Python is the latest booming programming language for beginners as well as for heads-over-heels experts. What actually made Python so popular was its simplicity and ease of code usage. So even if you are a beginner, you don’t need to stress hard like with the C, JavaScript, or C++ programming languages.
There are several useful tools available to make Python coding much easier and more efficient. In this article, let’s look at the top 10 Python tools.
1. PyCharm IDE :
The PyCharm IDE for Python developers was made by JetBrains, a reputable company that also makes developer tools and IDEs for other programming languages besides Python. It is arguably the best IDE for Python developers ever made available online. The PyCharm IDE is a high-quality Python development tool with an excellent reputation for being a comprehensive yet lightweight development environment for Python developers. PyCharm provides more than 400 utilities, which come with a rich set of Python and other object-oriented programming support.
2. Juрyter Nоtebооk :
Jupyter Notebook is a popular IDE among data scientists and machine learning engineers because it makes the creation and execution of code simple and allows you to test the code by executing only one cell rather than the complete program like other IDEs do. The IDE is browser-based, and you can add notes to your code and titles as well as expose them as.ipynb or.pdf files. It is also a good option for 3D visualisation.
[Also Read, Python Interview Questions and Answers]
3. Kerаs
Keras is a tool for artificial intelligence (AI) that was developed on top of TensorFlow and other libraries, including Theano and NTK, to create deep neural networks that mimic the human brain in some ways while also making the creation of these deep neural networks simpler. Because Keras is open-source, it encourages developers to continue working on it, making the creation of neural networks as simple as typing commands and setting up markers.
4. Рiр Расkаge :
Assume you have knowledge of the Python programming language and desire to specialise in a particular area, such as data science, artificial intelligence, or data analysis. You will need to install some packages in order to do this, and a handy tool called iPip is now available. Every developer should have iPython since it is used to install any Python package that you want to utilise in your Python programme. You only need to type “Pip” followed by the name of the package, and this simple tool will download and install it for you. This requires an internet connection. Keep it updated at all times to make sure it functions properly.
5. Рythоn Аnywhere :
Consider reading an article on Python and wanting to give it a try, but not wanting to download Python and experiment with different ideas to discover which one works best. Instead, you may host and run your code from any location by utilising the Python online service. Therefore, you may use this service to generate code directly from your browser if you are new to Python and are not sure whether it is the best choice for you. You may access their platform for free, but you must upgrade your plan for a $5 monthly fee if you need more power.
[Also Read, What is Python? A Guide for Beginners]
6. Sсikit-Leаrn :
SCIkit-Learn is an open-source machine learning library that is built on top of several other libraries, such as Matplotlib for data visualisation, Numsy for mathematical computation, and SciPy for scientific computing, among others, to make SCIkit-Learn significantly more powerful. If you have some knowledge of Python and want to specialise in data science or machine learning, you may utilise the straightforward and effective tool Scikit-learn. This tool has integrated templates for executing machine learning algorithms on your data, including classification and linear regression, among other things. Additionally, you may utilise their built-in data to run your data science or analysis libraries without having to search the web for and download the necessary data.
7. Sрhinx :
The variety of codes that can be found online, for instance, on GitHub or other code hosting platforms, is one of the aspects that makes Python so popular. Many developers develop and distribute their own open-source programmes. To do this, you must create documentation for your code, which is where Sphinx enters the picture. Sphinx is the most practical tool for creating documentation for your programmes; it runs on the Windows terminal or command prompt and prompts you for information about your name, what your code does, its name, release date, and other details.
8. Selenium
Selenium is a tool or framework for testing online applications across several browsers, such as WordPress. Like many other programming languages, Python may be used to automate testing or to create a simple script. Numerous factors, such as this tool’s compatibility with numerous programming languages, such as C#, Java, Ruby, and others, as well as its support for numerous operating systems, such as Linux, Mac, and Windows, as well as numerous browsers, such as Chrome, Firefox, and Safari, all contributed to its popularity.
9. Beautiful Sоuр :
Beautiful-soup is a programming module that can be used to parse HTML documents from websites as well as XML. It can also be used to extract data from HTML files, allowing you to easily create a programme script to carry out this task. This tool is frequently used by data scientists to create a simple script that can extract large amounts of data from websites and then visualise or upload that data to automate learning programmes for scholarly research.
10. Sublime Text :
The last developer tool in this article is exquisite, a lightweight text editor that can be used to create clean and attractive Python code in a manner similar to that of SysHarm and Jupyter Notebook, but that is much faster and supports many more languages than Python. This code editor supports plugins, which are little pieces of software that may be added to your editor to provide features like automatic completion, among others.
Conclusion :
Python is a widely used tool for developers because of its ease of use and powerful functionality. Many developers use this language to build websites or web applications, or they may create data visualisations and interactive web pages. One type of developer that may use Python is a data scientist, which is why these tools are the most useful for a developer working in this field.
