30 skills found
hamvocke / Spring TestingA Spring Boot application with lots of test examples
pactumjs / PactumREST API Testing Tool for all levels in a Test Pyramid
Amitpnk / Clean Architecture ASP.NET CoreComplete solution template which is built on Clean Architecture with all essential feature, CI/CD, best practice, testing Strategy using the testing pyramid and documentation using .NET 5!
sanusanth / Python Basic ProgramsWhat is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Good to know The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular. In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files. Python Syntax compared to other programming languages Python was designed for readability, and has some similarities to the English language with influence from mathematics. Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses. Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose. Applications for Python Python is used in many application domains. Here's a sampling. The Python Package Index lists thousands of third party modules for Python. Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS. Python's standard library supports many Internet protocols: HTML and XML JSON E-mail processing. Support for FTP, IMAP, and other Internet protocols. Easy-to-use socket interface. And the Package Index has yet more libraries: Requests, a powerful HTTP client library. Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML. Feedparser for parsing RSS/Atom feeds. Paramiko, implementing the SSH2 protocol. Twisted Python, a framework for asynchronous network programming. Scientific and Numeric Python is widely used in scientific and numeric computing: SciPy is a collection of packages for mathematics, science, and engineering. Pandas is a data analysis and modeling library. IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing. The Software Carpentry Course teaches basic skills for scientific computing, running bootcamps and providing open-access teaching materials. Education Python is a superb language for teaching programming, both at the introductory level and in more advanced courses. Books such as How to Think Like a Computer Scientist, Python Programming: An Introduction to Computer Science, and Practical Programming. The Education Special Interest Group is a good place to discuss teaching issues. Desktop GUIs The Tk GUI library is included with most binary distributions of Python. Some toolkits that are usable on several platforms are available separately: wxWidgets Kivy, for writing multitouch applications. Qt via pyqt or pyside Platform-specific toolkits are also available: GTK+ Microsoft Foundation Classes through the win32 extensions Software Development Python is often used as a support language for software developers, for build control and management, testing, and in many other ways. SCons for build control. Buildbot and Apache Gump for automated continuous compilation and testing. Roundup or Trac for bug tracking and project management. Business Applications Python is also used to build ERP and e-commerce systems: Odoo is an all-in-one management software that offers a range of business applications that form a complete suite of enterprise management applications. Try ton is a three-tier high-level general purpose application platform.
knaufk / Flink Testing PyramidExample of a tested Apache Flink application.
eddyerburgh / Example Front End Test Pyramid AppAn example app demonstrating the front-end pyramid
paulojunior-ufla / Piramide De Teste PraticaTradução do artigo "The Practical Test Pyramid" para PT-BR
kriscfoster / Spring Boot Testing PyramidNo description available
ricardo-comar / Test PyramidSimple project to apply Test Pyramid methodology together with Clean Architecture
Amitpnk / Modular Architecture ASP.NET CoreQuickApp solution template which built on Modular Monolith Architecture (plug & play) with WebAPI, GraphQL, gRPC, essential feature, CI/CD, best practice, testing Strategy using the testing pyramid and documentation using .NET Core!
shoom3301 / React Testing PyramidNo description available
fizyk / Pytest Pyramidpytest_pyramid provides basic fixtures for testing pyramid applications with pytest test suite
weaverj / TestpyramidexampleA working demo project illustrating the test pyramid concept
lvcarnevalli / JavacleanJAVA Clean template clean architecture, feature toggles and test pyramid
rafaelfgx / MicroservicesScreaming Architecture, Clean Architecture, Event-Driven Architecture, Clean Code, DDD, SOLID, Test Pyramid, Patterns (Ambassador, Circuit Breaker, Mediator, Outbox, Result, Retry, Strategy), Java 25, Spring Boot 4, Kong, Keycloak, Kafka, MongoDB, Redis, Elastic, Testcontainers, Docker
DanailMinchev / Gatsby Starter TestingA simple Gatsby starter with configured testing frameworks and tools for each layer of the The Testing Pyramid and more.
SatishKumarAnbalagan / Semantic SegmentationClassified & clustered every pixel in cityscape dataset image belonging to same object class in modified Google DeepLabV3 architecture. Enhanced boundary detection of the Image Net (ResNet) with atrous conv & Atrous Spatial Pyramid Pooling (ASPP) with variable dilation rates by using end to end Holistic Edge Detection(HED) technique. Added Squeeze & Excitation (SE) block to improve channel attention & also tested softmax in stead of sigmoid for last layer of SE.
AdyKalra / TestingToolsviaTestPyramidList of all testing tools in every programming language , based on the Testing Pyramid
damienbeaufils / Tests Pyramid CalculatorTest pyramid calculator for Java/Spring application
mikelane / Pytest Test CategoriesPytest plugin enforcing Google's hermetic testing best practices. Test categorization (small/medium/large), timing limits, resource isolation, and test pyramid validation. No escape hatches.
