def display_coins(category: str,
top: int = 250,
sortby: str = "Symbol",
export: str = "") -> None:
"""Display top coins [Source: CoinGecko]
Parameters
----------
category: str
Coingecko category. If no category is passed it will search for all coins. (E.g., smart-contract-platform)
top: int
Number of records to display
sortby: str
Key to sort data
export : str
Export dataframe data to csv,json,xlsx file
"""
df = pycoingecko_model.get_coins(top=top, category=category)
if not df.empty:
df = df[[
"symbol",
"name",
"total_volume",
"market_cap",
"market_cap_rank",
"price_change_percentage_7d_in_currency",
"price_change_percentage_24h_in_currency",
]]
df = df.set_axis(
COINS_COLUMNS,
axis=1,
inplace=False,
)
if sortby in COINS_COLUMNS:
df = df[(df["Volume [$]"].notna())
& (df["Market Cap [$]"].notna())].sort_values(
by=sortby, ascending=False)
for col in ["Volume [$]", "Market Cap [$]"]:
if col in df.columns:
df[col] = df[col].apply(
lambda x: lambda_very_long_number_formatter(x))
print_rich_table(
df.head(top),
headers=list(df.columns),
show_index=False,
)
console.print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"cgtop",
df,
)
else:
console.print("\nUnable to retrieve data from CoinGecko.\n")
def get_stable_coins(top: int = 20) -> pd.DataFrame:
"""Returns top stable coins [Source: CoinGecko]
Returns
-------
pandas.DataFrame
Rank, Name, Symbol, Price, Change_24h, Exchanges, Market_Cap, Change_30d, Url
"""
df = get_coins(top=top, category="stablecoins")
return df[COINS_COLUMNS]
def test_get_coins(kwargs, recorder):
result = pycoingecko_model.get_coins(**kwargs)
recorder.capture(result)