def display_losers(period: str, top: int, sortby: str, descend: bool,
links: bool, export: str) -> None:
"""Shows Largest Losers - coins which lost the most in given period of time. [Source: CoinGecko]
Parameters
----------
period: str
Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y]
top: int
Number of records to display
sortby: str
Key by which to sort data
descend: bool
Flag to sort data descending
links: bool
Flag to display urls
export : str
Export dataframe data to csv,json,xlsx file
"""
if sortby == "Change":
sortby = f"%Change_{period}"
df = pycoingecko_model.get_gainers_or_losers(period=period, typ="losers")
if not df.empty:
df = df.sort_values(by=sortby, ascending=descend)
df_data = df.copy()
if not links:
df.drop("Url", axis=1, inplace=True)
if gtff.USE_TABULATE_DF:
print(
tabulate(
df.head(top),
headers=df.columns,
floatfmt=".4f",
showindex=False,
tablefmt="fancy_grid",
),
"\n",
)
else:
print(df.to_string, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"losers",
df_data,
)
else:
print("")
print("Unable to retrieve data from CoinGecko.")
print("")
def display_gainers(period: str = "1h",
top: int = 20,
sortby: str = "Symbol",
export: str = "") -> None:
"""Shows Largest Gainers - coins which gain the most in given period. [Source: CoinGecko]
Parameters
----------
period: str
Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y]
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_gainers_or_losers(top=top,
period=period,
typ="gainers")
if not df.empty:
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__)),
"gainers",
df,
)
else:
console.print("\nUnable to retrieve data from CoinGecko.\n")
def gainers(other_args: List[str]):
"""Shows Largest Gainers - coins which gain the most in given period from www.coingecko.com
Parameters
----------
other_args: List[str]
Arguments to pass to argparse
"""
parser = argparse.ArgumentParser(
prog="gainers",
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description="""
Shows Largest Gainers - coins which gain the most in given period.
You can use parameter --period to set which timeframe are you interested in. eg. 1h, 24h, 7d, 14d, 30d, 60d, 1y
You can look on only top N number of records with --top,
You can sort by Rank, Symbol, Name, Volume, Price, Change with --sort and also with --descend flag to set it
to sort descending.
There is --links flag, which will display one additional column you all urls for coins.
""",
)
parser.add_argument(
"-p",
"--period",
dest="period",
type=str,
help="time period, one from [1h, 24h, 7d, 14d, 30d, 60d, 1y]",
default="1h",
choices=["1h", "24h", "7d", "14d", "30d", "60d", "1y"],
)
parser.add_argument(
"-t",
"--top",
dest="top",
type=int,
help="top N number records",
default=15,
)
parser.add_argument(
"-s",
"--sort",
dest="sortby",
type=str,
help="Sort by given column. Default: Rank",
default="Rank",
choices=["Rank", "Symbol", "Name", "Volume", "Price", "Change"],
)
parser.add_argument(
"--descend",
action="store_false",
help="Flag to sort in descending order (lowest first)",
dest="descend",
default=True,
)
parser.add_argument(
"-l",
"--links",
dest="links",
action="store_true",
help="Flag to show urls. If you will use that flag you will additional column with urls",
default=False,
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
if ns_parser.sortby == "Change":
sortby = f"%Change_{ns_parser.period}"
else:
sortby = ns_parser.sortby
df = gecko.get_gainers_or_losers(
period=ns_parser.period, typ="gainers"
).sort_values(by=sortby, ascending=ns_parser.descend)
if not ns_parser.links:
df.drop("Url", axis=1, inplace=True)
print(
tabulate(
df.head(ns_parser.top),
headers=df.columns,
floatfmt=".4f",
showindex=False,
tablefmt="fancy_grid",
),
"\n",
)
except Exception as e:
print(e, "\n")