> For the complete documentation index, see [llms.txt](https://openrarity.gitbook.io/developers/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://openrarity.gitbook.io/developers/quick-guides/integrating-openrarity-in-your-application.md).

# Integrating OpenRarity in your application

To use OpenRarity library with your own NFT datasets use following code snippet in your application:

```python
# OpenRarity version 0.4.0-beta
from open_rarity import (
    Collection,
    Token,
    RarityRanker,
    TokenMetadata,
    StringAttribute,
)
from open_rarity.models.token_identifier import EVMContractTokenIdentifier
from open_rarity.models.token_standard import TokenStandard

# Create OpenRarity collection object and provide all metadata information
collection = Collection(
    name="My Collection Name",
    attributes_frequency_counts={
        "hat": {"cap": 1, "visor": 2},
        "shirt": {"blue": 2, "green": 1},
    },
    tokens=[
        Token(
            token_identifier=EVMContractTokenIdentifier(
                contract_address="0xa3049...", token_id=1
            ),
            token_standard=TokenStandard.ERC721,
            metadata=TokenMetadata(
                string_attributes={
                    "hat": StringAttribute(name="hat", value="cap"),
                    "shirt": StringAttribute(name="shirt", value="blue"),
                }
            ),
        ),
    ],
)  # Replace inputs with your collection-specific details here


# Generate scores for a collection
ranked_tokens = RarityRanker.rank_collection(collection=collection)

# Iterate over the ranked and sorted tokens
for token_rarity in ranked_tokens:
    token_id = token_rarity.token.token_identifier.token_id
    rank = token_rarity.rank
    score = token_rarity.score
    print(f"\tToken {token_id} has rank {rank} score: {score}")

```

If you don't have internal datasets , consider using OpenSea api to provide collection data. This example using library helper methods that are resolving collection/token information from OpenSea API:

```python
# OpenRarity version 0.4.0-beta
from open_rarity import RarityRanker
from open_rarity.resolver.opensea_api_helpers import (
    get_collection_from_opensea,
)

slug = 'proof-moonbirds'
# Create OpenRarity collection object from OpenSea API
collection = get_collection_from_opensea(slug)

# Generate scores for a collection
ranked_tokens = RarityRanker.rank_collection(collection=collection)

# Iterate over the ranked and sorted tokens
for token_rarity in ranked_tokens:
    token_id = token_rarity.token.token_identifier.token_id
    rank = token_rarity.rank
    score = token_rarity.score
    print(f"\tToken {token_id} has rank {rank} score: {score}")

```


---

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