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Advanced Python

Currently Python is one of the most popular programming language in the IT domain, and has become the first pick in many domains like web development, Cloud computing, software testing any mobile testing among many other. Because of its unique and versatile features that allow developers to code less, organizations and programmers have been trying to master it to build applications for mobile, web, and GUI. Python has surpassed Java as the top language used and there is huge demand for individuals who have mastered Python. IIHT’s in-depth Python training programme exposes candidates to the essentials of Object-Oriented Programming, debugging Python programs, organizing Python codes into packages, Python thread, and advanced packaging options. The training course will ensure that candidates receive hands-on development experience and prepare them to be experts in Python programming.
6 Days
08 Apr To 13 Apr 2019
19:30 - 22:30 (Online)
INR 14999(Amount Exclusive of all taxes and 18% GST)
Enroll Now

Build and package Python modules to allow code re-usability

Design object‐oriented programs with Python

Learn how the Python interpreter executes programs and properties of the global interpreter lock (GIL).

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We recommend that attendees of this course have the following prerequisites:

  • Basic concepts of OOPS

Course Content

Python Review

  • A brief review of Python basics including syntax, core datatypes, file I/O, functions, error handling, and classes.

Classes and Objects

  • An introduction to creating and using user-defined objects in Python.
  • Describes how to use the class statement to create new objects and presents details on various special methods that can be defined to customize object behavior.
  • Commonly used object oriented programming techniques are also presented.

Advanced I/O Handling

  • An in-depth examination of the Python I/O system including text handling, binary data handling, and different I/O models such as blocking, non-blocking, and event-driven I/O.

Idiomatic Data Handling

  • An introduction to various tools and techniques for effective data processing. o Discusses different options for creating data structures and gives an inside look at how the built-in datatypes are put together along with their performance and memory usage properties.
  • Participants will learn how to apply list, set, and dictionary comprehensions to various problems in data handling.

Inside the Python Object Model

  • A detailed tour of how the Python object system is implemented.
  • Topics include the definition of objects, object representation, attribute binding, inheritance, descriptors, properties, slots, private attributes, static methods, and class methods.
  • Cover important details concerning Python memory management and garbage collection.

Testing, Debugging and Logging

  • Coverage of how to test and debug Python programs with a focus on three major topics.
  • First, testing Python programs with the doctest and unittest modules is described.
  • Next, the Python Debugger and profiler are presented. o Finally, the logging package is described.

Packages and Distribution

  • How to organize Python code into packages and how to distribute packages to users and programmers.
  • Covers the underlying mechanics of how packages are put together and the distutils module for creating distributions.
  • Also covers more advanced packaging options such as Distribute and setuptools.

Iterators, Generators, Coroutines

  • The section starts with a description of the iteration protocol and moves on to practical use of generators and coroutines.
  • A major focus on this section is on the use of generators and coroutines to set up processing pipelines, much like pipes in Unix programming.
  • You will see how generators and coroutines can lead to very elegant programming abstractions for processing data and how such programs can be used to process huge datafiles and streaming I/O.

Functional Programming

  • Advanced details of how to program with functions in Python.
  • Discusses more advanced features of functions including variadic parameters, nested functions, closures, lazy evaluation, anonymousfunctions (lambda), and function attributes.


  • Loosely defined, metaprogramming refers to programs that are able to manipulate their own program structure (functions, classes, etc.) or the structure of other programs as data.
  • This section introduces and covers practical examples of Python’s metaprogramming features including function decorators, class decorators, metaclasses, and context managers.
  • A major emphasis of this section is to understand how advanced programming frameworks utilize these features to provide a richer programming environment for their end users.

Extension Programming

  • How to create C and C++ extensions to Python. Covers the absolute basics of the Python C API followed by some details on using the ctypes library and Swig code generator.
  • A major focus of this section is on how to organize extension code so that it can more seamlessly integrate with the Python environment.
  • Topics include memory management, data handling, encapsulation, and common pitfalls.

Concurrent Programming with Threads

  • An introduction to programming with Python threads.
  • Starts with the basics of using the threading library and dives into a variety of more advanced topics including a survey of how and when to use the different thread synchronization primitives, queues, deadlock avoidance, and thread debugging.
  • Also includes detailed information on how the Python interpreter executes programs and properties of the global interpreter lock (GIL).


  • An introduction to the multiprocessing library that allows programs to distribute their work across independent processes or machines.
  • Covers processes, queues, pipes, connections and process pools.