DEV Community: Samwel Njihia

Python for Everyone: Mastering Python the right way

Samwel Njihia — Wed, 02 Mar 2022 13:47:29 +0000

Are you new to the Python programming language? Are you at an advanced level?. Whatever level you are, this article is crucial as it will act as a guidance and as a reference in your Python programming journey. This article discusses the learning pathway which results in mastering Python the right way.

The learning Pathways

This section discusses the Python Learning Pathways, which will result in mastering Python the right way. What is the path from beginner to advanced, and the careers options are available in Python.

1. Learning Python Fundamentals

As with any other language such as Java, one needs to start from the basics concepts from the simple project setup and syntax. Learn also the python PEP 8 conventions and have the basic knowledge of how to use Python. You will start by exploring variables, expressions, operators, conditional loops, and functions (You can get all these concept here with examples Python 101: Ultimate Python Guide or Introduction to Modern Python )
Also, learn python data structures, i.e., the python in-built and user-defined data structure; moreover, learning algorithms in Python. All these concepts about data structure and algorithms with examples are discussed here in this article: Python 102: Introduction to Data Structures and Algorithms With Python. ). After mastering the basic python fundamentals, one should start practicing with some mini projects to apply the basic fundamentals concepts learned.

2. Become Advanced in Python.

Here you will add more advanced concepts to your python knowledge by learning how Python interacts with web Data, i.e., web scrapping, how to use Python for Object-Oriented Programming (Classes, Inheritance, Data Abstraction, and Encapsulation are the main concepts covered here). Final but not list concept to be covered here is integrating Python with databases( SQL Databases, No-SQL Databases, and APIs).

3. Focus on Career pathway

After covering the two above and being advanced in Python, it is time to focus and explore the career pathway. This will involve focusing and studying the Python Libraries and Frameworks that are specific to certain career paths. This section will discuss the common pathways for Python developers and their related libraries or frameworks.

a). Web Development

Python offers a wide range of frameworks for web development. These framework include Flask, CherryPy, Pyramid, Django and web2py.

b). Data Science

This will involve learning data Sourcing, Data Analysis, and Machine Learning with Python. Libraries that one can learn for this are: Numpy, Matplotlib, Pandas, SciPy, and SciKit Learn for ML, among others.

c). Machine Learning and Artificial Intelligence

AI is a popular career path that keeps gaining popularity in the current world. The top libraries that one can learn are :SciKit Learn, Tensorflow, Keras, Natural Language Toolkit (NLTK), PyTorch, Theano, etc.

d). Graphical User Interface (GUI) Programming

This involves creating of graphical application using Python. Some of the libraries to learn are: kinter, wxPython, PyQT, Kivy etc.

Game Development

Game development is an interesting to explore.One needs to learn PyGame library for game development in python.

Conclusion

In conclusion Python is among the top programming language that is is in demand in the current market. One should spare some time and learn this language. The following are a suggestions of various projects that one can try to develop at different levels. Please drop some more suggestions of various projects in comment section:

Python 102: Introduction to Data Structures and Algorithms With Python.

Samwel Njihia — Sun, 20 Feb 2022 10:07:32 +0000

This article is beginner friendly to kick start learning data structure and algorithms using python programming language. This article discusses the in-built data structures such list, tuples, set, dictionaries, and user defined data structures such linked list, graph, trees etc., and algorithms. Data is crucial which means that it needs to be stored and accessed in timely manner (This is archived via data structures). The articles discussed data structured and algorithms in python.

Data Structure Definition

Refers to data organization, storage, and data management format that enables efficient modification and access. Data structure allows organization of data in such a way that storage of data collection, relation and and performance of operation between them is possible.

Type of Data Structures in Python

The following is a simple breakdown:

a.) Built-in Data Structures

These structures are called List, Dictionary, Tuple and Set.

i.) List

They have positive and negative index, the +ve index starts from 0 and the -ve index starts from -1.

Elements are ordered, changeable and allow duplicates
Items can be added or removed
Defined using [] or the list() constructor
Use dot(.) to get in-build method to perform sort, remove etc

Example:

my_list = [] #empty list
print(my_list)
my_list = [10, 22, 3, 'Sam', 3.132] #list with data
print(my_list)

Results:

[]
[10, 22, 3, 'Sam', 3.132]

Some of operations that can be performed using List are append
clear
copy
count
extend
insert
index
pop
remove
reverse
sort

ii.) Dictionary

They are used to store key value pairs.

They are ordered , changeable, and do not allow duplicates(from python 3.7 and above)

Example:

my_dict = {} #empty dictionary
print(my_dict)
my_dict = {1: 'Django', 2: 'Laravel'} #With elements
print(my_dict)

Results:

{}
{1: 'Django', 2: 'Laravel'}

The following are operations that can be performed using Dictoionary
clear()
copy()
values()
update()
fromkeys()
get()
items()
keys()
pop()
popitem()
setdefault()

iii.) Tuple

They are the same as lists with the exception that the data once entered into the tuple cannot be changed no matter what.

Items are ordered, unchangeable, and allow duplicates values
Items can be accessed by referring to the index number, inside square brackets

Example

names= ("apple", "banana", "cherry")
print(names)

Results:

('apple', 'banana', 'cherry')

iv.) Sets

They are a collection of unordered elements that are unique. Meaning that even if the data is repeated more than one time, it would be entered into the set only once.

Unordered, unchangeable, unindexed, and do not allow duplicate values
Items in a set cannot be accessed using index but can be accessed using loop #####Example:

num_set = {1, 3, 6, 70}
print(num_set )

Results:

{1, 3, 6, 70}

Operation in set are Union, intersection, Difference etc

Example

my_set = {1, 2, 3, 4}
my_set_2 = {3, 4, 5, 6}
print(my_set.union(my_set_2), '----------', my_set | my_set_2)
print(my_set.intersection(my_set_2), '----------', my_set & my_set_2)
print(my_set.difference(my_set_2), '----------', my_set - my_set_2)
print(my_set.symmetric_difference(my_set_2), '----------', my_set ^ my_set_2)
my_set.clear()
print(my_set)

Results:

{1, 2, 3, 4, 5, 6} ———- {1, 2, 3, 4, 5, 6}
{3, 4} ———- {3, 4}
{1, 2} ———- {1, 2}
{1, 2, 5, 6} ———- {1, 2, 5, 6}
set()

b.) User defined Data Structures

These include Queue, tree, Linked List, Stack, graph, map etc

NB Array Vs List

They are the same with one difference. Lists allow heterogeneous data element storage whereas Arrays allow only homogeneous elements to be stored within them.

i.) Stacks

They are linear Data Structures which are based on the principle of Last-In-First-Out (LIFO) where data which is entered last will be the first to get accessed. Built using the array structure and has operations namely, pushing (adding) elements, popping (deleting) elements and accessing elements only from one point in the stack called the TOP.TOP is the pointer to the current position of the stack

Operation in Stacks

PUSH

Adds an element at the top of the stack

POP

Removes an element from the top of the stack

ii.) Queue

Is a linear data structure which is based on the principle of First-In-First-Out (FIFO) where the data entered first will be accessed first.It is built using the array structure and has operations which can be performed from both ends of the Queue, i.e, head-tail or front-back. Operations such as adding and deleting elements are called En-Queue and De-Queue and accessing the elements can be performed.

iii.) Tree

They are non-linear data structure that have roots and node.The root is the node from where the data originates and the nodes are the other data points that are available to us. The node that precedes is the parent and the node after is called the child. There are levels a tree has to show the depth of information. The last nodes are called the leaves.

iv.) Linked List

Linked lists are linear Data Structures which are not stored consequently but are linked with each other using pointers. The node of a linked list is composed of data and a pointer called next.

v) Graph

Graphs are used to store data collection of points called vertices (nodes) and edges (edges). Graphs can be called as the most accurate representation of a real-world map. They are used to find the various cost-to-distance between the various data points called as the nodes and hence find the least path.

v) HashMaps

are the same as what dictionaries are in Python. They can be used to implement applications such as phonebooks, populate data according to the lists

ALGORITHMS

They are instructions or rules that are formulated in a finite sequential order to solver problems and get results. They provide pseudo-code for problems and they are not language specific as they can be implemented in any language.

How to write an algorithm

Figure out what is the exact problem
Determine where you need to start
Determine where you need to stop
Formulate the intermediate steps
Review your steps #####Algorithm Classes: Some examples of algorithms include Tree Traversal Algorithms, Searching Algorithms, Sorting Algorithms, etc.

Python 101: Ultimate Python Guide or Introduction to Modern Python

Samwel Njihia — Sun, 13 Feb 2022 10:42:13 +0000

Introduction

Python is a dynamically typed language, i.e., the data type of any variable or function is checked at run time, and due to this, python does not require the definition of data type as in java(Although you can define your data type in python which is not a must). Python is applied in fields such as web development, game development, AI and Machine learning, software development, etc. The article discusses python's basics and how to get started with the python programming language.

Variable Declaration

Variables are containers for storing values of the data.
Example of how to declare and assign values to variable

name = "John"
age = 45

As seen above there is no data type for each variable but data type for each variable can be done as shown

age = int(56) #age will be intenger
height = str(10) #height will be string

age:int = 56 #age will be intenger
height:str = 10 #height will be string

Data type that a function return can be specified as shown

def hello() ->int:
return 6

NB Declaration of datatype is not mostly done

Comments

Comment are not executed and they are for code explanation

Single Line Comments

# put comment here

Multi-line Comments

"""
This is a multline
comment
"""

Data Types

These include int, str, boolean and we have already seen how you can specifies them if you want

Data Structures(Collections/Arrays) in Python

These are dictionaries, list, tuples, and sets.

Lists

Elements are ordered, changeable and allow duplicates
Items can be added or removed
Defined using [] or the list() constructor
Use dot(.) to get in-build method to perform sort, remove etc

numbers = [10,23,90] #declaring using []
num =list((1, 4, 6)) #list constructor, note the double brackets

Sets

Unordered, unchangeable, unindexed, and do not allow duplicate values
Items in a set cannot be accessed using index but can be accessed using loop

num_set = {1, 3, 6, 70}
print(num_set )

a) Sets Union (|)

This combination of everything in the sets

lettersA = {"A", "B", "C", "D"}
lettersB = {"E", "F"}
print(lettersA | lettersB )

Results:

{'A', 'D', 'C', 'E', 'B', 'F'}

b) Sets Intersection(&)

This what is common between the given sets

lettersA = {"A", "B", "C", "D"}
lettersB = {"B", "G"}
print(lettersA & lettersB )

Results:

{'B'}

c) Sets Difference(-)

Deference A-B means what is in A and not in B

lettersA = {"A", "B", "C", "D"}
lettersB = {"B", "E", "F"}
print(lettersA - lettersB )

Results:

{'C', 'A', 'D'}

Dictionaries

They are unordered mutable python container that stores mappings of the unique keys to values

They are ordered , changeable, and do not allow dublicates(from python 3.7 and above)

student = {
    "name" : "john",
    "age" : 34,
    "address" : "US"
}

print(student["name"])

Results:

john

Tuples

Items are ordered, unchangeable, and allow duplicates values
Items can be accessed by referring to the index number, inside square brackets

names= ("apple", "banana", "cherry")
print(names)

results

('apple', 'banana', 'cherry')

Conditional Statements

If Statement

Executes is the given condition is true

a = 4
b = 10
if b > a:
   print("B is greater than A")

Results:

B is greater than A

If ELse Statement

if executes when given condition is true and else executes when the condition fails

b = 4
a = 10
if b > a:
   print("B is greater than A")
else:
   print("B is not greater than A")

Results:

B is not greater than A

if---elif--else

used to express multiple conditions

num = 0

if num > 0:
  print("Number Positive")
elif num == 0:
  print("Number is equal to 0")
else:
  print("Number is negative ")

Results:

Number is equal to 0

Loops

These are the while and for loops and they execute as long as the given condition is true

The while loop

The following executes as long as i is < 5

i = 1
while i < 5:
  print(i)
  i += 1

Results:

For loop

A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).
The following will print each fruits

fruits = ["apple", "banana", "mango"]
for x in fruits:
  print(x)

apple
banana
mango

Functions and Function Call

Function is a block of code that will executes when it is called

def helloWorld():
  print("Hello code Gurus")

helloWorld()# function Call

Results

Hello code Gurus

Passing Parameters and Arguments to Functions

Parameters are variables in method while arguments are data passed to the method's parameters
Arguments is the actual value of the variable that get passed to function

def helloWorld(name):
  name = 'Hello code Gurus'
  print(name)

helloWorld(name)

Results:

Hello code Gurus