Llama_slobber is a package of python3 tools useful for Learned League data analysis.
It consists of screen scraping routines which can be used to extract data from Learned League web pages, calculation routines for various Llama Slobber statistics, and some formatting routines to help generate web pages and csv files.
Learned League is a website hosting a series of on-line trivia tournaments (see this Washington Post article for more information). Due to the fact that Learned League starts with the letters LL, members of this league tend to refer to themsleves as llamas.
During some on-line discussion on this site, someone off-handedly refered to some members of the group as Learned League Sabrmetricians which definitely is the wrong term. Sabrmetrics refers to the analysis of baseball data performed by the Society of American Baseball Research. We were clearly different. So I have started the Society of Learnedleague Obscure and Byzantine Reseach (abbreviated SLOBR), and developed this package to aid others in doing analysis of Learned League data.
Llama_slobber has been packaged on the Python Package Index website and can be downloaded using the following
command: python -m pip install llama_slobber. It also requires the requests
packages, so if this is not installed, you should also run:
python -m pip install requests.
In order to use the tools in llama_slobber, one must be able to login to the Learned League website. So before any of these tools can work, the user must create a file named logindata.ini which would contain the following:
[DEFAULT]
username = <your Learned League user name>
password = <your Learned League user password>
This logindata.ini file should be placed in the directory from which the user's python code will be run.
All of the methods documented in the files listed in the Further Documentaion section of this document can be used by importing the method and calling the method with the appropriate variables. For example, the following code will caculate hun values for the B_Pacific rundle during season 78, and print the hun values for 'usuiw' as an html page
from llama_slobber import get_rundle_comp
from llama_slobber import gen_html_table
.
.
.
foo = get_rundle_comp(78, 'B_Pacific', 6)
print(gen_html_table('usuiw', foo['usuiw']))
Most of the other files in this directory are in the application subdirectory, which contains files that are used to produce the Llama Slobber website. (http://warrensusui.com/llama_slobber/main_page.html)
This project is licensed under the MIT License
FAQs
Slobr utilities
We found that llama-slobber demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Fluent Assertions is facing backlash after dropping the Apache license for a commercial model, leaving users blindsided and questioning contributor rights.
Research
Security News
Socket researchers uncover the risks of a malicious Python package targeting Discord developers.
Security News
The UK is proposing a bold ban on ransomware payments by public entities to disrupt cybercrime, protect critical services, and lead global cybersecurity efforts.