Forem: Lizaatis1

Python for everyone: Mastering Python The Right Way

Lizaatis1 — Mon, 28 Feb 2022 17:33:06 +0000

Python is an interpreted language. It's one language that is taking over the field of programming with a storm. It can be applied in various areas; from AI, web development, software engineering , Machine learning and data science

Despite having very many areas of application and having simple syntax and few lines of code, python is one language that is challenging to learn especially if you lack proper guidance

I can support this from my own experience, I have been learning python for over 5 years and this is the year i have been able to understand the syntax and put things together

I remember the number of times I downloaded each topic from W3 schools, saving them online and reading each topic one by one and the only level I managed to reach was python classes which confused me even more

I tried tutorials point, YouTube videos, bought Udemy courses and still ended up learning to the classes section which i never understood, i gave up several times. I remember downloading python for Everybody course and waking up early in the morning to try out the practical questions as theory proved not to be working for me. Still it never worked.
Mine was contributed with laziness, procrastination and lack of understanding of whatever i was learning, after all the coding and reading i still could not put the concepts together to understand how the applications built by the language were all put together, By the end of 2021 i gave up on python and
started learning C+, this became even more confusing because I had to start learning new syntax and everything in C was just too unfamiliar
I bought books on C but was unable to read , it all sounded like Greek.

By 2022 I had given up on my dream of becoming a software engineer and started learning mobile App development, I learnt simple platforms such as Kdular and later started learning flutter. They were fun too but i never felt satisfied. in around Januar, i came a cross training advert offered by Lux Academy and decided to apply
it wa an interesting programme because it had python and javascript the two languages have always wanted to learn and has struggled for years to understand, just imagining the data bundles i bought to download videos, books and tutorial notes offline just to learn same things over and over and still was unable to put everything together.

This is my fourth week at Lux Academy, its online and we have only 2 classes per week,okey only one class because i decided to concentrate on
python alone and i can proudly say i am learning well and i have gained much knowledge and im able to work on small projects without copy pasting codes, Its exciting and i feel like finally my dream is becoming true
.
What makes me improve
First thing i did was to take up my online training serious
in the past i was not so serious and was very lazy and never read deeply like now.
Secondly i decided to b committed to learn python and Javascript, i attend the classes and concentrate fully during class and take in each instrustions.

From these reasons above i have been able to come up with perfect ideas that can help those interested in python to learn well, these can be applied in any language not only python.

So what are the best ways to learn python?
get enrolled to an online class, this is not for everyone but mostly for those that are struggling with self studies.
enroll in online class that is actuve and you are able to interact with instructors, ask questions and get guidance, or join a physical class and most of all lookout for free training programs and take them very seriously

Read about python topics, you can use resources such as W3schools.com, Tutorials-point and YouTube Videos from Edureka, they have awesome instructors

Do a lot of research on each topic to understand the concept
Try short projects and assignments on each topic/ concept ; this helps in understanding each building block
Learn the Basic Syntax, this is the most important for beginners

Introduction To Data Structures and Algorithms with JavaScript

Lizaatis1 — Mon, 21 Feb 2022 19:17:08 +0000

Data Structures
Python Data Structures –
Tuples
A tuple is a built-in data structure in Python that is an ordered collection of objects. The primary differing characteristic between lists and tuples is mutability. Lists are mutable, whereas tuples are immutable. Tuples cannot be modified, added, or deleted once they’ve been created. Lists are defined by using parentheses to enclose the elements, which are separated by commas.
The use of parentheses in creating tuples is optional, but they are recommended to distinguish between the start and end of the tuple. A sample tuple is written as follows:
tuple_A = (item 1, item 2, item 3,…, item n)
Tuples are preferred when the user does not want the data to be modified. Use less memory
Sets
A set is defined as a unique collection of unique elements that do not follow a specific order
they can be modified, added, replaced, or removed. A sample set can be represented as follows:
set_a = {“item 1”, “item 2”, “item 3”,….., “item n”}

List
A list is defined as an ordered collection of items, and it is one of the essential data structures when using Python to create a project
re just like the arrays, declared in other languages which is an ordered collection of data. It is very flexible as the items in a list do not need to be of the same type.
The costly operation is inserting or deleting the element from the beginning of the List as all the elements are needed to be shifted. Insertion and deletion at the end of the list can also become costly in the case where the pre-allocated memory becomes full.
List = [1, 2, 3, "GFG", 2.3]
print(List)
In python starting index of the list, sequence is 0 and the ending index is (if N elements are there) N-1

Python Dictionary
in Python is an unordered collection of data values, used to store data values like a map, which, unlike other Data Types that hold only a single value as an element, Dictionary holds key:value pair
In Python, a Dictionary can be created by placing a sequence of elements within curly {} braces, separated by ‘comma’. Dictionary holds pairs of values, one being the Key and the other corresponding pair element being its Key:value.
Dict = {1: 'Geeks', 2: 'For', 3: 'Geeks'}

Python are immutable objects that only support methods and operators that produce a result without affecting the frozen set or sets to which they are applied. While elements of a set can be modified at any time, elements of the frozen set remain the same after creation.
If no parameters are passed, it returns an empty frozenset
frozenset({'g', 'e', 'f'})

String
Python Strings are arrays of bytes representing Unicode characters. In simpler terms, a string is an immutable array of characters
Bytearray
Python Bytearray gives a mutable sequence of integers in the range 0 <= x < 256.
Example: Python Bytearray Operations

Creating bytearray

a = bytearray((12, 8, 25, 2))

Advanced Data structures are one of the essential branches of data science which is used for storage, organization and management of data and information for efficient, easy accessibility and modification of data

Primitive types
Primitive types are either a basic building block or are a built-in type support function
Boolean data type– A Boolean data type is a computer-science related algorithm where there are only two possible values of the function- true and false
Composite or non-primitive type
Array- It is a collection of elements identified by a key or array index.
b) Records- It is structured data usually in the form of rows.
c) Union- They are a collection of several representations.
Abstract data types
In this data type, the behaviour is analyzed from the point of view of the user. The further list includes the following-
a) Container- This has a collection of the variable for problem-solving.
b) List- This includes ordered values of countable values
c) Graph- It represents pictorial representation of data for better understanding and evaluation.
d)Other abstract data types include tuple, multimap, set, multiset, stack, queue, double-ended queue.

Linear Data Structures
A data structure is linear if the imageelements of that data structure form a linear pattern or sequence.
Control table
Image
Matrix
Lists
Tree types
Tree types include the main head (parent node) and then the branches (nodes) are divided based on subcategories and are further divided. This continues until all the elements have been allocated properly in their branches.
Binary trees- In this tree function, there is a maximum of two sub-nodes. They are referred to as a left child and a right child.
b) Decision trees- This tree is a systematic analysis of the possible consequences, events, outcomes to display an algorithm.
Graphs
A pictorial representation of data for better understanding purposes.
a) Multigraph- it is permitted to have multiple edges which may have an identity and may not have an identity.
b) Adjacency matrix- This is used for representing finite graphs.

Python: Beginners Guide to Data Structures

Lizaatis1 — Mon, 21 Feb 2022 18:50:01 +0000

`DATA STRUCTURES AND ALGORITHM IN PYTHON
What are data structures?
Data structures allow you easy access to efficient modification
Organize, store, relate and perform operations on them accordingly

There are two categories of data structures in python
• Built-in data structures
• User defined data structures
Built-in data structures
Enables you to store and access data. They include:
Lists
Sets
Tuples
Dictionary

User defined
Aallow users to create there own data structures
Stack
Queue
Tree
LinkedList
Graph
HashMap

Built in data structures
Lists
Lists used to store data of different data types in a sequential manner
They are mutable. To create a list, you use the square brackets and add elements into it accordingly. If you do not pass any elements inside the square brackets, you get an empty list as the output.
1
2
3
4 my_list = [] #create empty list
print(my_list)
my_list = [1, 2, 3, 'example', 3.132] #creating list with data
print(my_list)

Tuple are same as list , only that when data enters a tuple it cannot be modified. Not mutable
You create a tuple using parenthesis or using the tuple() function.
1
2 my_tuple = (1, 2, 3) #create tuple

A tuple is a built-in data structure in Python that is an ordered collection of objects. The primary differing characteristic between lists and tuples is mutability. Lists are mutable, whereas tuples are immutable. Tuples cannot be modified, added, or deleted once they’ve been created. Lists are defined by using parentheses to enclose the elements, which are separated by commas
Dictionary
Used to store key value pairs, example is mapping employee names with employee IDs
Created using curly braces
Dictionaries can be created using the flower braces or using the dict() function. You need to add the key-value pairs whenever you work with dictionaries.
my_dict = {1: 'Python', 2: 'Java'} #dictionary with elements
print(my_dict)
are used to store key-value pairs

Sets
A collection of unordered elements
They are mutable, can be created using curly braces.
Creating a set
Sets are created using the flower braces but instead of adding key-value pairs, you just pass values to it.
1
2 my_set = {1, 2, 3, 4, 5, 5, 5} #create set

User-defined data structures
Stack
Linear data structures based on the principle of last in first out. Built using array structures.
Applications. Recursive programming, reverse inverse, word editors

Queues
Linear data structure that is based on principle of first in first out. Data entered first will be accessed first. Built using array structures. Allows insertion of elements from one end and deletion from the other.
queue = ['first', 'second', 'third']
print(queue)
Aq

Trees
Non linear data structures with roots and nodes. Root is where the data originate and nodes are data point that are available to us. Node preceding is the parent and node that is after is the child. Last node is the leaves.
Uses:
Html pages, searching purposes

Linked list
Linear data structures that are not stored consequently but are linked to each other using pointers. Node is composed of data and a pointers called the nest. These are used in image viewing applications

Graph
Used to store data collection of point called

Uses
Google maps, uber to find the shortest distance

Hashmaps
Same as dictionary
Used in phone books, populate data according to the data

=
Algorithms
These are rules or instructions that are formulated in a finite, sequential order to solve problems. They provide pseudocode for problems for various languages.

Process for writing algorithms
Identify the problem
Identify starting point
Determine end point
Formulate intermediate steps
Review steps
Can be done depending on user preferences
Elements
Defined output and input
Flexibility

Algorithm Classes
Greedy algorithms- This involves taking the easiest step without worrying about future complexity
Dynamic programming- Divide problem into sections and remember the result of each section and apply to similar ones.
Divide and Conquer- Divides problems into sections and solve them separately

Tree Traversal algorithms
This refers to visiting each node present in the tree exactly once in order to update

Types of tree traversals
In-order traversal- refers to visiting the left nodes followed by the root and then right
Post-order traversal- refers to visiting the left nodes followed by the right nodes and then root node
Pre-order traversal- refers to visiting the root nodes and then right nodes.

Sorting Algorithms
Sorting algorithms denote the ways to arrange data in a particular format. Sorting ensures that data searching is optimized to a high level and that the data is
• Bubble Sort – This algorithm is based on comparison in which there is repeated swapping of adjacent elements if they are in an incorrect order.
• Merge Sort – Based on the divide and conquer algorithm, Merge sort divides the Array into two halves, sorts them, and then combines them.
• Insertion Sort – This sorting begins with comparing and sorting the first two elements. Then, the third element is compared with the two previously sorted elements and so on.
• Shell Sort – It is a form of Insertion sort, but here, far away elements are sorted. A large sub-list of a given list is sorted, and the size of the list is progressively reduced until all the elements are sorted.
• Selection Sort – This algorithm begins by finding the minimum value from a list of elements and puts it into a sorted list. The process is then repeated for each of the remaining elements in the list which is unsorted. The new element entering the sorted list is compared with its existing elements and placed at the correct position. The process goes on until all the elements are sorted.

Searching Algorithms
Searching algorithms help in checking and retrieving an element from different data structures. One type of searching algorithm applies the method of sequential search where the list is sequentially traversed, and every element is checked (linear search). In another type, the interval search, elements are searched for in sorted data structures (binary search). Let us look at some of the examples:
• Linear Search **– In this algorithm, each item is sequentially searched one by one.
• **Binary Search – The search interval is repeatedly divided in half. If the element to be searched is lower than the central component of the interval, the interval is narrowed to the lower half. Otherwise, it is narrowed to the upper half. The process is repeated until the value is found.
Graph Algorithms
There are two methods of traversing graphs using their edges. These are:
• Depth-first Traversal (DFS) – In this algorithm, a graph is traversed in a depth-ward motion. When any iteration faces a dead end, a stack is used to go to the next vertex and start a search. DFS is implemented in Python using the set data types.
• Breadth-first Traversal (BFS) – In this algorithm, a graph is traversed in a breadthward motion. When any iteration faces a dead end, a queue is used to go to the next vertex and start a search. BFS is implemented in Python using the queue data structure.
Algorithm Analysis
• A Priori Analysis – This represents a theoretical analysis of the algorithm before its implement ation. An algorithm’s efficiency is measured by presuming that factors, such as processor speed, are constant and have no consequence on the algorithm.
• A Posterior Analysis – This refers to the empirical analysis of the algorithm after its implementation. A programming language is used to implement the selected algorithm, followed by its execution on a computer. This analysis collects statistics, such as the time and space required for the algorithm to run.

AQ `DATA STRUCTURES AND ALGORITHM IN PYTHON
What are data structures?
Data structures allow you easy access to efficient modification
Organize, store, relate and perform operations on them accordingly

There are two categories of data structures in python
• Built-in data structures
• User defined data structures
Built-in data structures
Enables you to store and access data. They include:
Lists
Sets
Tuples
Dictionary

User defined
Aallow users to create there own data structures
Stack
Queue
Tree
LinkedList
Graph
HashMap

Sets
A collection of unordered elements
They are mutable, can be created using curly braces.
Creating a set
Sets are created using the flower braces but instead of adding key-value pairs, you just pass values to it.
1
2 my_set = {1, 2, 3, 4, 5, 5, 5} #create set

User-defined data structures
Stack
Linear data structures based on the principle of last in first out. Built using array structures.
Applications. Recursive programming, reverse inverse, word editors

Queues
Linear data structure that is based on principle of first in first out. Data entered first will be accessed first. Built using array structures. Allows insertion of elements from one end and deletion from the other.
queue = ['first', 'second', 'third']
print(queue)
Aq

Trees
Non linear data structures with roots and nodes. Root is where the data originate and nodes are data point that are available to us. Node preceding is the parent and node that is after is the child. Last node is the leaves.
Uses:
Html pages, searching purposes
Linked list
Linear data structures that are not stored consequently but are linked to each other using pointers. Node is composed of data and a pointers called the nest. These are used in image viewing applications

Graph
Used to store data collection of point called

Uses
Google maps, uber to find the shortest distance

Hashmaps
Same as dictionary
Used in phone books, populate data according to the data

=
Algorithms
These are rules or instructions that are formulated in a finite, sequential order to solve problems. They provide pseudocode for problems for various languages.

Process for writing algorithms
Identify the problem
Identify starting point
Determine end point
Formulate intermediate steps
Review steps
Can be done depending on user preferences
Elements
Defined output and input
Flexibility

Algorithm Classes
Greedy algorithms- This involves taking the easiest step without worrying about future complexity
Dynamic programming- Divide problem into sections and remember the result of each section and apply to similar ones.
Divide and Conquer- Divides problems into sections and solve them separately

Tree Traversal algorithms
This refers to visiting each node present in the tree exactly once in order to update

Types of tree traversals
In-order traversal- refers to visiting the left nodes followed by the root and then right
Post-order traversal- refers to visiting the left nodes followed by the right nodes and then root node
Pre-order traversal- refers to visiting the root nodes and then right nodes.
Sorting Algorithms
Sorting algorithms denote the ways to arrange data in a particular format. Sorting ensures that data searching is optimized to a high level and that the data is
• Bubble Sort – This algorithm is based on comparison in which there is repeated swapping of adjacent elements if they are in an incorrect order.
• Merge Sort – Based on the divide and conquer algorithm, Merge sort divides the Array into two halves, sorts them, and then combines them.
• Insertion Sort – This sorting begins with comparing and sorting the first two elements. Then, the third element is compared with the two previously sorted elements and so on.
• Shell Sort – It is a form of Insertion sort, but here, far away elements are sorted. A large sub-list of a given list is sorted, and the size of the list is progressively reduced until all the elements are sorted.
• Selection Sort – This algorithm begins by finding the minimum value from a list of elements and puts it into a sorted list. The process is then repeated for each of the remaining elements in the list which is unsorted. The new element entering the sorted list is compared with its existing elements and placed at the correct position. The process goes on until all the elements are sorted.
Searching Algorithms
Searching algorithms help in checking and retrieving an element from different data structures. One type of searching algorithm applies the method of sequential search where the list is sequentially traversed, and every element is checked (linear search). In another type, the interval search, elements are searched for in sorted data structures (binary search). Let us look at some of the examples:
• Linear Search – In this algorithm, each item is sequentially searched one by one.
• Binary Search – The search interval is repeatedly divided in half. If the element to be searched is lower than the central component of the interval, the interval is narrowed to the lower half. Otherwise, it is narrowed to the upper half. The process is repeated until the value is found.
Graph Algorithms
There are two methods of traversing graphs using their edges. These are:
• Depth-first Traversal (DFS) – In this algorithm, a graph is traversed in a depthward motion. When any iteration faces a dead end, a stack is used to go to the next vertex and start a search. DFS is implemented in Python using the set data types.
• Breadth-first Traversal (BFS) – In this algorithm, a graph is traversed in a breadthward motion. When any iteration faces a dead end, a queue is used to go to the next vertex and start a search. BFS is implemented in Python using the queue data structure.
Algorithm Analysis
• A Priori Analysis – This represents a theoretical analysis of the algorithm before its implementation. An algorithm’s efficiency is measured by presuming that factors, such as processor speed, are constant and have no consequence on the algorithm.
• A Posterior Analysis – This refers to the empirical analysis of the algorithm after its implementation. A programming language is used to implement the selected algorithm, followed by its execution on a computer. This analysis collects statistics, such as the time and space required for the algorithm to run.

User defined
Aallow users to create there own data structures
Stack
Queue
Tree
LinkedList
Graph
HashMap

User-defined data structures
Stack
Linear data structures based on the principle of last in first out. Built using array structures.
Applications. Recursive programming, reverse inverse, word editors

Graph
Used to store data collection of point called

Uses
Google maps, uber to find the shortest distance

Hashmaps
Same as dictionary
Used in phone books, populate data according to the data

=
Algorithms
These are rules or instructions that are formulated in a finite, sequential order to solve problems. They provide pseudocode for problems for various languages.

Tree Traversal algorithms
This refers to visiting each node present in the tree exactly once in order to update

Introduction To JavaScript

Lizaatis1 — Mon, 14 Feb 2022 13:49:36 +0000

*Who is this course for? *
This course is for developers of every level, from beginner to advanced, who want to improve their JavaScript skills and get up to date with all the upgrades done to the language specification since 2015

What is Javascript?
Javascript is a lightweight, interpreted, or just-in-time compiled programming language with first-class functions. JavaScript was developed by Brendan Eich in 1995.

What can Javascript do?

JavaScript Can Change HTML Content
Can Change HTML Attribute Values
Change HTML Styles (CSS)
JavaScript Can Hide HTML Elements
Show HTML Elements

How does JavaScript work?
JavaScript can be added to a page’s code using tags with the type attribute text/javascript or as a header file with the extension .js. A web browser then downloads and runs the script, changing it into the dynamic objects and effects seen on a screen. JS framework ReactJS, Angular, Vue.js and Bootstrap. How it is used <ul> <li>Build web and mobile applications</li> <li>Add interactive elements to a website</li> <li>Many developers use JavaScript to make web pages more interactive</li> <li>Develop games</li> <li>The programming language</li> <li>Build efficient IoT systems</li> </ul> How to Run JavaScript? JavaScript cannot run on its own. When a user requests an HTML page with JavaScript in it, the script is sent to the browser and it is up to the browser to execute it. To start with, you need a text editor to write your code and a browser to display the web pages you develop. You can use a text editor of your choice including Notepad++, Visual Studio Code, Sublime Text, Atom or any other text editor you are comfortable with. You can use any web browser including Google Chrome, Firefox, Microsoft Edge, Internet Explorer Main uses are: <ul> <li>Client-side validation,</li> <li>Dynamic drop-down menus,</li> <li>Displaying date and time,</li> <li>Displaying pop-up windows and dialog boxes (like an alert dialog box, confirm dialog box and prompt dialog box),</li> <li>Displaying clocks etc.</li> </ul> JavaScript Example <script> document.write("Hello JavaScript by JavaScript");

*Javascript frameworks and libraries available:
*
Angular
-React

jQuery
Vue.js
Ext.js
Ember.js
Meteor
Mithril
Node.js
Polymer
Aurelia
Backbone.js `

Ultimate Guide TO Python programming

Lizaatis1 — Mon, 14 Feb 2022 13:28:00 +0000

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. It was created by Guido van Rossum during 1985- 1990

*Characteristics of Python Programming -
*

-It supports functional and structured programming methods as well as OOP.
-It can be used as a scripting language or can be compiled to byte-code for building large applications.
-It provides very high-level dynamic data types and supports dynamic type checking.
-It supports automatic garbage collection.
-It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.

_For download and installation check
Setting up Visual Studio Code
**
Setting up the VS Code, you follow these steps:**

First, navigate to the VS Code official website and download the VS code based on your platform (Windows, macOS, or Linux).

launch the setup wizard and follow the steps.
Once the installation completes, you can launch the VS code application:
Install Python Extension

To make the VS Code works with Python, you need to install the Python extension from the Visual Studio Marketplace.

steps:

click the Extensions tab.
- type the python keyword on the search input.
- click the Python extension. It’ll show detailed information on the right pane.
Finally, click the Install button to install the Python extension.

Creating a new Python project

Create a new folder called helloworld.
Launch the VS code and open the helloworld folder.
create a new app.py file and enter the following code and save the file:
print('Hello, World!')

A function

When you sum two numbers, that’s a function. And when you multiply two numbers, that’s also a function.
Each function takes your inputs, applies some rules, and returns a result.
In the above example, the print() is a function. It accepts a string and shows it on the screen.
Python has many built-in functions like the print() function to use them out of the box in your program.
In addition, Python allows you to define your functions, which you’ll learn how to do it later.

*Executing the Python program on VS
*

To execute the pro.py file, you first launch the Command Prompt on OS.

, navigate to the helloworld folder.

then type the following command to execute the pro.py file:

python pro.py
Code language: Python (python)

If everything is fine, you’ll see the following message on the screen:

Hello, World!
Code language: Python (python)

If you use VS Code, you can also launch the Terminal within the VS code by:

Accessing the menu Terminal > New Terminal
Or using the keyboard shortcut Ctrl+Shift+`.

Typically, the backtick key (`) locates under the Esc key on the keyboard.

Python IDLE

In full is Python Integration Development Environment (IDE), it comes with the Python distribution by default.
The Python IDLE is also known as an interactive interpreter. It has many features such as:

Code editing with syntax highlighting
Smart indenting
And auto-completion

Python IDLE helps you experiment with Python quickly in a trial-and-error manner.
Process for launching python IDE:

Lunch the Python IDLE program:
A new Python Shell window will display as follows:
Now, you can enter the Python code after the cursor >>> and press Enter to execute it. For example, you can type the code print('Hello, World!') and press Enter, you’ll see the message Hello, World! immediately on the screen: Python Hello World - Executing code

Summary

Use the python pro.py command from the Command Prompt on Windows or Terminal on macOS or Linux to execute the app.py file.
Use the print() function to show a message on the screen.
Use the Python IDLE to type Python code and execute it immediately.

Python basics

- Fundamentals
- Syntax
- variables
- strings
- numbers
- boleans
- constants
- comments
- Type conversion