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Python Course Online at Greatonlinetraining





 
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About The Course:-

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

Who should go for this course?

Experienced Professional or a Beginner, Anyone who wants to learn programming with Python can start right away!

Pre-requisites

Although there are no hard pre-requisites, attendees having prior programming experience and familiarity with basic concepts such as variables/scopes, flow-control, and functions would be beneficial. Prior exposure to object-oriented programming concepts is not required, but definitely beneficial.

Course Objectives:-

The Course goes with the aim to understand key concepts about:

  • After the completion of the course, you should be able to:
    • Introduction to Python & Python Fundamentals
    • Python Basics
    • Python Control Structures
    • Functions
    • Modules
    • I/O & Exception handling
    • Regular Expressions
    • OOPs in Python
    • Standard libraries
    • Database Programming
    • Threads
    • Web Programming
    • Django web framework

1 A Python Q&A Session
Why Do People Use Python?
Software Quality
Developer Productivity
Is Python a “Scripting Language”?
OK, but What’s the Downside?
Who Uses Python Today?
What Can I Do with Python?
Systems Programming
GUIs
Internet Scripting
Component Integration
Database Programming
Rapid Prototyping
Numeric and Scientific Programming
And More: Gaming, Images, Data Mining, Robots, Excel
How Is Python Developed and Supported?
Open Source Tradeoffs
What Are Python’s Technical Strengths?
It’s Object-Oriented and Functional
It’s Free
It’s Portable
It’s Powerful
It’s Mixable
It’s Relatively Easy to Use
It’s Relatively Easy to Learn
It’s Named After Monty Python
How Does Python Stack Up to Language X?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

2 How Python Runs Programs
Introducing the Python Interpreter
Program Execution
The Programmer’s View
Python’s View
Execution Model Variations
Python Implementation Alternatives
Execution Optimization Tools
Frozen Binaries
Future Possibilities?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

3 How You Run Programs
The Interactive Prompt
Starting an Interactive Session
The System Path
New Windows Options in : PATH, Launcher
Where to Run: Code Directories
What Not to Type: Prompts and Comments
Running Code Interactively
Why the Interactive Prompt?
Usage Notes: The Interactive Prompt
System Command Lines and Files
A First Script
Running Files with Command Lines
Command-Line Usage Variations
Usage Notes: Command Lines and Files
Unix-Style Executable Scripts: #!
Unix Script Basics
The Unix env Lookup Trick
The Python Windows Launcher: #! Comes to Windows
Clicking File Icons
Icon-Click Basics
Clicking Icons on Windows
The input Trick on Windows
Other Icon-Click Limitations
Module Imports and Reloads
Import and Reload Basics
The Grander Module Story: Attributes
Usage Notes: import and reload
Using exec to Run Module Files
The IDLE User Interface
IDLE Startup Details
IDLE Basic Usage
IDLE Usability Features
Advanced IDLE Tools
Usage Notes: IDLE
Other IDEs
Other Launch Options
Embedding Calls
Frozen Binary Executables
Text Editor Launch Options
Still Other Launch Options
Future Possibilities?
Which Option Should I Use?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part I Exercises
Part II Types and Operations

4 Introducing Python Object Types
The Python Conceptual Hierarchy
Why Use Built-in Types?
Python’s Core Data Types
Numbers
Strings
Sequence Operations
Immutability
Type-Specific Methods
Getting Help
Other Ways to Code Strings
Unicode Strings
Pattern Matching
Lists
Sequence Operations
Type-Specific Operations
Bounds Checking
Nesting
Comprehensions
Dictionaries
Mapping Operations
Nesting Revisited
Missing Keys: if Tests
Sorting Keys: for Loops
Iteration and Optimization
Tuples
Why Tuples?
Files
Binary Bytes Files
Unicode Text Files
Other File-Like Tools
Other Core Types
How to Break Your Code’s Flexibility
User-Defined Classes
And Everything Else
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

5 Numeric Types
Numeric Type Basics
Numeric Literals
Built-in Numeric Tools
Python Expression Operators
Numbers in Action
Variables and Basic Expressions
Numeric Display Formats
Comparisons: Normal and Chained
Division: Classic, Floor, and True
Integer Precision
Complex Numbers
Hex, Octal, Binary: Literals and Conversions
Bitwise Operations
Other Built-in Numeric Tools
Other Numeric Types
Decimal Type
Fraction Type
Sets
Booleans
Numeric Extensions
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

6 The Dynamic Typing Interlude
The Case of the Missing Declaration Statements
Variables, Objects, and References
Types Live with Objects, Not Variables
Objects Are Garbage-Collected
Shared References
Shared References and In-Place Changes
Shared References and Equality
Dynamic Typing Is Everywhere
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

7 String Fundamentals
This Chapter’s Scope
Unicode: The Short Story
String Basics
String Literals
Single- and Double-Quoted Strings Are the Same
Escape Sequences Represent Special Characters
Raw Strings Suppress Escapes
Triple Quotes Code Multiline Block Strings
Strings in Action
Basic Operations
Indexing and Slicing
String Conversion Tools
Changing Strings I
String Methods
Method Call Syntax
Methods of Strings
String Method Examples: Changing Strings II
String Method Examples: Parsing Text
Other Common String Methods in Action
The Original string Module’s Functions (Gone in X)
String Formatting Expressions
Formatting Expression Basics
Advanced Formatting Expression Syntax
Advanced Formatting Expression Examples
Dictionary-Based Formatting Expressions
String Formatting Method Calls
Formatting Method Basics
Adding Keys, Attributes, and Offsets
Advanced Formatting Method Syntax
Advanced Formatting Method Examples
Comparison to the % Formatting Expression
Why the Format Method?
General Type Categories
Types Share Operation Sets by Categories
Mutable Types Can Be Changed in Place
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

8 Lists and Dictionaries
Lists
Lists in Action
Basic List Operations
List Iteration and Comprehensions
Indexing, Slicing, and Matrixes
Changing Lists in Place
Dictionaries
Dictionaries in Action
Basic Dictionary Operations
Changing Dictionaries in Place
More Dictionary Methods
Example: Movie Database
Dictionary Usage Notes
Other Ways to Make Dictionaries
Dictionary Changes in Python X and
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

9 Tuples, Files, and Everything Else
Tuples
Tuples in Action
Why Lists and Tuples?
Records Revisited: Named Tuples
Files
Opening Files
Using Files
Files in Action
Text and Binary Files: The Short Story
Storing Python Objects in Files: Conversions
Storing Native Python Objects: pickle
Storing Python Objects in JSON Format
Storing Packed Binary Data: struct
File Context Managers
Other File Tools
Core Types Review and Summary
Object Flexibility
References Versus Copies
Comparisons, Equality, and Truth
The Meaning of True and False in Python
Python’s Type Hierarchies
Type Objects
Other Types in Python
Built-in Type Gotchas
Assignment Creates References, Not Copies
Repetition Adds One Level Deep
Beware of Cyclic Data Structures
Immutable Types Can’t Be Changed in Place
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part II Exercises
Part III Statements and Syntax

10 Introducing Python Statements
The Python Conceptual Hierarchy Revisited
Python’s Statements
A Tale of Two ifs
What Python Adds
What Python Removes
Why Indentation Syntax?
A Few Special Cases
A Quick Example: Interactive Loops
A Simple Interactive Loop
Doing Math on User Inputs
Handling Errors by Testing Inputs
Handling Errors with try Statements
Nesting Code Three Levels Deep
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

11 Assignments, Expressions, and Prints
Assignment Statements
Assignment Statement Forms
Sequence Assignments
Extended Sequence Unpacking in Python X
Multiple-Target Assignments
Augmented Assignments
Variable Name Rules
Expression Statements
Expression Statements and In-Place Changes
Print Operations
The Python X print Function
The Python X print Statement
Print Stream Redirection
Version-Neutral Printing
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

12 if Tests and Syntax Rules
if Statements
General Format
Basic Examples
Multiway Branching
Python Syntax Revisited
Block Delimiters: Indentation Rules
Statement Delimiters: Lines and Continuations
A Few Special Cases
Truth Values and Boolean Tests
The if/else Ternary Expression
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

13 while and for Loops
while Loops
General Format
Examples
break, continue, pass, and the Loop else
General Loop Format
pass
continue
break
Loop else
for Loops
General Format
Examples
Loop Coding Techniques
Counter Loops: range
Sequence Scans: while and range Versus for
Sequence Shufflers: range and len
Nonexhaustive Traversals: range Versus Slices
Changing Lists: range Versus Comprehensions
Parallel Traversals: zip and map
Generating Both Offsets and Items: enumerate
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

14 Iterations and Comprehensions
Iterations: A First Look
The Iteration Protocol: File Iterators
Manual Iteration: iter and next
Other Built-in Type Iterables
List Comprehensions: A First Detailed Look
List Comprehension Basics
Using List Comprehensions on Files
Extended List Comprehension Syntax
Other Iteration Contexts
New Iterables in Python X
Impacts on X Code: Pros and Cons
The range Iterable
The map, zip, and filter Iterables
Multiple Versus Single Pass Iterators
Dictionary View Iterables
Other Iteration Topics
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

15 The Documentation Interlude
Python Documentation Sources
# Comments
The dir Function
Docstrings: __doc__
PyDoc: The help Function
PyDoc: HTML Reports
Beyond docstrings: Sphinx
The Standard Manual Set
Web Resources
Published Books
Common Coding Gotchas
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part III Exercises
Part IV Functions and Generators

16 Function Basics
Why Use Functions?
Coding Functions
def Statements
def Executes at Runtime
A First Example: Definitions and Calls
Definition
Calls
Polymorphism in Python
A Second Example: Intersecting Sequences
Definition
Calls
Polymorphism Revisited
Local Variables
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

17 Scopes
Python Scope Basics
Scope Details
Name Resolution: The LEGB Rule
Scope Example
The Built-in Scope
The global Statement
Program Design: Minimize Global Variables
Program Design: Minimize Cross-File Changes
Other Ways to Access Globals
Scopes and Nested Functions
Nested Scope Details
Nested Scope Examples
Factory Functions: Closures
Retaining Enclosing Scope State with Defaults
The nonlocal Statement in X
nonlocal Basics
nonlocal in Action
Why nonlocal? State Retention Options
State with nonlocal: X only
State with Globals: A Single Copy Only
State with Classes: Explicit Attributes (Preview)
State with Function Attributes: X and X
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

18 Arguments
Argument-Passing Basics
Arguments and Shared References
Avoiding Mutable Argument Changes
Simulating Output Parameters and Multiple Results
Special Argument-Matching Modes
Argument Matching Basics
Argument Matching Syntax
The Gritty Details
Keyword and Default Examples
Arbitrary Arguments Examples
Python X Keyword-Only Arguments
The min Wakeup Call!
Full Credit
Bonus Points
The Punch Line
Generalized Set Functions
Emulating the Python X print Function
Using Keyword-Only Arguments
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

19 Advanced Function Topics
Function Design Concepts
Recursive Functions
Summation with Recursion
Coding Alternatives
Loop Statements Versus Recursion
Handling Arbitrary Structures
Function Objects: Attributes and Annotations
Indirect Function Calls: “First Class” Objects
Function Introspection
Function Attributes
Function Annotations in X
Anonymous Functions: lambda
lambda Basics
Why Use lambda?
How (Not) to Obfuscate Your Python Code
Scopes: lambdas Can Be Nested Too
Functional Programming Tools
Mapping Functions over Iterables: map
Selecting Items in Iterables: filter
Combining Items in Iterables: reduce
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

20 Comprehensions and Generations
List Comprehensions and Functional Tools
List Comprehensions Versus map
Adding Tests and Nested Loops: filter
Example: List Comprehensions and Matrixes
Don’t Abuse List Comprehensions: KISS
Generator Functions and Expressions
Generator Functions: yield Versus return
Generator Expressions: Iterables Meet Comprehensions
Generator Functions Versus Generator Expressions
Generators Are Single-Iteration Objects
Generation in Built-in Types, Tools, and Classes
Example: Generating Scrambled Sequences
Don’t Abuse Generators: EIBTI
Example: Emulating zip and map with Iteration Tools
Comprehension Syntax Summary
Scopes and Comprehension Variables
Comprehending Set and Dictionary Comprehensions
Extended Comprehension Syntax for Sets and Dictionaries
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

21 The Benchmarking Interlude
Timing Iteration Alternatives
Timing Module: Homegrown
Timing Script
Timing Results
Timing Module Alternatives
Other Suggestions
Timing Iterations and Pythons with timeit
Basic timeit Usage
Benchmark Module and Script: timeit
Benchmark Script Results
More Fun with Benchmarks
Other Benchmarking Topics: pystones
Function Gotchas
Local Names Are Detected Statically
Defaults and Mutable Objects
Functions Without returns
Miscellaneous Function Gotchas
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part IV Exercises
Part V Modules and Packages

22 Modules: The Big Picture
Why Use Modules?
Python Program Architecture
How to Structure a Program
Imports and Attributes
Standard Library Modules
How Imports Work
Find It
Compile It (Maybe)
Run It
Byte Code Files: __pycache__ in Python +
Byte Code File Models in Action
The Module Search Path
Configuring the Search Path
Search Path Variations
The syspath List
Module File Selection
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

23 Module Coding Basics
Module Creation
Module Filenames
Other Kinds of Modules
Module Usage
The import Statement
The from Statement
The from * Statement
Imports Happen Only Once
import and from Are Assignments
import and from Equivalence
Potential Pitfalls of the from Statement
Module Namespaces
Files Generate Namespaces
Namespace Dictionaries: __dict__
Attribute Name Qualification
Imports Versus Scopes
Namespace Nesting
Reloading Modules
reload Basics
reload Example
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

24 Module Packages
Package Import Basics
Packages and Search Path Settings
Package __init__py Files
Package Import Example
from Versus import with Packages
Why Use Package Imports?
A Tale of Three Systems
Package Relative Imports
Changes in Python X
Relative Import Basics
Why Relative Imports?
The Scope of Relative Imports
Module Lookup Rules Summary
Relative Imports in Action
Pitfalls of Package-Relative Imports: Mixed Use
Python Namespace Packages
Namespace Package Semantics
Impacts on Regular Packages: Optional __init__py
Namespace Packages in Action
Namespace Package Nesting
Files Still Have Precedence over Directories
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

25 Advanced Module Topics
Module Design Concepts
Data Hiding in Modules
Minimizing from * Damage: _X and __all__
Enabling Future Language Features: __future__
Mixed Usage Modes: __name__ and __main__
Unit Tests with __name__
Example: Dual Mode Code
Currency Symbols: Unicode in Action
Docstrings: Module Documentation at Work
Changing the Module Search Path
The as Extension for import and from
Example: Modules Are Objects
Importing Modules by Name String
Running Code Strings
Direct Calls: Two Options
Example: Transitive Module Reloads
A Recursive Reloader
Alternative Codings
Module Gotchas
Module Name Clashes: Package and Package-Relative Imports
Statement Order Matters in Top-Level Code
from Copies Names but Doesn’t Link
from * Can Obscure the Meaning of Variables
reload May Not Impact from Imports
reload, from, and Interactive Testing
Recursive from Imports May Not Work
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part V Exercises
Part VI Classes and OOP

26 OOP: The Big Picture
Why Use Classes?
OOP from , Feet
Attribute Inheritance Search
Classes and Instances
Method Calls
Coding Class Trees
Operator Overloading
OOP Is About Code Reuse
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

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