2Python实现
import pandas as pd
import time
import os
import datetime
import ccxt
pd.set_option("expand_frame_repr", False) #
TIMEOUT = 6 # 6 second
BITFINEX_LIMIT = 5000
BITMEX_LIMIT = 500
BINANCE_LIMIT = 500
def crawl_exchanges_datas(exchange_name, symbol, start_time, end_time):
"""
爬取交易所数据的方法.
:param exchange_name: 交易所名称.
:param symbol: 请求的symbol: like BTC/USDT, ETH/USD等。
:param start_time: like 2018-1-1
:param end_time: like 2019-1-1
:return:
"""
exchange_class = getattr(ccxt, exchange_name) # 获取交易所的名称 ccxt.binance
exchange = exchange_class() # 交易所的类. 类似 ccxt.bitfinex()
print(exchange)
# exit()
current_path = os.getcwd()
file_dir = os.path.join(current_path, exchange_name, symbol.replace("/", ""))
if not os.path.exists(file_dir):
os.makedirs(file_dir)
start_time = datetime.datetime.strptime(start_time, "%Y-%m-%d")
end_time = datetime.datetime.strptime(end_time, "%Y-%m-%d")
start_time_stamp = int(time.mktime(start_time.timetuple())) * 1000
end_time_stamp = int(time.mktime(end_time.timetuple())) * 1000
print(start_time_stamp) # 1529233920000
print(end_time_stamp)
limit_count = 500
if exchange_name == "bitfinex":
limit_count = BITFINEX_LIMIT
elif exchange_name == "bitmex":
limit_count = BITMEX_LIMIT
elif exchange_name == "binance":
limit_count = BINANCE_LIMIT
while True:
try:
print(start_time_stamp)
data = exchange.fetch_ohlcv(symbol, timeframe="1m", since=start_time_stamp, limit=limit_count)
df = pd.DataFrame(data)
df.rename(columns={0: "open_time", 1: "open", 2: "high", 3: "low", 4: "close", 5: "volume"}, inplace=True)
start_time_stamp = int(df.iloc[-1]["open_time"]) # 获取下一个次请求的时间.
filename = str(start_time_stamp) + ".csv"
save_file_path = os.path.join(file_dir, filename)
print("文件保存路径为：%s" % save_file_path)
# exit()
df.set_index("open_time", drop=True, inplace=True)
df.to_csv(save_file_path)
if start_time_stamp > end_time_stamp:
print("完成数据的请求.")
break
time.sleep(3)
except Exception as error:
print(error)
time.sleep(10)
def sample_datas(exchange_name, symbol):
"""
:param exchange_name:
:param symbol:
:return:
"""
path = os.path.join(os.getcwd(), exchange_name, symbol.replace("/", ""))
print(path)
# exit()
file_paths = []
for root, dirs, files in os.walk(path):
if files:
for file in files:
if file.endswith(".csv"):
file_paths.append(os.path.join(path, file))
file_paths = sorted(file_paths)
all_df = pd.DataFrame()
for file in file_paths:
df = pd.read_csv(file)
all_df = all_df.append(df, ignore_index=True)
all_df = all_df.sort_values(by="open_time", ascending=True)
print(all_df)
return all_df
def clear_datas(exchange_name, symbol):
df = sample_datas(exchange_name, symbol)
df["open_time"] = df["open_time"].apply(lambda x: (x//60)*60)
print(df)
df["Datetime"] = pd.to_datetime(df["open_time"], unit="ms") + pd.Timedelta(hours=8)
df.drop_duplicates(subset=["open_time"], inplace=True)
df.set_index("Datetime", inplace=True)
print("*" * 20)
print(df)
symbol_path = symbol.replace("/", "")
df.to_csv(f"{exchange_name}_{symbol_path}_1min_data.csv")
if __name__ == "__main__":
exchange_name = "mexc"
# 初始化交易所对象
exchange_class = getattr(ccxt, exchange_name) # 获取交易所的名称 ccxt.binance
exchange = exchange_class() # 交易所的类. 类似 ccxt.bitfinex()
# 输出交易所所有symbol
# if exchange.has["fetchOHLCV"]:
# for symbol in exchange.load_markets():
symbol = "BTC/USDT"
crawl_exchanges_datas(exchange_name, symbol, "2022-8-1", "2022-10-25")
# 合并文件
# sample_datas(exchange_name, symbol)
文章为作者独立观点，不代表股票交易接口观点
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