This is the third part of the Protecting a Python codebase series. This time we will be playing with Python interpreter in order to protect the original code of a Python based project.
Most any entrepreneurial person has searched for a trademark on the USPTO.gov website. Their search feature is straight forward, if somewhat innefficient and inflexible. It’s as old-school as it gets.
This is the second part of the Protecting a Python codebase series. This time we will be playing with Python Abstract Syntax Trees in order to protect the original code of a Python based project.
And so…I just moved back to Los Angeles from beautiful, friendly and surprisingly sunny Portland, Oregon. The Beaver state, go Ducks, Multnomah Falls, Ava Genes, Poler Outdoor Stuff, real public transportation, facial hair, beer and cocktail culture.
Today it is quite common to write applications that depend on third-party APIs, or even internal APIs, in this modularized digital world. But it makes testing tricky because dependency has an impact during the testing process:
Credit: This article is based off of the templating library mote. I was inspired by the simplicity of the library and it makes a great study piece for those who haven’t looked into the internals of templating engines before.
The very nature of Python makes the task of protecting the source code complicated. As an interpreted language, the source code must be available in some form in order to execute it.
“Product-Market Fit” is the buzzword of today. The digital revolution is upon us and success is up for grabs for those companies that can just nail the product-market fit thing. Right?