messari.nfts.upshot package

Submodules

messari.nfts.upshot.helpers module

This module is dedicated to helpers for the Upshot class

messari.nfts.upshot.helpers.format_df(df_in: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

format a typical DF from Upshot, replace date & drop duplicates

Parameters
df_in: pd.DataFrame

input DataFrame

Returns
DataFrame

formated pandas DataFrame

messari.nfts.upshot.upshot module

This module is meant to contain the Upshot class

class messari.nfts.upshot.upshot.Upshot

Bases: messari.dataloader.DataLoader

This class is a wrapper around the Upshot API

Methods

get_asset(contract_address[, asset_id, ...])

retrieve upshot asset data

get_asset_events(contract_address, asset_id)

retrieve the event history for a given asset

get_pricing(contract_address, asset_id[, ...])

Returns all the price history for given asset(s) Parameters ---------- contract_address: str, List single address in or list of addresses in asset_id: int, List single asset id in or list of asset ids in from_time: int unix time for starting time to_time: int unix time for ending time confidence: str Only return pricings above the provided confidence level. 0.1 is the minimum and 1 is the highest, with a default level of 0.1 source: str A pricing can be one of the following types: - MARKET: open-market transactions (always a confidence level of 1) - UPSHOT: sourced from Upshot's proprietary machine learning models.

get_pricing_current(contract_address, asset_id)

Returns an asset's most recent price information.

get_response(endpoint_url[, params, headers])

Gets response from endpoint and checks for HTTP errors when requesting data.

set_api_dict(api_dict)

Sets a new dictionary to be used as an API key pair

set_taxonomy_dict(taxonomy_dict)

Sets a new dictionary to be used for taxonomy translations

translate(input_slugs)

Wrapper around messari.utils.validate_input, validate input & check if it's supported by DeFi Llama
get_asset(contract_address: Union[str, List], asset_id: Optional[Union[int, List]] = None, limit: Optional[int] = None, offset: int = 0) → pandas.core.frame.DataFrame

retrieve upshot asset data

Parameters
contract_address: str, List

single address in or list of addresses in

asset_id: int, List

single asset id in or list of asset ids in

limit: int

if no asset_id is given, set number of assets to get from contracts

offset: int

for pagination

Returns
DataFrame

DataFrame containing information about asset(s)

get_asset_events(contract_address: Union[str, List], asset_id: Union[int, List], market_type: Optional[str] = None, event_type=None) → pandas.core.frame.DataFrame

retrieve the event history for a given asset

Parameters
contract_address: str, List

single address in or list of addresses in

asset_id: int, List

single asset id in or list of asset ids in

market_type: str
filter the events based on the market in which it occurred

  • ‘PRIMARY’

  • ‘SECONDARY’

event_type: str
Filter events by the event type:

  • ‘BID’

  • ‘ASK’

  • ‘SALE’

  • ‘TRANSFER’

Returns
DataFrame

DataFrame containing events for given asset(s)

get_pricing(contract_address: Union[str, List], asset_id: Union[int, List], from_time: Optional[int] = None, to_time: Optional[int] = None, confidence: Optional[str] = None, source: str = 'UPSHOT') → pandas.core.frame.DataFrame

Returns all the price history for given asset(s) Parameters ———-

contract_address: str, List

single address in or list of addresses in

asset_id: int, List

single asset id in or list of asset ids in

from_time: int

unix time for starting time

to_time: int

unix time for ending time

confidence: str

Only return pricings above the provided confidence level. 0.1 is the minimum and 1 is the highest, with a default level of 0.1

source: str
A pricing can be one of the following types:

  • MARKET: open-market transactions (always a confidence level of 1)

  • UPSHOT: sourced from Upshot’s proprietary machine learning models

Returns
DataFrame

timeseries DataFrame with price history

get_pricing_current(contract_address: Union[str, List], asset_id: Union[int, List], confidence: Optional[str] = None, source: str = 'UPSHOT') → pandas.core.frame.DataFrame

Returns an asset’s most recent price information.

Parameters
contract_address: str, List

single address in or list of addresses in

asset_id: int, List

single asset id in or list of asset ids in

confidence: str

Only return pricings above the provided confidence level. 0.1 is the minimum and 1 is the highest, with a default level of 0.1

source: str
A pricing can be one of the following types:

  • MARKET: open-market transactions (always a confidence level of 1)

  • UPSHOT: sourced from Upshot’s proprietary machine learning models

Returns
DataFrame

DataFrame containing recent price information

Module contents

Module to handle initialization, imports, for Upshot class