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How to index the different contracts that share the same interface?

Multiple contracts can provide the same interface (like FA1.2 and FA2 standard tokens) but have a different storage structure. If you try to use the same typename for them, indexing will fail. However, you can modify typeclasses manually. Modify types/<typename>/storage.py file and comment out unique fields that are not important for your index:

# dipdup: ignore


class ContractStorage(BaseModel):
    class Config:
        extra = Extra.ignore

    common_ledger: Dict[str, str]
    # unique_field_foo: str
    # unique_field_bar: str

Note the # dipdup: ignore comment on the first line. It tells DipDup not to overwrite this file on init --overwrite-types command.

Don't forget Extra.ignore Pydantic hint, otherwise, storage deserialization will fail.

What is the correct way to process off-chain data?

DipDup provides convenient helpers to process off-chain data like market quotes or IPFS metadata. Follow the tips below to use them most efficiently.

  • Do not perform off-chain requests in handers until necessary. Use hooks instead, enriching indexed data on-demand.
  • Use generic http datasources for external APIs instead of plain aiohttp requests. This way you can use the same features DipDup uses for internal requests: retry with backoff, rate limiting, Prometheus integration etc.
  • Database tables that store off-chain data can be marked as immune, preventing them from being removed on reindexing.

One of my indexes depends on another one's indexed data. How to process them in a specific order?

Indexes of all kinds are fully independent. They are processed in parallel, have their message queues, and don't share any state. It is one of the essential DipDup concepts, so there's no "official" way to manage the order of indexing.

Avoid waiting for sync primitives like asyncio.Event or asyncio.Lock in handlers. Indexing will be stuck forever, waiting for the database transaction to complete.

Instead, save raw data in handlers and process it later with hooks when all conditions are met. For example, process data batch only when all indexes in the dipdup_index table have reached a specific level.

How to perform database migrations?

DipDup does not provide any tooling for database migrations. The reason is that schema changes almost always imply reindexing when speaking about indexers. However, you can perform migrations yourself using any tool you like. First, disable schema hash check in config:

    schema_modified: ignore

You can also use the schema approve command for a single schema change.

To determine what manual modifications you need to apply after changing models.py, you can compare raw SQL schema before and after the change. Consider the following example:

-    timestamp = fields.DatetimeField()
+    timestamp = fields.DatetimeField(auto_now=True)
dipdup schema export > old
# ...modify `models.py` here...
dipdup schema export > new
diff old new
<     "timestamp" TIMESTAMP NOT NULL,

Now you can prepare and execute an ALTER TABLE query manually or using SQL hooks.