Satya Prakash SharmaDevelopers prefer Python because of its versatility, usage, and ease of access. In the software industry, it is one of the frequently used programming languages across several disciplines, such as data science, artificial intelligence, machine learning, and mathematical computation.
To get the most out of this programming language, developers must know the most helpful Python tools. We are listing handpicked tools for Python developers that can enhance their software development lifecycle skills.
1. PyCharm IDE
Every developer has their favorite Integrated Development Environment or IDE. However, if you are writing code in Python, you will be most productive when using PyCharm IDE. It is developed by JetBrains which is one of the best companies in creating IDEs for many different programming languages and not just Python.
This Python IDE is essentially the best code editor for Python developers out there. It lets you code much more efficiently due to its autocomplete feature that suggests all available keywords in Python. It also highlights any typo or missing syntax or keyword within your code. Also, it is effortless to install Python libraries in PyCharm, further extending its scope.
2. Pip Package
The robustness of Python is due to the availability of hundreds of open-source packages that you can use to customize its application for a particular field. Installing the Python packages can be tedious, which is why you can take the help of an intelligent tool called Pip.
Pip is one of the most widely used Python tools that allows developers to install any Python package with a single command line. It is highly beneficial when you are working on a project and want to import a package while writing code; you can easily do it using Pip. Just type the command – Pip package name to install the package without ever leaving the IDE. It helps to keep the productivity of Python developers high.
3. Scikit-Learn
To use Python for data science or machine learning applications, you must familiarize yourself with the Scikit-Learn tool. It is an open-source Python tool that can perform data mining and analysis at speed. Most developers and data scientists use Scikit-Learn to benchmark sample datasets, given its efficiency, accuracy, and speed. You can install this Python library in the PyCharm IDE. Some of the essential features included in Scikit-Learn are classification, clustering, regression, dimensionality reduction, model selection, and preprocessing.
4. Sphinx
The open-source community greatly influences Python and the developers often create their Python packages and let other developers use them through GitHub or other code-sharing platforms. One of the requirements of making your packages is to document the code such that others can use it. Python has a solution for this too. Sphinx is a Python tool that can generate documentation for your code automatically.
Sphinx can generate program documentation through your terminal or Windows CMD. It will ask you questions about the code, what it does, the release date, etc., and based on the information, it will create documentation. You can publish the document as an HTML file or can download its PDF file.
5. Selenium
Most developers and testers use Selenium. It is one of the best Python tools for automation testing, which is used in the software industry for all kinds of software development projects. Selenium is an open-source Python framework that you must learn to automate web applications through scripts. This tool can run scripts in several programming languages, including Python, Java, Ruby, Perl, C#, and .Net.
Every developer must have this Python tool on their list. With Selenium, you can automate web applications for any browser (Chrome, Firefox, Safari, Opera, or Internet Explorer). It also works on all major operating systems and can be integrated with testing tools like TestNG and JUnit.
6. LXML
If you are working with a C project for machine learning, then you can use this Python tool to work with libxml2 and libxslt libraries. It is one of the most feature-rich Python tools designed for C developers that provides them easy access to the functionalities of the libxml2 and libxslt libraries through the ElementTree API. At the same time, several other tools offer the same functionality, LXML, distinct because it combines the XML capabilities with the speed and simplicity of the native Python API. This allows developers to code faster by extending the scope of the ElementTree API by adding support for XPath, RelaxNG, C14N, XML Schema, and XSLT.
Conclusion
You must be familiar with these Python tools if you are a beginner or intermediate Python developer. These tools can help you write Python code more efficiently and save time by installing and updating packages.
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Sumit Malviya
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