Python is a general-purpose, high-level programming language. Backend applications use it more frequently than frontend ones. Python has dynamic typing and garbage collection. The server-side coding, planning, deployment, and debugging of development projects are often done by the frontend and backend Python programmers. To handle the Python tools, you need to complete the online Python certification in a reputable institute. Here will look for the tools you must master as a backend developer:
What is a Python backend developer?
An IT expert with expertise in writing, testing, and managing Python code for backend operations is known as a Python backend developer. These experts are familiar with the fundamentals of data management as well as Python’s web development frameworks.
An open-source tool created for data science and machine learning is called Scikit-Learn. For data mining and analysis, it is widely utilized by developers, ML engineers, and data scientists. The incredible speed with which Scikit-Learn can complete various benchmarks on practice datasets is one of its best qualities.
This tool’s main features include model selection, preprocessing, regression, dimensionality reduction, and classification. In addition to the grid and random searches, it provides a consistent and user-friendly API.
Python-based Keras is an open-source high-level neural network library. Deep learning and machine learning work best with it. The four guiding principles of Keras are working with Python, modularity, straightforward extensibility, and usability. It allows neural networks to be expressed in the most basic manner imaginable. Keras, which is written in Python, can be used on top one.
SciPy is a free and open-source ecosystem of libraries for technical and scientific computing. In the fields of mathematics, science, and engineering, it is widely employed. SciPy uses other Python packages like NumPy, IPython, or Pandas to build libraries for typical programming tasks focused on math and science. It is an excellent tool for computerized number manipulation that also produces results that can be seen visually.
One of the best Python development tools is, without a doubt, Selenium. It is a free and open-source framework for web application automation. Java, C#, Python, PHP, Perl, Ruby, and .Net are just a few of the various programming languages you can use with Selenium to create test scripts. To use this one, you can do a Python online course with placement in a reputable institute.
Furthermore, you may run tests from any browser on Windows, macOS, or Linux using any of the three main operating systems. Additionally, Selenium may be integrated with applications like JUnit and TestNG to manage test cases and produce reports.
LXML is a Python-based tool made for the libxml2 and libxslt C libraries. It is one of the most user-friendly libraries for processing XML and HTML in Python and has many features. The ElementTree API enables secure and practical access to the libxml2 and libxslt libraries.
What makes it unique is that it blends the simplicity of a native Python API with the speed and XML functionality of these packages. It also supports XPath, RelaxNG, XML Schema, XSLT, and C14N to the ElementTree API.
A Python module called Beautiful Soup can be used to extract data from HTML and XML files. It can be integrated with the parser of your choice, allowing you to take advantage of several Pythonic idioms for traversing, searching, and altering a parse tree. The tool is used for tasks like screen-scraping and can automatically convert receiving documents to Unicode and export documents to UTF-8.
Web, mobile, and desktop automation testing are all supported by the testing automation program TestComplete. However, to utilize it, you need to get a commercial license. It includes a simple recording and playback feature.
Python, VBScript, and C++ script are scripting languages it supports. Software testers can conduct keyword-driven testing, just like Robot Framework. The ability of this Python utility to recognize GUI objects to identify and update UI elements is a significant feature. As a result, less work is needed to maintain test scripts.
As a backend developer, you need to know more tools to handle Python. The above listed are the few you need to master Python tools.