Bottle VS Toolz

Bottle.py: uber-fast and simple python web microframework, about 3x faster, saner, and more memory-efficient than Flask in my experience: https://github.com/bottlepy/bottle

Fossil: distributed version control and much more in a single executable, from the creators of SQLite: https://fossil-scm.org/

This walkthrough I am using as learning material says the vulnerable code (in the first snippet below, from github here: https://github.com/bottlepy/bottle/issues/900), is replicated in the webpage in the second snippet below and so I know this app is vulnerable to the exploit shown in highlighted in the github link.

Here's a web framework in a single file: bottle.py

I don't do much development for microcontrollers or limited resource environments, but it's nice to have a low boilerplate tool for throwing together quick web apps. I've used Bottle for that in the past. It looks like this might have more of an API focus, rather than templates or static pages? Very cool, will check it out.

However much makes sense for your project. bottle.py is a web framework in a single file, and it's about 4500 lines of code. Should you do the same thing? Probably not. But you can.

There was a time, I want to start a new project and have to choose what technologies to use for the frontend and backend parts as well. Research gets me to Aqueduct and Shelf, both of them weren't looking actively developing and supported and that leads me to the idea to make my own small micro-framework like Echo for Golang or Bottle for Python. And it was easy to decide: I've had time and motivation :)

It was developed by Marcel Hellkamp and Bottle was initially released on July 1 2009 it is cross-platform and open-source. its Github repository is https://github.com/bottlepy/bottle. It is integrated with Python, Vue JS, and Jinja.

My favourite lib would probably be toolz, it's just so elegant and fun to use. But it's more functional approach is not always the best fit for the time, so in practice I mostly use it in research, prototyping, console and notebooks.

I am not new to Python but only used it to write scripts. Should I start a Python book and then a PySpark book or go directly to PySpark? When reading the legacy code, I found there are usages like GitHub - pytoolz/toolz: A functional standard library for Python. I never heard of.

toolz is wildly useful https://github.com/pytoolz/toolz

Maybe the toolz[0] family would cover your use cases? There is also a Cython implementation if you need better performance.

[0] https://github.com/pytoolz/toolz/

You'll probably enjoy toolz.