modern-elt-demo VS black

There's this bootcamp https://dataengineercamp.com/ I haven't taken it myself, though I've seen some of the content (which was very good). Jonathan who runs it is a great guy and great at teaching too!

How is https://dataengineercamp.com/ ? The course is from Australia

Amazing post, lots of great tips and a comprehensive breakdown. Are these covered in https://dataengineercamp.com/?

With that, I am deciding whether: - to take up a Masters in Information Technology in one of the schools here in our country (An anonymous draft of the program can also be sent to hide the identity of the school), or - enroll in this bootcamp (https://dataengineercamp.com/) since based on some reviews and my limited knowledge, this could be a great help for me if I ever decide to find better opportunities.

P.S. I teach a data engineering bootcamp, if you'd like to learn more check out Data Engineer Camp.

If you're looking for a data engineering bootcamp, why not check out https://dataengineercamp.com/

Hello there, I'd suggest checking out Data Engineer Camp if you haven't already. Our next cohort is kicking off July/August 2023. Student testimonial here.

If your interest to become an applied data engineer and do data engineering for a company, then research (PhD) might be overkill. Having a computer science background (degree, or masters, or bootcamp) is sufficient. Most of the learnings will come from being on the job and learning data engineering patterns. I would recommend two books that are great at diving deeper into this topic: Fundamentals of Data Engineering, and Designing Data Intensive Applications. If you are looking for a course that introduces you to the concepts of data engineering, check out Data Engineering Zoomcamp. Disclaimer, I teach a paid data engineering bootcamp called Data Engineer Camp for people that want to be trained by experienced practitioners.

I was looking for some courses online about data engineering, and I came across this bootcamp from Australia (Data Engineer Camp. Has someone ever heard of it or taken it? The curriculum looks solid and the structure seems to be fine. The price is around usd$2,900, not that bad in comparison with other bootcamps, and has payment options.

Hey there, not a masters degree, but I teach a 14 week data engineering bootcamp if you're interested to find out more: https://dataengineercamp.com/

$ git commit -m "add pre-commit configuration" [INFO] Initializing environment for https://github.com/psf/black. [INFO] Installing environment for https://github.com/psf/black. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... black................................................(no files to check)Skipped [main 6e21eab] add pre-commit configuration 1 file changed, 7 insertions(+)

Black: Known as “The Uncompromising Code Formatter”, Black automatically formats your Python code to conform to the PEP 8 style guide. It takes away the hassle of having to manually adjust your code style.

black @ git+https://github.com/psf/black

In the realm of Python development, there is a multitude of code formatters that adhere to PEP 8 guidelines. Today, we will briefly discuss how to install and utilize black.

Perfect, that worked, thank you!

I thought this could be solved by changing the directory to src/ and then executing that command, but this didn't work.

This also seems to be an issue with the web app, e.g. the repository for the formatter black is only one white dot https://dep-tree-explorer.vercel.app/api?repo=https://github...

Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.

What I am looking for is something like Black for Python, which is opinionated, with reasonable defaults, and auto-fixes most/all issues.

1. LICENSE: This file contains information about the rights and permissions granted to users regarding the use, modification, distribution, and sharing of the software. I already had an MIT License in my project. 2. pyproject.toml: It is a configuration file typically used for specifying build requirements and backend build systems for Python projects. I was already using this file for Black code formatter configuration. 3. README.md: Used as a documentation file for your project, typically includes project overview, installation instructions and optionally, contribution instructions. 4. example_package_YOUR_USERNAME_HERE: One big change I had to face was restructuring my project, essentially packaging all files in this directory. The name of this directory should be what you want to name your package and shoud not conflict with any of the existing packages. Of course, since its a Python Package, it needs to have an __init__.py. 5. tests/: This is where you put all your unit and integration tests, I think its optional as not all projects will have tests. The rest of the project remains as is.

using pylint and black ("the uncompromising code formatter")