The Python Standard Libraries
In this article, we will talk about the definition of libraries in programming languages in general, and about Python libraries in particular, where we will address a list of 19 excellent Python libraries, which you can rely on in writing Python to accomplish any programming task in this wonderful language.
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| Python Standard Libraries |
What are Libraries in Programming Languages?
The library in the programming language; It is a set of ready-made functions that you can import into your code without having to write or define them yourself.
These specialized libraries and developers work, and then publish them to everyone to help them create their programming projects with ease, and to integrate them into their code without having to write it again.
The idea with these libraries is for the best developers to cut down on you time and effort, rather than building everything from scratch, or as programmers like to say, reinvent the wheel.
This is very important. Instead of sitting for hours trying to write a single function that you want to use… In less than five seconds, you can import a function from the Pandas library that specializes in data analysis, for example, or a function from the TensorFlow library for deep learning .
If you are a beginner in programming, you will say what is the problem with spending hours to come up with this function, but the idea that the project you are working on will need dozens and hundreds of these ready-made library functions, and dispensing with them will greatly extend the time you need to write your project.
What is the difference between a library and a framework in programming languages?
There is another term in programming called framework, and although it is very different from the library, the two terms are confused and used in place of each other, and this is of course a big mistake; A framework is a slightly broader concept than a library, and its user is bound by certain rules that must be adhered to.
The framework can be defined as a set of ready-made code that programmers can use without writing it from scratch, but instead of calling it and controlling it, it is the one who requests your code and tells you the data it wants, meaning that the difference between them is in the Inversion of Control feature that Enjoy the framework.
In the library, you can call the property you want in your code, and use it as you like, unlike using the framework, which is like filling in the required missing spaces, or walking through pre-defined steps to finish your project, and you can liken the framework to a picture frame or frame that It controls the size and shape of the image in which it is placed.
Libraries in the Python programming language
Python is one of the most famous and most popular programming languages that exist today and has a very large community, and one of the advantages of this is the presence of many of its libraries, statistics estimate the number of Python libraries at about 137,000 libraries in various fields from data analysis and artificial intelligence to cybersecurity and game design .
This momentum and the huge amount of libraries was one of the biggest contributors to the fact that the Python language has the position we know today, especially in the field of artificial intelligence and data science , as we will see when reviewing the Python language libraries, we will find that one of the most famous libraries that we will review are data analysis and machine learning and deep learning.
It is worth noting that as a programmer, you do not need to know all the libraries in the programming language that you use, and even you do not need to have detailed knowledge about all the libraries in your field, but you only have to know well the libraries you use, and keep abreast of developments and updates by following what is new in your field, tools, libraries and frameworks Work Frameworks used.
The 19 Most Important Python Code Libraries
Although there are a large number of libraries in the Python language -137 thousand as we mentioned - but in the winners we have chosen for you the most famous and most important 19 libraries in the Python language in the various fields of Python programming, which are:
1. NumPy library
NumPy is one of the most famous libraries in the Python language, and its name comes from Numerical Python, and it deals in general with vectors, Arrays, and provides many functions for mathematical operations, linear algebra and matrices.
You can say that this library is the most important library ever in the Python language, as the ease of dealing with it and being open source in addition to its strength and efficiency have contributed to making Python one of the powerful languages in many fields.
When you delve into the research, you will find that many important libraries in the different fields that Python deals with rely heavily on the NumPy library, for example, but not limited to:
1. Data Science and Representation: The most popular libraries in this field rely on NumPy such as Pandas, Jupyter, Matplotlib, Seaborn, and dozens of others.
2. Machine Learning and Deep Learning: Libraries such as PyTorch, scikit-learn, SciPy, and TensorFlow that dominate this field are all based on NumPy.
3. Image processing: Scikit-image library, OpenCV library, Mahotas library, etc.
4. Quantum Computing: Industry-leading libraries such as QuTiP, PyQuil, and Qiskit rely on NumPy as well.
5. Bioinformatics: The popular BioPython package in bioinformatics and in general biocomputing applications is based on NumPy.
It is also worth noting that the famous event of the first image of a black hole in April 2019 was a success factor for the Numpy libraries that depend on it.
2. Pandas Library
Pandas library is a powerful library that is indispensable for any programmer who deals with data. It can explore, analyze, clean and manipulate data. For simplicity, you can consider it an advanced Excel program that you can use in Python to do everything you can think of with the data.
Reliance on the secret Pandas library; Being able to deal with many forms of data either; With data arranged in rows and columns tabular data, or data arranged or unordered in time series, or array data, and even unlabeled data that needs to be processed before it can be used.
With the Pandas library, you can read and modify various forms of data, format data, handle missing data, shape data as you wish, and perform dozens of other tasks you'll need when working with data.
The three libraries Numpy, Pandas, and Matplotlib are often used in conjunction with each other in data science.
3. Matplotlib . library
Matplotlib library is the leading library in the field of data visualization , and it is one of the most used libraries in the fields of data science and scientific fields in general, and you can say that this library is your magician that will help you make the graph you need for your data.
You can understand the power of this library by seeing the huge amount of graphs that you can create with Matplotlib.
4. Seaborn Library
The Seaborn library is very similar to the previous one, Matplotlib, both because it is based on it and because many of its functions intersect with it, but the Seaborn library is used to create more attractive Statistical Graphs than Matplotlib makes.
The difference between these two libraries is that the Seaborn library has more advanced graphs than Matplotlib that deals with simple and primitive graphs, in addition to having default themes for representing data, which makes it easier than Matplotlib, and the Seaborn library is more intuitive and efficient in dealing with frameworks Data from Pandas.
5. Scikit-Learn Library
Scikit-Learn is a very powerful library that is widely used in the fields of machine learning, because it provides many algorithms that help with supervised learning and unsupervised learning, and it is compatible with popular data-handling libraries such as NumPy, Pandas and Matplotlib.
Through the Scikit-Learn library, you can perform many tasks, such as:
- Regression analysis.
- Classification.
- Clustering analysis.
- Model selection.
- Preprocessing.
6. OpenCV Library
OpenCV is one of the most popular Python libraries ever. It is the leading computer vision library, which has dozens of uses today based on image and video analysis.
Where it is used in:
- Face Detection.
- Identify Objects.
- Classification of Human Actions.
- Motion Tracking.
- Automated Inspection and Surveillance.
- And many other uses.
OpenCV library is one of the largest libraries ever. It contains more than 1900 algorithms and can be used in several programming languages such as Python, Java, C++ and MATLAB.
It also works on many operating systems and Linux, and is used by the largest programming companies in the world or what they call technology whales.
7. TensorFlow Library
TensorFlow library is a leading library in the fields of machine learning and deep learning, as it is the most important in the field to the extent that experts say that 70% of deep learning applications are done through it, and you can understand the secret of this superiority if you know that the library was developed by Google and made open source For programmers all over the world.
One of the advantages of TensorFlow library is that it is easy to build a machine learning model or deep learning through it with its very powerful and efficiency, and it is faster than other deep learning libraries, and although it is specialized in deep learning, you can use it in machine learning.
These previous features made many major companies around the world primarily use the TensorFlow library, including:
- AMD
- Lenovo
- Xiaomi
- Uber
- PayPal
8. Keras . Library
Keras is a famous library in the field of deep learning based on the famous Tensorflow library and Theano library, designed by François Cholet, the famous artificial intelligence scientist, who works for Google to be simpler, easier and faster than other libraries in the field of deep learning such as TensorFlow library.
The great advantage of Keras library is that it does not deal with low-level details, that is, it is a high-level library, and this makes dealing with Neural Networks through it more User Friendly.
9. PyTorch Library
PyTorch is a famous library in the field of deep learning created by Facebook, and it is used in many applications of deep learning, natural language processing and computer vision, which enables you to make neural networks easily and perform their operations quickly.
Although the PyTorch library is not used like the leading libraries in the field of deep learning TensorFlow and Keras, it has many advantages that make AI and deep learning professionals pay attention to it, such as: its simple interface, its being a Python-based library in addition to its compatibility with the NumPy library.
10. Theano . Library
Theano library is one of the most famous libraries that are used in the field of neural networks, it was built by a team of machine learning researchers from the University of Montreal, and it supports many neural networks in the field of deep learning such as Convolutional Neural Network (CNN), and Recurrent Neural Networks (RNN).
Theano library has the advantage of being able to perform a lot of operations, as well as improving the stability of the deep learning model even if unstable models are used by integrating them with more stable models, and it is famous for its speed of running deep learning models.
11. Scipy Library
One of the most widely used libraries in science and engineering, Scipy is an open source library of many mathematical algorithms frequently used in physics and engineering, and is often described as a scientific computing library.
The Scipy library deals with many mathematical topics, such as:
- Linear Algebra.
- Integration.
- Statistics.
- Fourier Transform.
- Signal Processing.
- Image Processing.
12. NLTK Library
The NLTK library - from Natural Language Toolkit- is the leading library in the field of Natural Language Processing, and it contains a lot of algorithms that deal with texts, and this library is so powerful that it is used in other fields such as psychology, linguistics, and others.
The NLTK library is used in most NLP applications, such as:
- Text categorization.
- Text Prediction.
- Exclude common words Stop Word.
- Text Analysis.
- Sentiment Analysis.
- Dozens of other applications.
13. TextBlob Library
TextBlob is one of the most famous libraries in the field of Natural Language Processing. It is based on the NLTK library, so it is very powerful, very simple and easy, and can be used in many text-related applications, and is very popular in the field of Sentiment Analysis.
14. Selenium Library
Selenium library is a famous library that has gained momentum and fame in the recent period due to its strength and uses, and through the Selenium library you can control your browser and make it able to perform several functions, which made this library very popular in the fields of automation, and it is also used to extract Information from Internet pages automatically or Web scraping.
15. Beautiful Soup . Library
Beautiful Soup is one of the very important libraries in the Python language, and it specializes in extracting information from Internet pages automatically or what is known as Web Scraping, and it also allows converting the extracted data to other types of files, and it can save the programmer and data scientist days and weeks From manual search.
16. SQLAlchemy Library
SQLAlchemy library is one of the important libraries in the Python language, and this is because it facilitates dealing with SQL or Structured Query Language. A set of relationships, not just values.
17. PyQt . Library
PyQt is a very powerful Python library that contains more than 6000 functions and 440 classes that help programmers create graphical user interface for different applications. It supports networks, databases, regular expressions, markup languages, and many other things.
18. Pillow Library
Pillow is a very popular Python image processing library that efficiently supports many image formats and its ability to process images is impressive given its speed, simplicity, and ease of use. This is in addition to its powerful features such as filtering the images in your database through several filters, enhancing and modifying them, or adding texts.
Through the Pillow library, you can also process images through each pixel separately, and choose the pixels that you process and the ones you want to ignore. You can view the documentation for the library from here .
19. Manim . Library
I've been wondering a lot about the unique way 3Blue1Brown's popular channel videos are made, and how the math is done, until I read that Stanford University mathematician Grant Sanderson created this library for his amazing videos.
With the Manim library, and using the Python programming language, you can also create your own beautiful videos with all their parts from shapes and texts to adding sounds, and all this with a very low computing power that produces high-quality videos with low space
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