Python is popular because of it's simplicity, flexibility and readability. There is also a large open-source community and a huge range of libraries and modules that can make it easy for people to create programs and scripts and work more efficiently.
- Python has a range of uses such as web development particularly the backend with frameworks such as Django and Flask.
- Python is also used in data science with AI/ML libraries such as SciPy and Scikit-Learn.
- Python can be used in automation testing using tools such as PyUnit and Pytest.
- Also, Python can be used to develop games using a library such as pyGame.
Python is being used by individuals for personal projects, small start-ups due to open-source nature, all the way to large companies and businesses such as Google, Facebook, Amazon and Microsoft.
For example, Amazon use Python in their 'deal recommendation system' which uses AI and ML to analyse and recommend products to users.
Python is in demand due to it's flexibility, readability, and diversity. It is also easy to learn and use so many developers and people in the tech industry can pick it up quickly.
Python is used in a range of jobs, an example list of some job roles is shown below:
- Data scientist
- Data analyst
- Software engineer
- DevOps engineer
- Web developer
- Machine learning engineer
Overall, these jobs which use Python as a key skill demand a high salary. For example an average salary for a Python developer demands between £45,000 to £80,000 (talent.com, 2023)
Python is used in the field of DevOps because of it's ease-to-use, making it easy and quick to use and script when needed. It is also very versatile and can be integrated into APIs quite easily, especially due to the community constantly updating features and adding libraries and APIs for existing software. For example, Cisco have developed their own Python API.
Scripting is focusing on solving a specific task and looks to automate it via a (usually small) piece of code, especially manual tasks performed by humans. This is different to programming, which looks to solve more complex use cases and tasks.
The key difference between scripting and programming is the scope of what they try to achieve.
There are many use cases for scripts, some examples are web-scraping, testing, data analysis and processing and system/server administration.
Python is used as a scripting language, as mentioned, because of its ease-to-use, simple and easy to follow syntax. Since scripting is usually small bites of code written for a range of applications, it needs to be platform-independent, which a language such as Python is. (other languages that are not platform independent are C or C++ so are not a good choice)
Scripting is important for DevOps Engineers to automate tasks and simplify processes in their workflows.
This ultimately saves time and reduces human errors through automation of tasks such as deployment, configuration management, monitoring and testing.
- Testing scripts for continuous testing and integration.
- Compliance scripts to ensure systems meet regulatory requirements.
- Log analysis scripts for troubleshooting and debugging issues.
- Deployment scripts for CI/CD pipelines.
- Configuration management scripts using tools such as Ansible.
- Monitoring scripts to check the health of systems such as cloud servers.
- Backup scripts for databases and other critical data.
- Security scripts for vulnerability scanning and patch management.
- Scaling scripts for auto-scaling infrastructure based on demand (e.g. lambda functions).
- Network automation scripts for managing network equipment (switches, routers, and firewalls).