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python PYPI package to dump all needed crypto historical data from binance just by 2 lines of code

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binance_historical_data

GitHub last commit GitHub license<space><space> PyPI PyPI - Python Version

binance_historical_data is a python package (py>=3.8) which makes download of historical crypto data (prices and volumes) from binance server as simple as it can only be. You don't even need to have an account at binance.com to download all history of crypto data

Dumped locally and then unzipped,
so you would have an identical local ready to use data copy
Using this package you will be able to have full historical data of prices and volumes with only 3 lines of python code
And if you need to update already downloaded data then once again 3 lines of python code will do the job
Limitations: The previous day data appears on binance server a few minutes after 0 a.m. UTC
So there is a delay in which you can get the data.
pip install binance_historical_data
from binance_historical_data import BinanceDataDumper

data_dumper = BinanceDataDumper(
    path_dir_where_to_dump=".",
    asset_class="spot",  # spot, um, cm
    data_type="klines",  # aggTrades, klines, trades
    data_frequency="1m",
)

Arguments:

  1. path_dir_where_to_dump:
    (string) Path to folder where to dump the data
  2. asset_class:
    (string) Source of data: [spot, um, cm] um: usd(t) margined futures, cm: coin margined futures
  3. data_type="klines":
    (string) data type to dump:
    [aggTrades, klines, trades] for spot
    [aggTrades, klines, trades, indexPriceKlines, markPriceKlines, premiumIndexKlines, metrics] for futures (metrics only supported for um)
    Refer to binance doc for additional info: https://github.com/binance/binance-public-data
  4. str_data_frequency:
    (string) One of [1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h]
    Frequency of price-volume data candles to get
data_dumper.dump_data(
    tickers=None,
    date_start=None,
    date_end=None,
    is_to_update_existing=False,
    tickers_to_exclude=["UST"],
)

Arguments:

  1. tickers=None:
    (list) Trading pairs for which to dump data
    if equals to None - all USDT pairs will be used
  2. date_start=None:
    (datetime.date) The date from which to start dump
    if equals to None - every trading pair will be dumped from the early begining (the earliest is 2017-01-01)
  3. date_end=True=None:
    (datetime.date) The last date for which to dump data
    if equals to None - Today's date will be used
  4. is_to_update_existing=False:
    (bool) Flag if you want to update the data if it's already exist
  5. tickers_to_exclude=None:
    (list) Tickers to exclude from dump

Delete all daily data for which full month monthly data was already dumped

data_dumper.delete_outdated_daily_results()
"Open time" - Timestamp
"Open"
"High"
"Low"
"Close"
"Volume"
"Close time" - Timestamp
"Quote asset volume"
"Number of trades"
"Taker buy base asset volume"
"Taker buy quote asset volume"
"Ignore"

Please be advised that the first data dump for all trading pairs might take some time (~40 minutes)

data_dumper.dump_data()
It's as easy as running the exactly same method dump_data once again
The data_dumper will find all the dates for which data already exists
and will try to dump only the new data
data_dumper.dump_data()
data_dumper.dump_data(
    date_start=datetime.date(year=2021, month=1, day=1),
    date_end=datetime.date(year=2022, month=1, day=1),
    is_to_update_existing=True
)
print(data_dumper.get_list_all_trading_pairs())
print(data_dumper.get_min_start_date_for_ticker())
print(
    data_dumper.get_all_tickers_with_data(timeperiod_per_file="daily")
)
print(
    data_dumper.get_all_dates_with_data_for_ticker(
        ticker,
        timeperiod_per_file="monthly"
    )
)
print(
    data_dumper.get_local_dir_to_data(
        ticker,
        timeperiod_per_file,
    )
)
print(
    data_dumper.create_filename(
        ticker,
        date_obj,
        timeperiod_per_file="monthly",
    )
)

This project is licensed under the MIT License.

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python PYPI package to dump all needed crypto historical data from binance just by 2 lines of code

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