DEV Community: Owino

Python for everyone : Mastering Python The Right Way

Owino — Mon, 07 Mar 2022 17:00:54 +0000

Python is a high-level programming language that is easy for everyone to learn due to its simple syntax.
Beginners will take a shorter period of time to be up and running!

It is widely used in web and APIs development, cryptography, games development, scripting (automation) tasks, artificial intelligence, data science, web scrapping (crawling) and many other areas.

In this blog post, I will explore the areas you need to cover all the way from beginner, intermediate and into advanced level. Thereafter, I will also highlight various specialization areas that you may need to look at depending on your area of interest.
I will also highlight some of the popular free Python learning resources.

The best practice on how to master Python programming just like any other programming language is to ensure you execute one or more project after each level before proceeding onto next levels. Think of any idea that you can implement using the concepts you have covered after during the completed level and make it you project.

1. Beginner Level

At this level ensure you cover and understand the following:

Application areas of Python
Downloading and Installing Python
User interfaces or IDEs like the ones listed below. Pick and use one of your desired IDEs while working with Python:
Program structure
Interactive shell
Executables or script files
Variables
Data types
Conditions
Chained conditions
Control flow
Loops and Iteration
Data structures ( Lists, Tuples, Sets and Dictionaries)
Functions
Common Methods
File input/output

This gives you a good base but before you proceed onto the next level, you have a milestone checkpoint (a project!).

Beginner Level Project : Think of a project or task you can accomplish using the concepts you have covered so far.

2. Intermediate Level

Here you need to explore the following key aspects of Python programming language:

Object Oriented Programming (classes and object, Encapsulation, Inheritance and Polymorphism)
Lambda functions
*args AND **kwargs in function definitions
pip (package installer for Python)
Virtual programming environments
Modules

Intermediate Level Project : Think of a project or task you can accomplish using the concepts you have covered so far including the beginner level concepts.

3. Advanced Level

Concepts you need to cover and understand:

Decorators
Generators
Testing (unittest, nose(or nose2) and pytest)
PEP 8 - Styling Guide for Python code
Packaging your python application
Cython

Advanced Level Project : Think of a project or task you can accomplish using the concepts you have covered so far all the way from beginner to the advanced.

4. Specialization Areas

After going through basic, intermediate and into advanced levels, you may decide to choose one or more of the areas to go deeper into the key application areas of Python programming language.

4.1 Web and APIs development

In web development explore the following Python web frameworks:

4.2 Cryptography

We have several libraries in Python that provides cryptographic recipes and primitives to python developers:

4.3 Games development

For games development enthusiasts, Python provides the following libraries / frameworks:

4.4 Scripting (automation) tasks

In case in systems administration, you will need to create Python code in files, make the files executable.
This helps to automate routine tasks.

4.5 Artificial Intelligence(AI)

Let's look at the libraries / frameworks that Python offers for AI areas: Machine Learning (ML), Compute Vision, Natural Language Processing (NLP), Neural Networks, Robotics, Fuzzy logic and Expert systems.

4.5.1 Machine Learning

4.5.2 Computer Vision

4.5.3 Natural Language Processing

4.5.4 Neural Networks

4.5.5 Robotics

4.5.6 Fuzzy Logic

4.5.6 Expert Systems

4.6 Data science

4.7 Web scrapping (crawling)
As web is text-based platform, Python has libraries for working with JSON, HTML, XML and other formats.

4.8 GUI Based desktop applications

In order to develop desktop GUI applications, Python provides the following capabilities:

5 Learning Resources

While learning, choose a particular resource and stick to it. Avoid hopping from one learning resource to the the other. Below I am sharing some of the common Python learning resources.

5.1 Websites

5.2 Youtube Channels

5.3 Books

Beginners

Intermediate

5.4 Coding Practice

For code challenges and practices you can check out the following websites:

6. Python Project Ideas

You can check out below list of project ideas that you can try to using Python programming language.

Quiz app
Calculator
Web automation
Classic snake game
Web crawler
Music Player
Instagram Bot
Twitter Bot
Reddit Bot
Alarm Clock
Image downloader
Face recognition
URL shortener
File explorer
Notification system
File rename tool
Password generator

7. Free platforms to host your test applications

Incase you need to host your trial applications, check the below free platforms:

Conclusion

Key takeaways:

Practice, practice and practice! code everyday.
Choose a study resource that suits you and stick to it.
Do projects before moving to the next level.
Document your learning journey in a blog since you learn more when you share.
Use code version control like Git/Github, bitbucket etc for all your code that you write.
Never stop learning.

Feel free to leave comments. Thank you!

Oh, I almost forgot, please checkout an instagram-video-and-photos-downloader I created. It is one of my projects.

Introduction to Data Structures and Algorithms With Python

Owino — Mon, 21 Feb 2022 20:54:00 +0000

Following my previous post on Python concepts Python 101: Ultimate Python Guide, I am excited to dive into the following aspects of python.

A Data structure is a method of organizing data in a system. Think of sequences of number, or tables of data: these are both well-defined data structures.
Python data structures are: Lists, Dictionaries, Tuples and Sets.

An Algorithm is a sequence of steps executed by a computer that takes some input and transforms into a target output.
Examples of algorithms that we will discuss in Python are: Queues, Stacks and Linked Lists.

Data structures:
I had covered some of these data structured but for those who haven't visited my previous post Python 101: Ultimate Python Guide, let's look at them.
1 - Lists
Lists in python is in other terms what other programming languages call arrays. Lists are mutable i.e. their elements can be changed, removed, new ones added etc.
Lists are used if you have collection of data that does not need random access.
The elements in a list are enclosed in square "[]" brackets. see below examples:
Here we declare a list named myFriends and use it.

myFriends = ["Mike", "John", "Peter", "Lenny", "Peter"]
print(myFriends)

When we run our python program it will print out the below:

['Mike', 'John', 'Peter', 'Lenny', 'Peter']

To count all my friends called 'Peter':

print(myFriends.count("Peter"))

Output:

Let's insert a friend to the list at index 1 of the list and print the list again:

print(myFriends.insert(1,"Arnold"))
print(myFriends

output:

['Mike', 'Arnold', 'John', 'Peter', 'Lenny', 'Peter']

Let's remove Friend 'Lenny' from the list and print the list once more:

print(myFriends.remove("Lenny"))
print(myFriends)

Output:

['Mike', 'Arnold', 'John', 'Peter', 'Peter']

Feel free to try out other list functions available in Python such as: clear(), copy(), extend(), index(), pop(), reverse() and sort().

2 - Dictionaries
Dictionaries are used to store data in key:value format.
Dictionaries are mutable.
You will need to use dictionaries if:
i - You need logical association between a key-value pair data.
ii - You need first lookup of your data based on a key.
iii - Your data is constantly being modified.
See below code:

student = {
    "firstName" : "Mark",
    "Age" : 23,
    "Hobby" : "Soccer"
}
print(student)

The output will be:

{'firstName': 'Mark', 'Age': 23, 'Hobby': 'Soccer'}

To print out the value of key Hobby in the student dictionary:

print(student["Hobby"])
#also the below code will do the same
print(student.get("Hobby"))

Output:

Soccer

3 - Tuples
Tuples are similar to list but their contents cannot be changed; they are immutable.
Therefore tuples are used for cases where the data does not need to be changed e.g. geographical coordinates etc.
The elements in a tuple are enclosed in round brackets "()".
See below example with our tuple named daysOfTheWeek.

daysOfTheWeek = ("Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday")
print(daysOfTheWeek)

The output when we run above:

('Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday')

To print the third element of the tuple:

print(daysOfTheWeek[3])

Output:

Wednesday

If we try to change any element of the tuple e.g. assigning a new value to element at index 1:

daysOfTheWeek[1] = "Friday"

Python will throw the following TypeError since elements in a tuple cannot be changed (tuples are immutable):

TypeError: 'tuple' object does not support item assignment

4 - Sets
Sets are unordered collections of unique objects.
Items in the set are unordered so they cannot be indexed, it either an item is in the set or not.
Sets elements are defined in curl braces "{}".
Sets are used if you need uniqueness of the elements.
Let's declare a set and print:

basket ={'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
print(basket)

The printout will remove duplicates and only unique items will be displayed i.e.

{'pear', 'apple', 'banana', 'orange'}

We can add an item to a set and print the current set:

basket.add('Pineapple')
print(basket)

Here you can see we now have an additional element to the set being shown:

{'Pineapple', 'pear', 'apple', 'orange', 'banana'}

There are other set functions like clear(), pop(), copy(), difference(), discard(), intersection(), issubset(), issuperset() etc please try them out.

Algorithms:
1 - Queues
A queue is a linear data structure that stores its elements in FIFO (First-In/First-out) manner.
Just like a queue of customers to be served in a supermarket, the ones who came first will be served first.
Python list is used as a way of implementing queues. The list’s append() and pop() methods can insert and delete elements from the queue.
Lets initialize an empty queue, add three element and prints it out:

myQueue = []

myQueue.append('Duncan')
myQueue.append('Owino')
myQueue.append('Mwamba')

print(myQueue)

We can now see our queue has elements:

['Duncan', 'Owino', 'Mwamba']

Lets dequeue (remove) elements from the queue:

myQueue.pop(0)
myQueue.pop(0)
myQueue.pop(0)

print(myQueue)

Now we have our queue as empty:

[]

2 - Stack
A stack is a linear data structure that stores items in LIFO (Last-In/First-Out) or FILO (First-In/Last-Out).
In a stack, a new element is added at one end and the element is removed from that end only.
The insert operation is called append() while the delete operation is called pop().

Lets declare an empty stack and append three elements into it and print the stack:

myStack = []

myStack.append('Duncan')
myStack.append('Owino')
myStack.append('Mwamba')
print(myStack)

The output will be:

['Duncan', 'Owino', 'Mwamba']

Now lets pop an element from the stack and print the stack:

myStack.pop()
print(myStack)

The elements of the stack now are:

['Duncan', 'Owino']

As you can see we have deleted element ['Mwamba'] from the stack.

Other operation/functions with stacks are: empty(), size(), top() etc. Please try them out.
3 - Linked List
A Linked list is an ordered collection of objects called nodes.
Each element of a linked list is called a node.
Every node has two different fields:

Data : This contains the value to be stored in the node.
Next : This contains a reference to the next node on the list.

Here’s what a typical node looks like:

The first node is called the head, and it’s used as the starting point for any iteration through the list. The last node must have its next reference pointing to None to determine the end of the list.
Therefore here is how a linked list looks:

There are many other algorithms that can be explored i.e. Hashtable, tree, graphs, sorting and searching, greedy algorithm ...

Please share your comments and feedback. Thank you!

Python 101: Ultimate Python Guide

Owino — Mon, 14 Feb 2022 08:28:18 +0000

Working in Cloud Orchestration, automation skills are vital; python lends a hand to this. Python is easy to learn!

What is Python?
Python is a high-level programming language. It can be used in scripting/automation, Artificial Intelligence(AI), Machine language (ML), Data Science, APIs and web development.

My Programming environment and setup
As I share this, below find my setup and programming environment:

Windows 10 64-bit. Python code can also be executed on other OS platforms e.g. Linux, macOS.
Python 3.8 (https://www.python.org/downloads/release/python-380/)
IDE & Code Editor: I use Visual Studio Code (https://code.visualstudio.com/). You can also opt to use other code editors of your choice like PyCharm, Idle, Sublime Text3, Spyder, Jupyter, Eclipse etc.

Follow me along as I take you through an exciting journey needed to keep you up and running in Python. Feel free to type the code as we get along. I will try to will make it as simple as possible!

Overview of Python
Variables and Datatypes, Comments in Python, How to get input from users, Operators, Data structures (lists, tuples and dictionaries), functions and control flow.

1. Variables and Datatypes
Python supports the following data types:

Strings
Numbers
Boolean

The below example shows how to use these three variables in Python. My file is saved as variables_and_datatypes.py in Visual studio code.

#Lets declare three variables names firstName, age and isMale all of different data type.
firstName = 'Mel' 
age = 10
isFemale = True

print(firstName) #This will print out Mel
print(age)       #This Will print out 10
print(isFemale)  #This will print out True

2. Comments in Python
It is very important to comment your line(s) of code as it helps others understand your code.
Moreover this helps you incase you come back to that section to see what you did days, months or even years later since it is easy to forget what your did days back.
You can use single line comment using # or multi-line comments by having text between a block of ''' ''' . See below example:


'''
This is my first program.
Python is a high-level programming language.
Here am using multi-line comment style.
'''

#This prints out strings to the user. Here I have used single line comment.
print('Python programming is fun!')

3. Getting input from users
Incase you need your program to get inputs from users, you need to use python input function. See below example on how this function is used.

'''
Here we are using input function to get name of the user and 
store in a variable named firstName'''
firstName = input("Enter your name: ")

'''
In this case are converting string input to an integer.
By default all inputs in Python are treated as strings so we have to convert them to our desired data type; in this case an integer.
'''

age = int(input("Enter your age: "))

#Here we concatenate(link together) the strings using f-string during printing to make a meaningful sentence.
print(f"Your name is: {firstName} and your {age}")

Below is what I will get if I run my python file named input.py:

Enter your name: Mel
Enter your age: 10
Your name is: Mel and your 10

4. Python Operators: Let's build a basic calculator
To perform mathematical operations in python, we use the following operators: + (for addition), - (for subtraction), * (for multiplication), ** (for exponentials) / (for division), % (for modulus), / (for division) and // (for quotient.
See below code snipped for the example of our simple calculator:

firstNumber = float(input("Enter the FIRST number: "))
secondNumber = float(input("Enter the SECOND number: "))

sum = firstNumber + secondNumber
print(f"The sum of {firstNumber} and {secondNumber} is {sum}")

multiplication = firstNumber * secondNumber
print(f"The product of {firstNumber} and {secondNumber} is {multiplication}")

exponential = firstNumber ** secondNumber
print(f"{firstNumber} raised to the power of {secondNumber} is {exponential}")

division = firstNumber / secondNumber
print(f"The Division of {firstNumber} by {secondNumber} is {division}")

subtraction = firstNumber - secondNumber
print(f"The Subtraction of {secondNumber} from {firstNumber} is {subtraction}")

modulus = firstNumber % secondNumber
print(f"The Modulus of {secondNumber} and {firstNumber} is {modulus}")

quotient = firstNumber // secondNumber
print(f"The quotient of {firstNumber} and {secondNumber} is {quotient}")

See the below output when we run our Python file named calculator.py:

Enter the FIRST number: 4
Enter the SECOND number: 2
The sum of 4.0 and 2.0 is 6.0
The product of 4.0 and 2.0 is 8.0
4.0 raised to the power of 2.0 is 16.0
The Division of 4.0 by 2.0 is 2.0
The Subtraction of 2.0 from 4.0 is 2.0
The Modulus of 2.0 and 4.0 is 0.0
The quotient of 4.0 and 2.0 is 2.0

5. Data structures in Python
You also need to understand the key data structures in Python. These are Lists, Tuples and Dictionaries. Let's go through each one:

5.1 Lists

Lists in python is in other terms what other programming languages call arrays. Lists are mutable i.e. their elements can be changed, removed, new ones added etc. The elements in a list are enclosed in square "[]" brackets. see below examples:
Here we declare a list named myFriends and use it.

myFriends = ["Mike", "John", "Peter", "Lenny", "Peter"]
print(myFriends)

When we run our python program it will print out the below:

['Mike', 'John', 'Peter', 'Lenny', 'Peter']

To count all my friends called 'Peter':

print(myFriends.count("Peter"))

Output:

Let's insert a friend to the list at index 1 of the list and print the list again:

print(myFriends.insert(1,"Arnold"))
print(myFriends

output:

['Mike', 'Arnold', 'John', 'Peter', 'Lenny', 'Peter']

Let's remove Friend 'Lenny' from the list and print the list once more:

print(myFriends.remove("Lenny"))
print(myFriends)

Output:

['Mike', 'Arnold', 'John', 'Peter', 'Peter']

Feel free to try out other list functions available in Python such as: clear(), copy(), extend(), index(), pop(), reverse() and sort().

5.2 Tuples
Tuples are similar to list but their contents cannot be changed; they are immutable.
The elements in a tuple are enclosed in round brackets "()".
See below example with our tuple named daysOfTheWeek.

daysOfTheWeek = ("Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday")
print(daysOfTheWeek)

The output when we run above:

('Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday')

To print the third element of the tuple:

print(daysOfTheWeek[3])

Output:

Wednesday

If we try to change any element of the tuple e.g. assigning a new value to element at index 1:

daysOfTheWeek[1] = "Friday"

Python will throw the following TypeError since elements in a tuple cannot be changed (tuples are immutable):

TypeError: 'tuple' object does not support item assignment

5.3 Dictionaries
Dictionaries are used to store data in key:value format.
See below code:

student = {
    "firstName" : "Mark",
    "Age" : 23,
    "Hobby" : "Soccer"
}
print(student)

The output will be:

{'firstName': 'Mark', 'Age': 23, 'Hobby': 'Soccer'}

To print out the value of key Hobby in the student dictionary:

print(student["Hobby"])
#also the below code will do the same
print(student.get("Hobby"))

Output:

Soccer

6. Functions
A function is a set of code which execute a particular logic in your program. For example you could be having multiple lines of code which are geared to perform a certain function in you program. To make it easier to maintain your program and also to call/refer that particular block of code in your program, you need to implement functions. Functions help to decompose a program (modular programming).
Functions in Python are declared using key word def. Lets explore a simple example of a function in Python. Please take note of the comments in the program:

def getUserInputs():
    #Here we are making sure that these variables are scoped even outside the function.
    global firstName, lastName, age  

    firstName = input("Enter your first name: ")
    lastName = input("Enter your last name: ")
    age = int(input("Enter your age: "))

#Now we are calling the function in our program.
getUserInputs()

print(f"Your name is {firstName} {lastName} and you are {age} years old")

The output with test inputs will yield the below:

Enter your first name: James
Enter your last name: Michael
Enter your age: 23
Your name is James Michael and you are 23 years old

7. Control Flow
Python supports the following logical conditions(operators):

Equals: a == b
Not Equals: a != b
Less than: a < b
Less than or equal to: a <= b
Greater than: a > b
Greater than or equal to: a >= b

These logical operators are used in various flow control mechanisms in Python. Let's use them in below cases:

7.1 If...else statements
For If statements, if the condition at the logical check is True, only that block of code gets executed. Lets see below code:

x = 4
y = 42

if x > y:
    print(f"{x} is greater than {y}")
elif x < 42:
    print(f"({x} is less than  {y})")
else:
    print(f"{x} is equal to {y}")

The output is:

(4 is less than  42)

7.2 While loop
For while loop, a block of code will continue to be executed as long as the condition remains True. For example the values printed will 0, 1, 2, 3, 4 and 5. It will stop there since 6 will not satisfy the condition; it will be False.

i = 0 #Here we have initialized our variable i to value 0.

while i <= 5:
    print(i)
    i = i + 1 # Here we are incrementing our value of i by 1 each time.

Output when we run the above program will be:

7.3 For loop
For loop is nice for iterating through a list, tuple or dictionary. see below example:

myFriends = ["Mike", "John", "Peter", "Lenny", "Peter"]

for name in myFriends:
    print(name)

The output will be:

Mike
John
Peter
Lenny
Peter

8. Let's improve our calculator
Now lets improve our calculator. We will use most of the concepts we have learned so far including functions and control flow.
See below code:

firstNumber = input("Enter the first number: ")
operator = input("Enter the operator ('+,*,-,/ or %) you want to use: ")
secondNumber = input("Enter the second number: ")

def calc(firstNumber, operator, secondNumber):
    if operator == "+":
       return (float(firstNumber) + float(secondNumber))
    elif operator == "*":
       return (float(firstNumber) * float(secondNumber))
    elif operator == "-":
       return (float(firstNumber) - float(secondNumber))
    elif operator == "/":
       return (float(firstNumber) / float(secondNumber))
    elif operator == "%":
       return (float(firstNumber) % float(secondNumber))   
    else:
       return print("Invalid operator")  

result = calc(firstNumber, operator, secondNumber)

print(f"{firstNumber} {operator} {secondNumber} equals {result}")

9. Let's put all we have learn in practice: Fibanocci sequence numbers!
Now to spice things up let's try to explore Fibanocci sequence numbers.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. For example, 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610 etc.
I created a program to check if a number is a Fibanocci number.
Please check it out on my github: https://github.com/emwadun/fibanocciCheck

What's next on my mind?
In this blog post, I have tried to keep it as simple as possible to address only the core concepts. Please feel free to review, comment and share some feedback.

On my next blog post I will explore the following aspects in Python:
[x] Reading files
[x] Writing to files
[x] Modules and PIP
[x] Classes and Objects
[x] Object Functions
[x] Inheritance