Python has been the buzzword in any programmer’s vocabulary for some years now, but why? In order to answer this question, let’s start at the beginning. What is Python?
It is an open source programming language , object oriented, very simple and easy to understand. It has a simple syntax that has a vast library of tools, which makes Python a unique programming language.
One of the main benefits of learning Python is the ability to create highly readable code, which saves time and resources, making it easier to understand and implement.
These factors, and others that we will see later, have made Python one of the most widely used programming languages. From web applications to artificial intelligence, the uses for Python are endless.
These are the main industries that use this programming language:
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Python In Artificial Intelligence (AI)
Python is a fast, scalable, robust and open source writing language, advantages that make Python a perfect ally for Artificial Intelligence.
It allows you to capture complex ideas with a few lines of code, which is not possible with other languages.
There are libraries like ” Keras ” and ” TensorFlow “, which contain a lot of information about the functionalities of machine learning.
In addition, there are libraries provided by Python, which are widely used in AI algorithms such as Scikitl, a free machine learning library that features various regression, classification, and grouping algorithms.
But above all, Python is a free open source language with a large active community, which provides support to any programmer. All of these reasons combined make learning Python an easy choice over other languages for artificial intelligence applications.
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Python In Big Data
The use of it is very widespread in data analysis and the extraction of useful information for companies.
In addition to its simplicity, which is a great advantage, Python has data processing libraries such as ‘ Pydoop ‘, which are of great help for professionals, as you can write MapReduce code in Python and process the data in the cluster. HDFS.
Other libraries such as “Dask” and “Pyspark” make data analysis and management even easier. Python is fast and easily scalable, features that help you generate information in real-time environments and convert that information to the languages used in Big Data.
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Python In Data Science
Since the introduction of Python’s numeric engines like ‘Pandas’ and ‘NumPy’, researchers have switched to Python from the previous language, MATLAB.
It handles tabular, matrix, and statistical data, and even visualizes it with popular libraries like “Matplotlib” and “Seaborn.”
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In Test Frameworks:
Testing is another activity that has been switched to it.
It is ideal for validating ideas or products, as it has many built-in frameworks that help debug your code and offer fast execution and workflows.
Testing tools like ‘Unittest’, ‘Pytest’ and ‘Nose test’ make testing easier. It also supports cross-platform and cross-browser testing with different frameworks, such as “PyTest” and “Robot”.
Testing, which is usually one of the most arduous tasks, becomes something much simpler and faster.
In Web Development:
It allows you to build much more with fewer lines of code, so you can prototype more efficiently.
The Django framework, provided by it, is an advantage for all developers, as it can be used to create dynamic and highly secure web applications.
The Python language is also used for scraping, that is, obtaining information from other websites. Applications like Instagram, Bit Bucket, Pinterest are built on frameworks of this type.
The uses and applications of it lie far beyond the fields mentioned, from game development to data visualization, from networking to general software development. Python applications are numerous.
If you are a developer or want to dedicate yourself to one of the fields that we have talked about in this post, It is one of the languages that you must learn and master to work on the most cutting-edge technological projects.
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The labor market trend shows that the demand for Python professionals grows exponentially every year.
Proof of this is the report from the Stack overflow website, a reference website for developers around the world, with more than 40 million monthly users, which has presented the evolution of the volume of searches by type of language, and which shows that, clearly, Python is in the lead.