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Advanced Python Programming

Course Code: 1178
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$2495

Overview

This comprehensive advanced-level course on Python programming involves hands-on lab exercises, engaging lectures, demos and activities to ensure participants get a thorough understanding of the concepts being discussed. The course leads participants through a series of progressively advanced topics such as OS services, modules, unit tests, databases, XML data, packages, meta programming, network programming, threads, etc. The course is a skill-centric course, focusing on helping participants master advanced Python and web development skills, the latest techniques and coding practices. The course does not cover Python fundamentals.

Schedule Classes

Delivery Format
Starting Date
Starting Time
Duration

Live Classroom
Monday, 16 November 2020
10:00 AM - 6:00 PM EST
4 Days

$2495 Add to cart

Delivery Format
Starting Date
Starting Time
Duration

Live Classroom
Monday, 14 December 2020
10:00 AM - 6:00 PM EST
4 Days

$2495 Add to cart

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 5 days

Live Virtual Classroom
Duration: 5 days

What You'll learn

  • Leverage OS services
  • Code graphical interfaces for applications
  • Build modules
  • Create and run unit tests
  • Define classes
  • Working with network services
  • Query databases
  • Handle XML data

Outline

  • Data types
  • Sequences
  • Mapping types
  • Program structure
  • File and console I/O
  • Conditionals
  • Loops
  • Built-ins
  • The OS module
  • Environment variables
  • Launching external commands
  • Walking directory trees
  • Paths, directories and file names
  • Working with file systems
  • Dates and times
  • Basic date and time classes
  • Different time formats
  • Converting between formats
  • Formatting dates and times
  • Parsing date/time information
  • What is Binary Data?
  • Binary vs text
  • Using the Struct module
  • The Zen of Python
  • Common idioms
  • Lambda functions
  • List comprehensions
  • Generator expressions
  • String formatting
  • Four types of function parameters
  • Four levels of name scoping
  • Single/multi dispatch
  • Relative imports
  • Using __init__ effectively
  • Documentation best practices
  • Implicit properties
  • Globals() and locals()
  • Working with attributes
  • The inspect module
  • Decorators
  • Monkey patching
  • Class/static data and methods
  • Inheritance (or composition)
  • Abstract base classes
  • Implementing protocols (context, iterator, etc.) with special methods
  • Implicit properties
  • globals() and locals()
  • Working with object attributes
  • The inspect module
  • Callable classes
  • Decorators
  • Monkey patching
  • Analyzing programs with pylint
  • Using the debugger
  • Profiling code
  • Testing speed with benchmarking
  • What is a unit test?
  • Writing tests
  • Working with fixtures
  • Test runners
  • Mocking resources
  • The DB API
  • Available Interfaces
  • Connecting to a server
  • Creating and executing a cursor
  • Fetching data
  • Parameterized statements
  • Using Metadata
  • Transaction control
  • ORMs and NoSQL overview
  • Overview
  • Qt Architecture
  • Using designer
  • Standard widgets
  • Event handling
  • Extras
  • Builtin classes
  • Using requests
  • Grabbing web pages
  • Sending email
  • Working with binary data
  • Consuming RESTful services
  • Remote access (SSH)
  • The threading module
  • Sharing variables
  • The queue module
  • The multiprocessing module
  • Creating pools
  • About async programming
  • Running external programs
  • Parsing arguments
  • Creating filters to read text files
  • Logging
  • Working with XML
  • XML modules in Python
  • Getting started with ElementTree
  • Parsing XML
  • Updating an XML tree
  • Creating a new document
  • About JSON
  • Reading JSON
  • Writing JSON
  • Reading/writing CSV files
  • YAML, other formats as time permits
  • Discover the collections module
  • Use defaultdict, Counter, and namedtuple
  • Create dataclasses
  • Store data offline with pickle
  • Annotate variables
  • Learn what type hinting does NOT do
  • Use the typing module for detailed type hints
  • Understand union and optional types
  • Write stub interfaces
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Prerequisites

Participants need to have basic incoming practical experience working with Python, along with a working user-level knowledge of Unix/Linux, Mac or Windows. Participants also need to be trained or have equivalent practical skills in “Introduction to Basic Python Programming”, “Essential Python Programming” and “Mastering Python Programming”.

Who Should Attend

This is an intermediate to advanced level course and is highly recommended for –

  • Software developers
  • Back-end developers
  • Software engineers
  • Programmers
  • System administrators

Interested in this course? Let’s connect!