Top 10 Python Libraries
Python is a high-level programming language I think most of us know but still many of us wonder is it good to learn python. Python has developed a lot in recent years and its demand is also increased very much and what makes Python a very powerful language is its large and very effective powerful libraries. Such strong libraries give the power to python to do anything such as Web Crawling, Web Development, Machine Learning, Scientific Computing, Image Processing, Artificial Intelligence, Game Development, and many more so I am here with the top 10 Libraries of python which you must know about. There are a lot more to explore …
1. Scrapy: If you are a web scraper then this is the must tool for you. You can easily build and run your Web Spiders and also deploy them to the Scrapy cloud.
2. Requests: It is one of the most powerful libraries used for HTTP requests. Its Features include HTTP(s) proxy support, multipart file downloads, streaming downloads, keep-alive and connection pooling, International domain and URLs, chunked request, connection Timeout, and many more.
3. Selenium: It is a browser automation tool. Generally, it is used for web application testing but it might not be limited to that it can be used to automate several different tasks on the browser. Also, it has wide support for a wide variety of browsers.
4. Pandas: Pandas is a software library for python mainly for data manipulation and analysis. It has wide use in data science and statistics. It is based on DataFrame (a tabular data structure) for data manipulation with indexing. It provides several advanced data manipulation features such as Label-Based slicing, fancy indexing with support of multilevel indexing, Data set merging and joining, Reshaping and Pivoting of data sets, easy reading, and writing of data, Time Series, and many more. Highly recommended for Data Science enthusiasts.
5. NumPy: In my opinion, this is one of the most important Python libraries. It provides advance Mathematic functionalities for scientific computing. It comes with the powerful and N-dimensional array object, broadcasting feature, vectorization support, etc.
6. Matplotlib: A data scientist or a data analyzer can’t live without this library. This provides the graphical representation of the data by plotting against the axis. Yes, a very powerful data visualization library. You can generate plots, scatter plots, histograms, power spectra, contours, etc. It is very similar to MATLAB and also resembles most of the MATLAB features and functionalities.
7. TensorFlow: This is one of my favorite libraries. It is a framework that allows you to build Machine Learning models. It comes with a variety of tools to ease your implementation of Machine Learning. Companies such as Google, NVIDIA, Dropbox, etc use TensorFlow. It supports CUDA computing which allows you to train your model on GPU. TensorFlow is packed with some HIGH-LEVEL API such as Keras ( API for building and training deep learning model), Estimators (API that provides models ready for large-scale training and production).
FUN TIP: Have look at Tensorflow Playground, It plays with Neural Networks.
8. OpenCV: It is a Computer Vision Library for mainly for image processing in real-time.
9. PyGame: It is a cross-platform library for making multimedia applications such as Games.
10. BeautifulSoup: It has applications while crawling and scraping the web when you need to extract data from HTML and XML. It parses the HTML and XML and extracts useful data.
That’s all for Today’s Post, Please let me know in the comments what do you think and also which library do you think is most popular. Also, if you found any error in the post please write at tarun12.tarunkr@gmail.com.
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