mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-28 21:12:16 +00:00
6c9c6a68ec
* init * Update generate_terminal_markdown.py * Update generate_terminal_markdown.py * moved folders out of common into root * remove cat from trail if sub in [ ba, ta, qa ] * Update generate_terminal_markdown.py * un-indented example images * Update generate_terminal_markdown.py * Update generate_terminal_markdown.py * Update generate_terminal_markdown.py * replace ✨ with 🦋 * Update regression_model.py * updates * up * fix missing type hints, added defaults to sdk generation * typing * typing * datetime defaults, fix dict_keys([]) in choices * fix regression docstring, added divider on markdowns * fix get_hcp portfolio trailmap * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update .gitignore * Making it more 3.9 friendly * Update controller_doc_classes.py * Update generate_sdk_markdown.py * Update controller_doc_classes.py Co-authored-by: Chavithra <chavithra@gmail.com>
397 lines
11 KiB
Python
397 lines
11 KiB
Python
"""The BitQuery view"""
|
|
__docformat__ = "numpy"
|
|
|
|
import logging
|
|
import os
|
|
|
|
from openbb_terminal.cryptocurrency.dataframe_helpers import (
|
|
lambda_very_long_number_formatter,
|
|
)
|
|
from openbb_terminal.cryptocurrency.dataframe_helpers import (
|
|
prettify_column_names,
|
|
)
|
|
from openbb_terminal.cryptocurrency.onchain import bitquery_model
|
|
from openbb_terminal.decorators import log_start_end
|
|
from openbb_terminal.helper_funcs import export_data, print_rich_table
|
|
from openbb_terminal.decorators import check_api_key
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_dex_trades(
|
|
trade_amount_currency: str = "USD",
|
|
kind: str = "dex",
|
|
limit: int = 20,
|
|
days: int = 90,
|
|
sortby: str = "tradeAmount",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing Trades on Decentralized Exchanges aggregated by DEX or Month
|
|
[Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
kind: str
|
|
Aggregate trades by dex or time
|
|
trade_amount_currency: str
|
|
Currency of displayed trade amount. Default: USD
|
|
limit: int
|
|
Number of records to display
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
days: int
|
|
Last n days to query data. Maximum 365 (bigger numbers can cause timeouts
|
|
on server side)
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
"""
|
|
|
|
if kind == "time":
|
|
df = bitquery_model.get_dex_trades_monthly(trade_amount_currency, days, ascend)
|
|
else:
|
|
df = bitquery_model.get_dex_trades_by_exchange(
|
|
trade_amount_currency, days, sortby, ascend
|
|
)
|
|
|
|
if not df.empty:
|
|
df_data = df.copy()
|
|
|
|
column_names = ["tradeAmount", "trades"]
|
|
column_names = prettify_column_names(column_names)
|
|
|
|
df[column_names] = df[column_names].applymap(
|
|
lambda x: lambda_very_long_number_formatter(x)
|
|
)
|
|
|
|
print_rich_table(
|
|
df.head(limit),
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Trades on Decentralized Exchanges",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"lt",
|
|
df_data,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_daily_volume_for_given_pair(
|
|
symbol: str = "WBTC",
|
|
to_symbol: str = "USDT",
|
|
limit: int = 20,
|
|
sortby: str = "date",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing daily volume for given pair
|
|
[Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
symbol: str
|
|
ERC20 token symbol or address
|
|
to_symbol: str
|
|
Quote currency.
|
|
limit: int
|
|
Number of records to display
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
|
|
Returns
|
|
-------
|
|
pd.DataFrame
|
|
Token volume on different decentralized exchanges
|
|
"""
|
|
|
|
df = bitquery_model.get_daily_dex_volume_for_given_pair(
|
|
symbol=symbol,
|
|
to_symbol=to_symbol,
|
|
limit=limit,
|
|
sortby=sortby,
|
|
ascend=ascend,
|
|
)
|
|
|
|
if df.empty:
|
|
return
|
|
|
|
df_data = df.copy()
|
|
|
|
df[["Trade amount", "Trades"]] = df[["Trade amount", "Trades"]].applymap(
|
|
lambda x: lambda_very_long_number_formatter(x)
|
|
)
|
|
# The -d command takes the place of what would normally be -l. This means
|
|
# we want to print out all of the data from each --day. If there is
|
|
# more exchange data per day then we will have more than -d amount of
|
|
# rows. If we do not change this value then only -d amount of rows will
|
|
# be printed out, not -d amount of days which is what we want. So we set
|
|
# this to an arbitrary amount to cover the potential for more than
|
|
# one row per day
|
|
limit = 10
|
|
print_rich_table(
|
|
df.head(limit),
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Daily Volume for Pair",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"dvcp",
|
|
df_data,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_dex_volume_for_token(
|
|
symbol: str = "WBTC",
|
|
trade_amount_currency: str = "USD",
|
|
limit: int = 10,
|
|
sortby: str = "tradeAmount",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing token volume on different Decentralized Exchanges.
|
|
[Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
symbol: str
|
|
ERC20 token symbol or address
|
|
trade_amount_currency: str
|
|
Currency of displayed trade amount. Default: USD
|
|
limit: int
|
|
Number of records to display
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
|
|
Returns
|
|
-------
|
|
pd.DataFrame
|
|
Token volume on different decentralized exchanges
|
|
"""
|
|
|
|
df = bitquery_model.get_token_volume_on_dexes(
|
|
symbol=symbol,
|
|
trade_amount_currency=trade_amount_currency,
|
|
sortby=sortby,
|
|
ascend=ascend,
|
|
)
|
|
if not df.empty:
|
|
df_data = df.copy()
|
|
|
|
column_names = ["tradeAmount", "trades"]
|
|
column_names = prettify_column_names(column_names)
|
|
|
|
df[column_names] = df[column_names].applymap(
|
|
lambda x: lambda_very_long_number_formatter(x)
|
|
)
|
|
|
|
print_rich_table(
|
|
df.head(limit),
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Token Volume on Exchanges",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"tv",
|
|
df_data,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_ethereum_unique_senders(
|
|
interval: str = "days",
|
|
limit: int = 10,
|
|
sortby: str = "date",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing number of unique ethereum addresses which made a transaction in given time interval
|
|
[Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
interval: str
|
|
Time interval in which ethereum address made transaction. month, week or day
|
|
limit: int
|
|
Number of records to display. It's calculated base on provided interval.
|
|
If interval is month then calculation is made in the way: limit * 30 = time period,
|
|
in case if interval is set to week, then time period is calculated as limit * 7.
|
|
For better user experience maximum time period in days is equal to 90.
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
|
|
Returns
|
|
-------
|
|
pd.DataFrame
|
|
Number of unique ethereum addresses which made a transaction in given time interval
|
|
"""
|
|
|
|
df = bitquery_model.get_ethereum_unique_senders(interval, limit, sortby, ascend)
|
|
if not df.empty:
|
|
|
|
column_names = ["uniqueSenders", "transactions", "maximumGasPrice"]
|
|
column_names = prettify_column_names(column_names)
|
|
|
|
df[column_names] = df[column_names].applymap(
|
|
lambda x: lambda_very_long_number_formatter(x)
|
|
)
|
|
|
|
df_data = df.copy()
|
|
|
|
print_rich_table(
|
|
df,
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Unique Ethereum Addresses",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"ueat",
|
|
df_data,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_most_traded_pairs(
|
|
exchange: str = "Uniswap",
|
|
days: int = 10,
|
|
limit: int = 10,
|
|
sortby: str = "tradeAmount",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing most traded crypto pairs on given decentralized exchange in chosen time period.
|
|
[Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
exchange: str
|
|
Decentralized exchange name
|
|
days: int
|
|
Number of days taken into calculation account.
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
|
|
Returns
|
|
-------
|
|
pd.DataFrame
|
|
Most traded crypto pairs on given decentralized exchange in chosen time period.
|
|
"""
|
|
|
|
df = bitquery_model.get_most_traded_pairs(
|
|
exchange=exchange, limit=days, sortby=sortby, ascend=ascend
|
|
)
|
|
if not df.empty:
|
|
df_data = df.copy()
|
|
|
|
column_names = ["tradeAmount", "trades"]
|
|
column_names = prettify_column_names(column_names)
|
|
|
|
df[column_names] = df[column_names].applymap(
|
|
lambda x: lambda_very_long_number_formatter(x)
|
|
)
|
|
|
|
print_rich_table(
|
|
df.head(limit),
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Most Traded Crypto Pairs",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"ttcp",
|
|
df_data,
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
@check_api_key(["API_BITQUERY_KEY"])
|
|
def display_spread_for_crypto_pair(
|
|
symbol: str = "WETH",
|
|
to_symbol: str = "USDT",
|
|
limit: int = 10,
|
|
sortby: str = "date",
|
|
ascend: bool = True,
|
|
export: str = "",
|
|
) -> None:
|
|
"""Prints table showing an average bid and ask prices, average spread for given crypto pair for chosen
|
|
time period. [Source: https://graphql.bitquery.io/]
|
|
|
|
Parameters
|
|
----------
|
|
symbol: str
|
|
ERC20 token symbol
|
|
to_symbol: str
|
|
Quoted currency.
|
|
limit: int
|
|
Last n days to query data
|
|
sortby: str
|
|
Key by which to sort data
|
|
ascend: bool
|
|
Flag to sort data ascending
|
|
export : str
|
|
Export dataframe data to csv,json,xlsx file
|
|
|
|
Returns
|
|
-------
|
|
pd.DataFrame
|
|
Average bid and ask prices, spread for given crypto pair for chosen time period
|
|
"""
|
|
|
|
df = bitquery_model.get_spread_for_crypto_pair(
|
|
symbol=symbol, to_symbol=to_symbol, limit=limit, sortby=sortby, ascend=ascend
|
|
)
|
|
if not df.empty:
|
|
|
|
print_rich_table(
|
|
df,
|
|
headers=list(df.columns),
|
|
show_index=False,
|
|
title="Average Spread for Given Crypto",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.dirname(os.path.abspath(__file__)),
|
|
"baas",
|
|
df,
|
|
)
|