Intermediate Python 3.x Training in Fountain Valley
 
                    Enroll in or hire us to teach our Intermediate Python 3.x class in Fountain Valley,  California 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.  
                    
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                	 We offer private customized training for groups of 3 or more attendees.
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| 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 | 
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                    Gain insight and ideas from students with different perspectives and experiences.
                    - RED HAT ENTERPRISE LINUX SYSTEMS ADMIN I 
 3 November, 2025 - 7 November, 2025
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 15 December, 2025 - 19 December, 2025
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Python Programming Uses & Stats
Python Programming is Used For:
	            			Web Development
	            			Video Games 
	            			Desktop GUI's 
	            			Software Development
	            		| Difficulty | Popularity | Year Created1991 | 
| 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 |   Job Count |   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 | 






