CleanedVaultPriceRow

Documentation for eth_defi.research.wrangle_vault_prices.CleanedVaultPriceRow Python class.

class CleanedVaultPriceRow

Bases: TypedDict

Schema for a single row in the cleaned vault price DataFrame.

This is the enriched format produced by the cleaning pipeline in this module and consumed by calculate_lifetime_metrics().

It extends RawVaultPriceRow with denormalised metadata columns (id, name, event_count, protocol) and computed columns (returns_1h). The DataFrame uses a DatetimeIndex built from the timestamp column.

Columns are grouped by availability:

• General columns are present for all vault protocols.

• ERC-4626 only columns come from on-chain ERC-4626 calls and are NaN / empty for native protocols.

• Lending only columns are populated for lending protocol vaults (IPOR, Euler, Morpho, Gearbox, etc.) and NaN for others.

• Hypercore only columns come from the Hyperliquid native vault API and are NaN for all other protocols.

• Native protocol flow columns are populated for native protocols that provide daily deposit/withdrawal data (Hypercore, GRVT, Lighter, Hibachi) and NaN for ERC-4626 vaults.

Attributes summary

Methods summary

__init__(*args, **kwargs)
clear()	Remove all items from the dict.
copy()	Return a shallow copy of the dict.
fromkeys([value])	Create a new dictionary with keys from iterable and values set to value.
get(key[, default])	Return the value for key if key is in the dictionary, else default.
items()	Return a set-like object providing a view on the dict's items.
keys()	Return a set-like object providing a view on the dict's keys.
pop(k[,d])	If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem()	Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])	Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)	If E is present and has a .keys() method, then does: for k in E.keys(): D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()	Return an object providing a view on the dict's values.

__init__(*args, **kwargs)

__new__(**kwargs)

clear()

Remove all items from the dict.

copy()

Return a shallow copy of the dict.

fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items()

Return a set-like object providing a view on the dict’s items.

keys()

Return a set-like object providing a view on the dict’s keys.

pop(k[, d]) → v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None.  Update D from mapping/iterable E and F.

If E is present and has a .keys() method, then does: for k in E.keys(): D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values()

Return an object providing a view on the dict’s values.