Cloud computing is the on-demand delivery of computing and IT resources hosted by third-party cloud service providers over the Internet. The benefits of migrating to the cloud are many. Migrating to the cloud speeds up app development. It helps companies modernize, transform digitally, and connect with people efficiently from anywhere.
The demand for cloud experts is growing. If you want a career in this field, mastering programming languages is essential.
Python was once obscure but is now the most in-demand coding language in cloud computing.
Learn Python for cloud computing and give your career a boost.
What is Python?
Python, developed by Guido van Rossum, is a popular language with dynamic semantics. It is best for data science, machine learning, software development, and web app development.
It’s a multi-purpose language, and the source code is free to download. Python syntax is similar to natural languages and is easy to read.
The basics are brain-friendly and straightforward, making it easy for beginners to master coding.
Here are some use cases of Python:
- Server-side web development
- Automation with Python Script: Automation with Python Script includes automating mailouts, renaming many files at once, basic log analysis, file conversion, and checking for word duplication.
- Data Science and ML: Data labeling, data cleaning, identifying data attributes, data visualization, etc.
- Software Development: Debugging software, automating development processes, prototyping, project management, and developing games and mobile apps.
- Software Test Automation
Features and Benefits of Python
- High-level Language: Python is a high-level language. It converts code to machine language automatically, so you don’t need to handle low-level operations, garbage collection, or memory management.
- Interpreted: Python is interpreted. Before running code, the Python VM converts it into bytecodes. Python implementations can freely and directly execute instructions line by line without transforming them into machine languages.
- Open-source: Python’s source code is open and free to download, distribute, or modify, even for commercial purposes.
- Dynamically Typed: Python assigns variable types at runtime based on the variable’s value, so you don’t need to declare types when writing code.
- Multi-paradigm Programming Language: Python supports structural and object-oriented programming completely and functional and aspect-oriented programming partially.
- Portability and Cross-platform Compatibility: Python scripts run on almost all major operating systems, including Windows, Linux, and Mac OS X, without needing modifications.
- Extensible and Embedded: Python codes can integrate with codes written in other languages, such as C or C++, and compile them together.
Python Libraries
Python may seem dense due to its many modules and libraries, but it is easy to understand.
Python includes a standard library with over 200 core modules. Additionally, there are more than 137,000 libraries for faster and more accurate project execution. Just import actions from the modules into your code and run them; no need to write a program from scratch.
Here are some popular Python libraries:
- Numpy: Used for working with arrays, performing Fourier transformation, linear algebra, manipulating logical shapes, etc.
- Keras: A high-level ML API great for implementing neural networks.
- Matplotlib: Used for high-quality 2D/3D graphical plotting and data visualization.
- Pandas: Best for Machine Learning, data analysis, and Data Science applications.
- PyTorch: Great for deep learning research that accelerates neural network implementation.
Python Frameworks
Python frameworks are built-in modules and packages that facilitate web application development.
Some of the most used frameworks in Python are:
- Django: A full-stack, open-source web development framework with ready-to-use libraries. It supports authentication, web servers, and a template engine for website development. Its ORM allows code to run in many databases.
- Dash: A micro-framework for analytical web application development. Dash-based apps are mainly web servers that run Flask and interact with JSON packets via HTTP requests.
- Flask: A popular micro-framework that supports a template engine, unit testing, and inbuilt web servers for small web app development.
- Apache MXNet: An open-source deep learning software framework that supports different languages, great for developing deep learning apps and research prototypes.
Python IDE
An IDE is an Integrated Development Environment for writing, editing, debugging, and executing Python codes.
Popular Python IDEs are:
- IDLE: Python’s default IDE.
- PyCharm
- Pydev
- Sublime Text 3
- Spyder
- Atom
Why Learn Python for Cloud Computing
Python use is skyrocketing. Developers find it to be the best tool for developing, testing, and deploying data-intensive applications. It is used in IoT networks and robot automation.
In 2018, there were about 7 million Python developers worldwide. By April 2019, this number grew to over 8 million, surpassing Java developers.
Today, many cloud-based applications are built on Python. One significant advantage of developing applications in Python is that it allows developers to deploy apps on virtually any platform, including the cloud.
Python is highly readable. It helps experts categorize data and power data analytics. This makes Python a favorite among data scientists and app developers for analytics-based and IoT applications in the cloud.
Another reason Python is a favorite is that it supports imperative programming, which promotes code modularity. With Python, experts can write concise functions to execute complex tasks. These functional techniques are less verbose than other paradigms and work seamlessly with external systems.
Python makes it easy to write scripts for provisioning infrastructure with CSP’s SDKs. All major CSPs offer SDKs for Python. For example, AWS SDK for Python is called boto3. It is an API that helps developers manage AWS resources or services like SQS, EC2, S3, Identity management, SES, and AWSKMS from their Python scripts. Plus, AWS Lambda supports Python 3.9 runtime, making it a great tool for building serverless applications on AWS.
Google Cloud infrastructure also uses Python extensively. Python integrates seamlessly with Cloud Trace, Cloud Monitoring, Error Reporting, and Cloud Logging. These tools help developers find software bugs and analyze performance issues.
So, anyone interested in data science, Machine Learning, or Artificial Intelligence should learn Python. And if you work in a company that uses Google Machine Learning services or AWS resources, you must learn Python for cloud computing.
If you want to put these cloud computing skills into practice without a financial barrier, enrolling in a free cloud computing course with certificate is a smart, concrete next step. Earning a recognized credential not only validates your knowledge but also strengthens your resume as you transition into data science, ML, or AI roles. Many of these programs walk you through real-world scenarios, giving you the hands-on experience employers actually expect — all at no cost to you.
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