Python Training Overview

Python Fullstack Course Syllabus

1. Introduction to Python Language

What is Python, Uses of Python Programming Language / Python? Applications, Python for Software development, Python for Networking, Python for Automated Testing, Features of Python Programming Language, Implementations of Python, and Python career opportunities?

2. Download & Install Python

Download your operating system compatible Python Interpreter, install Python, set environment variable, customize Python shell, write & execute Python programs using Interactive mode and script mode. Python PyCharm or IDE, set Python for PyCharm IDE, configure PyCharm IDE, write & execute Python programs.

3. Python Language Syntax

Modes of Programming in Python, Interactive mode programming, Script mode programming, Creating Python program file, Python Identifiers, Python keywords, Lines and Indentation, Spilt Python statements, Join Python Statements, Writing code blocks, Comments in Python, and Quotation in Python.

4. Python Keywords and Identifiers

Python keywords or reserved words, Python keywords define the syntax and structure of the Python language, Python keywords are case sensitive, Python literals (True, False, Null), Python Identifiers, class names, variable names, function names, method names, and Identifier naming rules.

5. Python Comments

Purpose/use of comments in Computer Programming, Comments for Understanding Python code, Python Comment Syntax, Python Single line comment, Multiline comment in Python, and writing Python comments.

6. Python Variables

What is Variable? Declaration of Variables, Assign Values to Variables, Initialization, Reading, Variable naming restrictions, and Types of Python Variables.

7. Python Data Types

What is DataType? Implicit Declaration of Data Types, Python Numbers Integers, floating-point numbers, and complex numbers), Python Strings, Python boolean data type.

8. Python Operators

Python Arithmetic, Comparison/Relational Operators, Increment Operators, logical operators, Python Identity Operators, and Python Operators Precedence.

9. Python Control Flow – Decision Making

(Decision Making / Conditional Statements in Python, Simple If Structure, if else structure, if elif structure, and nested If Structure. Execute a block of Statements when the condition is true, Execute a block of Statements when a compound condition is true, Execute a block of Statements when the condition is true otherwise execute another block of Statements, Decide among several alternates(elif), and Execute a block of Statements when more than one condition is true (Nested if))

10. Python Control Flow – Looping

((Python Control Flow Statements, Python Loop Statements. Python while loop, Python for loop, Python range (), Python Nested Loop Structures, and Inserting conditions in Loops and vice versa.))

11. Python Control Flow – Branching

(Python Flow Control – Branching Statements, A branching statement is a statement that determines whether other statements will be executed. Python Branching Statements – break, continue, and pass)

12. Python Numbers

(Python Number data types are for storing numeric values, Python supports integers, floats, and complex numbers.)

13. Python Strings

(String is a sequence of characters written in single quotes or in double quotes or in three double quotes. The string may have Alphabets, Numbers, and Special Characters. Operations on Strings, Finding String length, Concatenating Strings, Print a String multiple times, Check whether the String has all numeric characters?, and Check whether the String has all alphabetic characters?.)

14. Python Lists

((Python Data Structures, Create Python Lists, Update Python Lists, Delete Elements from Python Lists, and Built-in Functions & Built-in Methods for Python Lists.))

15. Python Tuples

(Tuples are sequences, just like lists. The differences between tuples and lists are, the tuples cannot be changed unlike lists and tuples use parentheses, whereas lists use square brackets.)

16. Python Sets

(A Python set is a collection that is unordered and unindexed. In Python sets are written with curly brackets.)

17. Python Dictionaries

(A dictionary is a collection that is unordered, changeable, and indexed. In Python dictionaries are written with curly brackets, and they have keys and values.)

18. Python Arrays

(Array is a container that can hold a fixed number of items and these items should be of the same type. Python does not have built-in support for Arrays, but Python Lists can be used instead.)

19. Python user-defined Functions

(In all programming and scripting languages, a function is a block of program statements that can be used repetitively in a program. It saves the time of a developer. In Python concept of function is the same as in other languages. There are some built-in functions that are part of Python. Besides that, we can define functions according tour needs.)

20. Python Built-in Functions

(Python has several functions that are readily available for use. These functions are called built-in functions.)

21. Python – Modules

A module allows you to logically organize your Python code. Simply, a module is a file consisting of Python code. A module can define functions, classes, and variables. A module can also include runnable code.

22. Python User Input

Python user input from the keyboard can be read using the input () built-in function. The input from the user is read as a string and can be assigned to a variable.

23. Python File Handling

Python supports file handling and allows users to handle files i.e., to read and write files, along with many other file handling options, to cooperate on files.

24. Python Exceptions Handling

Python provides us with a way to handle the Exception so that the other part of the code can be executed without any disruption. However, if we do not handle the exception, the interpreter doesn’t execute all the code that exists after that.

25. Regular Expressions

(A RegEx, or Regular Expression, is a sequence of characters that forms a search pattern. Python has a built-in package called re, which can be used to work with Regular Expressions. The re module offers a set of functions that allows us to search a string for a match. RegEx Functions, Meta characters, and Special Sequences.)

26. Python Classes and Objects

(Classes provide a means of bundling data and functionality together. Creating a new class creates a new type of object, allowing new instances of that type to be made. Objects are an encapsulation of variables and Functions in a single entity. Objects get their variables and functions from classes. Classes are essentially a template to create your objects.)

27. Python Methods

(A Python method is a label that you can call on an object; it is a piece of code executed on that object. Methods are simply another kind of function that reside in classes. You create and work with methods in Python in precisely the same way that you functions, except that methods are always associated with a class. You can create to winds of methods: those associated with the class itself and those associated with an instance of a class.)

28. Python Constructors

(A constructor is a special type of method (function) that is used initialize the instance members of the class. Two types of Constructors in Python, Parameterized Constructor, Non-parameterized Constructor, Constructor Definition is executed when we create the object of this class.)

29. Python Inheritance

(Inheritance enables us to define a class that takes all the functionality from a parent class and allows us to add more. Inheritance is a powerful feature in object-oriented programming, Types Inheritance in Python, Single Inheritance, Multi-Level Inheritance, Multiple Inheritance, Hierarchical Inheritance, and Hybrid Inheritance.)

30. Python Polymorphism

(Python Object Oriented Programming – Polymorphism, What is Polymorphism?, Types of Polymorphism in Python, Compile Time Polymorphism (Method Overloading), Run Time Polymorphism (Method Overriding), Polymorphism with class methods, and Polymorphism with Inheritance)

31. Python Abstraction

(What is Abstraction?, hiding the implementation details and only showing the essential features of the object, Abstraction in Python is achieved by using abstract classes and interfaces.)

32. Python Encapsulation

(Encapsulation is one of the fundamental concepts in object-oriented programming (OOP). It describes the idea of wrapping data and the methods that work on data within one unit. Python is an interpreted programming language and implements weak encapsulation.)

33. Database Access

(For database programming, Python supports many database serversMySQL, Oracle, PostgreSQL, SQLite, Sybase, Microsoft SQL Server, mSQL, Microsoft Access, and many more. It alssupports Data Query Statements, Data Definition Language (DDL), and Data Manipulation Language (DML). The standard database interface for Python is Python DB-API. In CodeSquadz MySql/MongoDb)

34. Python Multithreading

(What is a Thread in Computer Science? What is multithreading in Computer Science? Advantages of Multithreading, Disadvantages of Multithreading, and Python Multithreading Modules.)

35. Python Networking Programming

(Python plays an essential role in network programming. The standard library of Python has full support for network protocols, encoding, and decoding of data and other networking concepts. What Are Sockets?)

36. Python GUI Programming

(GUI Programming in Python, Python has a huge number of GUI frameworks (or toolkits) available for it, from TkInter (traditionally bundled with Python, using Tk) ta number of other cross-platform solutions, as well as bindings to platform-specific (also known as “native”) technologies.)

37. Python Advance Concept

• Some More Component like Generator, Iterator, Closure and Decorator

DJANGO

How to install Django

• Install Python
• Get your database running
• Install the Django code

Models and databases

• Models
• Making queries
• Aggregation
• Search
• Managers
• Performing raw SQL queries
• Database transactions
• Multiple databases
• Tablespaces
• Database access optimization
• Database instrumentation
• Examples of model relationship API usage

Handling HTTP requests

• URL dispatcher
• Writing views
• View decorators
• File Uploads
• Django shortcut functions
• Generic views
• Middleware
• How to use sessions

Working with forms

• HTML forms
• Django’s role in forms
• Forms in Django
• Building a form
• More about Django Form classes
• Working with form templates
• Further topics

Templates

• The Django template language
• Support for template engines

Class-based views

• Introduction to class-based views
• Built-in class-based generic views
• Form handling with class-based views
• Using mixins with class-based views
• Basic examples
• Usage in your URLconf
• Sub classing generic views
• Asynchronous class-based views

Migrations

• The Commands
• Backend Support
• Workflow
• Transactions
• Dependencies
• Migration files
• Adding migrations to apps
• Reversing migrations
• Historical models
• Considerations when removing model fields
• Data Migrations
• Squashing migrations
• Serializing values
• Supporting multiple Django versions

Managing files

• Using files in models
• The File object
• File storage

Testing in Django

• Writing and running tests
• Testing tools
• Advanced testing topics

User authentication in Django

• Overview
• Installation
• Usage

Django’s cache framework

• Setting up the cache
• The per-site cache
• The per-view cache
• Template fragment caching
• The low-level cache API
• Asynchronous support
• Downstream caches
• Using Vary headers
• Controlling cache: Using other headers
• Order of MIDDLEWARE

Conditional View Processing

• The condition decorator
• Shortcuts for only computing one value
• Using the decorators with other HTTP methods
• Comparison with middleware conditional processing

Cryptographic signing

• Protecting SECRET_KEY and SECRET_KEY_FALLBACKS
• Using the low-level API

Sending email

• Quick example
• send_mail()
• send_mass_mail()
• mail_admins()
• mail_managers()
• Examples
• Preventing header injection
• The EmailMessage class
• Email backends
• Configuring email for development

Internationalization and localization

• Overview
• Definitions

Logging

• Overview
• Security implications
• Configuring logging

Pagination

• The Paginator class
• Example
• Paginating a ListView
• Using Paginator in a view function

Security in Django

• Cross site scripting (XSS) protection
• Cross site request forgery (CSRF) protection
• SQL injection protection
• Clickjacking protection
• SSL/HTTPS
• Host header validation
• Referrer policy
• Cross-origin opener policy
• Session security
• User-uploaded content
• Additional security topics

Performance and optimization

• Introduction
• General approaches
• Caching
• Understanding laziness
• Databases
• HTTP performance
• Template performance
• Using different versions of available software

Serializing Django objects

• Serializing data
• Deserializing data
• Serialization formats
• Natural keys

Djangsettings

• The basics
• Designating the settings
• Default settings
• Using settings in Python code
• Altering settings at runtime
• Security
• Available settings
• Creating your own settings
• Using settings without setting DJANGO_SETTINGS_MODULE

Signals

• Listening to signals
• Defining and sending signals
• Disconnecting signals

System check framework

• Writing your own checks

External packages

• Localflavor
• Comments
• Formtools

Asynchronous support

• Async views
• Async safety
• Async adapter functions