How are we suppose to use this library with a local dataset? #113
Description
I pulled this code down and have been very confused with the documentation on how to run it on a local data set. I'm looking at this piece of code below.
I have a CSV which has all the asset names along with the occurrences. What do I need to do to feed this data to calculate the rarities? Is it possible to just feed a dictionary with all the assets at once?
If you can show me an example of what I need to do that would be great!
Thank you!
from open_rarity import Collection, OpenRarityScorer, Token
from open_rarity.rarity_ranker import RarityRanker
if __name__ == "__main__":
scorer = OpenRarityScorer()
collection = Collection(
name="My Collection Name",
tokens=[
Token.from_erc721(
contract_address="0xa3049...",
token_id=1,
metadata_dict={"hat": "cap", "shirt": "blue"},
),
Token.from_erc721(
contract_address="0xa3049...",
token_id=2,
metadata_dict={"hat": "visor", "shirt": "green"},
),
Token.from_erc721(
contract_address="0xa3049...",
token_id=3,
metadata_dict={"hat": "visor", "shirt": "blue"},
),
],
) # Replace inputs with your collection-specific details here
# Generate scores for a collection
token_scores = scorer.score_collection(collection=collection)
print(f"Token scores for collection: {token_scores}")
# Generate score for a single token in a collection
token = collection.tokens[0] # Your token details filled in
token_score = scorer.score_token(collection=collection, token=token)
# Better yet.. just use ranker directly!
ranked_tokens = RarityRanker.rank_collection(collection=collection)
for ranked_token in ranked_tokens:
print(
f"Token {ranked_token.token} has rank {ranked_token.rank} "
"and score {ranked_token.score}"
)