https://github.com/heroickatora/doransguide

An ItemAPItizer for the popular game League of Legends, aka useful Item statistics
https://github.com/heroickatora/doransguide

Last synced: 2 months ago
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An ItemAPItizer for the popular game League of Legends, aka useful Item statistics

• Host: GitHub
• URL: https://github.com/heroickatora/doransguide
• Owner: HeroicKatora
• Created: 2015-08-25T08:22:36.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2015-09-01T08:25:22.000Z (over 9 years ago)
• Last Synced: 2025-01-26T01:46:24.350Z (4 months ago)
• Language: Python
• Size: 79.2 MB
• Stars: 0
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Doran's Guide

**Website: **

## Description

Doran's guide is a complete guide to item usage as well as a comparison for it 

between different data sets (more on this later). It parses thousands of games

and extracts the item related data from them to create very detailed and 

extensive statistics about their power.

These statistics are then visualized on a web page on which the viewer can also

choose to compare statistics based on one key value. Game data is sorted by

* Version

* Region

* Map

* Queue type

* Participant's rating

* Champion

* Item

But most importantly, instead of just giving the win rate or rate of item usage,

Doran's guide actually shows how these two key values depend on the time and

gold difference at the moment of purchase. This enables players to make more

sophisticated choices about when to buy which item. 

## Documentation

Usage of this project:

1. Run gamedownloader.py (to terminate the download process, press Enter)

2. Run gameanalyer.py (wait or interrupt the script when it's analyzing)

When using the scripts, you will most likely want to set the working directory

as src, since the scripts generate their data into the relative path ../data.

Also, every script that uses the Riot Api needs to be started with the argument

> -k {api-key}

to work properly. Otherwise, it will exit on start-up.

### gameanalyser.py

This python script uses the data generated by gamedownloader.py to generate the

analytical data that contain all data about item usage. Individual item events

are analyzed through the data that they hold.

 1. Version of the game

 2. Region in which the game was played

 3. Map on which the game was player

 4. Queue type in which the event took place

 5. Participant's rating

 6. Champion that the player played

 7. Item that was acquired by the player

 8. Time stamp of the item event, in 10 minute intervals

 9. Gold difference of the player's team relative to the enemy team, in 3k gold intervals

Command line arguments:

option | arguments | effect

-------|:-----------:|-------

-k | apiKey | [required] Tells the application what api-key to use.

The generated analysis is grouped into files and written to disk in blocks,

in order to save memory and a summary for each block is printed to the console. 

Each file follows the following rules:

* It is located in data/analysis/{region}/{patch}/{mapId}

* Its name is {queue type}.{ranking}.json

* Inside is a map in json format. Keys are string of the format

  

  {region}/{patch}/{mapId}/{queue type}/{ranking}/{championId}/{itemId}/{role}/{lane}

  

  For each of these parts, the values given by the Riot Games api as well as 

  the special key 

  > ANY

  

  are valid.

* The values of the map are json object with the four properties

  * timeAndGoldTable

  * timeTable

  * goldTable

  * winStatistic

  

  The first three contain a list, the last one a single instance of a WinStatistic,

  a list with exactly two entries. The first entry of a WinStatistic is the number

  of games played, the second one the number of games won. 

  timeAndGoldTable is the flat representation of a two dimensional map 

  > map[timeInterval][goldDifference].

### gamedownloader.py

This module loads the game data available from riot. It expects a folder structure

as in the .zip archive provided for the AP Item Category inside the folder itemsets.

It then loads one game after the other in round robin style extracting all item events

from the time line by analyzing each players inventory over the course of each game.

The events are then pickled into the directory data/raw the await further processing.

Command line arguments:

option | arguments | effect

-------|:-----------:|-------

-k | apiKey | [required] Tells the application what api-key to use. The downloader will automatically change its speed when receiving 429 codes.

-f | --- | Retry previously failed game. By default, the downloader will skip game ids that failed in previous runs

### Other modules

Name | Use|External packages

-----|----|-------

analysis| Contains all data types necessary for the gameanalyser to work correctly|

lolstatic| Gathers some data dynamically from the api but also has Enums to represent basic data types|

matchinfo| Extracts data from a match|

math| Some (unused) wrappers for bisection and ordered arrays|

riotapi| Contains wrapper code for the connection to the endpoint. For example, it limits the amount of accesses to a data point already overloaded or keeps connections alive for reuse| urllib3, certifi  

## Planned

Switching to a database and a web server would give the freedom to index the

game data by a few more key parameters, e.g. the role and lane of the player.