Skip to main content

# LLAMA SLOBBER

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.

## Name Origin

[Learned League](http://www.learnedleague.com) is a website hosting a series of on-line trivia tournaments (see this [Washington Post article](https://www.washingtonpost.com/lifestyle/style/the-coolest-weirdest-internet-community-youll-never-be-able-to-join/2014/08/20/3c3f565e-26eb-11e4-958c-268a320a60ce_story.html?noredirect=on&utm_term=.16ba008490a5) 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](https://sabr.org). 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.

## Installation

Llama_slobber has been packaged on the [Python Package Index website](https://pypi.org) 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.

## logindata.ini file

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.

## USAGE

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

`python 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'])) `

## Other files in this directory

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.

## Futher Documentation

## Author

## License

This project is licensed under the MIT License

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llama_slobber-1.0.9.tar.gz (15.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

llama_slobber-1.0.9-py3-none-any.whl (27.9 kB view details)

Uploaded Python 3

File details

Details for the file llama_slobber-1.0.9.tar.gz.

File metadata

  • Download URL: llama_slobber-1.0.9.tar.gz
  • Upload date:
  • Size: 15.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/28.8.0 requests-toolbelt/0.8.0 tqdm/4.27.0 CPython/3.6.2

File hashes

Hashes for llama_slobber-1.0.9.tar.gz
Algorithm Hash digest
SHA256 11a334369e80afba724b58de64538058ca6f3fdd3eb2b158dee78e4ddb3fe38a
MD5 0bdc224fddcdcdee01f4ad57e4362ca5
BLAKE2b-256 b4c043436dcca8dacd94ef650b8760a63c057788571ccc178b32fcf993c68223

See more details on using hashes here.

File details

Details for the file llama_slobber-1.0.9-py3-none-any.whl.

File metadata

  • Download URL: llama_slobber-1.0.9-py3-none-any.whl
  • Upload date:
  • Size: 27.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/28.8.0 requests-toolbelt/0.8.0 tqdm/4.27.0 CPython/3.6.2

File hashes

Hashes for llama_slobber-1.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 452a92ec91abe58de9f9334cafdbf54d60cc11c0c5f446cd19300f787ce54504
MD5 cfd162ccbe652f99d9a4c4f9fb3ebe86
BLAKE2b-256 a64bd757b4c28f4dd6cd850810ec3cfddc134ad84d81afe2ee54990b05dd9b32

See more details on using hashes here.

Release history Release notifications | RSS feed

1.0.27

2 files

1.0.14

2 files

This release

1.0.9 This release

2 files

1.0.8

2 files

1.0.7

2 files

1.0.1

2 files

1.0.0

2 files

0.0.95

2 files

0.0.92

2 files

0.0.91

2 files

0.0.72

2 files

0.0.71

2 files

0.0.70

2 files

0.0.60

2 files

0.0.59

2 files

0.0.58

2 files

0.0.57

2 files

0.0.55

2 files

0.0.52

2 files

0.0.50

2 files

0.0.49

2 files

0.0.48

2 files

0.0.47

2 files

0.0.40

2 files

0.0.35

2 files

0.0.34

2 files

0.0.33

2 files

0.0.32

2 files

0.0.28

2 files

0.0.25

2 files

0.0.18

2 files

0.0.17

2 files

0.0.15

2 files

0.0.9

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page