colorama VS Airflow

Try using https://github.com/tartley/colorama, that should straighten out most low level problems. If you still have issues, you need to adjust your color scheme in pycharm.

Pyshark: https://github.com/KimiNewt/pyshark Requests: https://github.com/psf/requests Colorama:https://github.com/tartley/colorama

from colorama import Fore, Style # Colorama doesn't support Underlined text because it # is struggling to make it work for windows users # https://github.com/tartley/colorama/issues/38 print(Fore.RED + Style.BRIGHT + 'Danger' + Style.NORMAL)

There are obviously a lot of libraries in python that color text, but I never loved their syntaxes, so I ended up creating this one a few years back. For comparison, this is how you print a red, bold, underlined string in **terminology**\: from terminology import in_red print(in_red('Danger').in_bold().underlined()) and this is how you do it with the other alternatives: **colorama** from colorama import Fore, Style # Colorama doesn't support Underlined text because it # is struggling to make it work for windows users # https://github.com/tartley/colorama/issues/38 print(Fore.RED + Style.BRIGHT + 'Danger' + Style.NORMAL)

The link to its github repository is this: colorama.

Escape sequences may vary depending on the terminal you use. You can try some package like Colorama which escapes those sequences and gives you the correct color in Windows. There is also Blessings.

As I mentioned earlier, Hype doesn't rely on any third-party library but then there are some plugins that third-party library powered Hype. For example, the color printing that is powered by colorama.

Looks really cool! Way more functionality than I'd ever need. I've been using colorama for color coding info, warning, and error messages in my Python projects. No complaints. From the feature list of rich it sounds like it probably pulls in a lot more dependencies?

Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.

In week Two, I contributed to the Apache Airflow repository.

Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.

Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.

AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!

I agree there are many options in this space. Two others to consider:

- https://airflow.apache.org/

- https://github.com/spotify/luigi

There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…

You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte