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Python Mastery: Design Patterns, SQLAlchemy, Pytest & CICD

Name: Python Mastery: Design Patterns, SQLAlchemy, Pytest & CICD
Rating: 3.6 (9 reviews)

Object-Oriented Programming (OOP), Database Interaction using SQLAlchemy, Pytest, SOLID and Creational Design pattern.

Created byNITISH MAHATO

Last updated 2/2025

English

What you'll learn

Object-Oriented Programming (OOP) in Python
SOLID and Design Patterns in Python
practical database integration using SQLAlchemy
mini project - SQLAlchemy, Github Action, Docker
unit test using pytest in Python
SQL Query in postgreSQL

Coding Exercises

This course includes our updated coding exercises so you can practice your skills as you learn.

Course content

13 sections • 155 lectures • 9h 52m total length

Course Introduction and Motivation1:27
Course Breakdown1:18
What to expect from this course0:34
What's included in this course0:13
Course Readiness Check

Indentation in Python1:52
Master how indentation defines scope in Python. See a simple add two numbers function to show which lines are inside the function and which are outside.
Variable4:37
Master Python variables with snake_case naming, type hints, and core data types. Explore optional and union types, lists, tuples, dictionaries, constants, and runtime behavior.
Variable
Complex Numbers1:01
Explore complex numbers in Python, with real and imaginary parts, using j for the imaginary unit, verify type as complex, and add two numbers to yield 5 and 7.
Arithmetic Operators1:29
Assignment Statements1:16
Explore the assignment operator and its short form with x += 3, showing how it equates to x = x + 3 and updates a variable in Python.
Comparison Operators1:06
User Input0:38
Use of Tuple and Namedtuple6:35
What is closure?3:01
Exception Handling9:46
Exception Handling Advance Concept9:09
Shell Command from Python2:43
Learn to run ls -a from Python with subprocess.Popen, capture standard output and standard error using universal new line as true, and print results with communicate.
How to run Python code in background6:56
How to create requirements file and install it using pip1:27
pip install default artifactory details2:12
find python package dependencies1:56
Learn to find Python package dependencies with two solutions: importlib.metadata in Python 3.8+ and package resources from setup tools, demonstrated on pandas with numpy and pytest.
SAST - Static Application Security Testing3:38
Learn static application security testing to analyze code without execution and detect vulnerabilities. Explore tent analysis, lexical analysis, false positives, false negatives, and SEST tools.
Python Package Vulnerability Analysis4:10
Identify python package vulnerabilities using resources from the National Vulnerability Database, CVE lists, and GitHub advisories. Analyze specific packages like pandas, requests, matplotlib, and sklearn, and review mitigations and patches.
Threat Model4:05
Identify risks in aws etl solution, define scope, and apply stride—spoofing, tampering, repudiation, information disclosure, denial of service, and privilege elevation—while encrypting data and securing credentials via aws secret manager.

Create Class with Attribute and Method1:43
How Class Help to Create Complex Solution12:40
Check Instance Type of Class2:47
Class Method and Attribute3:21
Class Method and Attribute - Coding Exercise
Callable Object1:31
Callable Object - Coding Exercise
Compare Class Object using Magic Method3:21
Magic Method str and repr2:26
Magic Method to Access Attribute5:48
Abstract Base Class1:37
Interface3:17
Inheritance1:58
Multiple Inheritance2:25
Composite Class2:55
Object Oriented Concept
Lazy Properties using Descriptor6:01

SOLID Design Pattern Overview3:22
Understanding SOLID Principles in Object-Oriented Design: A Comprehensive Guide
Single Responsibility1:21
Open/Close Principle3:59
Sample code will be available in below location for reference.
https://github.com/code-adhyayana/Udemy_Python_Design_Patterns/tree/04_Creational_Design_Pattern/01_Factory_Method
Liskov Substitution Principle - SOLID2:24
Interface Segregation Principle ISP - SOLID1:52
Dependency Inversion - SOLID3:27

Factory Method4:33
Code Along - Factory Method- interface requirement - Part 19:52
Sample code will be available in below location for reference.
https://github.com/code-adhyayana/Udemy_Python_Design_Patterns/tree/04_Creational_Design_Pattern/01_Factory_Method
Code Along - Factory Method- Object Creation using Factory - Part 25:27
Sample code will be available in below location for reference.
https://github.com/code-adhyayana/Udemy_Python_Design_Patterns/tree/04_Creational_Design_Pattern/01_Factory_Method
Code Along - Factory Method - Apply Open Close Principle - Part 316:34
Sample code will be available in below location for reference.
https://github.com/code-adhyayana/Udemy_Python_Design_Patterns/tree/04_Creational_Design_Pattern/01_Factory_Method
Builder Pattern Introduction1:11
Builder Pattern Demo4:08
Singleton Pattern - Mind Map Story1:32
Singleton Pattern4:30
Singleton Pattern - Summary0:15
Prototype Pattern6:34

Introduction SQLAlchemy1:08
Version Check0:01
Install SQLAlchemy0:15
Insert data into table - Core3:04
Create table - Core1:29
Read data from table - Core1:09
Read data from table using Pandas1:57
Load data to table using Pandas2:26
Update table data - Core1:34
Delete records from table - Core1:07
Delete table - Core0:55
Advantages of SQLAlchemy Core0:46
SQLAlchemy Core - Summary0:12
SQLAlchemy ORM - Introduction0:38
Classical Mapping - ORM2:09
Declarative API - ORM1:51
Declarative API Model Demo2:08
Create table and load data - ORM4:06
Read data from table - ORM0:50
Read data with filter - ORM1:09
Update table data - ORM2:29
Delete records from table - ORM1:19
Advantages of SQLAlchemy ORM0:45
Mini Project(SQLAlchemy) - Problem Statement0:20
Mini Project Demo using Docker - Preview0:43
Mini Project(SQLAlchemy) - Solution5:49

pytest Introduction1:07
Install pytest0:26
PyCharm Test Runner Configuration1:44
Version Check0:01
What is TDD1:06
TDD Example4:30
pytest assert3:37
Exceptions4:38
Command line arguments2:50
Command line arguments - Demo (Directory and -k)2:57
Command line arguments - Demo (mark and maxfail)3:43
Command line arguments - Demo (verbose, quite and ignore)2:46
Approx Numeric Value1:07
Test Fixtures5:24
Test Fixtures Example - Setup3:54
Test Fixture Example - Teardown3:47
Test Fixture Scope - Session and Function2:47
Test Fixture Scope - Module3:23
Test Fixture Scope - Class2:23
Test Fixture Param Example2:25
Test Fixture parametrized tests2:33
Pytest Coverage2:24
doctest4:31
pytest.ini file - configurations6:42
pytest log filename with timestamp1:11

Requirements

A Little Bit of Programming Knowledge is Beneficial, But Not Mandatory!

Description

This course title encapsulates the breadth of your tutorial, emphasizing the progression to advanced topics like Object-Oriented Programming (OOP), Design Patterns, and practical database integration using SQLAlchemy. It communicates a clear learning path for students interested in mastering Python and its applications in real-world scenarios.

The course you've outlined, covering Object-Oriented Concepts, Design Patterns, and Database integration using SQLAlchemy, Git, unit test using Pytest and CICD with mini project, is well-suited for the following audience:

Beginner to Intermediate Python Developers:

Individuals who have a basic understanding of Python and want to deepen their knowledge by exploring Object-Oriented Programming, Design Patterns, and database integration.

Computer Science Students:

Students pursuing computer science or related fields can benefit from a comprehensive course that covers foundational Python concepts, OOP principles, design patterns, and practical database integration.

Web Developers:

Web developers who want to expand their skills by understanding not only Python basics but also how to implement Object-Oriented Design, apply Design Patterns, and integrate databases using SQLAlchemy in web development projects.

Career Switchers:

Individuals looking to transition into a career in programming or software development who have some basic knowledge but want to build a strong foundation in Python and related concepts.

We provide a well-rounded learning experience in the specified Python-related topics.

Who this course is for:

Individuals who have a basic understanding of Python and want to deepen their knowledge by exploring Object-Oriented Programming, Design Patterns, and database integration.
Those who are passionate about programming and eager to learn more advanced concepts beyond the basics.
Experienced software engineers who wish to refresh their Python skills and deepen their understanding of key concepts like OOP, Design Patterns, and database integration
Individuals looking to transition into a career in programming or software development who have some basic knowledge but want to build a strong foundation in Python and related concepts
Those interested in databases and want to explore how Python, particularly with SQLAlchemy, can be utilized for effective database integration.
for Test Engineer to write unit test using pytest

Python Mastery: Design Patterns, SQLAlchemy, Pytest & CICD

What you'll learn

Explore related topics

Coding Exercises

Course content

Introduction4 lectures • 4min

Basic19 lectures • 1hr 8min

Object-Oriented Programming (OOP)14 lectures • 52min

SOLID Overview6 lectures • 16min

Creational Design Patterns10 lectures • 55min

Structural Patterns7 lectures • 56min

Behavioral Pattern12 lectures • 1hr 52min

Database Integration using SQLAlchemy26 lectures • 40min

Git6 lectures • 8min

Unit Test using Pytest25 lectures • 1hr 12min

Requirements

Description

Who this course is for: