rm-bdd 0.1.1a1

Binance Data Downloader

rm-binance-data-downloader

A Python library for downloading, extracting and formatting historical Binance market data.

The package provides a pipeline that:

1. Downloads data from Binance Vision
2. Extracts compressed archives
3. Formats data into a structured dataset

It is designed for fast data preparation for quantitative trading, backtesting and data analysis.

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Installation

pip install rm-bdd

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Features

• Download historical Binance data
• Automatic archive extraction
• Data formatting pipeline
• Metadata management
• Async architecture
• Easy integration into trading systems

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Quick Example

import asyncio
import time

from rm_bdd.data_downloader import DataDownloader
from rm_bdd.data_extractor import DataExtractor
from rm_bdd.data_formatter import DataFormatter
from rm_bdd.binance_metadata_manager import BinanceMetadataManager


class DataManager:

    def __init__(self, downloader, extractor, formatter):
        self._downloader = downloader
        self._extractor = extractor
        self._formatter = formatter

    async def download_and_save(self, symbol, timeframe, date_from=None, date_to=None):

        start = time.time()
        await self._downloader.download(symbol, timeframe, date_from=date_from, date_to=date_to)
        print("download time:", time.time() - start)

        start = time.time()
        await self._extractor.extract(symbol, timeframe, date_from=date_from, date_to=date_to)
        print("extract time:", time.time() - start)

        start = time.time()
        await self._formatter.format(symbol, timeframe, date_from=date_from, date_to=date_to)
        print("format time:", time.time() - start)


async def main():

    downloader = DataDownloader(
        "downloads/",
        BinanceMetadataManager("downloads/metadata.json")
    )

    extractor = DataExtractor(
        "downloads/",
        "extracts/",
        BinanceMetadataManager("extracts/metadata.json")
    )

    formatter = DataFormatter(
        "extracts/",
        "data/",
        BinanceMetadataManager("data/metadata.json")
    )

    manager = DataManager(downloader, extractor, formatter)

    await manager.download_and_save("BTCUSDT", "1m")


asyncio.run(main())

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Result Folder Structure

After execution the folders will look like:

downloads/
    BTCUSDT/
    metadata.json

extracts/
    BTCUSDT/
    metadata.json

data/
    BTCUSDT/
    metadata.json

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Pipeline Overview

The processing pipeline consists of three stages:

Downloader

Downloads historical data archives from Binance Vision.

Extractor

Extracts downloaded archives.

Formatter

Formats extracted CSV data into a structured dataset ready for analysis.

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Metadata Manager

The library uses a metadata system to track downloaded, extracted and formatted data.

This prevents duplicate downloads and processing.

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Example Use Case

Typical workflow:

download → extract → format → analyze

Used for:

• algorithmic trading
• backtesting
• machine learning datasets
• market research

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Requirements

Python 3.10+

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License

MIT