huenique / binance_historical_data

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

binance_historical_data

Table of Contents

• Overview
• Installation via pip:
• How to use it
  • Initialize main object: data_dumper
  • 1) The only method to dump the data
  • 2) Delete outdated daily results
    • .csv klines (candles) files columns
• Examples
  • How to dump all data for all USDT trading pairs
  • How to update data (get all new data)
  • How to update (reload) data for the asked time period
• Other useful methods
  • Get all trading pairs (tickers) from binance
  • Get the first data when data for the ticker can be found
  • Get all tickers with locally saved data
  • Get all dates for which there is locally saved data
  • Get directory where the local data of exact ticker lies
  • Create file name for the local file
• Links
• Project local Links
• Contacts
• License

Overview

binance_historical_data is a Python package designed to simplify the download of historical cryptocurrency data (prices and volumes) from the Binance server. Notably, you can download all historical data without needing an account on binance.com.

Data is sourced from Binance Data Vision, where it is dumped locally and unzipped, providing you with a ready-to-use local copy.

Using this package, you can access comprehensive historical data on prices and volumes with just three lines of Python code. Additionally, updating already downloaded data requires only another three lines of code.

Limitations: Data from the previous day is only available on the Binance server a few minutes after 0:00 AM UTC, which introduces a delay in data availability.

Installation via pip:

pip install binance_historical_data

How to use it

Initialize main object: data_dumper

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

1) The only method to dump the data

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

2) Delete outdated daily results

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

data_dumper.delete_outdated_daily_results()

.csv klines (candles) files columns

"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"

Examples

How to dump all data for all USDT trading pairs

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

data_dumper.dump_data()

How to update data (get all new 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()

How to update (reload) data for the asked time period

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
)

Other useful methods

Get all trading pairs (tickers) from binance

print(data_dumper.get_list_all_trading_pairs())

Get the first data when data for the ticker can be found

print(data_dumper.get_min_start_date_for_ticker())

Get all tickers with locally saved data

print(
    data_dumper.get_all_tickers_with_data(timeperiod_per_file="daily")
)

Get all dates for which there is locally saved data

print(
    data_dumper.get_all_dates_with_data_for_ticker(
        ticker,
        timeperiod_per_file="monthly"
    )
)

Get directory where the local data of exact ticker lies

print(
    data_dumper.get_local_dir_to_data(
        ticker,
        timeperiod_per_file,
    )
)

Create file name for the local file

print(
    data_dumper.create_filename(
        ticker,
        date_obj,
        timeperiod_per_file="monthly",
    )
)

Links

• PYPI
• GitHub

Project local Links

• CHANGELOG.
• CONTRIBUTING.

Contacts

• Email: [e-mail]
• vk.com
• Facebook

License

This project is licensed under the MIT License.