我们现在能够检索加密货币的 1 秒历史 klines答案

【问题标题】：We are now able to retrieve 1 second historical klines for cryptocurrencies我们现在能够检索加密货币的 1 秒历史 klines
【发布时间】：2022-11-13 07:03:17
【问题描述】：

检索加密货币的免费历史 klines（开盘高低收盘数据）的最小粒度曾是1分钟。

感谢币安，我们现在可以获得 1 秒粒度的历史数据！

【问题讨论】：

标签： python binance cryptocurrency ohlcv

【解决方案1】：

如何获取数据：

没有币安 REST API：

from io import BytesIO
from zipfile import ZipFile
from urllib.request import urlopen


def download_zip(
    coin_pair: str = "BTCUSDT",    # trading pair 
    date: str = "2022-11-11",      # desired day (one can also download a whole month, replace 'daily' with 'monthly' in the url)
    save_to_path: str = r"./tmp"   # path where to save the .csv file
):
    url = fr"https://data.binance.vision/data/spot/daily/klines/{coin_pair}/1s/{coin_pair}-1s-{date}.zip"
    with urlopen(url) as zipresp:
        with ZipFile(BytesIO(zipresp.read())) as zfile:
            zfile.extractall(save_to_path)

这将从特定日期将所需硬币对的 .csv 文件下载到指定文件夹。

如果愿意，我们现在可以将文件进一步处理为 pandas.DataFrame，并且只保留日期时间、开盘价、高价、低价、收盘价和成交量列：

import os
import pickle
import numpy as np
import pandas as pd
import datetime as dt


def process_files(
    path: str = r"./tmp",  # path to where we downloaded the .csv files
):
    files = [f for f in os.listdir(path) if f[-4:] == ".csv"]
    for file in files:
        file_path = path + "\" + file
        df = pd.read_csv(file_path, header=None, names=['dateTime', 'open', 'high', 'low', 'close', 'volume', 'closeTime', 'quoteAssetVolume', 'numberOfTrades', 'takerBuyBaseVol', 'takerBuyQuoteVol', 'ignore'])
        df = df[['dateTime', 'open', 'high', 'low', 'close', 'volume']]  # use this line if you are only interested in the ohlcv-data
        df['dateTime'] = df['dateTime'].apply(lambda t: dt.datetime.fromtimestamp(t / 1000.0))
        df.open = df.open.astype(np.float64)
        df.high = df.high.astype(np.float64)
        df.low = df.low.astype(np.float64)
        df.close = df.close.astype(np.float64)
        df.volume = df.volume.astype(np.float64)
        symbol = file.split("-")[0]  # use this and
        df['symbol'] = symbol        # this line, if you want to add a column with the trading pair
        df.set_index('dateTime', inplace=True)
        
        save_path = file_path.replace(".csv", "")
        with open(save_path, "wb") as fd:
            pickle.dump(df, fd)
    # remove the .csv files as they are no longer needed

使用币安 REST API

到目前为止，币安还没有更新他们的 REST API 来检索 1 秒的历史 klines，至少我不能正确地做到这一点。这部分帖子将在得到答案的帮助后更新。

【讨论】：