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Here are a few cool python pip packages to get started with
Pillow is actually a fork of PIL – Python Image Library. At first, pillow was mainly based on the PIL code-structure. But later, it transformed into something more friendly and better. Experts say Pillow is actually a modern version of PIL. However, pillow is your trusted company while working with images or any type of image format.
Features Of Pillow
- Using Pillow, you can not only open and save images but also influence the environment of images as well.
- Pillow supports a lot of file types such as PDF, WebP, PCX, PNG, JPEG, GIF, PSD, WebP, PCX, GIF, IM, EPS, ICO, BMP, and many others as well.
- With Pillow, you can easily create thumbnails for images. Thumbnails bear most of the valuable aspects of your image.
- Pillow supports a collection of image filters – FIND_EDGES, DETAIL, SMOOTH, BLUR, CONTOUR, SHARPEN, SMOOTH_MORE, and others.
- Pillow offers great support from the community who are eager to answer, challenge, and work through any of your inquiries.
Matplotlib
Matplotlib is a Python library that uses Python Script to write 2-dimensional graphs and plots. Often mathematical or scientific applications require more than single axes in a representation. This library helps us to build multiple plots at a time. You can, however, use Matplotlib to manipulate different characteristics of figures as well.
Features Of Matplotlib
- Matplotlib can create such quality figures that are really good for publication. Figures you create with Matplotlib are available in hardcopy formats across different interactive platforms.
- You can use MatPlotlib with different toolkits such as Python Scripts, IPython Shells, Jupyter Notebook, and many other four graphical user interfaces.
- A number of third-party libraries can be integrated with Matplotlib applications. Such as seaborn, ggplot, and other projection and mapping toolkits such as basemap.
- An active community of developers is dedicated to helping you with any of your inquiries with Matplotlib. Their contribution to Matplotlib is highly praisable.
- Good thing is that you can track any bugs, new patches, and feature requests on the issue tracker page from Github. It is an official page for featuring different issues related to Matplotlib.
Numpy
Numpy is a popular array – processing package of Python. It provides good support for different dimensional array objects as well as for matrices. Numpy is not only confined to providing arrays only, but it also provides a variety of tools to manage these arrays. It is fast, efficient, and really good for managing matrice and arrays.
Features Of Numpy
- Arrays of Numpy offer modern mathematical implementations on huge amount of data. Numpy makes the execution of these projects much easier and hassle-free.
- Numpy provides masked arrays along with general array objects. It also comes with functionalities such as manipulation of logical shapes, discrete Fourier transform, general linear algebra, and many more.
- While you change the shape of any N-dimensional arrays, Numpy will create new arrays for that and delete the old ones.
- This python package provides useful tools for integration. You can easily integrate Numpy with programming languages such as C, C++, and Fortran code.
- Numpy provides such functionalities that are comparable to MATLAB. They both allow users to get faster with operations.
OpenCV Python
OpenCV, a.k.a Open Source Computer Vision is a python package for image processing. It monitors overall functions that are focused on instant computer vision. Although OpenCV has no proper documentation, according to many developers, it is one of the hardest libraries to learn. However, it does provide many inbuilt functions through which you learn Computer vision easily.
Features Of OpenCV
- OpenCV is an ideal image processing package that allows you to both read and write images at the same time.
- Computer Vision allows you to rebuild, interrupt, and comprehend a 3D environment from its respective 2D environment.
- This package allows you to diagnose special objects in any videos or images. Objects such as faces, eyes, trees, etc.
- You can also save and capture any moment of a video and also analyze its different properties such as motion, background, etc.
- OpenCV is compatible with many operating systems such as Windows, OS-X, Open BSD, and many others.
Requests
Requests is a rich Python HTTP library. Released under Apache2.0 license, Requests is focused on making HTTP requests more responsive and user-friendly. This python library is a real blessing for beginners as it allows the use of most common methods of HTTP. You can easily customize, inspect, authorize, and configure HTTP requests using this library.
Features Of Requests
- Using basic Python Dictionaries in Requests, you can add parameters, headers, multi-part files, and form data as well.
- It is an easy library with tons of features that allow you to address custom headers, SSL certificate verifications, and sweep parameters towards URLs.
- With Requests, you can easily upload multiple files at a time. It allows you to work in a faster and efficient environment.
- Requests features automatic decompression that allows you to restore and revive compressed data into its authentic form in no time.
- Enjoy the benefits of HTTP proxy support with Requests. And allow your users with a faster and simpler route to your files and pages.
- Requests also features with value cookies, Unicode response bodies, Basic/Digest authentication, thread safety, connection pooling, and many more.
TensorFlow
TensorFlow is a free, open-source python machine learning library. It is very easy to learn and has a handful collection of useful tools. However, it is not limited to machine learning only; you can also use it for dataflow and programs that are differentiable. You can easily get to work with TensorFlow by installing Colab Notebooks in any browser you use.
Features Of TensorFlow
- TensorFlow uses automatic high-performance APIs such as – Keras. It offers an immediate iteration of machine learning models.
- This library features eager execution, which allows you to create, manipulate machine learning models, and make the debugging way easier.
- With TensorFlow, you can easily move your ML models in clouds, on any device and on-premises in any browser.
- TensorFlow comes with an easy to learn architecture. You can easily develop your concept into code and make your publications even easier.
- It has a solution to all of your common machine learning issues. You can easily implement it and go for giving your best.
BeautifulSoup
BeautifulSoup is a great python library. It is used for parsing. It can parse different broken HTML and XML documents, as well. It offers an easy way for web scraping by extracting direct data from HTML. Many professionals are really happy with its amazing performance. It can save quite a lot of time on your day.
Features Of BeautifulSoup
- BeautifulSoup can easily parse data out of HTML and XML. However, to do so, it needs a package and an exterior parser.
- It can be easily taught and learned. Parsing can be nicely done with simple html.parser command.
- BeautifulSoup4 comes with good support both for Python 2 and 3. However, BeautiSoup3 works with Python 2 only.
- Moreover, it offers users proper documentation of the package, which helps us to learn things quite fast.
- While working with BeautifulSoup, if you ever need any support, there is a large community to help you at an instance.
Bokeh
Bokeh is a data visualization library for python. It allows interactive data visualization. It is a special package, and it works quite differently than other data visualization libraries. This is because Bokeh uses HTML and JavaScript to provide its graphics, which makes it a reliable platform for contributing to dashboards and applications that are web-based.
Features Of Bokeh
- With Bokeh, you can create composite statistical scenarios easily using straight-forward commands.
- You can easily render your project output in different medias such as html, server, and notebook as well.
- Bokeh is a very compatible library that can easily work with different visualization and Django applications.
- You can have custom visualizations using Bokeh. It allows you to implement interactive layouts and other styling features for your data visualization.
- Bokeh is highly flexible, and it can convert your visualization that is written in other libraries such as matplotlib, ggplot, and others.
Pandas
Pandas is a python software package. It is a must to learn for data-science and dedicatedly written for Python language. It is a fast, demonstrative, and adjustable platform that offers intuitive data-structures. You can easily manipulate any type of data such as – structured or time-series data with this amazing package.
Features Of Pandas
- Pandas provide us with many Series and DataFrames. It allows you to easily organize, explore, represent, and manipulate data.
- Smart alignment and indexing featured in Pandas offer you a perfect organization and data labeling.
- Pandas has some special features that allow you to handle missing data or value with a proper measure.
- This package offers you such a clean code that even people with no or basic knowledge of programming can easily work with it.
- It provides a collection of built-in tools that allows you to both read and write data in different web services, data-structure, and databases as well.
- Pandas can support JSON, Excel, CSV, HDF5, and many other formats. In fact, you can merge different databases at a time with Pandas.