MyAnimeList.net manga and anime trend data.

This project collects manga and anime data from MyAnimeList.net for the purpose of tracking current and historical popularity trends. The data is provided in the jsonlines format.

You can download the latest files here:

These files are automatically updated every week.

The schema of these records is expressed in the following schema files:

You can read and work with the data files from this project as-is, line-by-line. Each line is a JSON array containing a record's values. There is no need to even load the entire file into memory if your use-case does not require it - simply read and work with one line at a time.

By storing only values instead of highly redundant dictionaries (i.e. keys and values), we are able to achieve a massive reduction in file size while still retaining the ability to express the complex structure of these records in JSON. If you would prefer to convert these records into dictionaries/objects, a reference implementation is provided below.

The reference implementation below uses the manga.json schema file to convert records from the manga.jsonl file into dictionaries/objects.

import json
from pathlib import Path

def map_schema(value, schema):
    if type(schema) is list:
        return [map_schema(v, schema[0]) for v in value]
    if type(schema) is dict:
        kvs = zip(schema.keys(), value, schema.values())
        return {k: map_schema(v, s) for k, v, s in kvs}
    return value

with open(Path('schema') / 'manga.json') as file:
    schema = json.load(file)

with open(Path('data') / 'manga.jsonl') as file:
    records = [map_schema(json.loads(line), schema) for line in file]

The records variable should now contain the records as dictionaries.

See the LICENSE file before using any of the files provided by this project in your own work.