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15 Python libraries we should know about

Python is a relatively simple programming language that is easy to learn due to its unique 'syntax' that focuses on readability. Reading and translating the code written in Python programming language is easier for 'developers' than other languages. This, in turn, reduces the costs of maintaining and developing programs written in this language because it allows teams to collaborate without facing language barriers and having different work experiences among team members.

Now we are going to examine the most important part of this article, which is the popular libraries in Python. Python can support various libraries well. In this article, we are going to introduce you to the best of these libraries.
1) Scrapy
Scrapy is a popular Python library for web scraping. This library is used to build the crawler. At first, this library was only used for scraping, but later things like data mining, test automation, etc. were used. Scrapy is a popular open source library.

In 2008, the Scrapy framework was released and is now considered one of the best Web Scraping and Web Crawling tools. Scrapy is simple enough for beginners and has enough positive features for professionals.

2) PyTorch
Pytorch is an open source Python library that can be used instead of Numpy. It also offers high efficiency for building deep neural networks. At the same time, you can use scipy, cypthon and numpy to develop functionality. Companies such as Facebook, Twitter, Nvidia, and Uber use Pytorch to develop the prototyping process in deep learning research and development.

PyTorch is a scientific computing package based on Python that takes advantage of the processing power of GPUs. This library is considered one of the comprehensive research platforms in the field of deep learning, which provides flexibility and acceptable speed. PyTorch is known for its two unique high-level capabilities, which include tensor computation using GPU-accelerated power and building deep neural networks in an Autograd system.

3) Pendulum
Pendulum is a Python package for working with time and date. If you replace all DateTimes in the project everything still works fine. Using Pendulum, you can display the date and time based on the time zone.

4) Requests
Requests is one of the most popular Python libraries available under the Apache2 license. This library helps humans interact with different languages. Using Requests, you don't need to worry about adding queries, writing strings manually, etc. You can send an http request using the Request library and at the same time send content such as headers, etc.

Requests is a comprehensive php library that focuses on communication protocols, especially HTTP, which is written by PHP and used in this programming language. The Requests library is an approximate model based on the APIs of the Python language library, which has been restored with a perfect interpretation and translation to the popular PHP language, and has created a strong API between Python libraries and the PHP web language, and the user interface between Python and PHP. has created. By using the Requests library, you have created a common boundary between php and the Python library, where you can easily benefit from Python's communication capabilities with the database and user, and use its algorithms and functions interpreted in the php language.

5) Zappa
Zappa is one of the best Python packages developed by Miserlou. It is very easy to create Server-Less applications using this tool and with the help of Amazon Web Service.

6) PyFlux
Pyflux is a Python library used for time series analysis and forecasting. This library was written by Ross Taylor and provides various interface options. Pyflux allows users to implement time series models such as GARCH.

7) Arrow
Arrow is a very popular Python library that provides many features for creating, formatting, converting date, time, and timestamps. This library supports Python 3 and 2 and is also considered a suitable alternative to datetime in Python.

8) Theano
This is a Python library for deep learning that is used to optimize, define and evaluate numerical mathematical equations. This library is developed by machine learning group. As such, it is known as an interpreter for mathematical operations and provides excellent integration mode with Numpy.

9) IPython
This is one of the very useful tools of Python that implements a very good structure for its users. This tool allows you to run Python code through the browser. Ipython works on most operating systems such as Windows, Mac, Linux and Unix family. Ipython gives you various features like a basic interpreter, along with features like working with numbers, additional functions, helper functions, advanced editor, etc.

10) Dash
Dash is a new open source Python library for building web-based applications. Web applications that make more use of data visualizations, this library is ideal for them.

Apart from Python, this library is based on Flask, Plotly.js and React. The application built using this library runs in the browser and is responsive on mobile devices.
11) TensorFlow
TensorFlow is a modern Python machine learning library created by the Google Brain team. This library is used to develop, train and design deep learning models. This tool can be used for numerical calculations and will somehow be an alternative to Theano. TensorFlow can run on mobile, single-CPU systems, and even on GPUs.

12) Fire
Fire is an open source library that automatically generates a CLI for any Python-based project. In this library, you don't need to write any code to create CLI in projects. You only need to call the Fire method and then put the things you want to be in the CLI as arguments in the method. Functions, objects, classes, dictionaries, you can even include the whole project in the CLI, for this you need to put the argument as empty.

13) Flashtext
FlashText is one of the best Python libraries for working with regular expressions. This library is provided as open source and offers various features.

14) Pipenv
Using Pipenv you can put all your requirements in one Pipfile. Pipfiles are generally created using command line commands. This tool can create a Pipfile.lock file for you. In this way, you can automate a large part of your work.

15) Luminoth
Images are everywhere nowadays and understanding their content is very important for some applications. Fortunately, image processing techniques have made many advances. Luminoth is an open source tool for Python built using TensorFlow and Sonnet. Currently, this library has the ability to recognize various objects.

Conclusion
Maybe the concept of library and its meaning seems a bit complicated. But in fact, the library is a collection of modules. The library contains modules written either in C or Python.

A set of standard pieces of code or independent packages that can be used to build a more complex structure is called a module. In simpler words, a module is a collection of lines of code that is used for a specific purpose and can be used in multiple programs, which avoids repetition, which is very important in programming.

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