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pricehub

Pricehub: Unified Python Package for Collecting OHLC Prices from Binance, Bybit, and Coinbase APIs into a DataFrame

  • 0.0.3.11
  • PyPI
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PriceHub: Unified Python Package for Collecting OHLC Prices from Binance, Bybit, and Coinbase APIs into a DataFrame

It supports multiple markets, including spot and futures, and provides flexible timestamp inputs and a wide range of intervals.

Effective trading begins with thorough data analysis, visualization, and backtesting. This package simplifies access to such data, providing a unified solution for retrieving OHLC information across various broker APIs.

Contents

Supported Brokers

  • Binance Spot
  • Binance Futures
  • Bybit Spot
  • Bybit Linear (Futures)
  • Bybit Inverse
  • Coinbase Spot

Key Features

  • Unified Interface: Supports multiple brokers and markets (spot, futures) with a single interface.
  • Unified Intervals: Use the same interval format across all brokers.
  • Timestamp Flexibility: Accepts timestamps (start, end) in various formats (int, float, string, Arrow, pandas, datetime).
  • No Credential Requirement: Fetch public market data without authentication.
  • Extended Date Ranges: This package will paginate and collect all data across large date ranges.
  • All fields from official API: Retrieve all fields available in the official API (e.g., Number of trades, Taker buy base asset volume).

Supported Intervals

(depends on the broker)

  • Seconds: 1s
  • Minutes: 1m, 3m, 5m, 15m, 30m
  • Hours: 1h, 2h, 4h, 6h, 12h
  • Days: 1d, 3d
  • Weeks: 1w
  • Months: 1M

Installation

pip install pricehub

Function Reference

def get_ohlc(broker: SupportedBroker, symbol: str, interval: Interval, start: Timestamp, end: Timestamp) -> pd.DataFrame

Retrieves OHLC data for the specified broker, symbol, interval, and date range.

  • Parameters:

    • broker: The broker to fetch data from (e.g., binance_spot, bybit_spot).
    • symbol: The trading pair symbol (e.g., BTCUSDT).
    • interval: The interval for OHLC data (1m, 1h, 1d, etc.).
    • start: Start time of the data (supports various formats).
    • end: End time of the data (supports various formats).
  • Returns:

    • pandas.DataFrame: A DataFrame containing OHLC data.

Example Usage

Save data to CSV, Excel, Parquet files


from pricehub import get_ohlc
df = get_ohlc("binance_spot", "BTCUSDT", "1d", "2024-10-01", "2024-10-05")
df.to_csv("btcusdt_1d_2024-10-01_2024-10-05.csv") # Save to CSV
df.to_excel("btcusdt_1d_2024-10-01_2024-10-05.xlsx") # Save to Excel
df.to_parquet("btcusdt_1d_2024-10-01_2024-10-05.parquet") # Save to Parquet, requires 'pyarrow', 'fastparquet'

Retrieve OHLC data from Binance Spot for a 6-hour interval

from pricehub import get_ohlc

df = get_ohlc(
    broker="binance_spot",
    symbol="BTCUSDT",
    interval="6h",
    start="2024-10-01",
    end="2024-10-02"
)
print(df)
                        Open     High      Low    Close      Volume              Close time  Quote asset volume  Number of trades  Taker buy base asset volume  Taker buy quote asset volume  Ignore
Open time                                                                                                                                                                                           
2024-10-01 00:00:00  63309.0  63872.0  63000.0  63733.9   39397.714 2024-10-01 05:59:59.999        2.500830e+09          598784.0                    19410.785                  1.232417e+09     0.0
2024-10-01 06:00:00  63733.9  64092.6  63683.1  63699.9   32857.923 2024-10-01 11:59:59.999        2.100000e+09          446330.0                    15865.753                  1.014048e+09     0.0
2024-10-01 12:00:00  63700.0  63784.0  61100.0  62134.1  242613.990 2024-10-01 17:59:59.999        1.512287e+10         2583155.0                   112641.347                  7.022384e+09     0.0
2024-10-01 18:00:00  62134.1  62422.3  60128.2  60776.8  114948.208 2024-10-01 23:59:59.999        7.031801e+09         1461890.0                    54123.788                  3.312086e+09     0.0
2024-10-02 00:00:00  60776.7  61858.2  60703.3  61466.7   51046.012 2024-10-02 05:59:59.999        3.133969e+09          668558.0                    27191.919                  1.669187e+09     0.0

Retrieve OHLC data from Bybit Spot for a 1-day interval

from pricehub import get_ohlc

df = get_ohlc(
    broker="bybit_spot",
    symbol="ETHUSDT",
    interval="1d",
    start=1727740800.0, # Unix timestamp in seconds for "2024-10-01"
    end=1728086400000, # Unix timestamp in ms for "2024-10-05"
)
print(df)
               Open     High      Low    Close        Volume      Turnover
Open time                                                                 
2024-10-01  2602.00  2659.31  2413.15  2447.95  376729.77293  9.623060e+08
2024-10-02  2447.95  2499.82  2351.53  2364.01  242498.88477  5.914189e+08
2024-10-03  2364.01  2403.50  2309.75  2349.91  242598.38255  5.716546e+08
2024-10-04  2349.91  2441.82  2339.15  2414.67  178050.43782  4.254225e+08
2024-10-05  2414.67  2428.69  2389.83  2414.54  106665.69595  2.573030e+08

Plot Close 1d data with matplotlib: BTCUSDT Futures on Binance for the last year

from datetime import datetime, timedelta

import matplotlib.pyplot as plt
from pricehub import get_ohlc

now = datetime.now()
df = get_ohlc("binance_futures", "BTCUSDT", "1d", now - timedelta(days=365), now)
df["Close"].plot()
plt.show()

binance_btcusdt_futures.png

Plot OHLC 1w data with plotly: BTCUSDT Spot on Binance for the last five years

from datetime import datetime, timedelta
import plotly.graph_objects as go
from pricehub import get_ohlc

now = datetime.now()
df = get_ohlc("binance_spot", "BTCUSDT", "1w", now - timedelta(days=365 * 5), now)

fig = go.Figure(data=go.Candlestick(x=df.index, open=df['Open'], high=df['High'], low=df['Low'], close=df['Close']))

fig.update_layout()
fig.show()

binance_btc_usdt_spot_1w_5_years.png

Create custom intervals 10m for SOLUSDT Spot on Bybit for the last month

from datetime import datetime, timedelta
from pricehub import get_ohlc
now = datetime.now()
df = get_ohlc("bybit_spot", "SOLUSDT", "5m", now - timedelta(days=31), now)
df_10m = (
    df.resample(
        "10min",
    ).agg(
        {
            "Open": "first",
            "High": "max",
            "Low": "min",
            "Close": "last",
            "Volume": "sum",
        }
    )
)
print(df.head())
print(df_10m.head())
#5m
                      Open    High     Low   Close    Volume      Turnover
Open time                                                                  
2024-11-07 17:40:00  194.13  194.66  194.03  194.54  3391.378  6.592576e+05
2024-11-07 17:45:00  194.54  195.48  194.44  195.41  6075.927  1.184312e+06
2024-11-07 17:50:00  195.41  195.71  195.06  195.69  4073.276  7.961276e+05
2024-11-07 17:55:00  195.69  196.16  195.59  195.93  8774.224  1.719060e+06
2024-11-07 18:00:00  195.93  196.83  195.73  196.34  5075.807  9.973238e+05

#10m
                       Open    High     Low   Close     Volume
Open time                                                     
2024-11-07 17:40:00  194.13  195.48  194.03  195.41   9467.305
2024-11-07 17:50:00  195.41  196.16  195.06  195.93  12847.500
2024-11-07 18:00:00  195.93  196.83  194.66  195.29  12506.671
2024-11-07 18:10:00  195.29  196.13  194.70  195.58  20437.030
2024-11-07 18:20:00  195.58  196.00  194.84  195.81  16388.688

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