calculate rarity score - nft-generator-py helper

rarity-score.py

import json
import csv
from collections import Counter

#
# example usage: python3 rarity-score.py
#

# Load the JSON data
with open('./output/metadata/all-objects.json') as f:
    data = json.load(f)

# Count the occurrences of each attribute value per trait type
attribute_counts = {}
for obj in data:
    for attribute in obj['attributes']:
        if attribute['trait_type'] not in attribute_counts:
            attribute_counts[attribute['trait_type']] = Counter()
        attribute_counts[attribute['trait_type']][attribute['value']] += 1

# Calculate the rarity score for each object
for obj in data:
    rarity_score = 0
    for attribute in obj['attributes']:
        rarity_score += 1 / attribute_counts[attribute['trait_type']][attribute['value']]
    obj['rarity_score'] = rarity_score

# Sort the objects by rarity score in descending order
data.sort(key=lambda obj: obj['rarity_score'], reverse=True)

# Write the data to a CSV file
with open('rarity_scores.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(['File Number', 'Rarity Score', 'Position'])
    for i, obj in enumerate(data, start=1):
        writer.writerow([obj['token_id'], obj['rarity_score'] * 6133, i])

# Calculate the count of each trait and its layer
trait_counts = Counter()
layer_trait_counts = {}
for obj in data:
    for attribute in obj['attributes']:
        trait_counts[attribute['value']] += 1
        if attribute['trait_type'] not in layer_trait_counts:
            layer_trait_counts[attribute['trait_type']] = {}
        if attribute['value'] not in layer_trait_counts[attribute['trait_type']]:
            layer_trait_counts[attribute['trait_type']][attribute['value']] = 0
        layer_trait_counts[attribute['trait_type']][attribute['value']] += 1

# Calculate the total number of traits
total_traits = sum(trait_counts.values())

# Write the data to a CSV file
with open('rarity_traits.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(['Layer Name', 'Trait Name', 'Count', 'Percentage'])
    for layer_name, traits in layer_trait_counts.items():
        for trait_name, count in traits.items():
            percentage = (count / total_traits) * 100
            writer.writerow([layer_name, trait_name, count, percentage])