Welcome back to our two-part series where we pose questions from the Community to three Python developers from Sonar.
As part of our celebration of all things Python during April we took the opportunity to sit down with Nafiul, Cheng, and Yaniv, three Python fans with different roles at Sonar, and get their take on questions submitted by our Community. You can check out Part 1 here.
Tooling is quite good in Python although it isn't as good as Java in some cases. I mainly use PyCharm as my main IDE, and I have a few plugins installed like AceJump and SonarLint; I don't use much else. I think the place where Python could see a lot of improvement is packaging and package management.
I think the tooling of Python is very, very mature. On the IDE side you have two big options: VS code and PyCharm… VS Code is very good and meets most needs. I was a VS code user, and now I'm using PyCharm and I love it! When I do a lot of scientific computing I also use Spyder which is a specialized IDE for that.
With a huge and dynamic community, Python has a ton of packages that you can explore for almost everything that you could think of, and why not wrap your codes into a package and share it in the community, so everyone can use it?
The Python community stands out as the largest among other programming languages, if I may say so, making it a highly mature programming language. It is evident when encountering a problem or aiming to write a specific code; chances are high that someone has already tackled it within the community. Due to the popularity of Python, there is a demand for great tooling and many companies are after that demand.
My personal environment is very dependent on my project, usually, I'll use a simple script so it will be one file and probably IDLE/VS code. In case I program a bigger project I'll move to a more organized manner using GIT, PyCharm, Pyvenv, etc.
It’s not just one thing, but the fact that Python is constantly getting better. For example, we now have PyScript, which allows you to build front-end applications with Python. Pandas has a sort-of upgrade with a new library called Polars which allows you to do everything that you can do in Pandas but much faster. However, most importantly, the CPython interpreter itself is getting faster and faster with each release.
Here is a Tweet from PyPI regarding how much compute they were saving when they upgraded to Python 3.11, which introduced many performance enhancing features.
My first thought was the introduction of dataclasses in Python 3.7, but then I think the type hints from Python 3.5 are a more impactful change. Type hints greatly improve the code readability and let you spot mistakes easier before running the code. Several popular static type packages like mypy and pydantic also directly benefit from it. This complements Python's flexibility as a dynamically typed language.
Python type hints have been constantly evolving since their introduction and something that I liked recently is the explicit type alias and the simplified type union annotation introduced in 3.10. I'll give an example in the ML world. In ML we talk a lot about vectors, labels, samples, datasets…
A vector is a list of float or int numbers:
A label could be a boolean, an integer, or a string. A label could also be missing (None):
A data sample is a tuple of a vector and a label:
A dataset is a list of data samples:
Then we define a method train_model which takes in a dataset as argument and train the model, I can write
Without explicit type alias, I would write (a bit harder to read):
I know we are working to leverage Python type hints into our Sonar solution. This will be great, as I believe that knowing (somehow) the types of variables and methods will help the analysis be even more accurate and efficient.
I don't follow updates and changes in Python. For me, Python already has everything I need 😉.
A big thank you to Nafiul, Cheng, and Yaniv, three of Sonar's very own Python developers.
We discovered their views on tooling and what recent changes have excited them the most (and that Yaniv already has everything he needs 😀).
At Sonar we want to deliver solutions that add value to developers and help them create Clean Python Code. Follow us to learn more, or download our free and open-source plugin SonarLint from your favorite IDE marketplace to try it for yourself.
Nafiul Islam, programming since 14, has a decade of software experience. Adept in Python and exploring Rust, he authored "Mastering PyCharm" at 21. Nafiul has spoken at global Python conferences and held positions at JetBrains and Microsoft. In his free time, he loves reading fantasy novels. Follow him @gamesbrainiac on Twitter.
Cheng Chen trained as a computer scientist, Cheng has been working in machine learning and artificial intelligence since 15 years ago in different industry branches such as computer vision, FMCG, digital manufacturing, and biometrics. He recently joined Sonar to explore ML for code analysis.
Yaniv Nizry is a Vulnerability Researcher at Sonar where he leverages his expertise to identify and mitigate vulnerabilities in complex systems. Starting his way as a software engineer, he shifted his focus while serving in the IDF's 8200 unit, where he gained experience in both offensive and defensive cybersecurity tactics.
Enjoy all things Python, and want more? Register now for our upcoming webinar Clean Code for your Python projects, with Nafiul Islam - Wednesday, May 10th - 5 PM CEST / 10 AM CDT.