HARTMANN software group

Intermediate Python 3.x Training in Lafayette

Enroll in or hire us to teach our Intermediate Python 3.x class in Lafayette, Indiana by calling us @303.377.6176. Like all HSG classes, Intermediate Python 3.x may be offered either onsite or via instructor led virtual training. Consider looking at our public training schedule to see if it is scheduled: Public Training Classes
Provided there are enough attendees, Intermediate Python 3.x may be taught at one of our local training facilities.
We offer private customized training for groups of 3 or more attendees.
get pricing information

Course Description

  
This 4 day course picks up where Introduction to Python 3 leaves off, covering some topics in more detail, and adding many new ones, with a focus on enterprise development. This is a hands-on programming class. All concepts are reinforced by informal practice during the lecture followed by lab exercises. Many labs build on earlier labs, which helps students retain the earlier material.
Course Length: 4 Days
Course Tuition: $1290 (US)

Prerequisites
All students should be able to write simple Python scripts, using basic data types, program structures, and the standard Python library.

Course Outline

  
Python Refresher
Variables
Basic Python Data Types
Sequences
Mapping Types
Program Structure
Files And Console I/O
Conditionals
Loops
Builtins
 
OS Services
The OS Module
Paths, Directories, and Filenames
Environment Variables
Launching External Programs
Walking Directory Trees
The Datetime Module
The Calendar Module
 
Pythonic Programming
The Zen of Python
Common Python Idioms
Unpacking Function Arguments
Lambda Functions
List Comprehensions
Iterables
Writing Generators
String Tricks
String Formatting
 
Modules
Using Import
Module Search Path
Namespaces
Executing Modules as Scripts
Packages
Confguring Import With __Init__.Py
Name Resolution (AKA Scope)
Python Style
 
Classes
Defning Classes
Instance Objects
Instance Attributes
Instance Methods
__Init__
Properties
Class Data
Class Methods
Inheritance
Multiple Inheritance
Using Super ()
Special Methods
Class-Private Variables
Static Methods
 
Metaprogramming
Globals() and Locals()
Working with Attributes
The Inspect Module
Decorator Functions
Decorator Classes
Decorator Parameters
Creating Classes At Runtime
Monkey Patching
 
Developer Tools
Program Development
Comments
Pylint
Customizing Pylint
Using Pyreverse
The Unittest Module
Fixtures
Skipping Tests
Making a Suite of Tests
Automated Test Discovery
Using Nose
The Python Debugger
Starting Debug Mode
Stepping Through a Program
Setting Breakpoints
Profling
Benchmarking
 
Database access
The DB API
Available Interfaces
Connecting to a server
connect() examples
Creating a cursor
Executing a statement
Parameterized statements
Dictionary cursors
Metadata
Transactions
Object-relational mappers
 
PyQt4
Event Driven Applications
Gui Application Flow Chart
External Anatomy of a Pyqt4 Application
Internal Anatomy of a Pyqt4 Application
Using Designer
Anatomy of a Designer-Based Application
Naming Conventions
Common Widgets
Layouts
Selectable Buttons
Actions and Events
Menu Bar
Status Bar
Using Predefned Dialogs
Creating Custom Dialogs
Tabs
Niceties
Working with Images
Complete Example
 
Network Programming
Sockets
Socket Options
Client Concepts
Server Concepts
Application Protocols
Forking Servers
Grabbing Html from The Web
Consuming Web Services
Web Data the Easier Way
Sending Email
Binary Data
The Struct Module
 
Multiprogramming
What Are Threads?
The Python Thread Manager
The Threading Module
Threads for the Impatient
Creating a Thread Class
Variables Sharing
Using Queues
Debugging Threaded Programs
The Multiprocessing Module
Alternatives to Multiprogramming
 
System Administration and Scripting
The Subprocess Module
Subprocess Convenience Functions
Using the Sh Module
Permissions
Saving Information
Creating a Useful Command Line Script
Creating Filters
Parsing the Command Line
Simple Logging
Logging Levels
Formatting Log Entries
Logging to Other Destinations
 
XML and JSON
About Xml
Normal Approaches to Xml
Which Module to Use?
Getting Started With ElementTree
How ElementTree Works
Creating a New Xml Document
Parsing an Xml Document
Navigating the Xml Document
Using XPath
Advanced XPath
About JSON
Reading JSON
Writing JSON
 
Extending Python with C
Why Extend Python?
Ways to Extend Python With C
Hand-Coded C
Overview
The C Program
Methods
The Method Table
The Init Function
Handling Errors
Custom Exception Objects
Putting It All Together
Using SWIG
The Interface Fle
Generating the Wrappers
Building and Installing The Extension
Ctypes
For More Information
 
Appendix A: Python Books
Appendix B: Python Gotchas

Course Directory [training on all levels]

Technical Training Courses
Software engineer/architect, System Admin ... Welcome!
Business Training Courses
Project Managers, Business Analysts, Paralegals ... Welcome!
Upcoming Classes
Gain insight and ideas from students with different perspectives and experiences.

Python Programming Uses & Stats

Python Programming is Used For:
Web Development Video Games Desktop GUI's Software Development
Difficulty
Popularity
Year Created
1991
Pros
Easy to Learn:
The learning curve is very mild and the language is versatile and fast to develop.
 
Massive Libraries:
You can find a library for basically anything: from web development, through game development, to machine learning.
 
Do More with Less Code:
You can build prototypes and test out  ideas much quicker in Python than in other language
Cons

Speed Limitations:

It is an interpretive language and therefore much slower than compiled languages.

Problems with Threading:

Multi-threaded CPU-bound programs may be slower than single-threaded ones do to the Global Interpreter Lock (GIL) that allows only one thread to execute at a time.

Weak on Mobile:

Although, there are a number or libraries that provide a way to develop for both Android and iOS using Python currently Android and iOS don’t support Python as an official programming language.
Python Programming Job Market
Average Salary
$107,000
Job Count
26,856
Top Job Locations

New York City

Mountain View

San Francisco
Complimentary Skills to have along with Python Programming
The potential for career growth, whether you are new to the industry or plan to expand your current skills, depends upon your interests:
  - For knowledge in building in PC or windows, phone apps or you are looking your future in Microsoft learn C#
  - For android apps and also cross platform apps then learn Java
  - If you are an Apple-holic and want to build iOS and MAC apps and then choose Objective C or Swift
  - Interested in game development? C++
  - Data mining or statistics then go with R programming or MATLAB
  - Building an operating systems? C

Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.