def get_top_tokens() -> pd.DataFrame:
"""Get top 50 tokens. [Source: Ethplorer]
Returns
-------
pd.DataFrame:
DataFrame with list of top 50 tokens.
"""
response = make_request("getTopTokens")
tokens = response["tokens"]
df = pd.DataFrame(tokens)[[
"name",
"symbol",
"price",
"txsCount",
"transfersCount",
"holdersCount",
"twitter",
"coingecko",
]]
df["price"] = df["price"].apply(lambda x: x["rate"]
if x and "rate" in x else None)
create_df_index(df, "rank")
return df
def get_top_volume_coins() -> pd.DataFrame:
"""Scrapes top coins by trading volume "https://www.coingecko.com/en/coins/high_volume"
Returns
-------
pandas.DataFrame
Rank, Name, Symbol, Price, Change_1h, Change_24h, Change_7d, Volume_24h, Market_Cap
"""
columns = [
"Rank",
"Name",
"Symbol",
"Price",
"Change_1h",
"Change_24h",
"Change_7d",
"Volume_24h",
"Market_Cap",
]
url = "https://www.coingecko.com/en/coins/high_volume"
rows = scrape_gecko_data(url).find("tbody").find_all("tr")
results = []
for row in rows:
row_cleaned = clean_row(row)
if len(row_cleaned) == 9:
row_cleaned.insert(0, "?")
row_cleaned.pop(3)
results.append(row_cleaned)
df = replace_qm(pd.DataFrame(results, columns=columns))
df.drop("Rank", axis=1, inplace=True)
create_df_index(df, "Rank")
df["Price"] = df["Price"].apply(lambda x: float(x.strip("$").replace(",", "")))
return df
def get_derivatives():
"""Get list of crypto derivatives from CoinGecko API
Returns
-------
pandas.DataFrame
Rank, Market, Symbol, Price, Pct_Change_24h, Contract_Type, Basis, Spread, Funding_Rate, Volume_24h,
"""
df = pd.DataFrame(client.get_derivatives(include_tickers="unexpired"))
df.drop(
["index", "last_traded_at", "expired_at", "index_id", "open_interest"],
axis=1,
inplace=True,
)
df.rename(columns={"price_percentage_change_24h": "pct_change_24h"},
inplace=True)
create_df_index(df, "rank")
df["price"] = df["price"].apply(
lambda x: float(x.strip("$").replace(",", "")))
df.columns = [
"Rank",
"Market",
"Symbol",
"Price",
"Pct_Change_24h",
"Contract_Type",
"Basis",
"Spread",
"Funding_Rate",
"Volume_24h",
]
return df
def get_exchanges() -> pd.DataFrame:
"""Get list of top exchanges from CoinGecko API [Source: CoinGecko]
Returns
-------
pandas.DataFrame
Trust_Score, Id, Name, Country, Year_Established, Trade_Volume_24h_BTC, Url
"""
client = CoinGeckoAPI()
df = pd.DataFrame(client.get_exchanges_list(per_page=250))
df.replace({float(np.NaN): None}, inplace=True)
df = df[[
"trust_score",
"id",
"name",
"country",
"year_established",
"trade_volume_24h_btc",
"url",
]]
df.columns = [
"Trust_Score",
"Id",
"Name",
"Country",
"Year_Established",
"Trade_Volume_24h_BTC",
"Url",
]
create_df_index(df, "Rank")
return df
def get_stable_coins() -> pd.DataFrame:
"""Scrapes stable coins data from "https://www.coingecko.com/en/stablecoins" [Source: CoinGecko]
Returns
-------
pandas.DataFrame
Rank, Name, Symbol, Price, Change_24h, Exchanges, Market_Cap, Change_30d, Url
"""
columns = [
"Rank",
"Name",
"Symbol",
"Price",
"Change_24h",
"Exchanges",
"Market_Cap",
"Change_30d",
"Url",
]
url = "https://www.coingecko.com/en/stablecoins"
rows = scrape_gecko_data(url).find("tbody").find_all("tr")
results = []
for row in rows:
link = GECKO_BASE_URL + row.find("a")["href"]
row_cleaned = clean_row(row)
if len(row_cleaned) == 8:
row_cleaned.append(None)
(
rank,
name,
*symbols,
price,
volume_24h,
exchanges,
market_cap,
change_30d,
) = row_cleaned
symbol = symbols[0] if symbols else symbols
results.append([
rank,
name,
symbol,
price,
volume_24h,
exchanges,
market_cap,
change_30d,
link,
])
df = replace_qm(pd.DataFrame(results, columns=columns))
df.drop("Rank", axis=1, inplace=True)
create_df_index(df, "Rank")
df["Price"] = df["Price"].apply(
lambda x: float(x.strip("$").replace(",", "")))
return df
def get_indexes():
"""Get list of crypto indexes from CoinGecko API
Returns
-------
pandas.DataFrame
Name, Id, Market, Last, MultiAsset
"""
df = pd.DataFrame(client.get_indexes(per_page=250))
df.columns = ["Name", "Id", "Market", "Last", "MultiAsset"]
create_df_index(df, "Rank")
return df
def get_exchange_rates():
"""Get list of crypto, fiats, commodity exchange rates from CoinGecko API
Returns
-------
pandas.DataFrame
Index, Name, Unit, Value, Type
"""
df = pd.DataFrame(client.get_exchange_rates()["rates"]).T.reset_index()
df.drop("index", axis=1, inplace=True)
create_df_index(df, "index")
df.columns = ["Index", "Name", "Unit", "Value", "Type"]
return df
def get_financial_platforms():
"""Get list of financial platforms from CoinGecko API
Returns
-------
pandas.DataFrame
Rank, Name, Category, Centralized, Url
"""
df = pd.DataFrame(client.get_finance_platforms())
df.drop("facts", axis=1, inplace=True)
create_df_index(df, "rank")
df.columns = ["Rank", "Name", "Category", "Centralized", "Url"]
return df
def get_finance_products():
"""Get list of financial products from CoinGecko API
Returns
-------
pandas.DataFrame
Rank, Platform, Identifier, Supply_Rate, Borrow_Rate
"""
df = pd.DataFrame(
client.get_finance_products(per_page=250),
columns=[
"platform",
"identifier",
"supply_rate_percentage",
"borrow_rate_percentage",
],
)
df.columns = ["Platform", "Identifier", "Supply_Rate", "Borrow_Rate"]
create_df_index(df, "Rank")
return df
def get_address_info(address: str) -> pd.DataFrame:
"""Get info about tokens on you ethereum blockchain balance. Eth balance, balance of all tokens which
have name and symbol. [Source: Ethplorer]
Parameters
----------
address: str
Blockchain balance e.g. 0x3cD751E6b0078Be393132286c442345e5DC49699
Returns
-------
pd.DataFrame:
DataFrame with list of tokens and their balances.
"""
response = make_request("getAddressInfo", address)
if "tokens" in response:
tokens = response.pop("tokens")
for token in tokens:
token_info = token.pop("tokenInfo")
token.update({
"tokenName":
token_info.get("name"),
"tokenSymbol":
token_info.get("symbol"),
"tokenAddress":
token_info.get("balance"),
"balance":
token.get("balance") / (10**int(token_info.get("decimals"))),
})
else:
token_info = response.get("tokenInfo") or {}
tokens = [{
"tokenName":
token_info.get("name"),
"tokenSymbol":
token_info.get("symbol"),
"tokenAddress":
token_info.get("balance"),
"balance":
token_info.get("balance") / (10**int(token_info.get("decimals"))),
}]
eth = response["ETH"] or {}
eth_balance = eth.get("balance")
eth_row = [
"Ethereum",
"ETH",
"0x0000000000000000000000000000000000000000",
eth_balance,
]
cols = [
"tokenName",
"tokenSymbol",
"tokenAddress",
"balance",
]
df = pd.DataFrame(tokens)[cols]
eth_row_df = pd.DataFrame([eth_row], columns=cols)
df = pd.concat([eth_row_df, df], ignore_index=True)
df = df[df["tokenName"].notna()]
create_df_index(df, "index")
return df
