Welcome TurkHackTeam Members. Today I will be writing the most used, top 10 python libraries.
As you know, we use many libraries to create projects, develop our tools. There are thousands of libraries, more than 200.000 librariers, and not a single man is able to know all of them. However in this article I will show you what x library does and how it works. Let us begin if you are ready.
Note: These libraries I mentioned are mostly focused on Python packages that cover a wide range of programming scenarios and goals, as opposed to just focusing on a specific niche, like data science or Web development.
-1 NumPy-
You can do basic mathematical operations without any special Python packages. However, if youââ¬â¢re going to do any kind of complex math, the NumPy package will make your coding life much easier.
NumPy provides tools to help build multi-dimensional arrays and perform calculations on the data stored in them. You can solve algebraic formulas, perform common statistical operations, and much more. NumPy is mostly used for data science. You also need to know how to use this library for bigger projects.
While NumPy is a valuable Python package for a variety of general-purpose programming tasks, itââ¬â¢s particularly important if you want to do machine learning, since it provides part of the foundation for libraries like TensorFlow.
-2 Pendulum-
If you have at least a little Python programming experience, you probably know that you can use the datetime module to manage dates and times within an application. They are so important and you usually create some things using them.
While datetime is great for basic work along these lines, the Pendulum Python package makes it easier to do more complex coding involving dates and times. Itââ¬â¢s more intuitive to work with, and it manages time zones automatically. You know what pendulum means, so you can understand the whole process by its name.
Best of all, Pendulum is designed to be a drop-in replacement for datetime. That means you can use it with code youââ¬â¢ve already written based on datetime. With only a few exceptions, Pendulum will work just as well, without the need to modify the code, while providing extra features not present in plain-old datetime.
-3 Colorama-
Well, this is one of the my most liked python libraries. The original python terminal is so dull, isn't it? You can rid of this situation with this library.
Colorama colors your python projects. There are many options available. You can set different colors for your texts. It's not that complicated too.
However in some cases it looks like unicode, so you need to edit some on it. Your project will look like a rainbow.
-4 MoviePy-
MoviePy is to videos what Pillow is to images. It provides a range of functionality for common tasks associated with importing, modifying, and exporting video files. It also lets you do things like insert titles into videos or rotate videos 90 degrees. So this might not look so necessary but some people use this often and even if I do not, you can use if you need to.
Like Pillow, MoviePy is not intended as a tool for advanced data manipulation. If youââ¬â¢re writing a video editing app, youââ¬â¢ll probably also need to rely on OpenCV (which can work with videos as well as images) to provide the advanced functionality that MoviePy lacks. But for most standard tasks involving videos in Python code, MoviePy gets the job done quite well.
-5 Requests-
This one is the most used library in python. Almost in every project you can see requests.
Writing code that sends HTTP requests can be tricky, due in no small part to the fact that HTTP does not exactly format data in a way that is easy for humans to read.
The Requests Python package (motto: ââ¬ÅHTTP for Humansââ¬) tackles this problem by automating many of the tedious tasks that you would otherwise need to perform in order to send HTTP requests from your application. It removes the need to add query strings, or do POST form encoding. It also keeps connections with HTTP servers alive automatically, eliminating the need to write a bunch of code for doing that.
In short, if your application sends any data over HTTP, Requests is a must-have package.
-6 Tkinter-
Want to develop a Python app with a Graphical User Interface (GUI)? There are a variety of packages designed to help you do that (indeed, we could make a top ten list of just Python GUI packages). But I think most Python developers would agree that Tkinter is the most important ââ¬â and most commonly used ââ¬â framework for creating GUIs. It binds Python to the TK GUI toolkit, which works on virtually every modern operating system.
Regardless, this library is very difficult to use, comparing to the other libraries. You need to be expert to use this library completely.
Unless you have a strong preference for a different GUI toolkit, Tkinter is probably the best place to start when creating a Python GUI.
-7 PyQt-
The preceding sentence notwithstanding, PyQT, another Python package for building GUIs, is also a strong contender. It provides bindings to (you guessed it) the Qt toolkit, which is also cross-platform. Itââ¬â¢s intended for heavier-duty GUI programming than Tkinter. That means that PyQT may be overkill if youââ¬â¢re building an app that has a pretty simple interface ââ¬â say, just a window with some buttons and text fields ââ¬â but it is a good tool if you want to build a complex, multi-dimensional GUI.
-8 Pandas-
There is a long list of Python packages designed for working with complex data sets. But arguably, Pandas is the most important. Pandas helps you manipulate and analyze large sets of data without having to learn a specialized data-processing language like R.
I also made a coronavirus data science program using pandas. I recommend Pandas actually.
Pandas has its limits in that itââ¬â¢s not intended for advanced statistical modelling (in that case, you would want to learn R, or use a Python package like statsmodels). But if you need to do things like process time-series data or perform statistical analysis on a data set, Pandas has you covered.
-9 Pywin32-
For Windows Python programming in particular, Pywin32 is a must-have package. It provides access to many of the native Windows API functions, allowing you to do things like interact with the Windows registry, use the Windows clipboard, and much more.
Pywin32 wonââ¬â¢t do you much good if youââ¬â¢re building a cross-platform Python app, but Windows developers might find that they like it so much that they use it instead of native Windows tooling.
So you need to use this if you want to add your win system to the project.
-10 Pytest-
If you have a Python development project of any complexity, being able to perform testing on new code is essential. The Pytest package provides a variety of modules to help you do this. Whether itââ¬â¢s a simple unit test or a more complex functional test, Pytest can help you write it.
So, this was all. Here we are at the ending. Thanks for reading. I hope you are more informed. Have a good day.
As you know, we use many libraries to create projects, develop our tools. There are thousands of libraries, more than 200.000 librariers, and not a single man is able to know all of them. However in this article I will show you what x library does and how it works. Let us begin if you are ready.
Note: These libraries I mentioned are mostly focused on Python packages that cover a wide range of programming scenarios and goals, as opposed to just focusing on a specific niche, like data science or Web development.
-1 NumPy-
You can do basic mathematical operations without any special Python packages. However, if youââ¬â¢re going to do any kind of complex math, the NumPy package will make your coding life much easier.
NumPy provides tools to help build multi-dimensional arrays and perform calculations on the data stored in them. You can solve algebraic formulas, perform common statistical operations, and much more. NumPy is mostly used for data science. You also need to know how to use this library for bigger projects.
While NumPy is a valuable Python package for a variety of general-purpose programming tasks, itââ¬â¢s particularly important if you want to do machine learning, since it provides part of the foundation for libraries like TensorFlow.
-2 Pendulum-
If you have at least a little Python programming experience, you probably know that you can use the datetime module to manage dates and times within an application. They are so important and you usually create some things using them.
While datetime is great for basic work along these lines, the Pendulum Python package makes it easier to do more complex coding involving dates and times. Itââ¬â¢s more intuitive to work with, and it manages time zones automatically. You know what pendulum means, so you can understand the whole process by its name.
Best of all, Pendulum is designed to be a drop-in replacement for datetime. That means you can use it with code youââ¬â¢ve already written based on datetime. With only a few exceptions, Pendulum will work just as well, without the need to modify the code, while providing extra features not present in plain-old datetime.
-3 Colorama-
Well, this is one of the my most liked python libraries. The original python terminal is so dull, isn't it? You can rid of this situation with this library.
Colorama colors your python projects. There are many options available. You can set different colors for your texts. It's not that complicated too.
However in some cases it looks like unicode, so you need to edit some on it. Your project will look like a rainbow.
-4 MoviePy-
MoviePy is to videos what Pillow is to images. It provides a range of functionality for common tasks associated with importing, modifying, and exporting video files. It also lets you do things like insert titles into videos or rotate videos 90 degrees. So this might not look so necessary but some people use this often and even if I do not, you can use if you need to.
Like Pillow, MoviePy is not intended as a tool for advanced data manipulation. If youââ¬â¢re writing a video editing app, youââ¬â¢ll probably also need to rely on OpenCV (which can work with videos as well as images) to provide the advanced functionality that MoviePy lacks. But for most standard tasks involving videos in Python code, MoviePy gets the job done quite well.
-5 Requests-
This one is the most used library in python. Almost in every project you can see requests.
Writing code that sends HTTP requests can be tricky, due in no small part to the fact that HTTP does not exactly format data in a way that is easy for humans to read.
The Requests Python package (motto: ââ¬ÅHTTP for Humansââ¬) tackles this problem by automating many of the tedious tasks that you would otherwise need to perform in order to send HTTP requests from your application. It removes the need to add query strings, or do POST form encoding. It also keeps connections with HTTP servers alive automatically, eliminating the need to write a bunch of code for doing that.
In short, if your application sends any data over HTTP, Requests is a must-have package.
-6 Tkinter-
Want to develop a Python app with a Graphical User Interface (GUI)? There are a variety of packages designed to help you do that (indeed, we could make a top ten list of just Python GUI packages). But I think most Python developers would agree that Tkinter is the most important ââ¬â and most commonly used ââ¬â framework for creating GUIs. It binds Python to the TK GUI toolkit, which works on virtually every modern operating system.
Regardless, this library is very difficult to use, comparing to the other libraries. You need to be expert to use this library completely.
Unless you have a strong preference for a different GUI toolkit, Tkinter is probably the best place to start when creating a Python GUI.
-7 PyQt-
The preceding sentence notwithstanding, PyQT, another Python package for building GUIs, is also a strong contender. It provides bindings to (you guessed it) the Qt toolkit, which is also cross-platform. Itââ¬â¢s intended for heavier-duty GUI programming than Tkinter. That means that PyQT may be overkill if youââ¬â¢re building an app that has a pretty simple interface ââ¬â say, just a window with some buttons and text fields ââ¬â but it is a good tool if you want to build a complex, multi-dimensional GUI.
-8 Pandas-
There is a long list of Python packages designed for working with complex data sets. But arguably, Pandas is the most important. Pandas helps you manipulate and analyze large sets of data without having to learn a specialized data-processing language like R.
I also made a coronavirus data science program using pandas. I recommend Pandas actually.
Pandas has its limits in that itââ¬â¢s not intended for advanced statistical modelling (in that case, you would want to learn R, or use a Python package like statsmodels). But if you need to do things like process time-series data or perform statistical analysis on a data set, Pandas has you covered.
-9 Pywin32-
For Windows Python programming in particular, Pywin32 is a must-have package. It provides access to many of the native Windows API functions, allowing you to do things like interact with the Windows registry, use the Windows clipboard, and much more.
Pywin32 wonââ¬â¢t do you much good if youââ¬â¢re building a cross-platform Python app, but Windows developers might find that they like it so much that they use it instead of native Windows tooling.
So you need to use this if you want to add your win system to the project.
-10 Pytest-
If you have a Python development project of any complexity, being able to perform testing on new code is essential. The Pytest package provides a variety of modules to help you do this. Whether itââ¬â¢s a simple unit test or a more complex functional test, Pytest can help you write it.
So, this was all. Here we are at the ending. Thanks for reading. I hope you are more informed. Have a good day.
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