Online training of Advanced Python Programming

Advanced Python Programming

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Online training of Advanced Python Programming
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Course Details

Duration: 40 hours Effort:8 hours per week

Price With GST: ₹17700/-

Subject: Level: Beginner
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About this course

It is important to underline that this chapter is purely about the language itself about features supported through special syntax complemented by functionality of the Python stdlib, which could not be implemented through clever external modules.
The process of developing the Python programming language, its syntax, is very transparent; proposed changes are evaluated from various angles and discussed via Python Enhancement Proposals PEPs. As a result, features described in this chapter were added after it was shown that they indeed solve real problems and that their use is as simple as possible. Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.
Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.
Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault.
Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. Python Overview, History of Python, Python Features, Advanced Python

What you'll learn

Lesson 1: Python Refresher 1.Data types 2.Sequences 3.Mapping types 4.Program structure 5.Files and console I/O 6.Conditionals 7.Loops 8.Built-ins

Lesson 2: OS Services 1.OS module 2.Environment variables 3.Launching external commands 4.Walking directory trees 5.Paths, directories, and filenames 6.Working with file systems 7.Dates and time

Lesson 3: Pythonic Programming 1.The Zen of Python 2.Common idioms 3.Lambda functions 4.List comprehensions 5.Generator expressions 6.String formatting

Lesson 4: Modules and packages 1.Initialization code 2.Namespaces 3.Executing modules as scripts 4.Documentation 5.Packages and name resolution 6.Naming conventions 7.Using imports

Lesson 5: Classes 1.Defining classes 2.Instance methods and data 3.Initializers 4.Class methods 5.Static methods 6.Inheritance 7.Multiple inheritance 8.Pseudo-private variable

Lesson 6: Meta Programming 1.Implicit properties 2.Globals() and Locals() 3.Attributes 4.The inspect module 5.Decorators 6.Monkey patching

Lesson 7: Programmer tools 1.Analyzing programs 2.Using pylint 3.Testing code 4.Using unittest 5.Debugging 6.Profiling

Lesson 8: Distributing modules 1.Distribution concepts 2.setuptools 3.creating 4.building installers 5.running installers

Lesson 9: Database access 1.The DB API 2.Available Interfaces 3.Connecting to a server 4.Creating and executing a cursor 5.Fetching data 6.Parameterized statements 7.Metadata 8.Transaction control ?

Lesson 10: GUI Programming 1.Overview 2.The mainwindow object 3.Widgets 4.Colors and fonts 5.GUI layout 6.Event handling

Lesson 11: Network Programming 1.Sockets 2.Clients 3.Servers 4.Application protocols 5.Forking servers 6.Threaded servers 7.Binary data 8.The struct module

Lesson 12: Threads 1.Why use threads? 2.Threads are different 3.Variables are shared 4.Python threads modules 5.The threading module 6.The queue module 7.The python thread manager 8.Debugging threaded programs

Lesson 13: XML and JSON 1.Working with XML 2.DOM and SAX 3.Introducing ElementTree 4.Parsing XML 5.Navigating the document 6.Creating a new XML document 7.JSON 8.Parsing JSON into Python 9.Converting Python into JSON

Lesson 14: Extending Python ? 1.About non-Python modules 2.Overview of a C extension 3.Creating functions 4.Registering functions 5.Initialization code 6.Loading the module 7.

Lesson 15: Using the sh module 8.The sh namespace 9.Running a simple command 10.Keyword arguments 11.Running commands in the background 12.Piping and redirection 13.Working with STDIN 14.Exit codes 15.Advanced features

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