PyBuilder: Software Build Automation Tool for Python

PyBuilder — an easy-to-use build automation tool for Python

PyBuilder is a software build tool written in 100% pure Python, mainly targeting Python applications.

PyBuilder is based on the concept of dependency based programming, but it also comes with a powerful plugin mechanism, allowing the construction of build life cycles similar to those known from other famous (Java) build tools.

PyBuilder is running on the following versions of Python 3.6, 3.7, 3.8, 3.9, 3.10, and PyPy 3.7.

See the GitHub Actions Workflow for version specific output.

Installing

PyBuilder is available using pip:

$ pip install pybuilder

For development builds use:

$ pip install --pre pybuilder

See the PyPI for more information.

Getting started

PyBuilder emphasizes simplicity. If you want to build a pure Python project and use the recommended directory layout, all you have to do is create a file build.py with the following content:

from pybuilder.core import use_plugin

use_plugin("python.core")
use_plugin("python.unittest")
use_plugin("python.coverage")
use_plugin("python.distutils")

default_task = "publish"

See the PyBuilder homepage for more details and a list of plugins.

Release Notes

The release notes can be found here. There will also be a git tag with each release. Please note that we do not currently promote tags to GitHub "releases".

Development

See Developing PyBuilder

Author: pybuilder
Source Code: https://github.com/pybuilder/pybuilder
License: Apache-2.0 License

#python 

What is GEEK

Buddha Community

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

• md5
• sha1
• sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips

Python Programming: A Beginner’s Guide

Python is an interpreted, high-level, powerful general-purpose programming language. You may ask, Python’s a snake right? and Why is this programming language named after it? Well, you are in the right place to discover the answer! and I’ll also answer the why, what, and how regarding Python programming.

Why do we need to know about Python?

People prefer Python over French (What 😮)

According to a recent survey, in the UK, Python overtook French to be the most popular language taught in primary schools. (OMG!) 6 of 10 parents preferred their children to learn Python over French.

The survey by Ocado group

So hurry up🏃‍♂️🏃‍♀️(or these kids will for sure)! Get ready to learn it! Because there’s a possibility of you being hired in one of the companies mentioned below!!!

#python #python-programming #software-development #python3 #python-tips #learn-python #python-top-story #python-skills

Automation Testing Tips

Thorough testing is crucial to the success of a software product. If your software doesn’t work properly, chances are strong that most people won’t buy or use it…at least not for long. But testing to find defects or bugs is time-consuming, expensive, often repetitive, and subject to human error. Automated testing, in which Quality Assurance teams use software tools to run detailed, repetitive, and data-intensive tests automatically, helps teams improve software quality and make the most of their always-limited testing resources.

Use these top tips to ensure that your software testing is successful and you get the maximum return on investment (ROI):

1. Decide What Test Cases to Automate
2. Test Early and Test Often
3. Select the Right Automated Testing Tool
4. Divide your Automated Testing Efforts
5. Create Good, Quality Test Data
6. Create Automated Tests that are Resistant to Changes in the UI

Decide What Test Cases to Automate

It is impossible to automate all testing, so it is important to determine what test cases should be automated first.

The benefit of automated testing is linked to how many times a given test can be repeated. Tests that are only performed a few times are better left for manual testing. Good test cases for automation are ones that are run frequently and require large amounts of data to perform the same action.

You can get the most benefit out of your automated testing efforts by automating:

• Repetitive tests that run for multiple builds.
• Tests that tend to cause human error.
• Tests that require multiple data sets.
• Frequently used functionality that introduces high-risk conditions.
• Tests that are impossible to perform manually.
• Tests that run on several different hardware or software platforms and configurations.
• Tests that take a lot of effort and time when manual testing.

Success in test automation requires careful planning and design work. Start out by creating an automation plan. This allows you to identify the initial set of tests to automate and serve as a guide for future tests. First, you should define your goal for automated testing and determine which types of tests to automate. There are a few different types of testing, and each has its place in the testing process. For instance, unit testing is used to test a small part of the intended application. To test a certain piece of the application’s UI, you would use functional or GUI testing.

After determining your goal and which types of tests to automate, you should decide what actions your automated tests will perform. Don’t just create test steps that test various aspects of the application’s behavior at one time. Large, complex automated tests are difficult to edit and debug. It is best to divide your tests into several logical, smaller tests. It makes your test environment more coherent and manageable and allows you to share test code, test data, and processes. You will get more opportunities to update your automated tests just by adding small tests that address new functionality. Test the functionality of your application as you add it, rather than waiting until the whole feature is implemented.

When creating tests, try to keep them small and focused on one objective. For example, separate tests for read-only versus reading/write tests. This allows you to use these individual tests repeatedly without including them in every automated test.

Once you create several simple automated tests, you can group your tests into one, larger automated test. You can organize automated tests by the application’s functional area, major/minor division in the application, common functions, or a base set of test data. If an automated test refers to other tests, you may need to create a test tree, where you can run tests in a specific order.

Test Early and Test Often

To get the most out of your automated testing, testing should be started as early as possible and ran as often as needed. The earlier testers get involved in the life cycle of the project the better, and the more you test, the more bugs you find. Automated unit testing can be implemented on day one and then you can gradually build your automated test suite. Bugs detected early are a lot cheaper to fix than those discovered later in production or deployment.

With the shift left movement, developers and advanced testers are now empowered to build and run tests. Tools allow users to run functional UI tests for web and desktop applications from within their favorite IDEs. With support for Visual Studio and Java IDEs such as IntelliJ and Eclipse, developers never have to leave the comfort of their ecosystem to validate application quality meaning teams can quickly and easily shift left to deliver software faster.

Select the Right Automated Testing Tool

Selecting an automated testing tool is essential for test automation. There are a lot of automated testing tools on the market, and it is important to choose the automated testing tool that best suits your overall requirements.

Consider these key points when selecting an automated testing tool:

• Support for your platforms and technology. Are you testing .Net, C# or WPF applications and on what operating systems? Are you going to test web applications? Do you need support for mobile application testing? Do you work with Android or iOS, or do you work with both operating systems?
• Flexibility for testers of all skill levels. Can your QA department write automated test scripts or is there a need for keyword testing?
• Feature-rich but also easy to create automated tests. Does the automated testing tool support record and playback test creation as well as manual creation of automated tests; does it include features for implementing checkpoints to verify values, databases, or key functionality of your application?
• Create automated tests that are reusable, maintainable, and resistant to changes in the applications UI. Will my automated tests break if my UI changes?

For detailed information about selecting automated testing tools for automated testing, see Selecting Automated Testing Tools.

Divide Your Automated Testing Efforts

Usually, the creation of different tests is based on QA engineers’ skill levels. It is important to identify the level of experience and skills for each of your team members and divide your automated testing efforts accordingly. For instance, writing automated test scripts requires expert knowledge of scripting languages. Thus, in order to perform these tasks, you should have QA engineers that know the script language provided by the automated testing tool.

Some team members may not be versed in writing automated test scripts. These QA engineers may be better at writing test cases. It is better when an automated testing tool has a way to create automated tests that do not require an in-depth knowledge of scripting languages.

You should also collaborate on your automated testing project with other QA engineers in your department. Testing performed by a team is more effective for finding defects and the right automated testing tool allows you to share your projects with several testers.

Create Good, Quality Test Data

Good test data is extremely useful for data-driven testing. The data that should be entered into input fields during an automated test is usually stored in an external file. This data might be read from a database or any other data source like text or XML files, Excel sheets, and database tables. A good automated testing tool actually understands the contents of the data files and iterates over the contents in the automated test. Using external data makes your automated tests reusable and easier to maintain. To add different testing scenarios, the data files can be easily extended with new data without needing to edit the actual automated test.

Typically, you create test data manually and then save it to the desired data storage. However, you will find tools that provide you with the Data Generator that assists you in creating Table variables and Excel files that store test data. This approach lets you generate data of the desired type (integer numbers, strings, boolean values, and so on) and automatically save this data to the specified variable or file. Using this feature, you decrease the time spent on preparing test data for data-driven tests.

Creating test data for your automated tests is boring, but you should invest time and effort into creating data that is well structured. With good test data available, writing automated tests becomes a lot easier. The earlier you create good-quality data, the easier it is to extend existing automated tests along with the application’s development.

Create Automated Tests That Are Resistant to Changes in the UI

Automated tests created with scripts or keyword tests are dependent on the application under test. The user interface of the application may change between builds, especially in the early stages. These changes may affect the test results, or your automated tests may no longer work with future versions of the application. The problem is automated testing tools use a series of properties to identify and locate an object. Sometimes a testing tool relies on location coordinates to find the object. For instance, if the control caption or its location has changed, the automated test will no longer be able to find the object when it runs and will fail. To run the automated test successfully, you may need to replace old names with new ones in the entire project, before running the test against the new version of the application. However, if you provide unique names for your controls, it makes your automated tests resistant to these UI changes and ensures that your automated tests work without having to make changes to the text itself. This also eliminates the automated testing tool from relying on location coordinates to find the control, which is less stable and breaks easily.

#automation-testing-tool #automation-testing #automation-tips #automation-software #automation