mirror of
https://github.com/OpenBB-finance/OpenBB.git
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0b554c6893
* Add separate view for finbrain for crypto curreny sentiment analysis * Move json with symbols to separate directory, little refactoring, update readme * Add screenshot of finbrain for PolkaDot * Coinbase menu added * Add more methods for coinbase * Add coinbase views, coinbase models. Add coinbase to load, chart, find commands. Add coinbase to controller * Add auth client for coinbase pro endpoints that needs auth * Add more views for coinbase to crypto menu * Add some print tests for Coinbase view * Add 2 more tests for coinbase view * Update README with Coinbase API keys * Cleaning empty lines, spaces etc. * Use os.path.join in imports, change column names in one normalized df * Move Coinbase to portfolio brokers. Adjust tests, and imports * precommit config return to prev ver * Fix coinbase accounts command, del column filter for deposits
153 lines
4.0 KiB
Python
153 lines
4.0 KiB
Python
"""Coinbase view"""
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__docformat__ = "numpy"
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import os
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from typing import Optional
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import pandas as pd
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from tabulate import tabulate
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from pandas.plotting import register_matplotlib_converters
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from gamestonk_terminal.helper_funcs import export_data
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from gamestonk_terminal import feature_flags as gtff
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from gamestonk_terminal.cryptocurrency.due_diligence import coinbase_model
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from gamestonk_terminal.cryptocurrency.cryptocurrency_helpers import plot_order_book
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register_matplotlib_converters()
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def display_order_book(product_id: str, export: str = "") -> None:
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"""Displays a list of available currency pairs for trading. [Source: Coinbase]
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Parameters
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----------
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product_id: str
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Trading pair of coins on Coinbase e.g ETH-USDT or UNI-ETH
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export : str
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Export dataframe data to csv,json,xlsx file
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"""
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bids, asks, pair, market_book = coinbase_model.get_order_book(product_id)
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plot_order_book(bids, asks, pair)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)),
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"book",
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pd.DataFrame(market_book),
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)
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def display_trades(
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product_id: str, limit: int = 1000, side: Optional[str] = None, export: str = ""
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) -> None:
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"""Display last N trades for chosen trading pair. [Source: Coinbase]
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Parameters
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----------
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product_id: str
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Trading pair of coins on Coinbase e.g ETH-USDT or UNI-ETH
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limit: int
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Last <limit> of trades. Maximum is 1000.
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side: Optional[str]
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You can chose either sell or buy side. If side is not set then all trades will be displayed.
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export : str
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Export dataframe data to csv,json,xlsx file
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"""
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df = coinbase_model.get_trades(product_id, limit, side)
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df_data = df.copy()
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if gtff.USE_TABULATE_DF:
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print(
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tabulate(
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df,
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headers=df.columns,
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floatfmt=".3f",
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showindex=False,
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tablefmt="fancy_grid",
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),
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"\n",
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)
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else:
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print(df.to_string, "\n")
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)),
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"trades",
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df_data,
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)
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def display_candles(product_id: str, interval: str, export) -> None:
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"""Get candles for chosen trading pair and time interval. [Source: Coinbase]
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Parameters
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----------
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product_id: str
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Trading pair of coins on Coinbase e.g ETH-USDT or UNI-ETH
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interval: str
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Time interval. One from 1m, 5m ,15m, 1h, 6h, 24h
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export : str
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Export dataframe data to csv,json,xlsx file
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"""
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df = coinbase_model.get_candles(product_id, interval)
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df_data = df.copy()
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if gtff.USE_TABULATE_DF:
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print(
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tabulate(
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df,
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headers=df.columns,
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floatfmt=".1f",
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showindex=True,
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tablefmt="fancy_grid",
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),
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"\n",
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)
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else:
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print(df.to_string, "\n")
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)),
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"candles",
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df_data,
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)
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def display_stats(product_id: str, export: str) -> None:
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"""Get 24 hr stats for the product. Volume is in base currency units.
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Open, high and low are in quote currency units. [Source: Coinbase]
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Parameters
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----------
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product_id: str
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Trading pair of coins on Coinbase e.g ETH-USDT or UNI-ETH
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export : str
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Export dataframe data to csv,json,xlsx file
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"""
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df = coinbase_model.get_product_stats(product_id)
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df_data = df.copy()
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if gtff.USE_TABULATE_DF:
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print(
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tabulate(
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df,
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headers=df.columns,
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floatfmt=".3f",
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showindex=False,
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tablefmt="fancy_grid",
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),
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"\n",
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)
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else:
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print(df.to_string, "\n")
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)),
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"stats",
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df_data,
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)
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