Design Patterns Training Classes in Parma, Ohio
Learn Design Patterns in Parma, Ohio and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current Design Patterns related training offerings in Parma, Ohio: Design Patterns Training
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16 December, 2024 - 17 December, 2024 - Fast Track to Java 17 and OO Development
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Blog Entries publications that: entertain, make you think, offer insight
Creating an enum in Python prior to Python 3.4 was accomplished as follows:
def enum(**enums)::
return type('Enum',(),enums)
then use as:
Animals=enum(Dog=1,Cat=2)
and accessed as:
Animals.Dog
The new version can be created as follows:
from enum import Enum
class Animal(Enum):
Dog=1
Cat=2
Writing Python in Java syntax is possible with a semi-automatic tool. Programming code translation tools pick up about 75% of dynamically typed language. Conversion of Python to a statically typed language like Java requires some manual translation. The modern Java IDE can be used to infer local variable type definitions for each class attribute and local variable.
Translation of Syntax
Both Python and Java are OO imperative languages with sizable syntax constructs. Python is larger, and more competent for functional programming concepts. Using the source translator tool, parsing of the original Python source language will allow for construction of an Abstract Source Tree (AST), followed by conversion of the AST to Java.
Python will parse itself. This capability is exhibited in the ast module, which includes skeleton classes. The latter can be expanded to parse and source each node of an AST. Extension of the ast.NodeVisitor class enables python syntax constructs to be customized using translate.py and parser.py coding structure.
The Concrete Syntax Tree (CST) for Java is based on visit to the AST. Java string templates can be output at AST nodes with visitor.py code. Comment blocks are not retained by the Python ast Parser. Conversion of Python to multi-line string constructs with the translator reduces time to script.
Scripting Python Type Inference in Java
Programmers using Python source know that the language does not contain type information. The fact that Python is a dynamic type language means object type is determined at run time. Python is also not enforced at compile time, as the source is not specified. Runtime type information of an object can be determined by inspecting the __class__.__name__ attribute.
Python’s inspect module is used for constructing profilers and debugging.
Implementation of def traceit (frame, event, arg) method in Python, and connecting it to the interpreter with sys.settrace (traceit) allows for integration of multiple events during application runtime.
Method call events prompt inspect and indexing of runtime type. Inspection of all method arguments can be conducted. By running the application profiler and exercising the code, captured trace files for each source file can be modified with the translator. Generating method syntax can be done with the translator by search and addition of type information. Results in set or returned variables disseminate the dynamic code in static taxonomy.
The final step in the Python to Java scrip integration is to administer unsupported concepts such as value object creation. There is also the task of porting library client code, for reproduction in Java equivalents. Java API stubs can be created to account for Python APIs. Once converted to Java the final clean-up of the script is far easier.
Related:
What Are The 10 Most Famous Software Programs Written in Python?
In this tutorial we are going to take a look at how you work with strings in Python. Now, any language worth its salt will have a number of options for working with text and Python is probably one of the best to use when it comes to processing text.
If you are new to programming in general you may be wondering what a string is. In terms of programming, a string is classed as any sequence of characters you can type with your keyboard, and let’s face it, if you want your application to be of any use to yourself or other users then you need it to tell you what it’s doing or to prompt you for an action, and that is where strings come into play.
They are your applications way of communicating with the user. Without the ability to enter and display text or software would be pretty useless.
So, how would you create a string in Python? Take a look at the following code:
Another blanket article about the pros and cons of Direct to Consumer (D2C) isn’t needed, I know. By now, we all know the rules for how this model enters a market: its disruption fights any given sector’s established sales model, a fuzzy compromise is temporarily met, and the lean innovator always wins out in the end.
That’s exactly how it played out in the music industry when Apple and record companies created a digital storefront in iTunes to usher music sales into the online era. What now appears to have been a stopgap compromise, iTunes was the standard model for 5-6 years until consumers realized there was no point in purchasing and owning digital media when internet speeds increased and they could listen to it for free through a music streaming service. In 2013, streaming models are the new music consumption standard. Netflix is nearly parallel in the film and TV world, though they’ve done a better job keeping it all under one roof. Apple mastered retail sales so well that the majority of Apple products, when bought in-person, are bought at an Apple store. That’s even more impressive when you consider how few Apple stores there are in the U.S. (253) compared to big box electronics stores that sell Apple products like Best Buy (1,100) Yet while some industries have implemented a D2C approach to great success, others haven’t even dipped a toe in the D2C pool, most notably the auto industry.
What got me thinking about this topic is the recent flurry of attention Tesla Motors has received for its D2C model. It all came to a head at the beginning of July when a petition on whitehouse.gov to allow Tesla to sell directly to consumers in all 50 states reached the 100,000 signatures required for administration comment. As you might imagine, many powerful car dealership owners armed with lobbyists have made a big stink about Elon Musk, Tesla’s CEO and Product Architect, choosing to sidestep the traditional supply chain and instead opting to sell directly to their customers through their website. These dealership owners say that they’re against the idea because they want to protect consumers, but the real motive is that they want to defend their right to exist (and who wouldn’t?). They essentially have a monopoly at their position in the sales process, and they want to keep it that way. More frightening for the dealerships is the possibility that once Tesla starts selling directly to consumers, so will the big three automakers, and they fear that would be the end of the road for their business. Interestingly enough, the big three flirted with the idea of D2C in the early 90’s before they were met with fierce backlash from dealerships. I’m sure the dealership community has no interest in mounting a fight like that again.
To say that the laws preventing Tesla from selling online are peripherally relevant would be a compliment. By and large, the laws the dealerships point to fall under the umbrella of “Franchise Laws” that were put in place at the dawn of car sales to protect franchisees against manufacturers opening their own stores and undercutting the franchise that had invested so much to sell the manufacturer’s cars. There’s certainly a need for those laws to exist, because no owner of a dealership selling Jeeps wants Chrysler to open their own dealership next door and sell them for substantially less. However, because Tesla is independently owned and isn’t currently selling their cars through any third party dealership, this law doesn’t really apply to them. Until their cars are sold through independent dealerships, they’re incapable of undercutting anyone by implementing D2C structure.
Tech Life in Ohio
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
Nationwide Insurance Company | Columbus | Financial Services | Insurance and Risk Management |
Owens Corning | Toledo | Manufacturing | Concrete, Glass, and Building Materials |
FirstEnergy Corp | Akron | Energy and Utilities | Gas and Electric Utilities |
The Lubrizol Corporation | Wickliffe | Manufacturing | Chemicals and Petrochemicals |
Sherwin-Williams | Cleveland | Retail | Hardware and Building Material Dealers |
Key Bank | Cleveland | Financial Services | Banks |
TravelCenters of America, Inc. | Westlake | Retail | Gasoline Stations |
Dana Holding Company | Maumee | Manufacturing | Automobiles, Boats and Motor Vehicles |
O-I (Owens Illinois), Inc. | Perrysburg | Manufacturing | Concrete, Glass, and Building Materials |
Big Lots Stores, Inc. | Columbus | Retail | Department Stores |
Limited Brands, Inc. | Columbus | Retail | Clothing and Shoes Stores |
Cardinal Health | Dublin | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
Progressive Corporation | Cleveland | Financial Services | Insurance and Risk Management |
Parker Hannifin Corporation | Cleveland | Manufacturing | Manufacturing Other |
American Financial Group, Inc. | Cincinnati | Financial Services | Insurance and Risk Management |
American Electric Power Company, Inc | Columbus | Energy and Utilities | Gas and Electric Utilities |
Fifth Third Bancorp | Cincinnati | Financial Services | Banks |
Macy's, Inc. | Cincinnati | Retail | Department Stores |
Goodyear Tire and Rubber Co. | Akron | Manufacturing | Plastics and Rubber Manufacturing |
The Kroger Co. | Cincinnati | Retail | Grocery and Specialty Food Stores |
Omnicare, Inc. | Cincinnati | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
The Procter and Gamble Company | Cincinnati | Consumer Services | Personal Care |
training details locations, tags and why hsg
The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:
- Learn from the experts.
- We have provided software development and other IT related training to many major corporations in Ohio since 2002.
- Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
- Discover tips and tricks about Design Patterns programming
- Get your questions answered by easy to follow, organized Design Patterns experts
- Get up to speed with vital Design Patterns programming tools
- Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
- Prepare to hit the ground running for a new job or a new position
- See the big picture and have the instructor fill in the gaps
- We teach with sophisticated learning tools and provide excellent supporting course material
- Books and course material are provided in advance
- Get a book of your choice from the HSG Store as a gift from us when you register for a class
- Gain a lot of practical skills in a short amount of time
- We teach what we know…software
- We care…