happen? Well simply put, you used dependencies specific to your personal system, not universal. Another developer to test out your application will also need to manually install these dependencies on his personal system, and the chain continues that way. Along the way, there are more chances of your app breaking,....Oh no!!!

Scenario 2

You have built out your first application, but would like to test it out using a different operating system. How do you go about that?
After making some consultations from your workmates, news has it that its very possible through Virtual Machines.
Hurray, you feel great utilizing the concept of Virtualization!!
Virtualization has greatly aided developers in their ability to construct and produce from their computers as if they were separate platforms. They can use virtual computers to construct completely virtual operating systems in which to operate and build.

A developer can run a virtual Windows computer on their Macbook to evaluate the operation of a Windows-constructed application. Running a virtual machine is more cheaper and easier than buying a brand new one. I guess it's a really great option saving you a couple of thousand dollars.

Look at the difference between Docker and Virtual Machines from the illustration below.

Problems arising ...

As you enjoy trying out different virtual machines on your local device, you start noticing a few hiccups arising. These could be and not limited to;

Exhaustion of computing resources like ram, storage
Network congestion
Marginal app performance inside the Virtual machine

With the virtual machines installed, they share the same hardware resources with your normal operating system. So the issue of scalability arises since your virtual machine keeps expanding but not your hardware performance.

Do you notice that problem now?

Leaving problems alone...

There are quite a number of scenarios to list out in regards to traditional Software development practices. But I just highlighted on a few to whet our appetite and understand how Docker comes in the picture. Having understood those challenges, am sure your mind is sparked to solution mode already.

Let us refocus

Who comes to our rescue? Docker !!!

What is Docker?

Docker is a computer program that accelerates the way you build, share and run modern applications. Essentially it solves all the problem scenarios we have discussed above.
Docker takes away tedious, monotonous configuration procedures and is utilized across the development lifecycle for quick, simple and portable application development both on desktop and cloud.
In other words, while you use docker development becomes more efficient and predictable.

Docker is a tool for building, running, and deploying containerized applications. An application's code, libraries, tools, dependencies, and other files are all contained in a Docker image. When a user executes an image, it might turn into one or more containers.

How Specifically?

Okay to answer this question, I will split the concept into 3 ways;

Build
Share
Run

Build

Everything in Docker is based on images and containers.
A Docker image is a file that a Docker container uses to run programs. Docker images, like a template, serve as a collection of instructions for constructing a Docker container. When utilizing Docker, Docker images also serve as a starting point. In virtual machine (VM) settings, an image is similar to a snapshot.

Docker images include several layers, each of which is derived from the one before it but differs from it. The layers reduce disk use while boosting reusability and speeding up Docker builds. Image layers are read-only files as well. A written layer is put on top of the unchangeable images once a container is formed, enabling a user to make modifications.

Official images are those created by Docker, and community images are those created by Docker users. Docker applications are monitored by the CoScale agent, which is an official Docker image.
With confidence, leverage Images from the Docker Hub image repository that are Docker verified and official. As a basis for your application development, use these reliable and secure images.

Code, config files, environment variables, libraries, and runtimes are all included in a Docker image for running a containerized application. The image may be run as a Docker container once it has been deployed to a Docker environment. Docker run builds a container based on a specified image.

In simple terms, you build your image that contains all the libraries, and dependencies for your app and upon running that image you generate a container which is an instance of your application. You can make multiple versions of your application.

For example;
You can build an image for your flask project based on ;

Python
Flask
MySQL

When you run that image you create an instance of your application which you can share to anyone and will run without any issues.

Do you see how much Docker saves you!!

Once you have built your image you are able to share it to the world and anyone can use it (if you choose to).
You may deploy containers and test and share images from private or public repositories, such as those in the Docker Hub cloud registry service. Image management and access control are also available through Docker Hub's Docker Trusted Registry.

Users may use the docker push command to publish custom images to the Docker Hub and generate new images from existing ones. Docker offers comments to authors prior to publication to ensure the quality of community images. The author is responsible for updating the image once it has been published.

With Docker it is easy to collaborate with team members and other developers to come up with new ideas, and simply upload images to Docker Hub. It is even possible to have roles-based access control and Docker Hub Audit Logs. That makes it easier customize developer access to images and gain insight into activity history.

Run

Remember we said that when you run the docker run command, you are making an instance of your application. You can make as many instances as you like, for example:

Instance for development
Instance for testing
Instance for staging
Instance for production (One being used by application users)

So the concept is to deliver numerous apps with ease, and have them operate the same way in all of your settings - desktop or cloud-native - including design, testing, staging, and production.

How do we do that?

It is really simple, Deploy your applications in separate containers independently and in different languages. Reduce the risk of conflict between languages, libraries or frameworks.

Using the ease of Docker Compose CLI, you can deploy your apps locally and in the cloud with AWS ECS, Azure ACI, and Google GKS with just one command.

Yes!!! That is it about Docker. Hope you have learnt some concepts about what Docker is?

Getting Started Guide.

Docker is a really great tool to include in your software development workflow.

To have a more whetting experience about docker, please refer to the guide.

Getting-Started-With-Docker

Without installing Docker on your system, you can leverage the online play ground and practice how to use Docker Images and containers.

Play-with-Docker

Congratulations upon finishing the article. I trust that you have learnt something.

How was the article?

I love learning with the friends I share content with. Are there any insights you have about the article? Any additional features/concepts that would have been of real value to the article? Whatever it is, please share in the discussion section.

For now... I tap out. Enjoy yourself and see you next time.

Dealing with Environment Variables in Flask

kubona Martin Yafesi — Tue, 10 Aug 2021 16:00:05 +0000

Welcome to yet another article. Thanks for being a dedicated reader. More knowledge unto you, more skills learnt, and a better you. Before we begin on today's article, we will just have a brief recap of what we have learned over the course of time together.

What is Python?

Python is a widely-used, interpreted, object-oriented, and high-level programming language with dynamic semantics, used for general-purpose programming.
It was created by Guido van Rossum as a 'hobby' programming project.

Why do we love Python?

Because it is an easy and intuitive language;
Open source programming language. As a result, everyone may contribute to its growth;
Code that is as simple to comprehend as plain English;
Appropriate for day-to-day work, with quick development times

What is Python used for?

Python has its application domains in many areas and these are but not limited to;

Web Applications
Data Science
Mobile Applications
Big Data
Artificial Intelligence
Automation
Testing

To have a more detailed Introduction to Python, please feel free to check out this resource. Python Basics, Pythons 101!

Once that article has been read, we have a look at some concepts in Python worth remembering. These may not be explained exhaustively for beginners but gives a refresher to intermediate and expert python programmers. Even beginners can relate, good news!!

Data Types

Literals are data whose values are decided by the literal itself, which Python provides out of the box.

Common literals in Python include;

Numeric literals
Strings literals
Special literal None
Boolean literals
Collection literals

In simple terms, literals are the raw data that are assigned to variables or constants while programming.

Arithmetic operations in Python

Python supports out of the box support for arithmetic operations. With it you can perform these operations using expressions and operators.

Variables

A variable is a named location reserved to store values in the memory.

Whenever you want to store results from operations, use a container called a variable to store them. When naming variables, make sure you follow the PEP Standards defined here, PEP 8 --Style Guide for Python Code

Comments

Comments can be used to add more information to your code. At runtime, they are removed. Human readers are addressed by the information left in source code. A comment in Python is a line of text that starts with # for single line and """ for multi-line comments

Functions

A function is a group of related statements that perform a given task. So whenever you call a function, those statements will perform that task, however many times you call the function.

Functions help us as programmers to;

Avoid code repetitions
Have cleaner and readable code
Decompose large problems into small chunks.

There are 3 major types of functions these are;

In-built functions
User defined functions
Pre-Installed module functions

For a more detailed guide on functions, please check out this resource. Introduction to Python Functions

Great, welcome back from that recap about Python. Remember, the more you familiarize yourself with what Python is and how you use it, the better programmer you become at Python.

Every expert was once a beginner.

Web development In Python

So one of the application domains of Python is Web development. You can use it to make powerful and fast web applications. In so making, a number of tools and frameworks have been developed to aid web development in Python.

Some of these are but not limited to;

Django
Flask
Pyramid

(The picture below shows a list of web frameworks using Python)

Our focus will be on the Flask framework. For an Introduction to FLASK, please checkout their official documentation.
Official Flask Documentation

And for a quick overview on how to get started with Python Web development, consider looking into, Getting Started with Python Web Development using FLASK

Once you have mastered the basic overview of flask, we will dive into the topic of the day. Phew!!! What an introduction !!! Hope you are enjoying the article. Let us refocus now.

Given a minimal Flask application, such as;


from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello World, dear Friend!'


@app.route('/page/<int:page_num>')
def content(page_num):
    return f'<h1>Yoo.. It is your page {page_num}</h1>'

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

The minimal application can be run following the steps below, (as you might be familiar),

On Bash

export FLASK_APP=app.py
flask run

Other scenarios you might want to specify the host and port number, environment, debug mode etc. for which you want your flask application to run, you would have to include all that into the export command above.
That can become tedious over time as you develop your cool project, pressing up arrow key many times to retrace the export command (bash users, you know what I mean).

Our goal is to save some time and when running our flask application, we simply do;

On Bash

flask run

The variables that we add to the export command are known as environment variables. These variables are used by your flask application to serve your project.

Examples of environment variables include;

FLASK_ENV
FLASK_DEBUG.
FLASK_RUN_EXTRA_FILES
FLASK_RUN_HOST
FLASK_RUN_PORT
FLASK_RUN_CERT
FLASK_RUN_KEY

Those are default flask environment variables defined by the framework. If not specified, they use their default values.

User defined variables

Also, if you wanted to connect your application to a database, you would have to hard code your credentials into your python code, which is not recommended.
A simple example would be;

from flask import Flask
app = Flask(__name__)

app.config[MYSQL_USER]="your_username"
app.config[MYSQL_HOST]="localhost"
app.config[MYSQL_DB]="my_appdb"
app.config[MYSQL_PASSWORD]="your_password"

@app.route('/')
def index():
    return {'Message': 'Hello World'}

That kind of hard coding credentials is not ideal if you are working on a large project with other people

Incase you do not follow Strict password policies and use one password everywhere....You are hacked!!!. You just shared your password with the world.

So how do we deal with the flask environment variables?

We are going to see how to load flask environment variables automatically. You are here because you're tired of setting environment variables every time you are running your flask app? Variables like FLASK_APP or FLASK_ENV using export command. Am going to help you do just that.

Step 1: Install python-dotenv

In your virtual environment, run;

pip install python-dotenv

I emphasize, always use virtual environments on your system to prevent corrupting your main Python installation. In case you want a recap on how to create virtual environments, refer to this guide. Creation of Virtual Environments

Step 2: Create `.env` and `.flaskenv` files in your project root folder

On Bash

touch .env
touch .flaskenv

Step 3: Place your flask environment variables in .flaskenv

Depending on your use case, this will guide you on what to include.

In .flaskenv

//this is the .flaskenv file
FLASK_ENV - Controls the environment.
FLASK_DEBUG - Enables debug mode.
FLASK_RUN_EXTRA_FILES - A list of files that will be watched by the re-loader in addition to the Python modules.
FLASK_RUN_HOST - The host you want to bind your app to.
FLASK_RUN_PORT - The port you want to use.
FLASK_RUN_CERT - A certificate file for so your app can be run with HTTPS.
FLASK_RUN_KEY - The key file for your cert.

for example; FLASK_APP=app.py

Boom, great work done. To run your app now, Simply do run;

That was fast,.... right?? Yes so you can now focus on programming instead of looking for which flask environment variable is missing.

So how about my-secretly-defined environment variables?

Yes getting to that now. Follow this guide.

Step 1. Place `your-secretly-defined environment variables` in `.env`

These can include;

Login credentials to the database
API keys
SECRET_KEY (among others)

In .env

//This is the .env file
MYSQL_USER=root
MYSQL_PASSWORD=my_mysql_password
MYSQL_DB=userdb
MYSQL_HOST=localhost
SECRET_KEY=topsecretkey
API_KEY=donotsharethisapikeywithanyone

Step 2: Create a settings.py file

(Since these variables are not served automatically, we have to load them through this settings.py file)

In settings.py

//This is the settings.py file

from os import environ
SECRET_KEY=environ.get('SECRET_KEY)
API_KEY=environ.get('API_KEY')
MYSQL_USER=environ.get('MYSQL_USER')
//add any more variables you have

Note: For consistency, it is good to keep the same variable name as the environment variable.

Step 3: Add the configurations to our app

In your app.py , the file that has your flask object.

app.config.from_pyfile('settings.py')
# loading all environment variables from settings.py

So what happens is that the settings.py will read the values you placed in your .env file and store them in variables as you defined them in settings.py.

When you use the flask object's config method, together with the from_pyfile sub-method, the app will have access to the secretly defined variables in a secure way.

Run your app as before, and boom you can now serve the world with your cool project

Bonus Tip:

To avoid surbotaging your efforts to secure your credentials, when using a version control system such as git , do not push the .flaskenv and .env files. You can use .gitignore file to ignore them in your project directory. They remain on your local system.

How was the article?

I love to learn with you dear reader. Share your feedback with me in the discussion section below. Are there better ways to do this?
A great friend improves another, feel free to share
I appreciate all the feedback in advance.

Introduction to Python Functions

kubona Martin Yafesi — Thu, 05 Aug 2021 19:58:35 +0000

Welcome dear friend to yet another exciting talk about Python.
Last time we were here, we discussed about what Python is, what it is used for and also looked at its application domains. I hope you enjoyed that!! If you are new here, please check it out here.

What is the agenda for today?

Well today is going to be another fun ride. We will talk about functions. Topics of discussion will be:

What functions are?
How to define them.
When and how to use them.

We will have some examples for illustration purposes

Great!! I cannot already wait to jump right in...

Ohh I see, let us head to the fun part without wasting much time.

Functions:

A function is a group of related statements that perform a given task. So whenever you call a function, those statements will perform that task, however many times you call the function.

You said related statements! What do you mean by that?

Great question. Yes, now suppose you want your code to print your name and calculate your age very many times. So traditionally you would write your code like this and repeat it many times. Have a look:

Code Example 1


name = "Cool Python Guy"
year_of_birth = int(input("What is your year of birth"))
age = 2021 - year_of_birth

print(f"My name is {name} and I am {age} years old")

To avoid repeating yourself to just print your name and age. You would create a function with your code. So whenever you want your name and age printed, guess what.... call the function!!!
Is that not cool?

Yeah that is really cool stuff!!! Please tell me more, I love doing cool things

So coming to the actual cool stuff, lets rewrite our code in a function. Are you ready? See this:

Code Example 2


def name_age():
   name = "Cool Python Guy"
   year_of_birth = int(input("What is your year of birth"))
   age = 2021 - year_of_birth
   # Printing the name and age
   return f"My name is {name} and I am {age} years old"

So if you wanted to print your name and age many times, simply call your function like;

Code Example 3

name_age()
name_age()
name_age()
""" 
You can call it any number of times you like
Your name and age will be printed those many times

"""

I see how that can save my a lot of time...

Yeah you can save plenty of time, and boost your productivity. Also you have the advantage of not repeating yourself. You will soon notice that using functions makes your code readable by say your fellow programmer or Chief Technical Officer (CTO). (You most likely will work with other people on a project). A big problem can be divided into smaller chunks of functions each doing a separate task.

Functions are really powerful creatures. So i noticed the way you called the `name_age` function was similar to how we `print`. Is print also a function?

Very nice question friend! You are picking up really fast. We might land on Mars soon enough. Until now I have showed you what we call User-Defined functions.
There is another type called Built-in functions.

In this article, we look at:
-User-Defined functions
-Built-in functions

Another type found in modules will be covered later in another piece

1. User-Defined Functions

The Code Example 2 shown above is an example of a user defined function.
These are functions that exist within our code and are defined by the programmer. In actual sense, we can call them custom made functions.

Uhmm, I see we made that `name_age` function by ourselves. Tell me about the other type...was it built-in?

2. Built-In Functions

Having learnt about user-defined functions, Its time we also get ourselves accustomed to built-in functions.
So these functions, are an integral part of the python programming language. They exist within python itself and are always available to use by any python programmer like you.
Actually you do not require any effort to use them, just call them... see here:

Code Example 4

# the print function is a built-in function
print('Hello Friend')
print('Hope you are enjoying python')
print('Please stick around till the end')

*Feel free to check out other types of built-in Python functions Built-in Python Functions
*

Thanks a ton!! I will check them out after here.

That would really be great. So until now we have discussed about what functions are and their different types, But you might ask...
How do we define functions? Is it obvious? Let me not take chances here, remember, we are soon reaching mars ...

Defining Functions

The syntax for defining a function is as:

def function_name(parameters):
    """ A doc string defining the purpose 
        of the function
    """
    `statements` 
    # Comments describing what certain code is meant to achieve
    `statements`

    return `some value`

Key takeaways

def - This keyword indicates the start of a function definition
function_name - This is the name of the function
parameters - These are optional, but are used if you want the function to use certain data to carry out a given task
doc string - Optional, but used to describe purpose of function.
comments - Simple statements to illustrate purpose of certain lines of code.
statements - Remember from our definition of functions
return - Optional, but used if you want to output a value.

This has been a smooth journey to Mars. A recap of what I learned is:

I now know what a function is.
I know the different types of functions.
I know how to call and use the different types of functions.
I know how to create my own functions.
I have access to other types of built-in functions.

Wow!! Such powerful knowledge you have attained today. Indeed you can now help Elon Musk write some functions for his rockets like turbo_charge().

It is a pleasure spending time with you. And I look forward to your company. Feel free to continue the discussion in the section below. I love learning new stuff and would be my pleasure to hear from you.

How was the article? Did you learn something or your mind sparked at something. Please share! Until then, I say goodbye for now.

           See you Again, Pythonista !!!

Python Basics, Pythons 101!

kubona Martin Yafesi — Thu, 22 Jul 2021 13:31:25 +0000

What is Python?

Python is a programming language. In specific, it is a high level language, general purpose and interpreted.

So, tell me!! What is python used for?

Well simply put, Python is used in a wide variety of fields in the computing world.
These sectors of application are but not even limited to:

1. Web Applications
2. Data Science
3. Mobile Applications
4. Big Data
5. Artificial Intelligence
6. Automation 
7. Testing

Ohhh!!! I see that is a wide variety of fields. Quite intersting, huh? Now i know where my area of focus could be. You also said something about interpreted ... or what???

Yes friend,

Python is a high level interpreted language

Other languages like java have to wait for the compiler to compile the whole file of your code before it can execute.

Python is behaves differently. After writing your source code in a file, Python will use an interpreter to compile the source code line by line into machine code . Machine code is the language the computer understands.

Now I understand! So is it because of those features that one uses Python over other languages?

Great Question! I personally love python because it is very easy to learn. Compared to other languages i have tried out, like java , Nah! Python is way cooler with even nice syntax.

Secondly, I love the fact that its able to cut across many different domains. Imagine you mastered Python!!!, You can work on websites, make some cool intructions for a robot, analyse your companies data, make an app, automate your computer...see list is endless. That is real.

Third with Python you can be rest assured that problems are going to be solved in the shortest period of time.

What???

Yes, with Python hard to imagine complex problems can be solved with fewer lines of code. That can boost your prodcutivity as a programmer, you worry less.

For example

java

public static void main(String[] args){
  System.out.println("Hello Friend")
  /**Am sorry i do not know your name */
}

See all that complexity there!!! , Now see the magic with Python

python

print("Hello Friend")

Oh wow!!! Thats cool stuff. Anything more about Python? I am enjoying this already....am waiting!!

Nice to know that you are loving Python already. And yeah there is a big community of Python developers all around the world to support you at every stage of your journey. Right from tonight, assuming you start coding today, haha If you get stuck, they will always help you. Is that not great?

Summing up, be rest assured that the programs you write in Python will run on all operating systems..name it.

Windows, Linux or even MacOS

Should the world know that you can program in Python?

Yes, there is high demand for Python developers. You will be spoilt for choice because you are needed urgently.

So what now?

Glad you have a prospect to learn Python. Over the next few days, stay tuned on my blog, follow me so that you do not miss any step towards becoming a great python developer.

I will guide you through the whole process, right from installation , set up , and writing your first program in Python. We will even make real life projects.

What did you learn from the post today?

Feel free to share with me your thoughts and any questions, I'd be glad to answer them all. Plus also, I never stop learning, so am open to new ideas from you, we grow together. Hurray!!!

See you next time, Bye Friend!!!

DEV Community: kubona Martin Yafesi

The Complete Guide to Setting Up Postgresql on Windows 11 and WSL2

Introduction

Prerequisites ( What we actually Need to get up and running )

The Definite Step by Step Guide

Step 1: Enable WSL2 & Install Ubuntu-22.04

Step 2: Download PostgreSQL Installer for Windows

Download website

Run the installer:

pgAdmin Setup

Step 3: Install PostgreSQL on WSL Ubuntu

Update your package lists:

Install PostgreSQL and its extensions:

Verify installation:

Start PostgreSQL service:

Check status:

Create a PostgreSQL User Matching Your WSL Username

Setup .bashrc to Default to postgres DB with Your User

Edit postgresql.conf to Allow External Connections (for pgAdmin)

Update pg_hba.conf to Allow External Authentication

Restart PostgreSQL to Apply Changes

Find WSL IP Address to Use in pgAdmin

Step 4: Add Connection in pgAdmin on Windows

Open pgAdmin

Step 5: Connect from WSL and Prepare for Windows Tools

Connect to PostgreSQL as the postgres user:

Create a test database:

Conclusion

Next in Our Data Engineering Foundations Series

Docker 101!

Diving right in …

The Problems before docker.

Scenario 1

The assignment...

How you start, lets see!!

Scenario 2

Leaving problems alone...

What is Docker?

How Specifically?

Build

Share

Run

How do we do that?

Getting Started Guide.

How was the article?

Dealing with Environment Variables in Flask

What is Python?

Why do we love Python?

What is Python used for?

Data Types

Arithmetic operations in Python

Variables

Comments

Functions

Web development In Python

Examples of environment variables include;

User defined variables

So how do we deal with the flask environment variables?

Step 1: Install python-dotenv

Step 2: Create .env and .flaskenv files in your project root folder

Step 3: Place your flask environment variables in .flaskenv

So how about my-secretly-defined environment variables?

Step 1. Place your-secretly-defined environment variables in .env

Step 2: Create a settings.py file

Step 3: Add the configurations to our app

Bonus Tip:

How was the article?

Introduction to Python Functions

What is the agenda for today?

Great!! I cannot already wait to jump right in...

Functions:

You said related statements! What do you mean by that?

Code Example 1

Yeah that is really cool stuff!!! Please tell me more, I love doing cool things

Code Example 2

Code Example 3

I see how that can save my a lot of time...

Functions are really powerful creatures. So i noticed the way you called the name_age function was similar to how we print. Is print also a function?

1. User-Defined Functions

Uhmm, I see we made that name_age function by ourselves. Tell me about the other type...was it built-in?

Step 2: Create `.env` and `.flaskenv` files in your project root folder

Step 1. Place `your-secretly-defined environment variables` in `.env`

Functions are really powerful creatures. So i noticed the way you called the `name_age` function was similar to how we `print`. Is print also a function?

Uhmm, I see we made that `name_age` function by ourselves. Tell me about the other type...was it built-in?