CI/CD: There are a number of robust testing frameworks, including PyTest, Nose, and the newer Ward. Python also integrates beautifully into most CI/CD frameworks, especially given the relative ease of deploying a package. (On that note, many Python projects even automate publishing their package to the Python Package Index using GitHub Actions or the like.)
Security Scanning: Bandit is one prominent example, and I know there are others.
I don't know about Lifecycle-Management, as I haven't used it, but a casual glance through the Python Package Index, or PyPI, it looks like there are plenty of options.
It's a common myth that Python isn't suitable for large projects. In fact, there are a number of very large applications and libraries built entirely in Python. It has its flaws, but Python is often excellent for software architecture and deployment because it "just works" in most situations, and aims to be intuitive while staying out of your way.
A Freelance DevOps doing container stuff and automating unhealthy amounts of software.
Need something automated or containerized? Feel free to hit me up :)
Thank you for your take, you never stop learning!
I guess I'll spend this weekend on Python and taking a look at the tools you mentioned.
The last time I had any python on my screen was when I wrote custom ansible filters and a few shallow dips into Django, which confused the hell out of me.
It's about time for a refresher :)
CI/CD: There are a number of robust testing frameworks, including PyTest, Nose, and the newer Ward. Python also integrates beautifully into most CI/CD frameworks, especially given the relative ease of deploying a package. (On that note, many Python projects even automate publishing their package to the Python Package Index using GitHub Actions or the like.)
Security Scanning: Bandit is one prominent example, and I know there are others.
I don't know about Lifecycle-Management, as I haven't used it, but a casual glance through the Python Package Index, or PyPI, it looks like there are plenty of options.
It's a common myth that Python isn't suitable for large projects. In fact, there are a number of very large applications and libraries built entirely in Python. It has its flaws, but Python is often excellent for software architecture and deployment because it "just works" in most situations, and aims to be intuitive while staying out of your way.
Thank you for your take, you never stop learning!
I guess I'll spend this weekend on Python and taking a look at the tools you mentioned.
The last time I had any python on my screen was when I wrote custom ansible filters and a few shallow dips into Django, which confused the hell out of me.
It's about time for a refresher :)
You may appreciate this, then:
Introducing "Dead Simple Python"
Jason C. McDonald ・ Jan 13 '19 ・ 3 min read